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List of 110+ Free Udemy & Popular Discounted : ETL & Data Integration Masterclass, HTML, JavaScript, & Bootstrap, Marketing Analytics, Microsoft Excel, Machine Learning, Android App Developer, React JS - A Complete Guide for Frontend Web Development, Python, Tableau, Instructional Design & Many More

ETL & Data Integration Masterclass, HTML, JavaScript, & Bootstrap, Marketing Analytics, Microsoft Excel, Machine Learning, Android App Developer, React JS - A Complete Guide for Frontend Web Development, Python, Tableau, Instructional Design & Many More
Source: Freebies Global - https://freebiesglobal.com/
  1. [English] 6h 24m HTML, JavaScript, & Bootstrap - Certification Course https://www.udemy.com/course/html-javascript-bootstrap-certification-course/?couponCode=YOUACCELOCT26 2 Days left at this price!
  2. [English] 0h 37m Quick Guide: Setup a Local Testing Server using WAMP or MAMP https://www.udemy.com/course/quick-guide-setup-a-local-testing-server-using-wamp-or-mamp/?couponCode=YOUACCELOCT26 2 Days left at this price!
  3. [English] 1h 27m Learn MySQL - For Beginners https://www.udemy.com/course/learn-mysql-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
  4. [English] 1h 28m Learn JavaScript - For Beginners https://www.udemy.com/course/learn-javascript-for-beginners-v/?couponCode=YOUACCELOCT26 2 Days left at this price!
  5. [English] 1h 47m Learn PHP - For Beginners https://www.udemy.com/course/learn-php-for-beginners-n/?couponCode=YOUACCELOCT26 2 Days left at this price!
  6. [English] 5h 57m JavaScript, Bootstrap, & PHP - Certification for Beginners https://www.udemy.com/course/javascript-bootstrap-php-certification-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
  7. [English] 2h 23m Learn XML-AJAX - For Beginners https://www.udemy.com/course/learn-xml-ajax-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
  8. [English] 2h 45m Learn Bootstrap - For Beginners https://www.udemy.com/course/learn-bootstrap-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
  9. [English] 1h 15m Learn jQuery - For Beginners https://www.udemy.com/course/learn-jquery-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
  10. [English] 3h 9m CSS & JavaScript - Certification Course for Beginners https://www.udemy.com/course/css-javascript-certification-course-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
  11. [English] 6h 2m Ultimate AWS Certified Alexa Skill Builder Specialty 2020 https://www.udemy.com/course/ultimate-aws-certified-alexa-skill-builder-specialty/?couponCode=20F2F1085B9FE981B09C 2 Days left at this price!
  12. [English] 9h 13m Pentaho for ETL & Data Integration Masterclass 2020- PDI 9.0 https://www.udemy.com/course/pentaho-for-etl-data-integration-masterclass/?couponCode=OCTXXVI20 1 Day left at this price!
  13. [English] 34h 56m Machine Learning & Deep Learning in Python & R https://www.udemy.com/course/data_science_a_to_z/?couponCode=OCTXXVI20 1 Day left at this price!
  14. [English] 0h 52m Public Speaking: A tactical approach https://www.udemy.com/course/publicspeakingtactics/?couponCode=9546D2A90B72DB31BF85 2 Days left at this price!
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  16. [English] 3h 36m The Complete React JS Course - Basics to Advanced https://www.udemy.com/course/react-js-basics-to-advanced/?couponCode=FREEOCTOBER 2 Days left at this price!
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  18. [Spanish] 11h 40m Curso Excel y Power BI – Análisis y Visualización de Datos https://www.udemy.com/course/curso-tutorial-aprender-como-usar-power-bi-excel-ejercicios-practicos/?couponCode=OCT20-1 2 Days left at this price!
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  23. [German ] 2h 52m Werde ein Menschen-Magnet - Die Charisma-Formel https://www.udemy.com/course/werde-ein-menschen-magnet-die-charisma-formel/?couponCode=CHARISTART 2 Days left at this price!
  24. [English] 12h 46m Complete Machine Learning with R Studio - ML for 2020 https://www.udemy.com/course/machine-learning-with-r-studio/?couponCode=OCTXXVI20 1 Day left at this price!
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  35. [English] 2h 36m EMDR Therapy For PTSD Post Traumatic Stress Disorder https://www.udemy.com/course/certificate-in-ptsd-symptom-relief-through-emdr-therapy/?couponCode=1CE6BA95EB2043A8612C 2 Days left at this price!
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  40. [English] 0h 31m Fundamentals of Network Security https://www.udemy.com/course/fundamentals-of-network-security-b/?couponCode=HARISH_INDIA 2 Days left at this price!
  41. [English] 1h 14m Sell Photo Online: Beginners Guide Stock Photography https://www.udemy.com/course/mastering-stock-photography-step-by-step-guideline/?couponCode=STOCKOCT2020F3 2 Days left at this price!
  42. [English] 6h 5m Tableau 2020 Training for Data Science & Business Analytics https://www.udemy.com/course/tableau-for-data-science-and-business-analytics/?couponCode=FB27OCT2020 2 Days left at this price!
