In Which Exchange Rate Models Do Forecasters Trust?

on the fakeness of the internet

funny to see that subject pop up again. it was what drove me insane enough to find this sub in the first place.
at any rate, the problem is not the bots. I thought it was, but those are just part of the parasitic ecosystem.
but to get that, first we need to take a few steps back on web history, ad serving, UX, tracking technology and media advertising.
too lazy to gather links, but you know, do your googlin'.
I assume that most of you are fairly web literate here, but I'll try to go down into the bare bones as much as possible for those who aren't.
so let's start with a basic question - what is a web visitor anyway?
from the standpoint of a normal person, that would be a person browsing a given website or piece of content. from the standpoint of technology however all you know is that some device has downloaded content from your server using the http protocol. thanks to the wonderful technology of web browsers, you can plant browser cookies on a visitor - stuff that's used to remember if they logged in, what their preferences are, stuff that your service can read from the device. it also serves usually very basic telemetry like last visit time, session time, and so on.
this, over time has evolved in what we call browser fingerprinting, a convoluted bunch of technology that allows websites and web services to uniquely identify you.
it still doesn't know if you're a human or not, but from the standpoint of the web technology, you're a visitor.
now back in ye old days of the web, when the first banner ads were springing up, these were important questions. most consumers were still to be reached on traditional media channels, and ad spend would have to be justified somehow on the risky ventures of online business. so beyond traditional polls that would infer the value of visitors, websites would start tracking number of visitors, time on page and so on. these were used to milk the advertising cow so to speak, and it gave in to some funny developments like the creation of the popup ad - if I recon correctly on geocities, where they would just but the ads everywhere until some big auto company noticed that they're appearing on porn sites. so - put the ad in the popup, and you can claim it's not in the context of porn!
around this point in time the online ad business is still pretty low tech. you actually have to call a physical human being, they send you ppts and pdfs, you send back image files and excel sheets, you wire money, the ads run, and so on. this is called direct sales, and it's tracked again by counting a bunch of visitors, and telling you how much impressions and clicks your marvelous creatives and ad budget generated.
now enter google - or more precisely, a technology firm called doubleclick that was to be acquired by google. they developed a tool for automatic ad serving, later to be called programmatic advertising, that keeps the pesky sales dude out of the loop and achieves reasonable amounts of scale for a more hefty price - after all, if the sales are automated, you get a bidding war for attention between different advertisers, and you're paying for clicks.
so you can see how this was a strategic move for google - they already had the most valuable data available in this situation. they were seeing in real time what people were searching for, and using the programmatic ad serving system, you could effectively bid not just for general attention - but for attention with an intent to buy.
...and the way that google got this data is because they indexed the web, using bots. at least GoogleBot would identify itself as a site visitor, but in the meantime they developed a service for websites to comprehensively track their own visitors and where they were coming from and what they were doing on your website. incidentally, you could also put on google's ads on your webpage to earn quite a bit of money, as content relevant ads would be shown through the doubleclick system.
this kicked off two things:
one, the ability to classify your website visitors into different clusters and segments allowed businesses to start tailoring the appearance of the website or service to fit that specific audience segment, starting off the great fracture - segmentation of the web (in the sense that two people viewing the same website at the same time were not seeing the same thing)
two, it created a very strong financial incentive for people to trick google into thinking they were having actual human visitors that would click on ads, when in fact they were bots. in an even funnier twist, some of them were from browser hijackers, commonly known as malware at the time, which google cross-financed. look up download valley and crossrider.
at the cross section of the above two, you had one interesting twist: websites that would appear differently to the security bots or the compliance officers of Google as they would to fake visitors or malware jacked human beings. the former would get a benign looking website, while the latter would get bombarded with auto clicking ads.
this kicked off the billion dollar arms race called online advertising fraud.
I'm not here to shed a tear for big money corps bleeding money. the real fallout lay somewhere else, but for that you have to understand that you never really saw the real internet, you only saw your corner and the one that was personalized for you.
but if you ever had the pleasure of watching daytime TVs or off channels and witnessing the ads, you could kind of infer what kind of audience must be watching these shows generally. from quite clear rip offs to magic number lotteries and television fortune telling, these sorts of programming was aimed at the most gullible, bought for pennies, where the smallest audience portion had to be converted into a money making operation.
...and with audience segmentation and data gathering, that was now possible at unprecedented scale, automatically. so big was the scale in fact, that it gave birth to an entire new beast of an industry called affiliate marketing, where instead of a regular payroll, you'd get a cut of the sale should you figure out an angle on where to push whatever fucking bullshit the vendors were offering to whoever the fuck would be dumb enough to click on an ad and buy. (the funniest story I recall was someone pulling five figures a month because he figured out that if you buy ads on anime-hentai pages and sell PUA shit courses and e-books you'd make a killing)
at any rate, affiliate marketing brought with it the killer landing page, the thing that's supposed to hammer the nail in the coffin once you get through the banner ad. the earliest form of deceptiveness in memory comes from various pirate sites, that had fake download buttons as banner ads and virus alerts as the landing pages. but then at some point, some schmuck realized that for certain type of products, like diet pills or forex trading or whatever, the best lander is in fact a fake news page that comes packed with comments and all. that would convert like crazy, because it had the appearance of social proof.
until at least the lawsuits came raining down, and these sorts of landing pages and campaigns for being banned left right and centre on all platforms. which just launched a new arms race as the campaigns would be disguised for the bots doing the checkups, and aged facebook profiles would start selling for like 5K USD - these people were making 30-40k a day, they could afford to spend that much to continue running the shop.
speaking of facebook - it came just about the right time for the shit to brew max total. first they were unprecedented in the amount of data they were getting off of their users, and they came just in time to catch the full swing of what we call the 'responsive web' - that no user at the same time would see the same thing on their page, it was all allocated through an intricate web of recommendations, running real time, based on previously gathered and forecast behavioral data.
it also ran on one simple premise: take over the starting page position from google for most people, then they do not have to justify, ever, any ad spend that takes place on their platform, as long as it performs. furthermore, it was completely lacking any revenue share sort of scheme (save for the short period of facebook gaming, see Zynga), thus there was no incentive for the amount of bot traffic that the previous internet era had bred. instead, it came with an entirely different one - bots that would offer social proof in the way of shares and likes, but would not directly risk the business model, thus giving no incentive for facebook to fight them. (note that google didn't do much jack shit either besides indiscriminately penalizing websites it deemed suspicious when they reached critical payout thresholds)
the rest of the story you kind of sort of know. how the obama campaign was brilliant in using the new social media to inspire hope and blah blah blah, kicking the door open for big money politics who could hire the best snake oil salesmen in the market, who had the data and as you can see from the above, had the ethical standards of a shoe. at around 2014-2015 the press (the mainstream media) started to raise question about the duopoly, the buzzword of filter bubbles started appearing, not entirely unrelated to the fact that facebook by this time cannibalized their traffic with a fucking embedded share / like button and started charging money for them to reach their own audience. after 2016 the cries of fake news were everywhere, because there was no online space left which everyone was viewing the same way, and you had no way to verify what the person next to you was looking at.
since then, we've all become grandpa yelling at the television set, with nobody around us seeing what we're seeing on the screen, so we're being accused as bots and looking for bots under the carpet.
but it's been a long way coming, and the bots are honestly the least of our worries. trust me, I went bankrupt over that one. truth or fake doesn't even begin to describe the magnitude of the problem: more like we entered the phase where every word, event or picture is defined by who ever the fuck wins the auction over it, as the marketers of human attention grind the gears of the money mill without even understanding how fast they're digging towards hell.
don't believe me? look around the marketing and advertising related subs these days. the priests are eating the indulgences, and we're only now entering the period of deep fakes, good algo generated audio and good enough NLP. and in the meantime, the shadowrunners running up between two corp headquarter-highrises are skinning your belief systems.
so the best you can do is really, not litter the remnants of cyberspace which are not being mined, astroturfed or being pulled apart by the algos. no human connections on a nuclear trash heap mate.
submitted by gergo_v to sorceryofthespectacle [link] [comments]

Immediate Aftermath : The more data we collect and analyze, the clearer the picture becomes.

