Forex Point and Figure Trading by Giler Kong - Issuu

No, the British did not steal $45 trillion from India

This is an updated copy of the version on BadHistory. I plan to update it in accordance with the feedback I got.
I'd like to thank two people who will remain anonymous for helping me greatly with this post (you know who you are)
Three years ago a festschrift for Binay Bhushan Chaudhuri was published by Shubhra Chakrabarti, a history teacher at the University of Delhi and Utsa Patnaik, a Marxist economist who taught at JNU until 2010.
One of the essays in the festschirt by Utsa Patnaik was an attempt to quantify the "drain" undergone by India during British Rule. Her conclusion? Britain robbed India of $45 trillion (or £9.2 trillion) during their 200 or so years of rule. This figure was immensely popular, and got republished in several major news outlets (here, here, here, here (they get the number wrong) and more recently here), got a mention from the Minister of External Affairs & returns 29,100 results on Google. There's also plenty of references to it here on Reddit.
Patnaik is not the first to calculate such a figure. Angus Maddison thought it was £100 million, Simon Digby said £1 billion, Javier Estaban said £40 million see Roy (2019). The huge range of figures should set off some alarm bells.
So how did Patnaik calculate this (shockingly large) figure? Well, even though I don't have access to the festschrift, she conveniently has written an article detailing her methodology here. Let's have a look.
How exactly did the British manage to diddle us and drain our wealth’ ? was the question that Basudev Chatterjee (later editor of a volume in the Towards Freedom project) had posed to me 50 years ago when we were fellow-students abroad.
This is begging the question.
After decades of research I find that using India’s commodity export surplus as the measure and applying an interest rate of 5%, the total drain from 1765 to 1938, compounded up to 2016, comes to £9.2 trillion; since $4.86 exchanged for £1 those days, this sum equals about $45 trillion.
This is completely meaningless. To understand why it's meaningless consider India's annual coconut exports. These are almost certainly a surplus but the surplus in trade is countered by the other country buying the product (indeed, by definition, trade surpluses contribute to the GDP of a nation which hardly plays into intuitive conceptualisations of drain).
Furthermore, Dewey (2019) critiques the 5% interest rate.
She [Patnaik] consistently adopts statistical assumptions (such as compound interest at a rate of 5% per annum over centuries) that exaggerate the magnitude of the drain
Moving on:
The exact mechanism of drain, or transfers from India to Britain was quite simple.
Convenient.
Drain theory possessed the political merit of being easily grasped by a nation of peasants. [...] No other idea could arouse people than the thought that they were being taxed so that others in far off lands might live in comfort. [...] It was, therefore, inevitable that the drain theory became the main staple of nationalist political agitation during the Gandhian era.
- Chandra et al. (1989)
The key factor was Britain’s control over our taxation revenues combined with control over India’s financial gold and forex earnings from its booming commodity export surplus with the world. Simply put, Britain used locally raised rupee tax revenues to pay for its net import of goods, a highly abnormal use of budgetary funds not seen in any sovereign country.
The issue with figures like these is they all make certain methodological assumptions that are impossible to prove. From Roy in Frankema et al. (2019):
the "drain theory" of Indian poverty cannot be tested with evidence, for several reasons. First, it rests on the counterfactual that any money saved on account of factor payments abroad would translate into domestic investment, which can never be proved. Second, it rests on "the primitive notion that all payments to foreigners are "drain"", that is, on the assumption that these payments did not contribute to domestic national income to the equivalent extent (Kumar 1985, 384; see also Chaudhuri 1968). Again, this cannot be tested. [...] Fourth, while British officers serving India did receive salaries that were many times that of the average income in India, a paper using cross-country data shows that colonies with better paid officers were governed better (Jones 2013).
Indeed, drain theory rests on some very weak foundations. This, in of itself, should be enough to dismiss any of the other figures that get thrown out. Nonetheless, I felt it would be a useful exercise to continue exploring Patnaik's take on drain theory.
The East India Company from 1765 onwards allocated every year up to one-third of Indian budgetary revenues net of collection costs, to buy a large volume of goods for direct import into Britain, far in excess of that country’s own needs.
So what's going on here? Well Roy (2019) explains it better:
Colonial India ran an export surplus, which, together with foreign investment, was used to pay for services purchased from Britain. These payments included interest on public debt, salaries, and pensions paid to government offcers who had come from Britain, salaries of managers and engineers, guaranteed profts paid to railway companies, and repatriated business profts. How do we know that any of these payments involved paying too much? The answer is we do not.
So what was really happening is the government was paying its workers for services (as well as guaranteeing profits - to promote investment - something the GoI does today Dalal (2019), and promoting business in India), and those workers were remitting some of that money to Britain. This is hardly a drain (unless, of course, Indian diaspora around the world today are "draining" it). In some cases, the remittances would take the form of goods (as described) see Chaudhuri (1983):
It is obvious that these debit items were financed through the export surplus on merchandise account, and later, when railway construction started on a large scale in India, through capital import. Until 1833 the East India Company followed a cumbersome method in remitting the annual home charges. This was to purchase export commodities in India out of revenue, which were then shipped to London and the proceeds from their sale handed over to the home treasury.
While Roy's earlier point argues better paid officers governed better, it is honestly impossible to say what part of the repatriated export surplus was a drain, and what was not. However calling all of it a drain is definitely misguided.
It's worth noting that Patnaik seems to make no attempt to quantify the benefits of the Raj either, Dewey (2019)'s 2nd criticism:
she [Patnaik] consistently ignores research that would tend to cut the economic impact of the drain down to size, such as the work on the sources of investment during the industrial revolution (which shows that industrialisation was financed by the ploughed-back profits of industrialists) or the costs of empire school (which stresses the high price of imperial defence)