  43. [English] 11h 46m Futures Trading Ninja: DIY 12Hour TOP-NOTCH Trading Strategy https://www.udemy.com/course/futures-trading/?couponCode=1OCT20 2 Days left at this price!
  44. [Spanish] 5h 35m Google Adsense. 99 Secretos que Internet No te Enseña. 2020. https://www.udemy.com/course/google-adsense-gana-dinero-achirou-alvaro-chirou-pablo-munoz/?couponCode=TWITCH 2 Days left at this price!
  45. [English] 7h 0m CNN for Computer Vision with Keras and TensorFlow in Python https://www.udemy.com/course/cnn-for-computer-vision-with-keras-and-tensorflow-in-python/?couponCode=OCTXXVI20 1 Day left at this price!
  46. [English] 6h 29m HR Analytics Course with R https://www.udemy.com/course/hr-analytics-course-with-?couponCode=ANALYTICS27 2 Days left at this price!
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  60. [Spanish] 1h 18m Comienza con R ¡Añade valor a tu CV en 2 horas! https://www.udemy.com/course/el-arte-de-programar-en-r-anade-valor-a-tu-cv/?couponCode=B90E90DE425C8BAC6D10 2 Days left at this price!
  61. [Spanish] 1h 15m Aprende SQL desde cero: ¡Curso con mas de 50 ejercicios! 1 https://www.udemy.com/course/aprende-sql-desde-cero-curso-con-mas-de-50-ejercicios/?couponCode=9497A0979D086BC59ACA 2 Days left at this price!
  62. [Spanish] 1h 41m Tableau: Crea un impacto con la información https://www.udemy.com/course/tableau-10-desde-cero/?couponCode=0B9A15DAABECEF4283E3 2 Days left at this price!
  63. [Spanish] 1h 4m Microsoft Excel - Análisis de datos con tablas dinámicas https://www.udemy.com/course/microsoft-excel-analisis-de-datos-con-tablas-dinamicas/?couponCode=E132A1381313060EADBA 2 Days left at this price!
  64. [Spanish] 1h 47m SQL: Creación de Bases de Datos (De cero a profesional) https://www.udemy.com/course/sql-creacion-de-bd/?couponCode=4C2909E4D310F1B4FA41 2 Days left at this price!
  65. [Arabic] 0h 43m YouTube SEO mini course (Get more views) in Arabic https://www.udemy.com/course/youtube-seo-mini-course/?couponCode=B9CB7555A84C81E259A6 2 Days left at this price!
  66. [English] 4h 48m Microsoft Excel - Learn MS EXCEL For DATA Analysis https://www.udemy.com/course/microsoft-excel-learn-ms-excel-for-data-analysis/?couponCode=23966F2BE2A43C33E5ED 2 Days left at this price!
  67. [English] 0h 33m 30 Days Challenge for a Better Time Management https://www.udemy.com/course/30-days-challenge-for-a-better-time-management/?couponCode=TMFREE 2 Days left at this price!
  68. [English] 2h 15m Outsource Mastery: How To Earn More Money By Doing Less Work https://www.udemy.com/course/outsource-mastery/?couponCode=OCTFREEOUTSOURCE 2 Days left at this price!
  69. [English] 4h 44m Microsoft Excel: Beginner to Data Analysis and Dashboards https://www.udemy.com/course/getting-started-with-microsoft-excel/?couponCode=4471C851C1F635EA50B6 2 Days left at this price!
  70. [English] 1h 55m Machine Learning & Data Science Foundations Masterclass https://www.udemy.com/course/machine-learning-data-science-foundations-masterclass/?couponCode=CLUB11 2 Days left at this price!
  71. [English] 1h 26m Public Speaking: You Can Speak to Large Audiences https://www.udemy.com/course/how-to-speak-to-large-audiences/?couponCode=D862393E365C81A88F76 2 Days left at this price!
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  73. [English] 1h 0m Basics Of Stop Motion Animation Using Canva And OpenShot https://www.udemy.com/course/basics-of-stop-motion-animation-using-canva-and-openshot/?couponCode=87D29D78BE69CC4A77E6 2 Days left at this price!
  74. [English] 1h 23m Basics Of Flat Design Illustrations In Canva https://www.udemy.com/course/how-to-do-flat-design-for-social-media-marketing-in-canva/?couponCode=7C34A04E50CDC001F0FB 2 Days left at this price!
  75. [English] 1h 6m TEDx for NGOs, NonProfits & Volunteers https://www.udemy.com/course/tedx-nonprofit-org/?couponCode=TNNPVEXPOCT292020 2 Days left at this price!
  76. [English] 0h 49m Color Theory Basics: Learning Color Theory With Adobe Color https://www.udemy.com/course/color-theory-basics-learning-color-theory-with-adobe-colo?couponCode=6950A9D3ED98C8948A02 2 Days left at this price!
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85+ Free Udemy Courses: Ultimate AWS Certified Alexa, Python, Lean, MySQL, Public Speaking, NodeJS, Big Data, Adobe Premiere , Excel & More

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Udemy
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submitted by ViralMedia007 to FREECoursesEveryday [link] [comments]

Trading economic news

The majority of this sub is focused on technical analysis. I regularly ridicule such "tea leaf readers" and advocate for trading based on fundamentals and economic news instead, so I figured I should take the time to write up something on how exactly you can trade economic news releases.
This post is long as balls so I won't be upset if you get bored and go back to your drooping dick patterns or whatever.

