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Everything You Always Wanted To Know About Swaps* (*But Were Afraid To Ask)

Hello, dummies
It's your old pal, Fuzzy.
As I'm sure you've all noticed, a lot of the stuff that gets posted here is - to put it delicately - fucking ridiculous. More backwards-ass shit gets posted to wallstreetbets than you'd see on a Westboro Baptist community message board. I mean, I had a look at the daily thread yesterday and..... yeesh. I know, I know. We all make like the divine Laura Dern circa 1992 on the daily and stick our hands deep into this steaming heap of shit to find the nuggets of valuable and/or hilarious information within (thanks for reading, BTW). I agree. I love it just the way it is too. That's what makes WSB great.
What I'm getting at is that a lot of the stuff that gets posted here - notwithstanding it being funny or interesting - is just... wrong. Like, fucking your cousin wrong. And to be clear, I mean the fucking your *first* cousin kinda wrong, before my Southerners in the back get all het up (simmer down, Billy Ray - I know Mabel's twice removed on your grand-sister's side). Truly, I try to let it slide. I do my bit to try and put you on the right path. Most of the time, I sleep easy no matter how badly I've seen someone explain what a bank liquidity crisis is. But out of all of those tens of thousands of misguided, autistic attempts at understanding the world of high finance, one thing gets so consistently - so *emphatically* - fucked up and misunderstood by you retards that last night I felt obligated at the end of a long work day to pull together this edition of Finance with Fuzzy just for you. It's so serious I'm not even going to make a u/pokimane gag. Have you guessed what it is yet? Here's a clue. It's in the title of the post.
That's right, friends. Today in the neighborhood we're going to talk all about hedging in financial markets - spots, swaps, collars, forwards, CDS, synthetic CDOs, all that fun shit. Don't worry; I'm going to explain what all the scary words mean and how they impact your OTM RH positions along the way.
We're going to break it down like this. (1) "What's a hedge, Fuzzy?" (2) Common Hedging Strategies and (3) All About ISDAs and Credit Default Swaps.
Before we begin. For the nerds and JV traders in the back (and anyone else who needs to hear this up front) - I am simplifying these descriptions for the purposes of this post. I am also obviously not going to try and cover every exotic form of hedge under the sun or give a detailed summation of what caused the financial crisis. If you are interested in something specific ask a question, but don't try and impress me with your Investopedia skills or technical points I didn't cover; I will just be forced to flex my years of IRL experience on you in the comments and you'll look like a big dummy.
TL;DR? Fuck you. There is no TL;DR. You've come this far already. What's a few more paragraphs? Put down the Cheetos and try to concentrate for the next 5-7 minutes. You'll learn something, and I promise I'll be gentle.
Ready? Let's get started.
1. The Tao of Risk: Hedging as a Way of Life
The simplest way to characterize what a hedge 'is' is to imagine every action having a binary outcome. One is bad, one is good. Red lines, green lines; uppie, downie. With me so far? Good. A 'hedge' is simply the employment of a strategy to mitigate the effect of your action having the wrong binary outcome. You wanted X, but you got Z! Frowny face. A hedge strategy introduces a third outcome. If you hedged against the possibility of Z happening, then you can wind up with Y instead. Not as good as X, but not as bad as Z. The technical definition I like to give my idiot juniors is as follows:
Utilization of a defensive strategy to mitigate risk, at a fraction of the cost to capital of the risk itself.
Congratulations. You just finished Hedging 101. "But Fuzzy, that's easy! I just sold a naked call against my 95% OTM put! I'm adequately hedged!". Spoiler alert: you're not (although good work on executing a collar, which I describe below). What I'm talking about here is what would be referred to as a 'perfect hedge'; a binary outcome where downside is totally mitigated by a risk management strategy. That's not how it works IRL. Pay attention; this is the tricky part.
You can't take a single position and conclude that you're adequately hedged because risks are fluid, not static. So you need to constantly adjust your position in order to maximize the value of the hedge and insure your position. You also need to consider exposure to more than one category of risk. There are micro (specific exposure) risks, and macro (trend exposure) risks, and both need to factor into the hedge calculus.