Since tropical goods were highly prized in other cold temperate countries which could never produce them, in effect these free goods represented international purchasing power for Britain which kept a part for its own use and re-exported the balance to other countries in Europe and North America against import of food grains, iron and other goods in which it was deficient.
Re-exports necessarily adds value to goods when the goods are processed and when the goods are transported. The country with the largest navy at the time would presumably be in very good stead to do the latter.
The British historians Phyllis Deane and WA Cole presented an incorrect estimate of Britain’s 18th-19th century trade volume, by leaving out re-exports completely. I found that by 1800 Britain’s total trade was 62% higher than their estimate, on applying the correct definition of trade including re-exports, that is used by the United Nations and by all other international organisations.
While interesting, and certainly expected for such an old book, re-exporting necessarily adds value to goods.
When the Crown took over from the Company, from 1861 a clever system was developed under which all of India’s financial gold and forex earnings from its fast-rising commodity export surplus with the world, was intercepted and appropriated by Britain. As before up to a third of India’s rising budgetary revenues was not spent domestically but was set aside as ‘expenditure abroad’.
So, what does this mean? Britain appropriated all of India's earnings, and then spent a third of it aboard? Not exactly. She is describing home charges see Roy (2019) again:
Some of the expenditures on defense and administration were made in sterling and went out of the country. This payment by the government was known as the Home Charges. For example, interest payment on loans raised to finance construction of railways and irrigation works, pensions paid to retired officers, and purchase of stores, were payments in sterling. [...] almost all money that the government paid abroad corresponded to the purchase of a service from abroad. [...] The balance of payments system that emerged after 1800 was based on standard business principles. India bought something and paid for it. State revenues were used to pay for wages of people hired abroad, pay for interest on loans raised abroad, and repatriation of profits on foreign investments coming into India. These were legitimate market transactions.
Indeed, if paying for what you buy is drain, then several billions of us are drained every day.
The Secretary of State for India in Council, based in London, invited foreign importers to deposit with him the payment (in gold, sterling and their own currencies) for their net imports from India, and these gold and forex payments disappeared into the yawning maw of the SoS’s account in the Bank of England.
It should be noted that India having two heads was beneficial, and encouraged investment per Roy (2019):
The fact that the India Office in London managed a part of the monetary system made India creditworthy, stabilized its currency, and encouraged foreign savers to put money into railways and private enterprise in India. Current research on the history of public debt shows that stable and large colonies found it easier to borrow abroad than independent economies because the investors trusted the guarantee of the colonist powers.

Against India’s net foreign earnings he issued bills, termed Council bills (CBs), to an equivalent rupee value. The rate (between gold-linked sterling and silver rupee) at which the bills were issued, was carefully adjusted to the last farthing, so that foreigners would never find it more profitable to ship financial gold as payment directly to Indians, compared to using the CB route. Foreign importers then sent the CBs by post or by telegraph to the export houses in India, that via the exchange banks were paid out of the budgeted provision of sums under ‘expenditure abroad’, and the exporters in turn paid the producers (peasants and artisans) from whom they sourced the goods.
Sunderland (2013) argues CBs had two main roles (and neither were part of a grand plot to keep gold out of India):
Council bills had two roles. They firstly promoted trade by handing the IO some control of the rate of exchange and allowing the exchange banks to remit funds to India and to hedge currency transaction risks. They also enabled the Indian government to transfer cash to England for the payment of its UK commitments.

The United Nations (1962) historical data for 1900 to 1960, show that for three decades up to 1928 (and very likely earlier too) India posted the second highest merchandise export surplus in the world, with USA in the first position. Not only were Indians deprived of every bit of the enormous international purchasing power they had earned over 175 years, even its rupee equivalent was not issued to them since not even the colonial government was credited with any part of India’s net gold and forex earnings against which it could issue rupees. The sleight-of-hand employed, namely ‘paying’ producers out of their own taxes, made India’s export surplus unrequited and constituted a tax-financed drain to the metropolis, as had been correctly pointed out by those highly insightful classical writers, Dadabhai Naoroji and RCDutt.
It doesn't appear that others appreciate their insight Roy (2019):
K. N. Chaudhuri rightly calls such practice ‘confused’ economics ‘coloured by political feelings’.