How economic news is released

First, it helps to know how economic news is compiled and released. Let's take Initial Jobless Claims, the number of initial claims for unemployment benefits around the United States from Sunday through Saturday. Initial in this context means the first claim for benefits made by an individual during a particular stretch of unemployment. The Initial Jobless Claims figure appears in the Department of Labor's Unemployment Insurance Weekly Claims Report, which compiles information from all of the per-state departments that report to the DOL during the week. A typical number is between 100k and 250k and it can vary quite significantly week-to-week.
The Unemployment Insurance Weekly Claims Report contains data that lags 5 days behind. For example, the Report issued on Thursday March 26th 2020 contained data about the week ending on Saturday March 21st 2020.
In the days leading up to the Report, financial companies will survey economists and run complicated mathematical models to forecast the upcoming Initial Jobless Claims figure. The results of surveyed experts is called the "consensus"; specific companies, experts, and websites will also provide their own forecasts. Different companies will release different consensuses. Usually they are pretty close (within 2-3k), but for last week's record-high Initial Jobless Claims the reported consensuses varied by up to 1M! In other words, there was essentially no consensus.
The Unemployment Insurance Weekly Claims Report is released each Thursday morning at exactly 8:30 AM ET. (On Thanksgiving the Report is released on Wednesday instead.) Media representatives gather at the Frances Perkins Building in Washington DC and are admitted to the "lockup" at 8:00 AM ET. In order to be admitted to the lockup you have to be a credentialed member of a media organization that has signed the DOL lockup agreement. The lockup room is small so there is a limited number of spots.
No phones are allowed. Reporters bring their laptops and connect to a local network; there is a master switch on the wall that prevents/enables Internet connectivity on this network. Once the doors are closed the Unemployment Insurance Weekly Claims Report is distributed, with a heading that announces it is "embargoed" (not to be released) prior to 8:30 AM. Reporters type up their analyses of the report, including extracting key figures like Initial Jobless Claims. They load their write-ups into their companies' software, which prepares to send it out as soon as Internet is enabled. At 8:30 AM the DOL representative in the room flips the wall switch and all of the laptops are connected to the Internet, releasing their write-ups to their companies and on to their companies' partners.
Many of those media companies have externally accessible APIs for distributing news. Media aggregators and squawk services (like RanSquawk and TradeTheNews) subscribe to all of these different APIs and then redistribute the key economic figures from the Report to their own subscribers within one second after Internet is enabled in the DOL lockup.
Some squawk services are text-based while others are audio-based. FinancialJuice.com provides a free audio squawk service; internally they have a paid subscription to a professional squawk service and they simply read out the latest headlines to their own listeners, subsidized by ads on the site. I've been using it for 4 months now and have been pretty happy. It usually lags behind the official release times by 1-2 seconds and occasionally they verbally flub the numbers or stutter and have to repeat, but you can't beat the price!
Important - I’m not affiliated with FinancialJuice and I’m not advocating that you use them over any other squawk. If you use them and they misspeak a number and you lose all your money don’t blame me. If anybody has any other free alternatives please share them!