This is the updated first part of the list that has recorded the notable events as the world deals with the COVID-19 pandemic. [2nd Part] ― The LINKS to events and sources are placed throughout the timeline.
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The More Data We Collect and Analyze, the Clearer the Picture Becomes.
Someone threw a stone in a pond a long way away. And we're only just feeling the ripples. — Fukuhara from Giri/Haji, Netflix series
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On Jan 30, Italian PM announced that Italy had blocked all flights to and from China. While Italy has banned people from air-travelling to China, however according to IATA data, there's no measurement implemented for air-travellers from China into Italy till the Mar 07. Especially for Chinese people who have EU passports.
On Jan 31, the US announced the category-I travel restrictions, barring all foreigners who have been in China for the past 14 days, with measures including the refusal of visas and mandatory quarantine.
• "Because the US focused on China and didn't expect the infected people's entry from Europe and the Middle East, the Maginot Line was breached from behind. And so little of credible data at the beginning made the US government to miscalculate its strategic response to the virus." — Dr. Zhang Lun, currently a visiting scholar at Harvard (economics & sociology), during the interview with ICPC on Mar 29.
Also on Jan 31, the WHO changed its tune and declared the coronavirus outbreak a Global Public Health Emergency of international concern (PHEIC).
Decisions on a PHEIC always involve politics .... West African countries discouraged a declaration in 2014 after they were hit by the largest Ebola virus outbreak on record, mainly because of concern about the economic impact.
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On Feb 02, regarding the US category-I travel restrictions, Kamala Harris, the former Democratic presidential candidate, declared on Twitter:
Since 2017, Trump’s travel bans have never been rooted in national security—they’re about discriminating against people of color. They are, without a doubt, rooted in anti-immigrant, white supremacist ideologies. This travel ban is no different.
On Feb 03, criticizing Trump for his travel restrictions continues. Chinese foreign ministry spokeswoman Hua Chunying (华春莹), a Peking University professors James Liang (梁建章), New York Times, the Nation, OBSERVER, the Boston Globe, Yahoo, and Daily Kos were saying,
it's a "panicky" decision and "racist" or it's "cruel and callous," he's stoking fear for political gains, and the president is "inappropriately overreacting." And professors Liang even said the US ban "will hurt goodwill and cooperation [with China] in the future." [1] [2] [3] [4] [5] [6] [7] [8] [9]
Also on Feb 03, Mr. Tedros of the WHO said there's no need for travel ban measure that "unnecessarily interfere with international travel and trade" trying to halt the spread of the virus.
China's delegate took the floor ... and denounced measures by "some countries" that have denied entry to people holding passports issued in Hubei province - at the centre of the outbreak - and to deny visas and cancel flights.
Also on Feb 03, China is expected to gradually implement a larger stimulus packages (in total) than a USD $572 billion from 2008. — We'd never find out but my guess is that the fund will probably go to Shanghai clique.
On Feb 04, The FDA has given emergency authorization to a new test kit by the CDC that promises to help public health labs meet a potential surge in cases.
The speed ... pushing through a new diagnostic test shows just how seriously they’re taking the potentially pandemic threat of 2019-nCoV. It’s also a sign that the world is starting to learn how to deal with an onslaught of new pathogens.
Also on Feb 04, the Wuhan Institute of Virology and China's Academy of Military Medical Sciences (AMMS, Chief Chen Wei belongs to) have jointly applied to patent the use of Remdesivir. Scientists from both institutes said in a paper published in Nature’s Cell Research that they found both Remdesivir and Chloroquine to be an effective way to inhibit the coronavirus.
On Feb 06, Jamestown Foundation, a Washington-based research & analysis unit, noted that with State Council of PRC praising his performance of containing the pandemic situation, the council expanded Li Keqiang's political control over Politburo Standing Committee of CCP. (Li Keqiang = Communist Youth League = Shanghai clique)
Also, on Feb 06, as the US evacuation planes leave China, the wave of the US evacuees have arrived who are met by the CDC personnel at the quarantine sites for screening, and those who were suspected of infection will be placed under quarantine for 14 days.
Also, on Feb 06, a CDC-developed lab test kit to detect the new coronavirus began shipping to qualified US laboratories and international ones. — However, on Feb 12, the CDC said some of the testing kits have flaws and do not work properly. The CDC finally ended up shipping the working test kits for mass testings on Feb 27. This was three weeks later than originally planned.
On Feb 07, China National Petroleum has recently declared Force Majeure on gas imports. They are trying to create a breathing room for their foreign exchange reserves shortage. China's foreign exchange reserves fell to mere USD $3.1 trillion in Oct. 2019.
On the same day, Bloomberg reported that PetroChina has directed employees in 20 countries to buy N95 face masks and send them home in China. The goal is to get 2 million masks shipped back. You can also find YouTube videos that show Overseas Chinese are scouring the masks at the Home Depot to ship them to China (the video in Korean). Also Chris Smith is pissed.
On Feb 09, Trump renews his national emergency on its southern border, and Elizabeth Goitein from the Brennan Center for Justice, published an opinion article on New York Times titled "Trump Has Abused This Power. And He Will Again if He’s Not Stopped."
On Feb 10, Dr. Tedros said that an advance three-person team of the WHO arrived in Beijing for a joint mission to discuss with Chinese officials the agenda and questions. Then, the joint mission of about 10 international experts will soon follow, he said. — Those WHO experts ended up visiting Chinese epicentre for the first time on Feb 24.
On Feb 12, the US targets Russian oil company for helping Venezuela skirt sanctions. The US admin seemingly tried to secure leverage against Russia after noticing something suspicious was up.
On the same day, Trump told Reuters "I hope this outbreak or this event (for the US) may be over in something like April." — Dr. Zhong Nanshan (钟南山), China's top tier SARS-hero doctor, also said "the peak of the virus (for China) should come in mid to late February, followed by a plateau or decrease," adding that his forecast was based on on mathematical modelling and data from recent events and government action.
On Feb 13, Tom Frieden who is a former US CDC chief and currently the head of public health nonprofit Resolve to Save Lives, said:
As countries are trying to develop their own control strategies, they are looking for evidence of whether the situation in China is getting worse or better. [But] We still don't have very basic information. [since the WHO just entered China] We hope that information will be coming out.
On the same day, the CDC reports that the 15th case in the US was confirmed. The patient was a part of group who were under a federal quarantine order at the JBSA-Lackland base because of a recent trip to Hubei Province, China.
By Feb 13, China hasn't accepted the US CDC's offer to send top experts, and they haven't released the "disaggregated" data (specific figures broken out from the overall numbers) even though repeatedly been asked.
On Feb 14, CCP's United Front posted an article on its official website, saying (Eng. text by Google Translation):
Fast! There is no time difference to raise urgently needed materials! Some Overseas Chinese have used their professions in the field of medicine in order to purchase relevant materials Hubei province in short of supply (to send them to China). .... Some Overseas Chinese took advantage of the connection resources, opened green transportation channels through our embassies and consulates abroad, and their related enterprises, and quickly sent large quantities of medical supplies (to China), making this love relay link and cooperation seamless.
On Feb 18, Reuters reports that 3M is on the list of firms eligible for China loans to ease coronavirus crisis.
There is no indication from the list that loans offered will necessarily be sought, or that such firms are in any financial need. The Bank of Shanghai told Reuters it will lend 5.5 billion yuan ($786 million) to 57 firms on its list.
On Feb 21, Xi Jinping writes a thank-you letter to Bill Gates for his foundation’s support to China regarding COVID-19 outbreak.
On Feb 24, China was rumoured on Twitter to delay the phase one trade deal implementation indefinitely which includes the increase of China's purchasing American products & services by at least $200 billion over the next two years.
Also on Feb 24, S&P 500 Index started to drop. Opened with 3225.9 and closed 3128.2. By the Mar 23, it dropped to 2208.9.
Also on Feb 24, China's National Health Commission says the WHO experts have visited Wuhan city for the first time, the locked-down central Chinese city at the epicentre, inspecting two hospitals and a makeshift one at a sports centre.
On Feb 26, IF the picture that has been circulated on Twitter were real, then chief Chen Wei and her team have developed the first batch of COVID-19 vaccine within time frame of a month.
On the same day, the CDC's latest figures displays 59 people in the US who have tested positive for COVID-19.
Also on Feb 26, the Washington Post published an article that says:
.... the WHO said it has repeatedly asked Chinese officials for "disaggregated" data — meaning specific figures broken out from the overall numbers — that could shed light on hospital transmission and help assess the level of risk front-line workers face. "We received disaggregated information at intervals, though not details about health care workers," said Tarik Jasarevic of the WHO. — The comment, in an email on Feb 22 to the Post, was one of the first instances that the WHO had directly addressed shortcomings in China's reporting or handling of the coronavirus crisis.
On Feb 27, after missteps, the CDC says its test kit is ready and the US started to expand testing.
On Feb 28, China transferred more than 80,000 Uighurs to factories used by global brands such as Apple, Nike, & Volkswagen & among others.
Also on Feb 28, the WHO published the official report of the WHO-China joint mission on coronavirus disease 2019. (PDF)
On Feb 29, quoting Caixin media's investigation published on the same day, Lianhe Zaobao, the largest Singapore-based Chinese-language newspaper, published an article reporting the following:
Dr. Li Wenliang said in the interview with Caixin media; [in Dec 2019] another doctor (later turned out to be Dr. Ai Fen) examined and tried to treat a patient who exhibited SARS-like symptoms which akin to influenza resistant to conventional treatment methods. And "the family members who took care of her (the patient) that night also had a fever, and her other daughter also had a fever. This is obviously from person to person" Dr. Li said in the interview."
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On Mar 01, China's State Council super tighten up their already draconian internet law.
On the same day, Princelings published an propaganda called "A Battle Against Epidemic: China Combating COVID-19 in 2020" which compiles numerous state media accounts on the heroic leadership of Xi Jinping, the vital role of the Communist Party, and the superiority of the Chinese system in fighting the virus.
Starting on Mar 03, the US Fed has taken two significant measures to provide monetary stimulus. It's going to be no use as if a group of people with serious means are manipulating the markets to make sure MM will have liquidity concerns when they need it most.
On Mar 04, Xinhua News, China's official state-run press agency posted an article "Be bold: the world should thank China" which states that
If China retaliates against the US at this time, it will also announce strategic control over medical products, and ban exports of said products to the US. ... If China declares today that its drugs are for domestic use only, the US will fall into the hell of new coronavirus epidemic.
On Mar 05, Shanghai Index has recovered the coronavirus loss almost completely.
On Mar 07, Saudi's Ahmed bin Abdulaziz and Muhammad bin Nayef were arrested on the claims of plotting to overthrow King Salman. — Ahmed bin Abdulaziz is known to have very tight investment-interest relationship with Bill Gates, Bill Browder, Blackstone, & BlackRock: One common factor that connects these people is China.
On Mar 08, the Russia–Saudi oil price war has begun. The ostensible reason was simple: China, the biggest importer of oil from Saudi and Russia, was turning back tankers while claiming that the outbreak forced its economy to a standstill.
On Mar 10, the Washington Post published the article saying that the trade group for manufacturers of personal protective equipment urged in 2009 "immediate action" to restock the national stockpile including N95 masks, but it hasn't been replenished since.
On Mar 11, the gentleman at the WHO declares the coronavirus outbreak a "Global Pandemic." He called on governments to change the course of the outbreak by taking "urgent and aggressive action." This was a full twelve days after the organization published the official report regarding the situation in China.
On Mar 13, the US admin declared a National Emergency and announced the plan to release $50 billion in federal resources amid COVID-19.
Also on Mar 13, China's Ministry of Commerce states that China is now the best region for global investment hedging.
On Mar 15, Business Insider reports that Trump tried to poach German scientists working on a coronavirus vaccine and offered cash so it would be exclusive to the US. The problem is the official CureVac (the German company) twitter account, on Mar 16, 2020, tweeted the following:
To make it clear again on coronavirus: CureVac has not received from the US government or related entities an offer before, during and since the Task Force meeting in the White House on March 2. CureVac rejects all allegations from press.
On Mar 16, the fan club of European globalists has published a piece titled, "China and Coronavirus: From Home-Made Disaster to Global Mega-Opportunity." The piece says:
The Chinese method is the only method that has proved successful [in fighting the virus], is a message spread online in China by influencers, including many essentially promoting propaganda. ... it is certainly a message that seems to be resonating with opinion leaders around the world.
On the same day, unlike China that had one epicentre, Wuhan city, the US now overtakes China with most cases reporting multiple epicentres simultaneously.
Also on Mar 16, the US stocks ended sharply lower with the Dow posting its worst point drop in history. But some showed a faint hint of uncertain hope.
On Mar 17, according to an article on Chinese version of Quora, Zhihu, chief Chen Wei and her team with CanSino Biologics officially initiated a Phase-1 clinical trial for COVID-19 vaccine at the Wuhan lab, Hubei China, which Bloomberg News confirmed. — Click HERE, then set its time period as 1 year, and see when the graph has started to move up.
Also on Mar 17, China's state media, China Global TV Network (CGTN), has produced YouTube videos for Middle Eastern audiences to spread the opinion that the US has engineered COVID-19 events.
Also on Mar 17, Al Jazeera reported that the US President has been criticized for repeatedly referring to the coronavirus as the "Chinese Virus" as critics saying Trump is "fueling bigotry."
• China's Xinhua News tweeted "Racism is not the right tool to cover your own incompetence."
• Tucker Carlson asked: "Why would America's media take China's side amid coronavirus pandemic?"
• Also, Mr. Bill Gates: "We should not call this the Chinese virus."
On Mar 19, for the first time, China reports zero local infections.
Also on Mar 19, Al Jazeera published an analysis report, titled "Coronavirus erodes Trump's re-election prospects."
On Mar 22, Bloomberg reports that China's mobile carriers lost 21 million users during this pandemic event. It's said to be the first net decline since starting to report monthly data in 2000.
On Mar 26, EURACTV reports that China cashes in off coronavirus, selling Spain $466 million in supplies. However, Spain returns 9,000 "quick result" test kits to China, because they were deemed substandard. — Especially the sensibility of the test was around 30 percent, when it should be higher than 80 percent.
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On Apr 03, Germany and other governments are bolstering corporate defenses to address worries that coronavirus-weakened companies could be easy prey for bargain hunting by China's state owned businesses.
On Apr 05, New York Times says "Trump Again Promotes Use of Unproven Anti-Malaria Drug (hydroxychloroquine)."
On Apr 06, a Democratic State Rep. Karen Whitsett from Detroit credits hydroxychloroquine and President Trump for "saving her in her battle with the coronavirus."
On Apr 07, the US CDC removed the following part from its website.
Although optimal dosing and duration of hydroxychloroquine for treatment of COVID-19 are unknown, some U.S. clinicians have reported anecdotally different hydroxychloroquine dosing such as: 400mg BID on day one, then daily for 5 days; 400 mg BID on day one, then 200mg BID for 4 days; 600 mg BID on day one, then 400mg daily on days 2-5.
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☞ If there were ever a time for people not to be partisan and tribal, the time has come: We need to be ever vigilant and attentive to all kinds of disinformation & misinformation to see it better as well as to be sharp in our lives. — We really do need to come together.
☞ At first, I was going to draw up a conspiracy theory-oriented list focused on Team-Z, especially Mr. Gates. However, although it's nothing new tbh, recently many chats and discussions seem overflowing with disinformation & misinformation which is, in my opinion, particularly painful at a time like this. Hence, this post became a vanilla list that's just recorded the notable events. — We all are subject to misinformation, miscalculation, and misjudgment. But the clearer the picture becomes the better we can identify Funkspiel.
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Immediate Aftermath pt.2.a
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Feasible Timeline of the Operation
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☞ Go Back to the Short Story.
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submitted by vanillabluesea to conspiracy [link] [comments]