Surplus budgets to effect such heavy tax-financed transfers had a severe employment–reducing and income-deflating effect: mass consumption was squeezed in order to release export goods. Per capita annual foodgrains absorption in British India declined from 210 kg. during the period 1904-09, to 157 kg. during 1937-41, and to only 137 kg by 1946.
Dewey (1978) points out reliability issues with Indian agriculutural statistics, however this calorie decline persists to this day. Some of it is attributed to less food being consumed at home Smith (2015), a lower infectious disease burden Duh & Spears (2016) and diversified diets Vankatesh et al. (2016).
If even a part of its enormous foreign earnings had been credited to it and not entirely siphoned off, India could have imported modern technology to build up an industrial structure as Japan was doing.
This is, unfortunately, impossible to prove. Had the British not arrived in India, there is no clear indication that India would've united (this is arguably more plausible than the given counterfactual1). Had the British not arrived in India, there is no clear indication India would not have been nuked in WW2, much like Japan. Had the British not arrived in India, there is no clear indication India would not have been invaded by lizard people, much like Japan. The list continues eternally.
Nevertheless, I will charitably examine the given counterfactual anyway. Did pre-colonial India have industrial potential? The answer is a resounding no.
From Gupta (1980):
This article starts from the premise that while economic categories - the extent of commodity production, wage labour, monetarisation of the economy, etc - should be the basis for any analysis of the production relations of pre-British India, it is the nature of class struggles arising out of particular class alignments that finally gives the decisive twist to social change. Arguing on this premise, and analysing the available evidence, this article concludes that there was little potential for industrial revolution before the British arrived in India because, whatever might have been the character of economic categories of that period, the class relations had not sufficiently matured to develop productive forces and the required class struggle for a 'revolution' to take place.
A view echoed in Raychaudhuri (1983):
Yet all of this did not amount to an economic situation comparable to that of western Europe on the eve of the industrial revolution. Her technology - in agriculture as well as manufacturers - had by and large been stagnant for centuries. [...] The weakness of the Indian economy in the mid-eighteenth century, as compared to pre-industrial Europe was not simply a matter of technology and commercial and industrial organization. No scientific or geographical revolution formed part of the eighteenth-century Indian's historical experience. [...] Spontaneous movement towards industrialisation is unlikely in such a situation.
So now we've established India did not have industrial potential, was India similar to Japan just before the Meiji era? The answer, yet again, unsurprisingly, is no. Japan's economic situation was not comparable to India's, which allowed for Japan to finance its revolution. From Yasuba (1986):
All in all, the Japanese standard of living may not have been much below the English standard of living before industrialization, and both of them may have been considerably higher than the Indian standard of living. We can no longer say that Japan started from a pathetically low economic level and achieved a rapid or even "miraculous" economic growth. Japan's per capita income was almost as high as in Western Europe before industrialization, and it was possible for Japan to produce surplus in the Meiji Period to finance private and public capital formation.
The circumstances that led to Meiji Japan were extremely unique. See Tomlinson (1985):
Most modern comparisons between India and Japan, written by either Indianists or Japanese specialists, stress instead that industrial growth in Meiji Japan was the product of unique features that were not reproducible elsewhere. [...] it is undoubtably true that Japan's progress to industrialization has been unique and unrepeatable
So there you have it. Unsubstantiated statistical assumptions, calling any number you can a drain & assuming a counterfactual for no good reason gets you this $45 trillion number. Hopefully that's enough to bury it in the ground.
1. Several authors have affirmed that Indian identity is a colonial artefact. For example see Rajan 1969:
Perhaps the single greatest and most enduring impact of British rule over India is that it created an Indian nation, in the modern political sense. After centuries of rule by different dynasties overparts of the Indian sub-continent, and after about 100 years of British rule, Indians ceased to be merely Bengalis, Maharashtrians,or Tamils, linguistically and culturally.
or see Bryant 2000:
But then, it would be anachronistic to condemn eighteenth-century Indians, who served the British, as collaborators, when the notion of 'democratic' nationalism or of an Indian 'nation' did not then exist. [...] Indians who fought for them, differed from the Europeans in having a primary attachment to a non-belligerent religion, family and local chief, which was stronger than any identity they might have with a more remote prince or 'nation'.