How the news affects forex markets

Institutional forex traders subscribe to these squawk services and use custom software to consume the emerging data programmatically and then automatically initiate trades based on the perceived change to the fundamentals that the figures represent.
It's important to note that every institution will have "priced in" their own forecasted figures well in advance of an actual news release. Forecasts and consensuses all come out at different times in the days leading up to a news release, so by the time the news drops everybody is really only looking for an unexpected result. You can't really know what any given institution expects the value to be, but unless someone has inside information you can pretty much assume that the market has collectively priced in the experts' consensus. When the news comes out, institutions will trade based on the difference between the actual and their forecast.
Sometimes the news reflects a real change to the fundamentals with an economic effect that will change the demand for a currency, like an interest rate decision. However, in the case of the Initial Jobless Claims figure, which is a backwards-looking metric, trading is really just self-fulfilling speculation that market participants will buy dollars when unemployment is low and sell dollars when unemployment is high. Generally speaking, news that reflects a real economic shift has a bigger effect than news that only matters to speculators.
Massive and extremely fast news-based trades happen within tenths of a second on the ECNs on which institutional traders are participants. Over the next few seconds the resulting price changes trickle down to retail traders. Some economic news, like Non Farm Payroll Employment, has an effect that can last minutes to hours as "slow money" follows behind on the trend created by the "fast money". Other news, like Initial Jobless Claims, has a short impact that trails off within a couple minutes and is subsequently dwarfed by the usual pseudorandom movements in the market.
The bigger the difference between actual and consensus, the bigger the effect on any given currency pair. Since economic news releases generally relate to a single currency, the biggest and most easily predicted effects are seen on pairs where one currency is directly effected and the other is not affected at all. Personally I trade USD/JPY because the time difference between the US and Japan ensures that no news will be coming out of Japan at the same time that economic news is being released in the US.
Before deciding to trade any particular news release you should measure the historical correlation between the release (specifically, the difference between actual and consensus) and the resulting short-term change in the currency pair. Historical data for various news releases (along with historical consensus data) is readily available. You can pay to get it exported into Excel or whatever, or you can scroll through it for free on websites like TradingEconomics.com.
Let's look at two examples: Initial Jobless Claims and Non Farm Payroll Employment (NFP). I collected historical consensuses and actuals for these releases from January 2018 through the present, measured the "surprise" difference for each, and then correlated that to short-term changes in USD/JPY at the time of release using 5 second candles.
I omitted any releases that occurred simultaneously as another major release. For example, occasionally the monthly Initial Jobless Claims comes out at the exact same time as the monthly Balance of Trade figure, which is a more significant economic indicator and can be expected to dwarf the effect of the Unemployment Insurance Weekly Claims Report.
USD/JPY correlation with Initial Jobless Claims (2018 - present)
USD/JPY correlation with Non Farm Payrolls (2018 - present)
The horizontal axes on these charts is the duration (in seconds) after the news release over which correlation was calculated. The vertical axis is the Pearson correlation coefficient: +1 means that the change in USD/JPY over that duration was perfectly linearly correlated to the "surprise" in the releases; -1 means that the change in USD/JPY was perfectly linearly correlated but in the opposite direction, and 0 means that there is no correlation at all.
For Initial Jobless Claims you can see that for the first 30 seconds USD/JPY is strongly negatively correlated with the difference between consensus and actual jobless claims. That is, fewer-than-forecast jobless claims (fewer newly unemployed people than expected) strengthens the dollar and greater-than-forecast jobless claims (more newly unemployed people than expected) weakens the dollar. Correlation then trails off and changes to a moderate/weak positive correlation. I interpret this as algorithms "buying the dip" and vice versa, but I don't know for sure. From this chart it appears that you could profit by opening a trade for 15 seconds (duration with strongest correlation) that is long USD/JPY when Initial Jobless Claims is lower than the consensus and short USD/JPY when Initial Jobless Claims is higher than expected.
The chart for Non Farm Payroll looks very different. Correlation is positive (higher-than-expected payrolls strengthen the dollar and lower-than-expected payrolls weaken the dollar) and peaks at around 45 seconds, then slowly decreases as time goes on. This implies that price changes due to NFP are quite significant relative to background noise and "stick" even as normal fluctuations pick back up.
I wanted to show an example of what the USD/JPY S5 chart looks like when an "uncontested" (no other major simultaneously news release) Initial Jobless Claims and NFP drops, but unfortunately my broker's charts only go back a week. (I can pull historical data going back years through the API but to make it into a pretty chart would be a bit of work.) If anybody can get a 5-second chart of USD/JPY at March 19, 2020, UTC 12:30 and/or at February 7, 2020, UTC 13:30 let me know and I'll add it here.

Backtesting

So without too much effort we determined that (1) USD/JPY is strongly negatively correlated with the Initial Jobless Claims figure for the first 15 seconds after the release of the Unemployment Insurance Weekly Claims Report (when no other major news is being released) and also that (2) USD/JPY is strongly positively correlated with the Non Farms Payroll figure for the first 45 seconds after the release of the Employment Situation report.
Before you can assume you can profit off the news you have to backtest and consider three important parameters.
Entry speed: How quickly can you realistically enter the trade? The correlation performed above was measured from the exact moment the news was released, but realistically if you've got your finger on the trigger and your ear to the squawk it will take a few seconds to hit "Buy" or "Sell" and confirm. If 90% of the price move happens in the first second you're SOL. For back-testing purposes I assume a 5 second delay. In practice I use custom software that opens a trade with one click, and I can reliably enter a trade within 2-3 seconds after the news drops, using the FinancialJuice free squawk.
Minimum surprise: Should you trade every release or can you do better by only trading those with a big enough "surprise" factor? Backtesting will tell you whether being more selective is better long-term or not.
Hold time: The optimal time to hold the trade is not necessarily the same as the time of maximum correlation. That's a good starting point but it's not necessarily the best number. Backtesting each possible hold time will let you find the best one.
The spread: When you're only holding a position open for 30 seconds, the spread will kill you. The correlations performed above used the midpoint price, but in reality you have to buy at the ask and sell at the bid. Brokers aren't stupid and the moment volume on the ECN jumps they will widen the spread for their retail customers. The only way to determine if the news-driven price movements reliably overcome the spread is to backtest.
Stops: Personally I don't use stops, neither take-profit nor stop-loss, since I'm automatically closing the trade after a fixed (and very short) amount of time. Additionally, brokers have a minimum stop distance; the profits from scalping the news are so slim that even the nearest stops they allow will generally not get triggered.
I backtested trading these two news releases (since 2018), using a 5 second entry delay, real historical spreads, and no stops, cycling through different "surprise" thresholds and hold times to find the combination that returns the highest net profit. It's important to maximize net profit, not expected value per trade, so you don't over-optimize and reduce the total number of trades taken to one single profitable trade. If you want to get fancy you can set up a custom metric that combines number of trades, expected value, and drawdown into a single score to be maximized.
For the Initial Jobless Claims figure I found that the best combination is to hold trades open for 25 seconds (that is, open at 5 seconds elapsed and hold until 30 seconds elapsed) and only trade when the difference between consensus and actual is 7k or higher. That leads to 30 trades taken since 2018 and an expected return of... drumroll please... -0.0093 yen per unit per trade.
Yep, that's a loss of approx. $8.63 per lot.
Disappointing right? That's the spread and that's why you have to backtest. Even though the release of the Unemployment Insurance Weekly Claims Report has a strong correlation with movement in USD/JPY, it's simply not something that a retail trader can profit from.
Let's turn to the NFP. There I found that the best combination is to hold trades open for 75 seconds (that is, open at 5 seconds elapsed and hold until 80 seconds elapsed) and trade every single NFP (no minimum "surprise" threshold). That leads to 20 trades taken since 2018 and an expected return of... drumroll please... +0.1306 yen per unit per trade.
That's a profit of approx. $121.25 per lot. Not bad for 75 seconds of work! That's a +6% ROI at 50x leverage.