Hibiscus Petroleum Berhad (5199.KL)


https://preview.redd.it/gp18bjnlabr41.jpg?width=768&format=pjpg&auto=webp&s=6054e7f52e8d52da403016139ae43e0e799abf15
Download PDF of this article here: https://docdro.id/6eLgUPo
In light of the recent fall in oil prices due to the Saudi-Russian dispute and dampening demand for oil due to the lockdowns implemented globally, O&G stocks have taken a severe beating, falling approximately 50% from their highs at the beginning of the year. Not spared from this onslaught is Hibiscus Petroleum Berhad (Hibiscus), a listed oil and gas (O&G) exploration and production (E&P) company.
Why invest in O&G stocks in this particularly uncertain period? For one, valuations of these stocks have fallen to multi-year lows, bringing the potential ROI on these stocks to attractive levels. Oil prices are cyclical, and are bound to return to the mean given a sufficiently long time horizon. The trick is to find those companies who can survive through this downturn and emerge into “normal” profitability once oil prices rebound.
In this article, I will explore the upsides and downsides of investing in Hibiscus. I will do my best to cater this report to newcomers to the O&G industry – rather than address exclusively experts and veterans of the O&G sector. As an equity analyst, I aim to provide a view on the company primarily, and will generally refrain from providing macro views on oil or opinions about secular trends of the sector. I hope you enjoy reading it!
Stock code: 5199.KL
Stock name: Hibiscus Petroleum Berhad
Financial information and financial reports: https://www.malaysiastock.biz/Corporate-Infomation.aspx?securityCode=5199
Company website: https://www.hibiscuspetroleum.com/

Company Snapshot

Hibiscus Petroleum Berhad (5199.KL) is an oil and gas (O&G) upstream exploration and production (E&P) company located in Malaysia. As an E&P company, their business can be basically described as:
· looking for oil,
· drawing it out of the ground, and
· selling it on global oil markets.
This means Hibiscus’s profits are particularly exposed to fluctuating oil prices. With oil prices falling to sub-$30 from about $60 at the beginning of the year, Hibiscus’s stock price has also fallen by about 50% YTD – from around RM 1.00 to RM 0.45 (as of 5 April 2020).
https://preview.redd.it/3dqc4jraabr41.png?width=641&format=png&auto=webp&s=7ba0e8614c4e9d781edfc670016a874b90560684
https://preview.redd.it/lvdkrf0cabr41.png?width=356&format=png&auto=webp&s=46f250a713887b06986932fa475dc59c7c28582e
While the company is domiciled in Malaysia, its two main oil producing fields are located in both Malaysia and the UK. The Malaysian oil field is commonly referred to as the North Sabah field, while the UK oil field is commonly referred to as the Anasuria oil field. Hibiscus has licenses to other oil fields in different parts of the world, notably the Marigold/Sunflower oil fields in the UK and the VIC cluster in Australia, but its revenues and profits mainly stem from the former two oil producing fields.
Given that it’s a small player and has only two primary producing oil fields, it’s not surprising that Hibiscus sells its oil to a concentrated pool of customers, with 2 of them representing 80% of its revenues (i.e. Petronas and BP). Fortunately, both these customers are oil supermajors, and are unlikely to default on their obligations despite low oil prices.
At RM 0.45 per share, the market capitalization is RM 714.7m and it has a trailing PE ratio of about 5x. It doesn’t carry any debt, and it hasn’t paid a dividend in its listing history. The MD, Mr. Kenneth Gerard Pereira, owns about 10% of the company’s outstanding shares.

Reserves (Total recoverable oil) & Production (bbl/day)