Bibliography

Chakrabarti, Shubra & Patnaik, Utsa (2018). Agrarian and other histories: Essays for Binay Bhushan Chaudhuri. Colombia University Press
Hickel, Jason (2018). How the British stole $45 trillion from India. The Guardian
Bhuyan, Aroonim & Sharma, Krishan (2019). The Great Loot: How the British stole $45 trillion from India. Indiapost
Monbiot, George (2020). English Landowners have stolen our rights. It is time to reclaim them. The Guardian
Tsjeng, Zing (2020). How Britain Stole $45 trillion from India with trains | Empires of Dirt. Vice
Chaudhury, Dipanjan (2019). British looted $45 trillion from India in today’s value: Jaishankar. The Economic Times
Roy, Tirthankar (2019). How British rule changed India's economy: The Paradox of the Raj. Palgrave Macmillan
Patnaik, Utsa (2018). How the British impoverished India. Hindustan Times
Tuovila, Alicia (2019). Expenditure method. Investopedia
Dewey, Clive (2019). Changing the guard: The dissolution of the nationalist–Marxist orthodoxy in the agrarian and agricultural history of India. The Indian Economic & Social History Review
Chandra, Bipan et al. (1989). India's Struggle for Independence, 1857-1947. Penguin Books
Frankema, Ewout & Booth, Anne (2019). Fiscal Capacity and the Colonial State in Asia and Africa, c. 1850-1960. Cambridge University Press
Dalal, Sucheta (2019). IL&FS Controversy: Centre is Paying Up on Sovereign Guarantees to ADB, KfW for Group's Loan. TheWire
Chaudhuri, K.N. (1983). X - Foreign Trade and Balance of Payments (1757–1947). Cambridge University Press
Sunderland, David (2013). Financing the Raj: The City of London and Colonial India, 1858-1940. Boydell Press
Dewey, Clive (1978). Patwari and Chaukidar: Subordinate officials and the reliability of India’s agricultural statistics. Athlone Press
Smith, Lisa (2015). The great Indian calorie debate: Explaining rising undernourishment during India’s rapid economic growth. Food Policy
Duh, Josephine & Spears, Dean (2016). Health and Hunger: Disease, Energy Needs, and the Indian Calorie Consumption Puzzle. The Economic Journal
Vankatesh, P. et al. (2016). Relationship between Food Production and Consumption Diversity in India – Empirical Evidences from Cross Section Analysis. Agricultural Economics Research Review
Gupta, Shaibal (1980). Potential of Industrial Revolution in Pre-British India. Economic and Political Weekly
Raychaudhuri, Tapan (1983). I - The mid-eighteenth-century background. Cambridge University Press
Yasuba, Yasukichi (1986). Standard of Living in Japan Before Industrialization: From what Level did Japan Begin? A Comment. The Journal of Economic History
Tomblinson, B.R. (1985). Writing History Sideways: Lessons for Indian Economic Historians from Meiji Japan. Cambridge University Press
Rajan, M.S. (1969). The Impact of British Rule in India. Journal of Contemporary History
Bryant, G.J. (2000). Indigenous Mercenaries in the Service of European Imperialists: The Case of the Sepoys in the Early British Indian Army, 1750-1800. War in History
submitted by GaslightEveryone to u/GaslightEveryone [link] [comments]

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]

Is Karatbit and Karatbars a scam?