That's why, in the real world, the value of hedging depends entirely on the design of the hedging strategy itself. Here, when we say "value" of the hedge, we're not talking about cash money - we're talking about the intrinsic value of the hedge relative to the the risk profile of your underlying exposure. To achieve this, people hedge dynamically. In wallstreetbets terms, this means that as the value of your position changes, you need to change your hedges too. The idea is to efficiently and continuously distribute and rebalance risk across different states and periods, taking value from states in which the marginal cost of the hedge is low and putting it back into states where marginal cost of the hedge is high, until the shadow value of your underlying exposure is equalized across your positions. The punchline, I guess, is that one static position is a hedge in the same way that the finger paintings you make for your wife's boyfriend are art - it's technically correct, but you're only playing yourself by believing it.
Anyway. Obviously doing this as a small potatoes trader is hard but it's worth taking into account. Enough basic shit. So how does this work in markets?
2. A Hedging Taxonomy
The best place to start here is a practical question. What does a business need to hedge against? Think about the specific risk that an individual business faces. These are legion, so I'm just going to list a few of the key ones that apply to most corporates. (1) You have commodity risk for the shit you buy or the shit you use. (2) You have currency risk for the money you borrow. (3) You have rate risk on the debt you carry. (4) You have offtake risk for the shit you sell. Complicated, right? To help address the many and varied ways that shit can go wrong in a sophisticated market, smart operators like yours truly have devised a whole bundle of different instruments which can help you manage the risk. I might write about some of the more complicated ones in a later post if people are interested (CDO/CLOs, strip/stack hedges and bond swaps with option toggles come to mind) but let's stick to the basics for now.
(i) Swaps
A swap is one of the most common forms of hedge instrument, and they're used by pretty much everyone that can afford them. The language is complicated but the concept isn't, so pay attention and you'll be fine. This is the most important part of this section so it'll be the longest one.
Swaps are derivative contracts with two counterparties (before you ask, you can't trade 'em on an exchange - they're OTC instruments only). They're used to exchange one cash flow for another cash flow of equal expected value; doing this allows you to take speculative positions on certain financial prices or to alter the cash flows of existing assets or liabilities within a business. "Wait, Fuzz; slow down! What do you mean sets of cash flows?". Fear not, little autist. Ol' Fuzz has you covered.
The cash flows I'm talking about are referred to in swap-land as 'legs'. One leg is fixed - a set payment that's the same every time it gets paid - and the other is variable - it fluctuates (typically indexed off the price of the underlying risk that you are speculating on / protecting against). You set it up at the start so that they're notionally equal and the two legs net off; so at open, the swap is a zero NPV instrument. Here's where the fun starts. If the price that you based the variable leg of the swap on changes, the value of the swap will shift; the party on the wrong side of the move ponies up via the variable payment. It's a zero sum game.
I'll give you an example using the most vanilla swap around; an interest rate trade. Here's how it works. You borrow money from a bank, and they charge you a rate of interest. You lock the rate up front, because you're smart like that. But then - quelle surprise! - the rate gets better after you borrow. Now you're bagholding to the tune of, I don't know, 5 bps. Doesn't sound like much but on a billion dollar loan that's a lot of money (a classic example of the kind of 'small, deep hole' that's terrible for profits). Now, if you had a swap contract on the rate before you entered the trade, you're set; if the rate goes down, you get a payment under the swap. If it goes up, whatever payment you're making to the bank is netted off by the fact that you're borrowing at a sub-market rate. Win-win! Or, at least, Lose Less / Lose Less. That's the name of the game in hedging.
There are many different kinds of swaps, some of which are pretty exotic; but they're all different variations on the same theme. If your business has exposure to something which fluctuates in price, you trade swaps to hedge against the fluctuation. The valuation of swaps is also super interesting but I guarantee you that 99% of you won't understand it so I'm not going to try and explain it here although I encourage you to google it if you're interested.