To begin analyzing the company, it’s necessary to understand a little of the industry jargon. We’ll start with Reserves and Production.
In general, there are three types of categories for a company’s recoverable oil volumes – Reserves, Contingent Resources and Prospective Resources. Reserves are those oil fields which are “commercial”, which is defined as below:
As defined by the SPE PRMS, Reserves are “… quantities of petroleum anticipated to be commercially recoverable by application of development projects to known accumulations from a given date forward under defined conditions.” Therefore, Reserves must be discovered (by drilling, recoverable (with current technology), remaining in the subsurface (at the effective date of the evaluation) and “commercial” based on the development project proposed.)
Note that Reserves are associated with development projects. To be considered as “commercial”, there must be a firm intention to proceed with the project in a reasonable time frame (typically 5 years, and such intention must be based upon all of the following criteria:)
- A reasonable assessment of the future economics of the development project meeting defined investment and operating criteria; - A reasonable expectation that there will be a market for all or at least the expected sales quantities of production required to justify development; - Evidence that the necessary production and transportation facilities are available or can be made available; and - Evidence that legal, contractual, environmental and other social and economic concerns will allow for the actual implementation of the recovery project being evaluated.
Contingent Resources and Prospective Resources are further defined as below:
- Contingent Resources: potentially recoverable volumes associated with a development plan that targets discovered volumes but is not (yet commercial (as defined above); and) - Prospective Resources: potentially recoverable volumes associated with a development plan that targets as yet undiscovered volumes.
In the industry lingo, we generally refer to Reserves as ‘P’ and Contingent Resources as ‘C’. These ‘P’ and ‘C’ resources can be further categorized into 1P/2P/3P resources and 1C/2C/3C resources, each referring to a low/medium/high estimate of the company’s potential recoverable oil volumes:
- Low/1C/1P estimate: there should be reasonable certainty that volumes actually recovered will equal or exceed the estimate; - Best/2C/2P estimate: there should be an equal likelihood of the actual volumes of petroleum being larger or smaller than the estimate; and - High/3C/3P estimate: there is a low probability that the estimate will be exceeded.
Hence in the E&P industry, it is easy to see why most investors and analysts refer to the 2P estimate as the best estimate for a company’s actual recoverable oil volumes. This is because 2P reserves (‘2P’ referring to ‘Proved and Probable’) are a middle estimate of the recoverable oil volumes legally recognized as “commercial”.
However, there’s nothing stopping you from including 2C resources (riskier) or utilizing 1P resources (conservative) as your estimate for total recoverable oil volumes, depending on your risk appetite. In this instance, the company has provided a snapshot of its 2P and 2C resources in its analyst presentation:
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Basically, what the company is saying here is that by 2021, it will have classified as 2P reserves at least 23.7 million bbl from its Anasuria field and 20.5 million bbl from its North Sabah field – for total 2P reserves of 44.2 million bbl (we are ignoring the Australian VIC cluster as it is only estimated to reach first oil by 2022).
Furthermore, the company is stating that they have discovered (but not yet legally classified as “commercial”) a further 71 million bbl of oil from both the Anasuria and North Sabah fields, as well as the Marigold/Sunflower fields. If we include these 2C resources, the total potential recoverable oil volumes could exceed 100 million bbl.
In this report, we shall explore all valuation scenarios giving consideration to both 2P and 2C resources.
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The company further targets a 2021 production rate of 20,000 bbl (LTM: 8,000 bbl), which includes 5,000 bbl from its Anasuria field (LTM: 2,500 bbl) and 7,000 bbl from its North Sabah field (LTM: 5,300 bbl).
This is a substantial increase in forecasted production from both existing and prospective oil fields. If it materializes, annual production rate could be as high as 7,300 mmbbl, and 2021 revenues (given FY20 USD/bbl of $60) could exceed RM 1.5 billion (FY20: RM 988 million).
However, this targeted forecast is quite a stretch from current production levels. Nevertheless, we shall consider all provided information in estimating a valuation for Hibiscus.
To understand Hibiscus’s oil production capacity and forecast its revenues and profits, we need to have a better appreciation of the performance of its two main cash-generating assets – the North Sabah field and the Anasuria field.

North Sabah oil field
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Hibiscus owns a 50% interest in the North Sabah field together with its partner Petronas, and has production rights over the field up to year 2040. The asset contains 4 oil fields, namely the St Joseph field, South Furious field, SF 30 field and Barton field.
For the sake of brevity, we shall not delve deep into the operational aspects of the fields or the contractual nature of its production sharing contract (PSC). We’ll just focus on the factors which relate to its financial performance. These are:
· Average uptime
· Total oil sold
· Average realized oil price
· Average OPEX per bbl
With regards to average uptime, we can see that the company maintains relative high facility availability, exceeding 90% uptime in all quarters of the LTM with exception of Jul-Sep 2019. The dip in average uptime was due to production enhancement projects and maintenance activities undertaken to improve the production capacity of the St Joseph and SF30 oil fields.
Hence, we can conclude that management has a good handle on operational performance. It also implies that there is little room for further improvement in production resulting from increased uptime.
As North Sabah is under a production sharing contract (PSC), there is a distinction between gross oil production and net oil production. The former relates to total oil drawn out of the ground, whereas the latter refers to Hibiscus’s share of oil production after taxes, royalties and expenses are accounted for. In this case, we want to pay attention to net oil production, not gross.
We can arrive at Hibiscus’s total oil sold for the last twelve months (LTM) by adding up the total oil sold for each of the last 4 quarters. Summing up the figures yields total oil sold for the LTM of approximately 2,075,305 bbl.
Then, we can arrive at an average realized oil price over the LTM by averaging the average realized oil price for the last 4 quarters, giving us an average realized oil price over the LTM of USD 68.57/bbl. We can do the same for average OPEX per bbl, giving us an average OPEX per bbl over the LTM of USD 13.23/bbl.
Thus, we can sum up the above financial performance of the North Sabah field with the following figures:
· Total oil sold: 2,075,305 bbl
· Average realized oil price: USD 68.57/bbl
· Average OPEX per bbl: USD 13.23/bbl

Anasuria oil field
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Doing the same exercise as above for the Anasuria field, we arrive at the following financial performance for the Anasuria field:
· Total oil sold: 1,073,304 bbl
· Average realized oil price: USD 63.57/bbl
· Average OPEX per bbl: USD 23.22/bbl
As gas production is relatively immaterial, and to be conservative, we shall only consider the crude oil production from the Anasuria field in forecasting revenues.

Valuation (Method 1)

Putting the figures from both oil fields together, we get the following data:
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Given that we have determined LTM EBITDA of RM 632m, the next step would be to subtract ITDA (interest, tax, depreciation & amortization) from it to obtain estimated LTM Net Profit. Using FY2020’s ITDA of approximately RM 318m as a guideline, we arrive at an estimated LTM Net Profit of RM 314m (FY20: 230m). Given the current market capitalization of RM 714.7m, this implies a trailing LTM PE of 2.3x.
Performing a sensitivity analysis given different oil prices, we arrive at the following net profit table for the company under different oil price scenarios, assuming oil production rate and ITDA remain constant:
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From the above exercise, it becomes apparent that Hibiscus has a breakeven oil price of about USD 41.8863/bbl, and has a lot of operating leverage given the exponential rate of increase in its Net Profit with each consequent increase in oil prices.
Considering that the oil production rate (EBITDA) is likely to increase faster than ITDA’s proportion to revenues (fixed costs), at an implied PE of 4.33x, it seems likely that an investment in Hibiscus will be profitable over the next 10 years (with the assumption that oil prices will revert to the mean in the long-term).

Valuation (Method 2)

Of course, there are a lot of assumptions behind the above method of valuation. Hence, it would be prudent to perform multiple methods of valuation and compare the figures to one another.
As opposed to the profit/loss assessment in Valuation (Method 1), another way of performing a valuation would be to estimate its balance sheet value, i.e. total revenues from 2P Reserves, and assign a reasonable margin to it.
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From the above, we understand that Hibiscus’s 2P reserves from the North Sabah and Anasuria fields alone are approximately 44.2 mmbbl (we ignore contribution from Australia’s VIC cluster as it hasn’t been developed yet).
Doing a similar sensitivity analysis of different oil prices as above, we arrive at the following estimated total revenues and accumulated net profit:
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Let’s assume that the above average of RM 9.68 billion in total realizable revenues from current 2P reserves holds true. If we assign a conservative Net Profit margin of 15% (FY20: 23%; past 5 years average: 16%), we arrive at estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion. Given the current market capitalization of RM 714 million, we might be able to say that the equity is worth about twice the current share price.
However, it is understandable that some readers might feel that the figures used in the above estimate (e.g. net profit margin of 15%) were randomly plucked from the sky. So how do we reconcile them with figures from the financial statements? Fortunately, there appears to be a way to do just that.
Intangible Assets
I refer you to a figure in the financial statements which provides a shortcut to the valuation of 2P Reserves. This is the carrying value of Intangible Assets on the Balance Sheet.
As of 2QFY21, that amount was RM 1,468,860,000 (i.e. RM 1.468 billion).
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Quite coincidentally, one might observe that this figure is dangerously close to the estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion we calculated earlier. But why would this amount matter at all?
To answer that, I refer you to the notes of the Annual Report FY20 (AR20). On page 148 of the AR20, we find the following two paragraphs:
E&E assets comprise of rights and concession and conventional studies. Following the acquisition of a concession right to explore a licensed area, the costs incurred such as geological and geophysical surveys, drilling, commercial appraisal costs and other directly attributable costs of exploration and appraisal including technical and administrative costs, are capitalised as conventional studies, presented as intangible assets.
E&E assets are assessed for impairment when facts and circumstances suggest that the carrying amount of an E&E asset may exceed its recoverable amount. The Group will allocate E&E assets to cash generating unit (“CGU”s or groups of CGUs for the purpose of assessing such assets for impairment. Each CGU or group of units to which an E&E asset is allocated will not be larger than an operating segment as disclosed in Note 39 to the financial statements.)
Hence, we can determine that firstly, the intangible asset value represents capitalized costs of acquisition of the oil fields, including technical exploration costs and costs of acquiring the relevant licenses. Secondly, an impairment review will be carried out when “the carrying amount of an E&E asset may exceed its recoverable amount”, with E&E assets being allocated to “cash generating units” (CGU) for the purposes of assessment.
On page 169 of the AR20, we find the following:
Carrying amounts of the Group’s intangible assets, oil and gas assets and FPSO are reviewed for possible impairment annually including any indicators of impairment. For the purpose of assessing impairment, assets are grouped at the lowest level CGUs for which there is a separately identifiable cash flow available. These CGUs are based on operating areas, represented by the 2011 North Sabah EOR PSC (“North Sabah”, the Anasuria Cluster, the Marigold and Sunflower fields, the VIC/P57 exploration permit (“VIC/P57”) and the VIC/L31 production license (“VIC/L31”).)
So apparently, the CGUs that have been assigned refer to the respective oil producing fields, two of which include the North Sabah field and the Anasuria field. In order to perform the impairment review, estimates of future cash flow will be made by management to assess the “recoverable amount” (as described above), subject to assumptions and an appropriate discount rate.
Hence, what we can gather up to now is that management will estimate future recoverable cash flows from a CGU (i.e. the North Sabah and Anasuria oil fields), compare that to their carrying value, and perform an impairment if their future recoverable cash flows are less than their carrying value. In other words, if estimated accumulated profits from the North Sabah and Anasuria oil fields are less than their carrying value, an impairment is required.
So where do we find the carrying values for the North Sabah and Anasuria oil fields? Further down on page 184 in the AR20, we see the following:
Included in rights and concession are the carrying amounts of producing field licenses in the Anasuria Cluster amounting to RM668,211,518 (2018: RM687,664,530, producing field licenses in North Sabah amounting to RM471,031,008 (2018: RM414,333,116))
Hence, we can determine that the carrying values for the North Sabah and Anasuria oil fields are RM 471m and RM 668m respectively. But where do we find the future recoverable cash flows of the fields as estimated by management, and what are the assumptions used in that calculation?
Fortunately, we find just that on page 185:
17 INTANGIBLE ASSETS (CONTINUED)
(a Anasuria Cluster)
The Directors have concluded that there is no impairment indicator for Anasuria Cluster during the current financial year. In the previous financial year, due to uncertainties in crude oil prices, the Group has assessed the recoverable amount of the intangible assets, oil and gas assets and FPSO relating to the Anasuria Cluster. The recoverable amount is determined using the FVLCTS model based on discounted cash flows (“DCF” derived from the expected cash in/outflow pattern over the production lives.)
The key assumptions used to determine the recoverable amount for the Anasuria Cluster were as follows:
(i Discount rate of 10%;)
(ii Future cost inflation factor of 2% per annum;)
(iii Oil price forecast based on the oil price forward curve from independent parties; and,)
(iv Oil production profile based on the assessment by independent oil and gas reserve experts.)
Based on the assessments performed, the Directors concluded that the recoverable amount calculated based on the valuation model is higher than the carrying amount.
(b North Sabah)
The acquisition of the North Sabah assets was completed in the previous financial year. Details of the acquisition are as disclosed in Note 15 to the financial statements.
The Directors have concluded that there is no impairment indicator for North Sabah during the current financial year.
Here, we can see that the recoverable amount of the Anasuria field was estimated based on a DCF of expected future cash flows over the production life of the asset. The key assumptions used by management all seem appropriate, including a discount rate of 10% and oil price and oil production estimates based on independent assessment. From there, management concludes that the recoverable amount of the Anasuria field is higher than its carrying amount (i.e. no impairment required). Likewise, for the North Sabah field.
How do we interpret this? Basically, what management is saying is that given a 10% discount rate and independent oil price and oil production estimates, the accumulated profits (i.e. recoverable amount) from both the North Sabah and the Anasuria fields exceed their carrying amounts of RM 471m and RM 668m respectively.
In other words, according to management’s own estimates, the carrying value of the Intangible Assets of RM 1.468 billion approximates the accumulated Net Profit recoverable from 2P reserves.
To conclude Valuation (Method 2), we arrive at the following:

Our estimates Management estimates
Accumulated Net Profit from 2P Reserves RM 1.452 billion RM 1.468 billion

Financials

By now, we have established the basic economics of Hibiscus’s business, including its revenues (i.e. oil production and oil price scenarios), costs (OPEX, ITDA), profitability (breakeven, future earnings potential) and balance sheet value (2P reserves, valuation). Moving on, we want to gain a deeper understanding of the 3 statements to anticipate any blind spots and risks. We’ll refer to the financial statements of both the FY20 annual report and the 2Q21 quarterly report in this analysis.
For the sake of brevity, I’ll only point out those line items which need extra attention, and skip over the rest. Feel free to go through the financial statements on your own to gain a better familiarity of the business.
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Income Statement
First, we’ll start with the Income Statement on page 135 of the AR20. Revenues are straightforward, as we’ve discussed above. Cost of Sales and Administrative Expenses fall under the jurisdiction of OPEX, which we’ve also seen earlier. Other Expenses are mostly made up of Depreciation & Amortization of RM 115m.
Finance Costs are where things start to get tricky. Why does a company which carries no debt have such huge amounts of finance costs? The reason can be found in Note 8, where it is revealed that the bulk of finance costs relate to the unwinding of discount of provision for decommissioning costs of RM 25m (Note 32).
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This actually refers to the expected future costs of restoring the Anasuria and North Sabah fields to their original condition once the oil reserves have been depleted. Accounting standards require the company to provide for these decommissioning costs as they are estimable and probable. The way the decommissioning costs are accounted for is the same as an amortized loan, where the initial carrying value is recognized as a liability and the discount rate applied is reversed each year as an expense on the Income Statement. However, these expenses are largely non-cash in nature and do not necessitate a cash outflow every year (FY20: RM 69m).
Unwinding of discount on non-current other payables of RM 12m relate to contractual payments to the North Sabah sellers. We will discuss it later.
Taxation is another tricky subject, and is even more significant than Finance Costs at RM 161m. In gist, Hibiscus is subject to the 38% PITA (Petroleum Income Tax Act) under Malaysian jurisdiction, and the 30% Petroleum tax + 10% Supplementary tax under UK jurisdiction. Of the RM 161m, RM 41m of it relates to deferred tax which originates from the difference between tax treatment and accounting treatment on capitalized assets (accelerated depreciation vs straight-line depreciation). Nonetheless, what you should take away from this is that the tax expense is a tangible expense and material to breakeven analysis.
Fortunately, tax is a variable expense, and should not materially impact the cash flow of Hibiscus in today’s low oil price environment.
Note: Cash outflows for Tax Paid in FY20 was RM 97m, substantially below the RM 161m tax expense.
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Balance Sheet
The balance sheet of Hibiscus is unexciting; I’ll just bring your attention to those line items which need additional scrutiny. I’ll use the figures in the latest 2Q21 quarterly report (2Q21) and refer to the notes in AR20 for clarity.
We’ve already discussed Intangible Assets in the section above, so I won’t dwell on it again.
Moving on, the company has Equipment of RM 582m, largely relating to O&G assets (e.g. the Anasuria FPSO vessel and CAPEX incurred on production enhancement projects). Restricted cash and bank balances represent contractual obligations for decommissioning costs of the Anasuria Cluster, and are inaccessible for use in operations.
Inventories are relatively low, despite Hibiscus being an E&P company, so forex fluctuations on carrying value of inventories are relatively immaterial. Trade receivables largely relate to entitlements from Petronas and BP (both oil supermajors), and are hence quite safe from impairment. Other receivables, deposits and prepayments are significant as they relate to security deposits placed with sellers of the oil fields acquired; these should be ignored for cash flow purposes.
Note: Total cash and bank balances do not include approximately RM 105 m proceeds from the North Sabah December 2019 offtake (which was received in January 2020)
Cash and bank balances of RM 90m do not include RM 105m of proceeds from offtake received in 3Q21 (Jan 2020). Hence, the actual cash and bank balances as of 2Q21 approximate RM 200m.
Liabilities are a little more interesting. First, I’ll draw your attention to the significant Deferred tax liabilities of RM 457m. These largely relate to the amortization of CAPEX (i.e. Equipment and capitalized E&E expenses), which is given an accelerated depreciation treatment for tax purposes.
The way this works is that the government gives Hibiscus a favorable tax treatment on capital expenditures incurred via an accelerated depreciation schedule, so that the taxable income is less than usual. However, this leads to the taxable depreciation being utilized quicker than accounting depreciation, hence the tax payable merely deferred to a later period – when the tax depreciation runs out but accounting depreciation remains. Given the capital intensive nature of the business, it is understandable why Deferred tax liabilities are so large.
We’ve discussed Provision for decommissioning costs under the Finance Costs section earlier. They are also quite significant at RM 266m.
Notably, the Other Payables and Accruals are a hefty RM 431m. What do they relate to? Basically, they are contractual obligations to the sellers of the oil fields which are only payable upon oil prices reaching certain thresholds. Hence, while they are current in nature, they will only become payable when oil prices recover to previous highs, and are hence not an immediate cash outflow concern given today’s low oil prices.
Cash Flow Statement
There is nothing in the cash flow statement which warrants concern.
Notably, the company generated OCF of approximately RM 500m in FY20 and RM 116m in 2Q21. It further incurred RM 330m and RM 234m of CAPEX in FY20 and 2Q21 respectively, largely owing to production enhancement projects to increase the production rate of the Anasuria and North Sabah fields, which according to management estimates are accretive to ROI.
Tax paid was RM 97m in FY20 and RM 61m in 2Q21 (tax expense: RM 161m and RM 62m respectively).

Risks

There are a few obvious and not-so-obvious risks that one should be aware of before investing in Hibiscus. We shall not consider operational risks (e.g. uptime, OPEX) as they are outside the jurisdiction of the equity analyst. Instead, we shall focus on the financial and strategic risks largely outside the control of management. The main ones are:
· Oil prices remaining subdued for long periods of time
· Fluctuation of exchange rates
· Customer concentration risk
· 2P Reserves being less than estimated
· Significant current and non-current liabilities
· Potential issuance of equity
Oil prices remaining subdued
Of topmost concern in the minds of most analysts is whether Hibiscus has the wherewithal to sustain itself through this period of low oil prices (sub-$30). A quick and dirty estimate of annual cash outflow (i.e. burn rate) assuming a $20 oil world and historical production rates is between RM 50m-70m per year, which considering the RM 200m cash balance implies about 3-4 years of sustainability before the company runs out of cash and has to rely on external assistance for financing.
Table 1: Hibiscus EBITDA at different oil price and exchange rates
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The above table shows different EBITDA scenarios (RM ‘m) given different oil prices (left column) and USD:MYR exchange rates (top row). Currently, oil prices are $27 and USD:MYR is 1:4.36.
Given conservative assumptions of average OPEX/bbl of $20 (current: $15), we can safely say that the company will be loss-making as long as oil remains at $20 or below (red). However, we can see that once oil prices hit $25, the company can tank the lower-end estimate of the annual burn rate of RM 50m (orange), while at RM $27 it can sufficiently muddle through the higher-end estimate of the annual burn rate of RM 70m (green).
Hence, we can assume that as long as the average oil price over the next 3-4 years remains above $25, Hibiscus should come out of this fine without the need for any external financing.
Customer Concentration Risk
With regards to customer concentration risk, there is not much the analyst or investor can do except to accept the risk. Fortunately, 80% of revenues can be attributed to two oil supermajors (Petronas and BP), hence the risk of default on contractual obligations and trade receivables seems to be quite diminished.
2P Reserves being less than estimated
2P Reserves being less than estimated is another risk that one should keep in mind. Fortunately, the current market cap is merely RM 714m – at half of estimated recoverable amounts of RM 1.468 billion – so there’s a decent margin of safety. In addition, there are other mitigating factors which shall be discussed in the next section (‘Opportunities’).
Significant non-current and current liabilities
The significant non-current and current liabilities have been addressed in the previous section. It has been determined that they pose no threat to immediate cash flow due to them being long-term in nature (e.g. decommissioning costs, deferred tax, etc). Hence, for the purpose of assessing going concern, their amounts should not be a cause for concern.
Potential issuance of equity
Finally, we come to the possibility of external financing being required in this low oil price environment. While the company should last 3-4 years on existing cash reserves, there is always the risk of other black swan events materializing (e.g. coronavirus) or simply oil prices remaining muted for longer than 4 years.
Furthermore, management has hinted that they wish to acquire new oil assets at presently depressed prices to increase daily production rate to a targeted 20,000 bbl by end-2021. They have room to acquire debt, but they may also wish to issue equity for this purpose. Hence, the possibility of dilution to existing shareholders cannot be entirely ruled out.
However, given management’s historical track record of prioritizing ROI and optimal capital allocation, and in consideration of the fact that the MD owns 10% of outstanding shares, there is some assurance that any potential acquisitions will be accretive to EPS and therefore valuations.