On Tuesday 16th July, just a few weeks ago I was invited to attend a Karatbit, Karatbars/Karatbank presentation. The presentation was touting everything including a blockchain mobile phone. Someone had approached me over the weekend to investigate an investment, they had made with Karatbit/Karatbars. I attended the presentation with some research which, to be honest, was not that favourable to the company but nevertheless still went with an open mind.
KaratBank, a Singapore-based financial organization, has propelled another digital currency that it claims is bound to real physical gold. Is this a progressive thought – or a trick?
KaratBank, an organization located in Singapore, has quite recently declared the dispatch of KaratBank Coins (KBC), another digital currency it said is attached to gold. Be that as it may, not just the cost of gold, as different monetary forms — to real bits of gold: they're embedded in plastic cards or banknotes. In any event, that is the way it appears upon first sight.
KaratBank is a sister company of KaratBars International, located in Germany. KaratBars really sells gold in exceptionally small quantities (like 0.1g to 1g bullions), inserted into plastic cards (Karatbars) or money like notes (CashGold). The notes are famously overpriced: back when 1 gram of gold was $40, the 1g CashGold note cost $65.
As per KaratBank whitepaper, 10,000 KBC can be traded for 0.1g CashGold notes.
The initial coin offering kicked off earlier this year and proceeded until March 21, with the ICO starting March 22 (1 KBC = $0.05), Coin Telegraph reports.
Be that as it may, KaratBars International as an organization is emphatically connected with scams. A basic search for KaratBars on Google returns three connections with the word "scam" in them on the first page. KaratBars was prohibited in Canada in 2014 over an Autorité des marchés agents (AMF) with a Scam warning.
The Canadian government found that KaratBars executes some kind of multi-layered marketing (MLM), or "pyramid" scheme organisation that urged individuals to get new recruits and profit from their sales, promising a return of $15,000 to $136,000 every month.
In any case, Is KaratBank is a different story? All things considered, yes and no. Upon a more intensive look at the organization's whitepaper, one finds the following:
"United States of America citizens, residents (tax or otherwise) or green card holders, as well as residents of Canada, the People's Republic of China or the Republic of Singapore, are not qualified to partake in the KaratBank ICO."
As indicated by the Behind MLM site, the explanation behind this may lie in the way that those nations have actualized strict regulation on ICOs, and KaratBank does not have any desire to have anything to do with them.
"ICOs are not unlawful in the US or Canada. In the US, however, ICOs are ordinarily viewed as securities and require registration with the [Securities and Exchange Commission]," the site reads. "Singapore hasn't prohibited ICOs however it is one of the nations KaratBars International works in through the shell companies KaratPay and KaratBars Singapore. Singapore regulators closing those organizations down would cripple KaratBars International. The board most likely figure it's best not to take any risks."
To work lawfully in any purview, KaratBars International would need to register itself with the proper securities regulator in that jurisdiction, which the organization appears to need to abstain from, raising doubts.
From one's point of view what is disheartening is that blockchain is a great new technology and companies like this seem to mix their existing business with cryptocurrencies. Knowing full well that the general public does not really understand cryptocurrencies, let alone blockchain or Distributed Ledger Technology (DLT). As a blockchain consultant, one feels obligated to pose some questions anyone thinking of getting involved should be asking.
At the presentation, I heard the presenters say “ Karatbars is giving its members the opportunity to buy gold in small quantities. They also encourage you to save in gold instead of paper money. This can easily be done by buying as little as 0.1 gram of gold or 1 gram - 2.5 gram or 5 grams.”
They said members can keep their gold in Karatbars' vault or ask them to send it to you. Cash gold is the most popular form of buying gold as the gold is embedded in a banknote. 24kt gold 99.9% pure makes it easier for anyone to accumulate wealth.
Karatbars is also involved in cryptocurrency and got their own coins, namely KBC and KCB coins. I'm going to get very deep into this, but the main thing to remember is that they say, “these coins are increasing in value and that it is backed by gold”. whereas and another Cryptocurrency is backed by nothing.
As a self-proclaimed proponent of blockchain and a graduate of Digital Forensics, I feel obligated to say a few words about this presentation on Karatbit or at least as a conscious citizen of this global world of technology users. Blockchain is a magnificent emerging technology that can be harnessed to do so many things. But most importantly it is a technology that provides one single source of truth. If groups are using this single source of truth technology to spread untruths, someone concerned must come out to say something. Blockchain is a technology that can put everyone on an even playing field but it seems very few understand it. The individuals with even the fleeting basic understanding can influence the general public perception of cryptocurrencies. This leads me to ask a great quote from a book called Richest Man in Babylon …. “if you want advice on investing in expensive jewels, why would you go to a butcher?”
The following is what the masses are being manipulated to attach their hopes and dreams. It is that “a further drop in the value of Bitcoin and other cryptocurrencies has recently left investors nursing heavy losses. Many proponents are holding out for a new breakout “if their digital assets can go mainstream.”
The most important part of that statement is “if their digital assets can go mainstream”. This made me ask some questions about Karatbit and this is what I came up with.
Something is fishy!! Can someone clarify the following?
Claim 1: Gold mine worth $900 million provides security.
Can’t find any official source as proof.
Reference: https://www.youtube.com/watch?v=TyKQIckXyIU
Claim 2: Backed by a gold mine in Africa
Can’t find any official source as proof.
Reference: https://www.youtube.com/watch?v=d5Q3ZvR4b04
Claim 3: Audit report by MM Revisors for a gold mine in Madagascar
Can’t find proof that MM Revisors exists. Not sure if this report was published by Karatbars Int (can’t find it on their official website), but this is being circulated by some investors as if it were.
Reference: https://karatbars-me.webnode.es/\_files/200000070-01d6002d18/audit.pdf
Claim 4: Karatcoin Bank is a fully licensed crypto bank and is situated in Miami
Can’t find proof that they are registered as a licensed financial institute in Miami, Florida.
Can’t find Karatcoin Bank as a registered corporation, but found Karat Coin Corp.
Reference: http://search.sunbiz.org/Inquiry/CorporationSearch/SearchResults?inquiryType=EntityName&searchNameOrder=KARATBANK&searchTerm=Karatbank
Reference: https://www.youtube.com/watch?v=YXip2Fizz5U&t=152s
Claim 5: Not a pyramid scheme
Karatbit describes this as an affiliate program but clearly is a pyramid scheme at best, see links below;
Canada: https://www.newswire.ca/news-releases/karatbars-quebec-activities-covered-by-prohibition-orders-514201571.html
Namibia: https://economist.com.na/43874/extra/karatbars-international-is-a-scamsays-central-bank/
Netherlands: https://www.afm.nl/en/nieuws/2014/mei/waarschuwing-karatbars
Claim 6: 100KBC = 1g of Gold at $40 per gram (1 KBC = $0.40) (guaranteed)