Because they're OTC, none of them are filed publicly. Someeeeeetimes you see an ISDA (dsicussed below) but the confirms themselves (the individual swaps) are not filed. You can usually read about the hedging strategy in a 10-K, though. For what it's worth, most modern credit agreements ban speculative hedging. Top tip: This is occasionally something worth checking in credit agreements when you invest in businesses that are debt issuers - being able to do this increases the risk profile significantly and is particularly important in times of economic volatility (ctrl+f "non-speculative" in the credit agreement to be sure).
(ii) Forwards
A forward is a contract made today for the future delivery of an asset at a pre-agreed price. That's it. "But Fuzzy! That sounds just like a futures contract!". I know. Confusing, right? Just like a futures trade, forwards are generally used in commodity or forex land to protect against price fluctuations. The differences between forwards and futures are small but significant. I'm not going to go into super boring detail because I don't think many of you are commodities traders but it is still an important thing to understand even if you're just an RH jockey, so stick with me.
Just like swaps, forwards are OTC contracts - they're not publicly traded. This is distinct from futures, which are traded on exchanges (see The Ballad Of Big Dick Vick for some more color on this). In a forward, no money changes hands until the maturity date of the contract when delivery and receipt are carried out; price and quantity are locked in from day 1. As you now know having read about BDV, futures are marked to market daily, and normally people close them out with synthetic settlement using an inverse position. They're also liquid, and that makes them easier to unwind or close out in case shit goes sideways.
People use forwards when they absolutely have to get rid of the thing they made (or take delivery of the thing they need). If you're a miner, or a farmer, you use this shit to make sure that at the end of the production cycle, you can get rid of the shit you made (and you won't get fucked by someone taking cash settlement over delivery). If you're a buyer, you use them to guarantee that you'll get whatever the shit is that you'll need at a price agreed in advance. Because they're OTC, you can also exactly tailor them to the requirements of your particular circumstances.
These contracts are incredibly byzantine (and there are even crazier synthetic forwards you can see in money markets for the true degenerate fund managers). In my experience, only Texan oilfield magnates, commodities traders, and the weirdo forex crowd fuck with them. I (i) do not own a 10 gallon hat or a novelty size belt buckle (ii) do not wake up in the middle of the night freaking out about the price of pork fat and (iii) love greenbacks too much to care about other countries' monopoly money, so I don't fuck with them.
(iii) Collars
No, not the kind your wife is encouraging you to wear try out to 'spice things up' in the bedroom during quarantine. Collars are actually the hedging strategy most applicable to WSB. Collars deal with options! Hooray!
To execute a basic collar (also called a wrapper by tea-drinking Brits and people from the Antipodes), you buy an out of the money put while simultaneously writing a covered call on the same equity. The put protects your position against price drops and writing the call produces income that offsets the put premium. Doing this limits your tendies (you can only profit up to the strike price of the call) but also writes down your risk. If you screen large volume trades with a VOL/OI of more than 3 or 4x (and they're not bullshit biotech stocks), you can sometimes see these being constructed in real time as hedge funds protect themselves on their shorts.
(3) All About ISDAs, CDS and Synthetic CDOs
You may have heard about the mythical ISDA. Much like an indenture (discussed in my post on $F), it's a magic legal machine that lets you build swaps via trade confirms with a willing counterparty. They are very complicated legal documents and you need to be a true expert to fuck with them. Fortunately, I am, so I do. They're made of two parts; a Master (which is a form agreement that's always the same) and a Schedule (which amends the Master to include your specific terms). They are also the engine behind just about every major credit crunch of the last 10+ years.
First - a brief explainer. An ISDA is a not in and of itself a hedge - it's an umbrella contract that governs the terms of your swaps, which you use to construct your hedge position. You can trade commodities, forex, rates, whatever, all under the same ISDA.