Opportunities

As with the existence of risk, the presence of material opportunities also looms over the company. Some of them are discussed below:
· Increased Daily Oil Production Rate
· Inclusion of 2C Resources
· Future oil prices exceeding $50 and effects from coronavirus dissipating
Increased Daily Oil Production Rate
The first and most obvious opportunity is the potential for increased production rate. We’ve seen in the last quarter (2Q21) that the North Sabah field increased its daily production rate by approximately 20% as a result of production enhancement projects (infill drilling), lowering OPEX/bbl as a result. To vastly oversimplify, infill drilling is the process of maximizing well density by drilling in the spaces between existing wells to improve oil production.
The same improvements are being undertaken at the Anasuria field via infill drilling, subsea debottlenecking, water injection and sidetracking of existing wells. Without boring you with industry jargon, this basically means future production rate is likely to improve going forward.
By how much can the oil production rate be improved by? Management estimates in their analyst presentation that enhancements in the Anasuria field will be able to yield 5,000 bbl/day by 2021 (current: 2,500 bbl/day).
Similarly, improvements in the North Sabah field is expected to yield 7,000 bbl/day by 2021 (current: 5,300 bbl/day).
This implies a total 2021 expected daily production rate from the two fields alone of 12,000 bbl/day (current: 8,000 bbl/day). That’s a 50% increase in yields which we haven’t factored into our valuation yet.
Furthermore, we haven’t considered any production from existing 2C resources (e.g. Marigold/Sunflower) or any potential acquisitions which may occur in the future. By management estimates, this can potentially increase production by another 8,000 bbl/day, bringing total production to 20,000 bbl/day.
While this seems like a stretch of the imagination, it pays to keep them in mind when forecasting future revenues and valuations.
Just to play around with the numbers, I’ve come up with a sensitivity analysis of possible annual EBITDA at different oil prices and daily oil production rates:
Table 2: Hibiscus EBITDA at different oil price and daily oil production rates
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The left column represents different oil prices while the top row represents different daily oil production rates.
The green column represents EBITDA at current daily production rate of 8,000 bbl/day; the orange column represents EBITDA at targeted daily production rate of 12,000 bbl/day; while the purple column represents EBITDA at maximum daily production rate of 20,000 bbl/day.
Even conservatively assuming increased estimated annual ITDA of RM 500m (FY20: RM 318m), and long-term average oil prices of $50 (FY20: $60), the estimated Net Profit and P/E ratio is potentially lucrative at daily oil production rates of 12,000 bbl/day and above.
2C Resources
Since we’re on the topic of improved daily oil production rate, it bears to pay in mind the relatively enormous potential from Hibiscus’s 2C Resources. North Sabah’s 2C Resources alone exceed 30 mmbbl; while those from the yet undiagnosed Marigold/Sunflower fields also reach 30 mmbbl. Altogether, 2C Resources exceed 70 mmbbl, which dwarfs the 44 mmbbl of 2P Reserves we have considered up to this point in our valuation estimates.
To refresh your memory, 2C Resources represents oil volumes which have been discovered but are not yet classified as “commercial”. This means that there is reasonable certainty of the oil being recoverable, as opposed to simply being in the very early stages of exploration. So, to be conservative, we will imagine that only 50% of 2C Resources are eligible for reclassification to 2P reserves, i.e. 35 mmbbl of oil.
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This additional 35 mmbbl of oil represents an 80% increase to existing 2P reserves. Assuming the daily oil production rate increases similarly by 80%, we will arrive at 14,400 bbl/day of oil production. According to Table 2 above, this would yield an EBITDA of roughly RM 630m assuming $50 oil.
Comparing that estimated EBITDA to FY20’s actual EBITDA:
FY20 FY21 (incl. 2C) Difference
Daily oil production (bbl/day) 8,626 14,400 +66%
Average oil price (USD/bbl) $68.57 $50 -27%
Average OPEX/bbl (USD) $16.64 $20 +20%
EBITDA (RM ‘m) 632 630 -
Hence, even conservatively assuming lower oil prices and higher OPEX/bbl (which should decrease in the presence of higher oil volumes) than last year, we get approximately the same EBITDA as FY20.
For the sake of completeness, let’s assume that Hibiscus issues twice the no. of existing shares over the next 10 years, effectively diluting shareholders by 50%. Even without accounting for the possibility of the acquisition of new oil fields, at the current market capitalization of RM 714m, the prospective P/E would be about 10x. Not too shabby.
Future oil prices exceeding $50 and effects from coronavirus dissipating
Hibiscus shares have recently been hit by a one-two punch from oil prices cratering from $60 to $30, as a result of both the Saudi-Russian dispute and depressed demand for oil due to coronavirus. This has massively increased supply and at the same time hugely depressed demand for oil (due to the globally coordinated lockdowns being implemented).
Given a long enough timeframe, I fully expect OPEC+ to come to an agreement and the economic effects from the coronavirus to dissipate, allowing oil prices to rebound. As we equity investors are aware, oil prices are cyclical and are bound to recover over the next 10 years.
When it does, valuations of O&G stocks (including Hibiscus’s) are likely to improve as investors overshoot expectations and begin to forecast higher oil prices into perpetuity, as they always tend to do in good times. When that time arrives, Hibiscus’s valuations are likely to become overoptimistic as all O&G stocks tend to do during oil upcycles, resulting in valuations far exceeding reasonable estimates of future earnings. If you can hold the shares up until then, it’s likely you will make much more on your investment than what we’ve been estimating.

Conclusion

Wrapping up what we’ve discussed so far, we can conclude that Hibiscus’s market capitalization of RM 714m far undershoots reasonable estimates of fair value even under conservative assumptions of recoverable oil volumes and long-term average oil prices. As a value investor, I hesitate to assign a target share price, but it’s safe to say that this stock is worth at least RM 1.00 (current: RM 0.45). Risk is relatively contained and the upside far exceeds the downside. While I have no opinion on the short-term trajectory of oil prices, I can safely recommend this stock as a long-term Buy based on fundamental research.
submitted by investorinvestor to SecurityAnalysis [link] [comments]

Wayland Group DD

I want to use this thread to present the key findings of going through recent Wayland news releases. Everything shown here is public accessible. I have no intention to accuse someone of fraud or something like this, just asking questions ....

Feb 20 2019: Wayland Group Provides Corporate Update
I do not want to speak about the well below average generated revenues nor the revenue forecasts. Just as a side note: Ben had a forecast of ~ $15,000,000 for Q4 2018 (October – December 2018). The corporate update states $1,305,033 for Q4 2018 (< 10 percentage of the forecast). In addition, you cannot whitewash the 480% increase to the previous quarter.

“Wayland has also entered into an agreement to obtain additional funds to support the expansion of the Company’s global footprint and fund development of its flagship Langton facility. This agreement is with certain investment funds managed by Alpha Blue Ocean Inc. (“Alpha Blue”) a money manager based in London, United Kingdom with a strong track record of partnering with public companies and delivering meaningful value to their shareholders.”