Total supply = 12,000,000,000 KBC (can’t find figures of circulating, so using supply instead)
Total gold needed to cover buy back of all coins:
12,000,000,000 / 100 = 120 000 000g = 120 tons (South Africa as a whole produced 139.9 tons of Gold in 2017).
Total money needed to buy back all the coins:
120 000 000g x $40 = $4.8 Billion
Can’t find proof that they have 120 tons of gold in storage (or backed up by the mines as claimed) or that they are at least worth $4.8 Billion to buy the gold?
Taking a more conservative approach:
According to icobench.com, they raised $100 000 000 with their ICO from 60% of the total supply.
Let’s assume the 60% of 12,000,000,000 is in circulation. This equals to 7,200,000,000 KBC.
Total gold needed for the buyback of 7,200,000,000 KBC:
7,200,000,000 / 100 = 72 000 000g = 72 tons
Total money needed to buy back all coins:
72 000 000g x $40 = $2.88 Billion
Loss for buying back the KBC that were sold during the ICO:
$100,000,000 - $2,880,000,000 = - $2,780,000,000
A potential loss of $2,78 Billion!!! Or am I taking crazy pills?
Reference: https://www.youtube.com/watch?v=KgeHjhlMfn0
Reference: https://icobench.com/ico/karatgold-coin
Claim 7: This Forbes.com article gives credibility to the KBC coin
This article was written by a Contributor.
Reference: https://www.forbes.com/sites/joresablount/2019/05/31/10-blockchain-companies-to-watch-in-2019/#308b507e543f
There is no traditional editing of contributors’ copy, at least not prior to publishing. If a story gets hot or makes the homepage, a producer will “check it more carefully,” DVorkin said.
Reference: https://www.poynter.org/reporting-editing/2012/what-the-forbes-model-of-contributed-content-means-for-journalism/
“Blogging for Forbes requires being what is commonly referred to as a "self-starter."
So far, nobody has said, "Um, you can't do that," or, "Oh, my God, no!"
Reference: https://www.forbes.com/sites/susannahbreslin/2011/04/06/how-to-become-a-forbes-blogge#231bb9972862
“Warning over 'scammers paradise' as watchdog reveals victims lost £27m to bitcoin, cryptocurrency and forex frauds last year”
• Some 1,850 cases were reported to Action Fraud, a 250% increase on 2017-18
• Victims lost an average of £14,600 - with fewer than 1 in 20 getting money back
• Investors are often initially told they've made a profit
• They are then encouraged to put in more money - at which point the fraudsters run off with their cash
Potential victims have been warned over bogus online 'get rich quick' schemes as it emerged people lost more than £27million to cryptocurrency and foreign exchange scams last year.
Fraudsters promise high returns to those who invest, according to Action Fraud and the Financial Conduct Authority.
Victims lost an average of £14,600 in 2018-19 and stand little chance of getting their money back.
Reports of cryptocurrency and forex investment scams increased by nearly 250 per cent in 2017-18, from 530 to nearly 1,850.
The scams work by criminals promoting get-rich-quick online trading platforms through social media. Posts often use fake celebrity endorsements and images of luxury items like expensive watches and cars.
Beat the scammers:
These then link to professional-looking websites where consumers are persuaded to invest.
Often investors are led to believe their first investment has successfully returned a profit, and are then enticed to invest more money or introduce friends in return for greater profits.
But the returns stop, the customer account is closed, and the scammer disappears with no further contact.
'Anyone handing over their hard-earned cash should make sure they understand what they're getting into, they've checked it's a legitimate investment, and not rely on hype and excitement from friends or social media.
'Investing isn't a get-rich-quick scheme - and anything that uses fear of missing out or requires you to invest before thinking is best to be avoided.'
Those considering an investment to check the following for tips on how to avoid investment fraud at www.fca.org.uk/scamsmart.
Scammers can be very convincing so always do your own research into any firm you are considering investing with, to make sure that they are the real deal.
'It's vital that people carry out the necessary checks to ensure that an investment they're considering is legitimate.
UK consumers are being increasingly targeted by crypto asset-related investment scams.
Certain crypto assets, like Bitcoin and Ether (also known as cryptocurrencies), are not regulated in the UK. This means that buying, selling or transferring these crypto-assets falls outside FCA remit. The same is true for the operation of a cryptocurrency exchange.
However, some types of crypto-asset products may be or may involve regulated investments depending on their nature and how they are structured. For example, firms that sell regulated investments with an underlying crypto asset element may need to be authorised by the FCA to do so.
In recent months, the FCA claims it has received an increasing number of reports about crypto-asset investment scams. Some of them may involve regulated activities, others don’t, but all use similar tactics.
How crypto-asset investment scams work
Cryptoasset fraudsters tend to advertise on social media – often using the images of celebrities or well-known individuals to promote cryptocurrency investments. In this case, laughably they said KaratBit was endorsed by Barak Obama’s sister. Who is she and what does she know about cryptocurrencies and blockchain? The ads then link to professional-looking websites. Consumers are then persuaded to make investments with the firm using cryptocurrencies or traditional currencies.
The firms operating the scams are usually based outside the UK but will claim to have a UK presence, often a prestigious City of London address.
Scam firms can manipulate software to distort prices and investment returns. They may scam people into buying the non-existent crypto asset. They are also known to suddenly close consumers’ online accounts and refuse to transfer the funds to them or ask for more money before the funds can be transferred.
Action Fraud has also issued a warning on cryptocurrency scams.
How to protect yourself
Be wary of adverts online and on social media promising high returns on investments in a crypto asset or crypto asset-related products.
Most firms advertising and selling investments in crypto-assets are not authorised by the FCA. This means that if you invest in certain crypto assets you will not have access to the Financial Ombudsman Service or the Financial Services Compensation Scheme if things go wrong.
The FCA doesn’t regulate crypto assets like Bitcoin or Ether which are vastly the most recognized cryptocurrencies, let alone KBC, they do regulate certain crypto-asset derivatives (such as futures contracts, CFDs and options), as well as those crypto assets I would consider securities. A firm must be authorised by FCA to advertise or sell these products in the UK – check FCA Register to make sure the firm is authorised. You can also check the FCA Warning List of firms to avoid.
You should do further research on the product you are considering and the firm you are considering investing with. Check with Companies House to see if the firm is registered as a UK company and for directors' names. To see if others have posted any concerns, search online for the firm's name, directors' names and the product you are considering.
If you’ve already decided you want to invest in gold, this might not be a bad company to side with. But if you’re just looking for an opportunity to earn a sustainable income and become financially independent, there are better options out there.
submitted by fourfingaz to u/fourfingaz [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
Generated with BBoe's Subreddit Stats (Donate)
submitted by subreddit_stats to subreddit_stats [link] [comments]