Make it real

If you want to do this for realsies, you need to run these numbers for all of the major economic news releases. Markit Manufacturing PMI, Factory Orders MoM, Trade Balance, PPI MoM, Export and Import Prices, Michigan Consumer Sentiment, Retail Sales MoM, Industrial Production MoM, you get the idea. You keep a list of all of the releases you want to trade, when they are released, and the ideal hold time and "surprise" threshold. A few minutes before the prescribed release time you open up your broker's software, turn on your squawk, maybe jot a few notes about consensuses and model forecasts, and get your finger on the button. At the moment you hear the release you open the trade in the correct direction, hold it (without looking at the chart!) for the required amount of time, then close it and go on with your day.
Some benefits of trading this way: * Most major economic releases come out at either 8:30 AM ET or 10:00 AM ET, and then you're done for the day. * It's easily backtestable. You can look back at the numbers and see exactly what to expect your return to be. * It's fun! Packing your trading into 30 seconds and knowing that institutions are moving billions of dollars around as fast as they can based on the exact same news you just read is thrilling. * You can wow your friends by saying things like "The St. Louis Fed had some interesting remarks on consumer spending in the latest Beige Book." * No crayons involved.
Some downsides: * It's tricky to be fast enough without writing custom software. Some broker software is very slow and requires multiple dialog boxes before a position is opened, which won't cut it. * The profits are very slim, you're not going to impress your instagram followers to join your expensive trade copying service with your 30-second twice-weekly trades. * Any friends you might wow with your boring-ass economic talking points are themselves the most boring people in the world.
I hope you enjoyed this long as fuck post and you give trading economic news a try!
submitted by thicc_dads_club to Forex [link] [comments]

Which are your Top 5 favourite coins out of the Top 100? An analysis.

I am putting together my investment portfolio for 2018 and made a complete summary of the current Top 100. Interestingly, I noticed that all coins can be categorized into 12 markets. Which markets do you think will play the biggest role in the coming year?
Here is a complete overview of all coins in an excel sheet including name, market, TPS, risk profile, time since launch (negative numbers mean that they are launching that many months in the future) and market cap. You can also sort by all of these fields of course. Coins written in bold are the strongest contenders within their market either due to having the best technology or having a small market cap and still excellent technology and potential. https://docs.google.com/spreadsheets/d/1s8PHcNvvjuy848q18py_CGcu8elRGQAUIf86EYh4QZo/edit#gid=0
The 12 markets are
  1. Currency 13 coins
  2. Platform 25 coins
  3. Ecosystem 9 coins
  4. Privacy 10 coins
  5. Currency Exchange Tool 8 coins
  6. Gaming & Gambling 5 coins
  7. Misc 15 coins
  8. Social Network 4 coins
  9. Fee Token 3 coins
  10. Decentralized Data Storage 4 coins
  11. Cloud Computing 3 coins
  12. Stable Coin 2 coins
Before we look at the individual markets, we need to take a look of the overall market and its biggest issue scalability first:
Cryptocurrencies aim to be a decentralized currency that can be used worldwide. Its goal is to replace dollar, Euro, Yen, all FIAT currencies worldwide. The coin that will achieve that will be worth several trillion dollars.
Bitcoin can only process 7 transactions per second (TPS). In order to replace all FIAT, it would need to perform at at least VISA levels, which usually processes around 3,000 TPS, up to 25,000 TPS during peak times and a maximum of 64,000 TPS. That means that this cryptocurrency would need to be able to perform at least several thousand TPS. However, a ground breaking technology should not look at current technology to set a goal for its use, i.e. estimating the number of emails sent in 1990 based on the number of faxes sent wasn’t a good estimate.
For that reason, 10,000 TPS is the absolute baseline for a cryptocurrency that wants to replace FIAT. This brings me to IOTA, which wants to connect all 80 billion IoT devices that are expected to exist by 2025, which constantly communicate with each other, creating 80 billion or more transactions per second. This is the benchmark that cryptocurrencies should be aiming for. Currently, 8 billion devices are connected to the Internet.
With its Lightning network recently launched, Bitcoin is realistically looking at 50,000 possible soon. Other notable cryptocurrencies besides IOTA and Bitcoin are Nano with 7,000 TPS already tested, Dash with several billion TPS possible with Masternodes, Neo, LISK and RHOC with 100,000 TPS by 2020, Ripple with 50,000 TPS, Ethereum with 10,000 with Sharding.
However, it needs to be said that scalability usually goes at the cost of decentralization and security. So, it needs to be seen, which of these technologies can prove itself resilient and performant.
Without further ado, here are the coins of the first market