Founder and CEO of Alpha Blue Ocean Inc. is Pierre Vannineuse (https://www.linkedin.com/in/piervan/)

Ok let’s have a look at their strong track record:

JUN 21 2018
QuickCool AB (Publ) ("QuickCool" or the "Company") has entered into a financing agreement with European High Growth Opportunities Securitization Fund through its financial advisor Alpha Blue Ocean Inc.
See: http://news.cision.com/quickcool/quickcool-ab-enters-into-a-financing-agreement-with-european-high-growth-opportunities-securitizatio,c2554476

See performance since financing: https://i.imgur.com/j7HxzPk.png

Okay next
MAR 28 2018: CybAero and European High Growth Opportunities Securitization Fund (“EHGO”), advised by Alpha Blue Ocean Advisors Ltd, member of the Alpha Blue Ocean Investment Group (“ABO”), has now signed an agreement regarding a financing solution of up to SEK 52.5 million in the form of thirteen convertible loans, the first loan of SEK 4.5 million and the following twelve loans each of SEK 4 million.
See: http://news.cision.com/cybaero/cybaero-signs-agreement-with-alpha-blue-ocean-for-up-to-sek-52-5-million,c2483046

Seriously? Just 3 months later:
June 22 2018: Sweden’s largest military drone maker files for bankruptcy
“CybAero had provisionally negotiated a financing solution with the Luxembourg-based European High Growth Opportunities Securitization Fund, or EHGO, to raise $6 million in the form of 13 convertible loans. The EHGO had hired the London-based Alpha Blue Ocean Advisors to mediate a deal. The first tranche in this solution involved a bridge loan amounting to $227,000.
Nasdaq First North rejected this first tranche arrangement and insisted that, in order for trading in its share to resume, CybAero needed to place a minimum of $114,000 in escrow on a authorized bank account. Moreover, Nasdaq First North launched an investigation to determine if the negotiated financing solution violated stock exchange rules.”
See: https://www.defensenews.com/newsletters/unmanned-systems/2018/06/22/swedens-largest-military-drone-maker-files-for-bankruptcy/

Also see: https://simplywall.st/stocks/se/capital-goods/sto-cba/cybaero-shares/news/will-you-be-burnt-by-cybaero-abs-stocba-cash-burn/

Okay next
Feb 20 2018: MOLOGEN AG enters into financing agreement with Alpha Blue Ocean's European High Growth Opportunities Securitization Fund
See: https://www.dgap.de/dgap/News/corporate/mologen-enters-into-financing-agreement-with-alpha-blue-oceans-european-high-growth-opportunities-securitization-fund/?newsID=1053753

See performance since financing: https://i.imgur.com/JXVJ7yq.png

Okay next
19 March 2018: Cereno Scientific enters into a financing agreement with European High Growth Opportunities Securitization Fund through its advisor Alpha Blue Ocean
See: https://www.cerenoscientific.se/en/en/ehgo_agreement

See performance since financing: https://i.imgur.com/CS7rq5y.png

Okay next
10 Jan 2018: FIT Biotech's EUR 10 million financing agreements' share loan and first part of commitment fee related shares have been handed over today to Alpha Blue Ocean
See: https://www.pm360online.com/fit-biotech-oy-fit-biotechs-eur-10-million-financing-agreements-share-loan-and-first-part-of-commitment-fee-related-shares-have-been-handed-over-today-to-alpha-blue-ocean/

See performance since financing: https://i.imgur.com/N0XhSQp.png

FIT Biotech Oy Company release 20.02.2019 at 14:30 EET
Liquidity crisis, request for a tranche and changes to financial calendar and date of the Annual General Meeting
Despite the financing agreement in force, Alpha Blue Ocean (”ABO”) has not paid tranches envisaged by the agreement since 12 November 2018. This has resulted in a liquidity crisis in FIT Biotech Oy (”Company”). The Company has today filed a latest request for a tranche with ABO. Unless ABO pays this tranche by 22 February 2019, Company will have to file for bankruptcy.
See: https://www.marketscreener.com/FIT-BIOTECH-OY-22752983/news/FIT-Biotech-Oy-Liquidity-crisis-request-for-a-tranche-and-changes-to-financial-calendar-and-date-o-28037452/

I think you are able to recognize the pattern. However the best is yet to come. Just google “alpha blue ocean death spiral”. Same type of financing for Element ASA – a Norwegian based mining company.

“The Induct Manager will demand a million dollar compensation from the "Death Spiral Mortgage Company" Alpha Blue Ocean Stock Exchange and Finance”
See: https://vaaju.com/norway/the-induct-manager-will-demand-a-million-dollar-compensation-from-the-death-spiral-mortgage-company-alpha-blue-ocean-stock-exchange-and-finance/

Why Would a Company Want Death Spiral Financing?
“A company that seeks death spiral financing basically has no other option to raise money to survive.”
See: https://www.investopedia.com/terms/d/deathspiral.asp

See also:


Biotech Firms Run Away After Industry Party With Topless Dancers
See: https://www.bloombergquint.com/business/after-biotech-party-features-topless-dancers-firms-pull-support#gs.RO9Bf8oK

https://i.imgur.com/oQ4n3TC.png
Haha … Sean?

Also have a look after Pierre Vannineuse other investing company Bracknor IG. I did not check, but it possibly has a similar track record.

I could go on like this, but I think you got it. So this means “strong track record and delivering meaningful value to their shareholders.” for Ben?

Next news release:
Feb. 07, 2019: Wayland Group Receives EU-GMP Certification for German Facility
“Wayland Group is pleased to announce that it has received both Good Manufacturing Practices and Good Distribution Practices certifications from the national authority in the State of Saxony for the Company’s Ebersbach facility in Germany.”
See: https://globenewswire.com/news-release/2019/02/07/1711837/0/en/Wayland-Group-Receives-EU-GMP-Certification-for-German-Facility.html

Welcome to EudraGMDP
EudraGMDP is the name for the Union database referred to in article 111(6) of Directive 2001/83/EC and article 80(6) of Directive 2001/82/EC. It contains the following information:
· Manufacturing and import authorisations
· Good Manufacturing Practice (GMP) certificates.
· Statements of non-compliance with GMP
· GMP inspection planning in third countries
See: http://eudragmdp.ema.europa.eu/inspections/displayWelcome.do

https://i.imgur.com/W2zdxqH.png

Looks promising

https://i.imgur.com/c6yVRxu.png

SCOPE OF AUTHORISATION
Name and address of the site : Maricann GmbH, Moritzburger Weg 1, Ebersbach OT Naunhof, Sachsen, 01561, Germany
Human Medicinal Products
Authorised Operations
IMPORTATION OF MEDICINAL PRODUCTS (according to part 2)
Part 2 - IMPORTATION OF MEDICINAL PRODUCTS
2.3 Other importation activities
2.3.1 Site of physical importation
2.3.2 Importation of intermediate which undergoes further processing

But where is the GMP certificate? Latest GMP certificates for Germany:

https://i.imgur.com/bZxouN0.png
https://i.imgur.com/ZOlvlwo.png

Just for their facility in Canada. Maybe the missing of the announced GMP certificate is because of the german tender process. Maybe not, who knows …

“These certifications provide Wayland with the foundation to start selling product into the lucrative German and other developing European markets …”

Oh really? Not in my view …

Next news release:
Jan. 31, 2019: Wayland Group Comments on Recent Promotional Market Activity

“Since September 1, 2017 the Company has engaged MJM Markets and Consulting (Toronto, Canada; Follow The Money Investor Group, o/a 2632436 Ontario Limited (Toronto, Canada); Harbor Access LLC (NY, USA); Investing News Network; M. Davis & Associates Capital Inc (Vancouver, Canada); ERPR AS (Oslo, Norway); BlackX GmbH (Germany); Tycona Media (Vancouver, Canada); DiePRBerator (Germany); Global Financial Network (Toronto, Canada), and Prosdocimi (London, UK) at various times to provide investor relations services, public relations services, marketing, native advertising or other related services including the promotion of the Company, its business and/or its securities.”

See: https://globenewswire.com/news-release/2019/01/31/1708838/0/en/Wayland-Group-Comments-on-Recent-Promotional-Market-Activity.html

Really? What is your business model @ Wayland?!

Just to give you one example:

BlackX GmbH received 1,300,000 shares (each $1.50 = $1,950,000) for the creation/translation of pump articles. See: https://webfiles.thecse.com/CSE_Form_9_-_Notice_of_Issuance_of_Securities_BlackX_12Nov2018.pdf?4gdPoHHl03IN_5qafloB2.0FP4zHeqYb=

For what exactly? Example:
https://www.dgap.de/dgap/News/dgap_media/maricann-group-inc-mit-volldampf-die-zukunft-ceo-ben-ward-gibt-ausblick-ueber-hervorragende-entwicklung-der-wayland-group/?newsID=1110809

A template lacking in content with share price predictions of 3 to 5 Euro (4.5 – 7.5 CAD).

Next news release:
Jan 30 2019: Wayland Group Corporation: European Cannabis Giant Wayland is said to be in advanced talks to purchase and re-open the Voss Water bottling plant in Norway
See: https://www.ftmig.com/company-news-releases/european-cannabis-giant-wayland-is-said-to-be-in-advanced-talks-to-purchase-and-re-open-the-voss-water-bottling-plant-in-norway/

The not named London based Norwegian investor in the last paragraph is probably Lars Christian Beitnes (also mentioned in the second paragraph). After reading his name in a Wayland press release again, I got excited. Again? Yes, I have done some DD about Beitnes when Wayland announced the first Malta LOI with Medican Holdings (USD$10.1MM for a recently created shell company in Malta) - see: https://www.newcannabisventures.com/maricann-to-pay-10-million-to-acquire-malta-licensed-cannabis-producer-medican-holdings/

I was glad when Malta Enterprise terminated this LOI “Malta Enterprise then contacted Maricann to request the Company make its own application, as their preference was to work through Maricann rather than Medican.“ – see: https://www.newcannabisventures.com/maricann-to-pursue-malta-medical-cannabis-license-independently/

Why am I shocked to see the name Beitnes and Wayland in a press release?
In my view Beitnes is far away from being a person you should do deals with. He is being accused to be part of several frauds/scams in the past/present and recently left as a Chairmen of Element ASA – see: https://www.dn.no/bors/element/lars-christian-beitnes/rikard-storvestre/avtroppende-styreleder-far-100000-kroner-i-maneden-for-radgivning/2-1-498862

Element ASA … wait … yea the norwegian based mining company who is the victim of the death spiral financing by Alpha Blue Ocean Inc.!!!

There is a long thread about him in a Norwegian stock community with everything mentioned why you should avoid him – see: https://forum.hegnar.no/thread/16282/view/0/0?page=1

Because of the length of the thread, see some highlights:

I know this is much content, but if you want to make your own picture of Beitnes just dig into this whole Element ASA debacle starting last year. Two auditors (EY & PwC) and the CFO left Element … Then Beitnes left as Chairmen but now serving as external consultant for Element receiving 100.000 NOK monthly. https://www.dn.no/bors/element/lars-christian-beitnes/rikard-storvestre/avtroppende-styreleder-far-100000-kroner-i-maneden-for-radgivning/2-1-498862 would be a good start. Or dig deeper into the Swedish Pensions Authority lawsuit against Beitnes.