My starting point with links

I figured why wait for your response here is what I sent one guy during the week.
profit.ly - join and follow some individuals that have 50%+ win trade percentage. free to join to brows around the forums.
http://forexwinners.ru/forex/category/tools/full-courses/ mostly forex stuff but you can find a lot of tim sykes dvds here. just download from the links provided.
finviz.com for scans if i didnt mention that.
dojispace.com i got a quick education on dojis from that place.
learn about bollinger bands they are helpful for intraday trading.
tradesystempro.com - tons of books. learn about doji's bollinger bands.
http://torrentz.eu/search?q=fous cameron fous very educational. not my style but i believe there is always something to learn from someone.
my style is more breakouts and then watch them thru the day (if my job wasnt 5 days a week i would) and then trade intraday for more profits like warrior trading. i would love to pay for his dvd package but youtube will have to do.
http://stockcharts.com/school/doku.php?id=chart_school this place is loads of info. it's like a college class online. everything you need is here or at least all the basics and you can later dive into things you want to know for your style.
one thing i learned from tim sykes and time grattani and nate machaud, is who cares what the company does. trade the ticker not the company. this holds 100% true if you are to be a day trader. you are chasing profits and not investing millions to make more millions long term. thats my opinion anyway.
zacks.com if you want to trade based on earnings but that doesn't always mean a good report will lead to an uptick in the chart.
this also has tims dvd's http://www.bengforum.com/Thread-GET-Timothy-Sykes-Trading-Strategy-Full-Course-8-DVDs havent tried to download from it so i don't know if it will get you all of them or how long it would take.
http://www.torrenthound.com/hash/b39fa669ddcf670758695600259d91be78a2af85/torrent-info/Investors-Live%253A-Textbook-Trading-DVD-by-Nathan-Michaud
the thing about nates dvd is he has a lot of good info but some of it is silence and watching his trade from some day at 10x the speed. http://torrentz.eu/4f71b50dc827111e7d6338901279d1df9ce20670 this is the second dvd in nates series
interactivebrokers.com is 99 cents a trade.
http://www.elitetrader.com/et/index.php?threads/trading-tickers-dvd-by-tim-grittani-99-huge-discount.296300/ this is tim grittani's dvd someone is selling on profit.ly it is for the streaming version. if you get it let me know, i might want to get it too if it is worth it.
just stumbled on this. it may be helpful and money saving. http://www.tradingdvdshop.com/
i found a similar place that was selling dvd's cheap but it must be on the history on my desktop. if i get a chance i can get that to you. probably thursday or friday night. but this should be plenty. don't get overwhelmed. it should be like going to school. watch a dvd or so for an hour. take a break. take notes.and finish one before you start the next. i would suggest also learn more about each tool the dvd's tell you about like bollinger bands after you finish the dvd or what ever interests you.
i personally use bollinger bands. exponential moving average (ema) for 13 day period like cameron fous. and then i stumbled on a volume weighted MACD. anything helps but too much clutters your screen.
when you learn more then move to learning how to create custom scans to meet criteria you like. that stockcharts chart school is a lot of reading but it is organized.
those are basically the resources ive used so far. like i said im new too. but im determined to make this part of my income. especially living in cali and i can be up and trade before work when stocks move the most. it's a no brainer. if i wake up that is. that's been a struggle someday. keep in touch tell me how things are going. maybe you could teach me somethings too. post your daily watchlist in the pennystocks forum and learn from everyone else too. it's a good forum so far.
I also have a book from warrior trading as a pdf. I can email that to you if you like
This I basically copied and pasted what I have sent to a few newbies like myself. To me it is a good starting point for your own style.
submitted by Gspot_1300135 to pennystocks [link] [comments]