Market 1 - Currency:

  1. Bitcoin: 1st generation blockchain with currently bad scalability currently, though the implementation of the Lightning Network looks promising and could alleviate most scalability concerns, scalability and high energy use.
  2. Ripple: Centralized currency that might become very successful due to tight involvement with banks and cross-border payments for financial institutions; banks and companies like Western Union and Moneygram (who they are currently working with) as customers customers. However, it seems they are aiming for more decentralization now.https://ripple.com/dev-blog/decentralization-strategy-update/. Has high TPS due to Proof of Correctness algorithm.
  3. Bitcoin Cash: Bitcoin fork with the difference of having an 8 times bigger block size, making it 8 times more scalable than Bitcoin currently. Further block size increases are planned. Only significant difference is bigger block size while big blocks lead to further problems that don't seem to do well beyond a few thousand TPS. Opponents to a block size argue that increasing the block size limit is unimaginative, offers only temporary relief, and damages decentralization by increasing costs of participation. In order to preserve decentralization, system requirements to participate should be kept low. To understand this, consider an extreme example: very big blocks (1GB+) would require data center level resources to validate the blockchain. This would preclude all but the wealthiest individuals from participating.Community seems more open than Bitcoin's though.
  4. Litecoin : Little brother of Bitcoin. Bitcoin fork with different mining algorithm but not much else.Copies everything that Bitcoin does pretty much. Lack of real innovation.
  5. Dash: Dash (Digital Cash) is a fork of Bitcoin and focuses on user ease. It has very fast transactions within seconds, low fees and uses Proof of Service from Masternodes for consensus. They are currently building a system called Evolution which will allow users to send money using usernames and merchants will find it easy to integrate Dash using the API. You could say Dash is trying to be a PayPal of cryptocurrencies. Currently, cryptocurrencies must choose between decentralization, speed, scalability and can pick only 2. With Masternodes, Dash picked speed and scalability at some cost of decentralization, since with Masternodes the voting power is shifted towards Masternodes, which are run by Dash users who own the most Dash.
  6. IOTA: 3rd generation blockchain called Tangle, which has a high scalability, no fees and instant transactions. IOTA aims to be the connective layer between all 80 billion IOT devices that are expected to be connected to the Internet in 2025, possibly creating 80 billion transactions per second or 800 billion TPS, who knows. However, it needs to be seen if the Tangle can keep up with this scalability and iron out its security issues that have not yet been completely resolved.
  7. Nano: 3rd generation blockchain called Block Lattice with high scalability, no fees and instant transactions. Unlike IOTA, Nano only wants to be a payment processor and nothing else, for now at least. With Nano, every user has their own blockchain and has to perform a small amount of computing for each transaction, which makes Nano perform at 300 TPS with no problems and 7,000 TPS have also been tested successfully. Very promising 3rd gen technology and strong focus on only being the fastest currency without trying to be everything.
  8. Decred: As mining operations have grown, Bitcoin’s decision-making process has become more centralized, with the largest mining companies holding large amounts of power over the Bitcoin improvement process. Decred focuses heavily on decentralization with their PoW Pos hybrid governance system to become what Bitcoin was set out to be. They will soon implement the Lightning Network to scale up. While there do not seem to be more differences to Bitcoin besides the novel hybrid consensus algorithm, which Ethereum, Aeternity and Bitcoin Atom are also implementing, the welcoming and positive Decred community and professoinal team add another level of potential to the coin.
  9. Aeternity: We’ve seen recently, that it’s difficult to scale the execution of smart contracts on the blockchain. Crypto Kitties is a great example. Something as simple as creating and trading unique assets on Ethereum bogged the network down when transaction volume soared. Ethereum and Zilliqa address this problem with Sharding. Aeternity focuses on increasing the scalability of smart contracts and dapps by moving smart contracts off-chain. Instead of running on the blockchain, smart contracts on Aeternity run in private state channels between the parties involved in the contracts. State channels are lines of communication between parties in a smart contract. They don’t touch the blockchain unless they need to for adjudication or transfer of value. Because they’re off-chain, state channel contracts can operate much more efficiently. They don’t need to pay the network for every time they compute and can also operate with greater privacy. An important aspect of smart contract and dapp development is access to outside data sources. This could mean checking the weather in London, score of a football game, or price of gold. Oracles provide access to data hosted outside the blockchain. In many blockchain projects, oracles represent a security risk and potential point of failure, since they tend to be singular, centralized data streams. Aeternity proposes decentralizing oracles with their oracle machine. Doing so would make outside data immutable and unchangeable once it reaches Aeternity’s blockchain. Of course, the data source could still be hacked, so Aeternity implements a prediction market where users can bet on the accuracy and honesty of incoming data from various oracles.It also uses prediction markets for various voting and verification purposes within the platform. Aeternity’s network runs on on a hybrid of proof of work and proof of stake. Founded by a long-time crypto-enthusiast and early colleague of Vitalik Buterin, Yanislav Malahov. Promising concept though not product yet
  10. Bitcoin Atom: Atomic Swaps and hybrid consenus. This looks like the only Bitcoin clone that actually is looking to innovate next to Bitcoin Cash.
  11. Dogecoin: Litecoin fork, fantastic community, though lagging behind a bit in technology.
  12. Bitcoin Gold: A bit better security than bitcoin through ASIC resistant algorithm, but that's it. Not that interesting.
  13. Digibyte: Digibyte's PoS blockchain is spread over a 100,000+ servers, phones, computers, and nodes across the globe, aiming for the ultimate level of decentralization. DigiByte rebalances the load between the five mining algorithms by adjusting the difficulty of each so one algorithm doesn’t become dominant. The algorithm's asymmetric difficulty has gained notoriety and been deployed in many other blockchains.DigiByte’s adoption over the past four years has been slow. It’s still a relatively obscure currency compared its competitors. The DigiByte website offers a lot of great marketing copy and buzzwords. However, there’s not much technical information about what they have planned for the future. You could say Digibyte is like Bitcoin, but with shorter blocktimes and a multi-algorithm. However, that's not really a difference big enough to truly set themselves apart from Bitcoin, since these technologies could be implemented by any blockchain without much difficulty. Their decentralization is probably their strongest asset, however, this also change quickly if the currency takes off and big miners decide to go into Digibyte.
  14. Bitcoin Diamond Asic resistant Bitcoin and Copycat