Let me explain. Remember when we talked about swaps? Right. So. You can trade swaps on just about anything. In the late 90s and early 2000s, people had the smart idea of using other people's debt and or credit ratings as the variable leg of swap documentation. These are called credit default swaps. I was actually starting out at a bank during this time and, I gotta tell you, the only thing I can compare people's enthusiasm for this shit to was that moment in your early teens when you discover jerking off. Except, unlike your bathroom bound shame sessions to Mom's Sears catalogue, every single person you know felt that way too; and they're all doing it at once. It was a fiscal circlejerk of epic proportions, and the financial crisis was the inevitable bukkake finish. WSB autism is absolutely no comparison for the enthusiasm people had during this time for lighting each other's money on fire.
Here's how it works. You pick a company. Any company. Maybe even your own! And then you write a swap. In the swap, you define "Credit Event" with respect to that company's debt as the variable leg . And you write in... whatever you want. A ratings downgrade, default under the docs, failure to meet a leverage ratio or FCCR for a certain testing period... whatever. Now, this started out as a hedge position, just like we discussed above. The purest of intentions, of course. But then people realized - if bad shit happens, you make money. And banks... don't like calling in loans or forcing bankruptcies. Can you smell what the moral hazard is cooking?
Enter synthetic CDOs. CDOs are basically pools of asset backed securities that invest in debt (loans or bonds). They've been around for a minute but they got famous in the 2000s because a shitload of them containing subprime mortgage debt went belly up in 2008. This got a lot of publicity because a lot of sad looking rednecks got foreclosed on and were interviewed on CNBC. "OH!", the people cried. "Look at those big bad bankers buying up subprime loans! They caused this!". Wrong answer, America. The debt wasn't the problem. What a lot of people don't realize is that the real meat of the problem was not in regular way CDOs investing in bundles of shit mortgage debts in synthetic CDOs investing in CDS predicated on that debt. They're synthetic because they don't have a stake in the actual underlying debt; just the instruments riding on the coattails. The reason these are so popular (and remain so) is that smart structured attorneys and bankers like your faithful correspondent realized that an even more profitable and efficient way of building high yield products with limited downside was investing in instruments that profit from failure of debt and in instruments that rely on that debt and then hedging that exposure with other CDS instruments in paired trades, and on and on up the chain. The problem with doing this was that everyone wound up exposed to everybody else's books as a result, and when one went tits up, everybody did. Hence, recession, Basel III, etc. Thanks, Obama.
Heavy investment in CDS can also have a warping effect on the price of debt (something else that happened during the pre-financial crisis years and is starting to happen again now). This happens in three different ways. (1) Investors who previously were long on the debt hedge their position by selling CDS protection on the underlying, putting downward pressure on the debt price. (2) Investors who previously shorted the debt switch to buying CDS protection because the relatively illiquid debt (partic. when its a bond) trades at a discount below par compared to the CDS. The resulting reduction in short selling puts upward pressure on the bond price. (3) The delta in price and actual value of the debt tempts some investors to become NBTs (neg basis traders) who long the debt and purchase CDS protection. If traders can't take leverage, nothing happens to the price of the debt. If basis traders can take leverage (which is nearly always the case because they're holding a hedged position), they can push up or depress the debt price, goosing swap premiums etc. Anyway. Enough technical details.
I could keep going. This is a fascinating topic that is very poorly understood and explained, mainly because the people that caused it all still work on the street and use the same tactics today (it's also terribly taught at business schools because none of the teachers were actually around to see how this played out live). But it relates to the topic of today's lesson, so I thought I'd include it here.
Work depending, I'll be back next week with a covenant breakdown. Most upvoted ticker gets the post.
*EDIT 1\* In a total blowout, $PLAY won. So it's D&B time next week. Post will drop Monday at market open.
submitted by fuzzyblankeet to wallstreetbets [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]