Point and Figure charts - YouTube Better Know An Indicator: Point And Figure Charts - YouTube Core Point and Figure Chart Patterns Point and Figure Chart Analysis with P&F Chart Explained ... Arthur Hill  Point and Figure Charting (Part 1) - YouTube Point And Figure Charting Basics - YouTube Learn Point & Figure charts and know how to trade them ...

Please order your printed copy of the book HERE! THE POINT AND FIGURE METHOD OF ANTICIPATING STOCK PRICE MOVEMENTS - Volume 1 . PREFACE TO THE ONLINE EDITION. As we now publish this classic stock market book online in the year 2009 I cannot help but to draw parallells between DeVillier's and Taylor's foreword and the market we are facing today. When the book was first published, in the ... As you can see, Point and Figure charts assign a value to each square on the chart, which P&F chartists call ‘boxes’. In the example above, each square or box is worth 1 point. As the price rises or falls by 1 point or more, new squares are filled. Any price change less than 1 point is therefore ignored. The value assigned to the box ... Point and figure (p&f) charts provide a simple, yet disciplined method of identifying current or emerging trends in stock prices. This brief guide aims to familiarise the investor with the basic concepts behind p&f charts and highlights some of the benefits from using them in one™s investment procedure. The balance between buyers and sellers P&F charts map out the relationship between supply ... Read The Definitive Guide to Point and Figure by Jeremy Du Plessis; Download PnFv4.zip and PnF_Instructions.txt; Extract PnFv4.zip into your Metatrader folder; Read PnF_Instructions.txt; If you've followed the instructions you should be able to understand and plot Point and Figure charts in Excel.You should then be able to perform simple Point and Figure analysis. Cheap Forex Trading Plan Template Pdf And Point And Figure Forex cookbook A Quick Guide To Trading Forex: Book: pdf: 1.446 (unknown) Application Of Multi-Agent Games To The Prediction Of Financial Time-Series: Article: pdf: 170 (unknown) Candlestick And Patterns in Forex: Article: pdf: 4.895 (unknown) Candlestick Trading Forum FAQ: Article: doc: 24 (unknown) Chart Patterns Tutorial: Article: doc: 182 (unknown) Choosing A Trading System That Actually Works: Article ... Forex Point and Figure Trading ATTENTION TRADERS: If you’re sick and tired of losing money in the markets, then allow me to offer you an alternative that actually works!

[index] [15305] [5547] [4440] [14263] [12411] [8806] [266] [6240] [15361] [19073]

Point and Figure charts - YouTube

This is a webinar on Point And Figure Charting Basics presented by Bull's-Eye Broker. You can download a free complimentary trial version of the Point And Fi... BTC Tipjar 12EAXwhbT6JaC2DvGY875SWFMtrzJi8vF1 Follow me on Twitter! https://twitter.com/CarpeNoctom Referral Links Trezor Hardware Wallet - https://buytrezor... I created this video with the YouTube Slideshow Creator (https://www.youtube.com/upload) and content image about Core Point and Figure Chart Patterns,,how to... More Trading Tips for Stock Traders at: http://www.TradingTips.com If you're not already familiar with Point and Figure charts, then prepare to have your min... Point and figure chart analysis aka p&f chart video you'll learn how to use point and figure charts when trading. 📚 Take our FREE courses here: https://bulli... Arthur Hill discusses Point and Figure Charting. Know how P&F charts are constructed and how to trade basic patterns. A Video by Prashant Shah. -----...

https://binary-optiontrade.medeasbwolf.tk