Finally … just ask yourself why does Ben deals with such shady persons? Did Ben no DD on those guys or did he not want to … And that is just the top of the iceberg.


TO BE CONTINUED
submitted by PHan222 to weedstocks [link] [comments]

WOLFPACKBOT -the world fastest crypto trading bot

Crypto asset are very volatile where traders need more technical and fundamental analysis before venturing into such career taking trading as source of income . the market capitalization is trading approximately 130billion USD as the time this article was published. This shows that there are lot of money to make out from the crypto market but unfortunate many traders have lose all most all their asset on their portfolio since inception of bitcoin and altcoin trading was introduce to the global community , trading hasn’t been easy especially trying to understand the different candle patterns and the time frame, this has be tedious and difficult for traders to comprehend , the worst scenario is that most trader sit down with their laptops and phone monitoring trading chart that which looks complex for them to make profit . This is just simply spending wise time and earning no or little profit.
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submitted by tosindesign1 to ico [link] [comments]

Student strikes back at lecturers idea. You won't believe what happens next!

Last year I took a management class as an extra class for points. Little did I know that the main lecturer would spend the whole semester preaching socialisty ideas at us. There was a lot of interesting stuff in the class really as it was mainly about labour-management relationships, but whenever she presented her ideas about the economy it often left me cringing. The best is when she got all exasperated claiming she couldn't understand how productivity and wages were linked.
Anyway. She presented us the idea based off a portion of this video suggesting it could be good for the New Zealand economy, I’d like to R1 the first idea of hers (Mods said I could!). She made us discuss the idea of Reducing the work week without reducing pay, implementing profit sharing and management-labour wage gap restrictions. This would be voluntary as governments would offer to cover a company’s payroll taxes in exchange for implementing these 3 things.
I am not R1ing the 20 year old video I am R1ing my lecturers idea based on this in a New Zealand context, the idea it’s from is at around 37 minutes.
I’ll admit I don’t know much about taxation, but according to the oecd website, New Zealand doesn’t actually have a payroll tax. Oops. What if the government legislates reduced work week and same pay in then? Well, I’m going to attempt to use the 3-equation model to see what would happen.
I’m basing this off the idea that this law would be a supply shift, shifting the wage setting curve upwards, just like unions not exercising bargaining restraint in context of wages. I’m trying to keep the model simple because I did this course a year ago, but feel free to criticise and/or correct me.
Assumptions: - wage setters define price level using domestic price level so ERU is vertical.
q= nominal exchange rate (^ = depreciation). r = real exchange rate. pi= inflation. N = employment, y = real output. w/p= real wage.
Enjoy my beautiful hand drawn graphs
Period 0: Start at equilibrium point A. Government introduces legislation, Wage Setting curve shifts upwards, Now there is a difference between equilibrium real wage and real wage, inflation increases(point B). Central bank forecasts the new PC and sets at point C, forex market predicts r>r*, central bank knows this so sets r0 on the RX curve. Forex will cause currency to appreciate and overshoot.
Period 1 onwards: The higher r0 and appreciated q0 cause disinflation, IS curve at point C. Real wages are lower. Economy will gradually shift from point C to point Z. Currency will depreciate to new appreciated equilibrium level, Inflation will return to target, real wage will return to old equilibrium level, real interest rates will return to world rate r*. Lower equilibrium employment and output ( Ye’ IF that doesn’t make sense, just ignore and look at my pretty graph.
I know you don't usually include the ws ps graph as it's shown through the ERU but I wanted to include the visual about real wages. And I made a mistake of labeling it PC not PS on the graph.
So what I get from this model is that the legislation probably wouldn’t improve real wages, but it would result in a lower rate of equilibrium employment/output and an appreciated real exchange rate. This doesn’t seem like it would have the desired effect of sharing the gains of production, or increasing employment. More leisure time though so yay.
submitted by gotschwifted to badeconomics [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

Top Commenters

  1. tuckerbalch (2296 points, 1185 comments)
  2. davebyrd (1033 points, 466 comments)
  3. yokh_cs7646 (320 points, 177 comments)
  4. rgraziano3 (266 points, 147 comments)
  5. j0shj0nes (264 points, 148 comments)
  6. i__want__piazza (236 points, 127 comments)
  7. swamijay (227 points, 116 comments)
  8. _ant0n_ (205 points, 149 comments)
  9. ml4tstudent (204 points, 117 comments)
  10. gatechben (179 points, 107 comments)
  11. BNielson (176 points, 108 comments)
  12. jameschanx (176 points, 94 comments)
  13. Artmageddon (167 points, 83 comments)
  14. htrajan (162 points, 81 comments)
  15. boyko11 (154 points, 99 comments)
  16. alyssa_p_hacker (146 points, 80 comments)
  17. log_base_pi (141 points, 80 comments)
  18. Ran__Ran (139 points, 99 comments)
  19. johnsmarion (136 points, 86 comments)
  20. jgorman30_gatech (135 points, 102 comments)
  21. dyllll (125 points, 91 comments)
  22. MikeLachmayr (123 points, 95 comments)
  23. awhoof (113 points, 72 comments)
  24. SharjeelHanif (106 points, 59 comments)
  25. larrva (101 points, 69 comments)
  26. augustinius (100 points, 52 comments)
  27. oimesbcs (99 points, 67 comments)
  28. vansh21k (98 points, 62 comments)
  29. W1redgh0st (97 points, 70 comments)
  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
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Weekly Forex Forecast  GBPUSD Forex Weekly Forecast 27 Of January - 1st Of February 2019 Weekly Forex Analysis 1 - 5 July Forecasting - Simple moving average - Example 1 - YouTube Forex Weekly Forecast 3rd - 9th February 2019 Forex Weekly Forecast 17 To 23rd Of March 2019 Forex EZ Trading - YouTube Forex Weekly Forecast 17-22nd of February 2019 SHOCKING!!! Secret of Forex Revealed by Fibo Warisan

Forex forecasting Basic Forex forecast methods: Technical analysis and fundamental analysis This article provides insight into the two major methods of analysis used to forecast the behavior of the Forex market. Technical analysis and fundamental analysis differ greatly, but both can be useful forecast tools for the Forex trader. They have the same goal - to predict a price or movement. The ... 2015, this paper introduces Arima model with four steps to forecast foreign exchange rate between VND/USD in the next twelve months of 2016. After having forecasted foreign exchange data, we compare them with real foreign exchange rate data to check the suitable level of Arima model for forecasting foreign exchange rate in Vietnam and the results show that Arima model is suitable for ... Model Needed A forecast needs a model, which specifies a function for St: St = f (Xt) • The model can be based on - Economic Theory (say, PPP: Xt =(Id,t –If,t) f (Xt)=Id,t –If,t) - Technical Analysis (say, past trends) - Statistics - Experience of forecaster - Combination of all of the above. 2/3/2020 2 Forecasting: Basics • A forecast is an expectation –i.e., what we expect on ... LECTURE 9: A MODEL FOR FOREIGN EXCHANGE 1. Foreign Exchange Contracts There was a time, not so long ago, when a U. S. dollar would buy you precisely .4 British pounds sterling1, and a British pound sterling would buy 2.5 U. S. dollars, and you could count on this rate of exchange to persist. By an agreement made in 1944 at the Bretton Woods ... Using Recurrent Neural Networks To Forecasting of Forex V.V.Kondratenko1 and Yu. A Kuperin2 1 Division of Computational Physics, Department of Physics, St.Petersburg State University 2 Laboratory of Complex Systems Theory, Department of Physics, St.Petersburg State University E-mail: [email protected] Abstract This paper reports empirical evidence that a neural networks model is ... models, continue to hang over efforts to develop a forecasting model that applies to a wide set of currencies across a wide span of time and conditions. These difficulties notwithstanding, exchange rate forecasting continues apace, and provides fertile ground for exploring our question. We compare the extent to which several popular models of exchange rate determination can account for market ... We produce forecasts for all 33 exchange rates in the panel, and show that our model produces systematically better forecasts than a random walk for most of the countries, and at all forecast ...

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Weekly Forex Forecast GBPUSD

Forex Weekly Forecast 17 To 23rd Of March 2019 - Traders Academy Club 👉Get Free Access To My Work - http://b.link/vrsponsorship Traders Academy Club presents... Forex Weekly Forecast 27 Of January - 1st Of February 2019 PDF format - https://bit.ly/2CScYt5 The video created by Vladimir Ribakov, a full-time trader & mentor in Traders Academy Club. My weekly forex analysis on forex market for the period from 1 - 5 July, what I see after the restart of US-China deal is to see Gold drop, US will rise up, but not for quite long time, this week ... Starten Sie in die Welt des Forex-Tradings, dem Devisenhandel, in nur 20 Sekunden! Wenn Sie am Handel mit Forex & CFD interessiert sind, schauen Sie sich uns... Fibo Warisan can Forecast market Start and Ending sharply. Our International telegram Link :- https://telegram.me/joinchat/CyymQkF9F8gJkqzWj0S68w Our Malaysi... In this video, you will learn how to find out the 3 month and 4 monthly moving average for demand forecasting. Weekly Forex Forecast EURUSD - Duration: 7 ... How To Convert pdf to word without software - Duration: 9:04. karim hamdadi Recommended for you. 9:04. How To Insert Image Into Another Image Using ... GBP USD Technical Analysis and Forecast. GBP/USD Chart Setup - Forex EZ Trading - Duration: 74 seconds. The way to use the weekly market analysis and weekly forex forecast is very simple. I set my trading directions and lay down a plan for the upcoming week. At that point I’m following the ... PDF format - https://bit.ly/2NbUkkI Traders Academy Club presents – Weekly Forecast Video The video is created by Vladimir Ribakov, a full-time trader & mentor in Traders Academy Club.

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