Market 2 - Platform

Most of the cryptos here have smart contracts and allow dapps (Decentralized apps) to be build on their platform and to use their token as an exchange of value between dapp services.
  1. Ethereum: 2nd generation blockchain that allows the use of smart contracts. Bad scalability currently, though this concern could be alleviated by the soon to be implemented Lightning Network aka Plasma and its Sharding concept.
  2. EOS: Promising technology that wants to be able do everything, from smart contracts like Ethereum, scalability similar to Nano with 1000 tx/second + near instant transactions and zero fees, to also wanting to be a platform for dapps. However, EOS doesn't have a product yet and everything is just promises still. Highly overvalued right now. However, there are lots of red flags, have dumped $500 million Ether over the last 2 months and possibly bought back EOS to increase the size of their ICO, which has been going on for over a year and has raised several billion dollars. All in all, their market cap is way too high for that and not even having a product.
  3. Cardano: Similar to Ethereum/EOS, however, only promises made with no delivery yet, highly overrated right now. Interesting concept though. Market cap way too high for not even having a product. Somewhat promising technology.
  4. VeChain: Singapore-based project that’s building a business enterprise platform and inventory tracking system. Examples are verifying genuine luxury goods and food supply chains. Has one of the strongest communities in the crypto world. Most hyped token of all, with merit though.
  5. Neo: Neo is a platform, similar to Eth, but more extensive, allowing dapps and smart contracts, but with a different smart contract gas system, consensus mechanism (PoS vs. dBfT), governance model, fixed vs unfixed supply, expensive contracts vs nearly free contracts, different ideologies for real world adoption. There are currently only 9 nodes, each of which are being run by a company/entity hand selected by the NEO council (most of which are located in china) and are under contract. This means that although the locations of the nodes may differ, ultimately the neo council can bring them down due to their legal contracts. In fact this has been done in the past when the neo council was moving 50 million neo that had been locked up. Also dbft (or neo's implmentation of it) has failed underload causing network outages during major icos. The first step in decentralization is that the NEO Counsel will select trusted nodes (Universities, business partners, etc.) and slowly become less centralized that way. The final step in decentralization will be allowing NEO holders to vote for new nodes, similar to a DPoS system (ARK/EOS/LISK). NEO has a regulation/government friendly ideology. Finally they are trying to work undewith the Chinese government in regards to regulations. If for some reason they wanted it shut down, they could just shut it down.
  6. Stellar: PoS system, similar goals as Ripple, but more of a platform than only a currency. 80% of Stellar are owned by Stellar.org still, making the currency centralized.
  7. Ethereum classic: Original Ethereum that decided not to fork after a hack. The Ethereum that we know is its fork. Uninteresing, because it has a lot of less resources than Ethereum now and a lot less community support.
  8. Ziliqa: Zilliqa is building a new way of sharding. 2400 tpx already tested, 10,000 tps soon possible by being linearly scalable with the number of nodes. That means, the more nodes, the faster the network gets. They are looking at implementing privacy as well.
  9. QTUM: Enables Smart contracts on the Bitcoin blockchain. Useful.
  10. Icon: Korean ethereum. Decentralized application platform that's building communities in partnership with banks, insurance providers, hospitals, and universities. Focused on ID verification and payments. No big differentiators to the other 20 Ethereums, except that is has a product. That is a plus. Maybe cheap alternative to Ethereum.
  11. LISK: Lisk's difference to other BaaS is that side chains are independent to the main chain and have to have their own nodes. Similar to neo whole allows dapps to deploy their blockchain to. However, Lisk is currently somewhat centralized with a small group of members owning more than 50% of the delegated positions. Lisk plans to change the consensus algorithm for that reason in the near future.
  12. Rchain: Similar to Ethereum with smart contract, though much more scalable at an expected 40,000 TPS and possible 100,000 TPS. Not launched yet. No product launched yet, though promising technology. Not overvalued, probably at the right price right now.
  13. ARDR: Similar to Lisk. Ardor is a public blockchain platform that will allow people to utilize the blockchain technology of Nxt through the use of child chains. A child chain, which is a ‘light’ blockchain that can be customized to a certain extent, is designed to allow easy self-deploy for your own blockchain. Nxt claims that users will "not need to worry" about security, as that part is now handled by the main chain (Ardor). This is the chief innovation of Ardor. Ardor was evolved from NXT by the same company. NEM started as a NXT clone.
  14. Ontology: Similar to Neo. Interesting coin
  15. Bytom: Bytom is an interactive protocol of multiple byte assets. Heterogeneous byte-assets (indigenous digital currency, digital assets) that operate in different forms on the Bytom Blockchain and atomic assets (warrants, securities, dividends, bonds, intelligence information, forecasting information and other information that exist in the physical world) can be registered, exchanged, gambled and engaged in other more complicated and contract-based interoperations via Bytom.
  16. Nxt: Similar to Lisk
  17. Stratis: Different to LISK, Stratis will allow businesses and organizations to create their own blockchain according to their own needs, but secured on the parent Stratis chain. Stratis’s simple interface will allow organizations to quickly and easily deploy and/or test blockchain functionality of the Ethereum, BitShares, BitCoin, Lisk and Stratis environements.
  18. Status: Status provides access to all of Ethereum’s decentralized applications (dapps) through an app on your smartphone. It opens the door to mass adoption of Ethereum dapps by targeting the fastest growing computer segment in the world – smartphone users.16. Ark: Fork of Lisk that focuses on a smaller feature set. Ark wallets can only vote for one delegate at a time which forces delegates to compete against each other and makes cartel formations incredibly hard, if not impossible.
  19. Neblio: Similar to Neo, but 30x smaller market cap.
  20. NEM: Is similar to Neo No marketing team, very high market cap for little clarilty what they do.
  21. Bancor: Bancor is a Decentralized Liquidity Network that allows you to hold any Ethereum token and convert it to any other token in the network, with no counter party, at an automatically calculated price, using a simple web wallet.
  22. Dragonchain: The Purpose of DragonChain is to help companies quickly and easily incorporate blockchain into their business applications. Many companies might be interested in making this transition because of the benefits associated with serving clients over a blockchain – increased efficiency and security for transactions, a reduction of costs from eliminating potential fraud and scams, etc.
  23. Skycoin: Transactions with zero fees that take apparently two seconds, unlimited transaction rate, no need for miners and block rewards, low power usage, all of the usual cryptocurrency technical vulnerabilities fixed, a consensus mechanism superior to anything that exists, resistant to all conceivable threats (government censorship, community infighting, cybenucleaconventional warfare, etc). Skycoin has their own consensus algorithm known as Obelisk written and published academically by an early developer of Ethereum. Obelisk is a non-energy intensive consensus algorithm based on a concept called ‘web of trust dynamics’ which is completely different to PoW, PoS, and their derivatives. Skywire, the flagship application of Skycoin, has the ambitious goal of decentralizing the internet at the hardware level and is about to begin the testnet in April. However, this is just one of the many facets of the Skycoin ecosystem. Skywire will not only provide decentralized bandwidth but also storage and computation, completing the holy trinity of commodities essential for the new internet. Skycion a smear campaign launched against it, though they seem legit and reliable. Thus, they are probably undervalued.