Asobi Coin - The world’s first Distributed Secondary Content Platform

Asobi Coin - The world’s first Distributed Secondary Content Platform

https://preview.redd.it/zpwipqhk15r11.png?width=1400&format=png&auto=webp&s=f92f1d8168619c43a729196f672f155507741956

What is a Platform Asobimo?

ASOBIMO is a decentralized platform where digital content will be offered for sale on a distributed secondary market. They will offer a safe and secure cloud platform called Decentralized Security System (DSS) with the help of Blockchain Technological innovation. The job utilizes blockchain technology to present a method that is secure to disperse content that is second-hand. Permits are not given by the digital content providers to customers, making it impossible to pay or if a service shuts down, their material is lost by the users.In ASOBI MARKET the consumer possesses the permit, which we could assure via DRM, Decentralized Security System (DSS). This program enables a secondary content transaction with ABX.The ASOBI marketplace is regarded as the world platform a platform that functions as a marketplace for publishers, for secondary material.
Asobimo is a leading gaming company in Japan known as MMORPG games for smartphone users. success with online games and various other games such as Avabel Stellacept, Celes Arca, and Alchemia Story. they have been popular with more than 10 million download users around the world and also asobimo still releases other JRPG games for smartphone users. Asobimo Founded in March 2007 in Tokyo, Japan and now led by the president and The purpose of the venture is the growth and execution of the Distributed Secondary Content Platform (a platform for distributing secondary online content). The platform was known as ASOBI MARKET and uses blocking technological innovation to give a secure and protected submission system for user content. Content that will be available under this platform: game products, software application, e-books, songs, movie, e-tickets. They also assured us the following: "When you shop in ASOBI MARKET, we can promise the secure return of secondary (second-hand) content and crypto forex through the DSS system.” Such a declaration is very pleasing too. The ASOBI COIN token will become the transaction means of this platform.
https://preview.redd.it/3vncd2io15r11.jpg?width=800&format=pjpg&auto=webp&s=2ecdb71097c91cfaa6d4ff6646c0d988d1cbfd5b
PROBLEM
How do we operate content digital redistribution that works for the creator, publisher, and user? While there so much digital content that easy to copy because of no license for users.
SOLUTION Well digital items can be copied very easily and users will face fraudulent so how to manage this problem where users can trade easily, for this problem the solution was Decentralized security system which will give the users irrefutable proof of content ownership where no other user or hackers can copy or cause fraudulent this will give the user the ownership to its particular item.

Why Choose ICO Asobi Coin?

Advantages of Using Asobi Market
  • Already accessible marketplace: unlike any other endeavor that endures for lack of market accessibility, ASOBI Market has available marketplace currently using 600 workers from many nations and area in Japan.
  • Team Behind Project: The ASOBI Market project has clique of capable individuals with several years of expertise as the founder of the undertaking.
  • Finished product: In my view this is definitely the most significant plus of the undertaking, this provider is the programmers of internet games with 15 decades of experience. The amount of downloads of the matches is 50 million. Enough is an quantity that is impressive.
  • Real Life Problem Solving: Contrary to any other job with no real-life situation usage, the Asobi Market advantage every user of this platform. Let us begin with the consumer. Both can be bought by the consumer in the manufacturer and secondhand to get a price from users. The advantage for producers is that when purchasing used gear to another, it is going to get a part of the benefit.
Token: ABXPlatform: EthereumToken Price: 0.01 USDToken for sale: 8,250,000,000 ABX (50%)Token supply: 16,500,000,000 ABXSoft cap: 5,000,000 USDHard cap: 50,000,000 USDStar advance: August 10Pre-sale end: August 20Bonus: 20%Price 1 ETH: 43,000 ABXprice 1 BTC: 750 000 ABXAccepting: ETH, BTC, BCHRestricted countries: China, United States of America

Detailed:

• Website(ICO): https://asobimo.io/en https://www.asobi.market/ https://wallet.asobimo.io/auth/ • Whitepaper: https://asobimo.io/pdf/white_paper_en.pdf • Bitcointalk Ann Thread : https://bitcointalk.org/index.php?topic=4884216 • Telegram: https://t.me/AsobiCoin_Official • Twitter: https://twitter.com/AsobiCoin • Facebook: https://www.facebook.com/Asobi-Coin-130436194467568/
MyAnn: https://bitcointalk.org/index.php?action=profile;u=1931085

submitted by Bandugan to u/Bandugan [link] [comments]

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

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  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)

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  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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Market Profile Trading - Part 1 - Basics - YouTube Trading with market profile - Part1 Trader Dale - Market Profile webinar - YouTube The Basics of Market Profile - YouTube BEST Forex Books to Increase Your Trading Profits - YouTube Market Profile - Is it right for you? Trading Forex with Market Profile (2015) - YouTube

Forex trend indicators form the indissoluble and essential part of doing technical analysis in Forex market. They help to interpret the price movement, indicating whether the price movement is appearing. There are so many juicy nuggets of info in this forex pdf, you may not even need to eat dinner today. Bon appetit. Get the PDF delivered to your email for FREE! Just sign up to our awesome newsletter: Leave this field empty if you're human: Here’s a little glimpse in what you will learn in this pdf: TOP 3 forex tools that professional traders use; TOP 9 factors that influence the forex ... Forex vs. Futures. If you use Market Profile with Forex data, you need to know that it will never be as precise as Futures data. The reason is simple. Forex is not centralized market. There are many brokers with different data so basically they are unable to be 100 % precise concerning traded volumes. Futures markets however, are centralized so the volumes are 100% correct. My personal ... Strategic experimentation in a dealership market — by Massimo Massa and Andrei Simonov. Limit Orders, Depth, and Volatility — by Hee-Joon Ahna, Kee-Hong Baeb and Kalok Chan. Reminiscences of a Stock Operator — the best of the best book on financial trading by Edwin Lefevre. Market Profile Basics — by Jayanthi Gopalakrishnan. Components Market Profile Techniques Forex Momentum and Direction Moving Average Support and Resistance levels Timeframes: 15minutes and 4hour charts Summary This is a very profitable foreign exchange trading system that can make 200 pips per week easily by identifying and capitalizing on the strong market momentum. The book contains the detailed trading system with many chart exemplifications ... Market Profile can be used just as effectively for other tradables. Software vendors such as Cqg and WindoTrader provide Market Profile displays for equities. IN THEORY The concept of Market Profile stems from the idea that markets have a form of organization determined by time, price, and volume. Each day, the market will develop a range for the day and a value area , which represents an ... Auction Market Theory and Market Profile 14825 replies. Market Profile And Volume Profile MT5 0 replies. Metatrader using 40% of the CPU all the time when using EA 6 replies. Forex Using Market Profile 1 reply. Market profile trader-Merged profile 0 replies

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Market Profile Trading - Part 1 - Basics - YouTube

This webinar goes over the concepts of Market Profile and how you can use these concepts for trading Forex. Learn how to read the market direction and identi... www.trader-dale.com Recommended brokers: Global Prime: https://globalprime.finly.com/c/DTFL2 IC Markets: http://icmarkets.com/?camp=11446 Do you want the sam... 95% Winning Forex Trading Formula - Beat The Market Maker📈 - Duration: 37:53. TRADE ATS 1,276,160 views. 37:53. J Dalton Trading Market Profile Mastery Series Kickstart Webinar #1 - Duration: ... Market Profile is popular with traders in various markets. In this video Navin introduces how it can have impact in forex as well. One thing you have to reme... Best forex books for beginners and experienced traders who are looking for books for trading. If you want to increase your profits, these are some of the bes... Forex traders normally rarely use market profile due to lack of special tools - the majority of trading terminals for Forex traders don’t allow to build market profile. Yet, today we can build ... This is the first part of 10 part series on Learn To Trade Market Profile Trading. Over the 10 parts, I have covered Market Profile basics and Advanced Marke...

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