Market 3 - Ecosystem

The 3rd market with 11 coins is comprised of ecosystem coins, which aim to strengthen the ease of use within the crypto space through decentralized exchanges, open standards for apps and more
  1. Nebulas: Similar to how Google indexes webpages Nebulas will index blockchain projects, smart contracts & data using the Nebulas rank algorithm that sifts & sorts the data. Developers rewarded NAS to develop & deploy on NAS chain. Nebulas calls this developer incentive protocol – basically rewards are issued based on how often dapp/contract etc. is used, the more the better the rewards and Proof of devotion. Works like DPoS except the best, most economically incentivised developers (Bookkeeppers) get the forging spots. Ensuring brains stay with the project (Cross between PoI & PoS). 2,400 TPS+, DAG used to solve the inter-transaction dependencies in the PEE (Parallel Execution Environment) feature, first crypto Wallet that supports the Lightening Network.
  2. Waves: Decentralized exchange and crowdfunding platform. Let’s companies and projects to issue and manage their own digital coin tokens to raise money.
  3. Salt: Leveraging blockchain assets to secure cash loands. Plans to offer cash loans in traditional currencies, backed by your cryptocurrency assets. Allows lenders worldwide to skip credit checks for easier access to affordable loans.
  4. CHAINLINK: ChainLink is a decentralized oracle service, the first of its kind. Oracles are defined as an ‘agent’ that finds and verifies real-world occurrences and submits this information to a blockchain to be used in smart contracts.With ChainLink, smart contract users can use the network’s oracles to retrieve data from off-chain application program interfaces (APIs), data pools, and other resources and integrate them into the blockchain and smart contracts. Basically, ChainLink takes information that is external to blockchain applications and puts it on-chain. The difference to Aeternity is that Chainlink deploys the smart contracts on the Ethereum blockchain while Aeternity has its own chain.
  5. WTC: Combines blockchain with IoT to create a management system for supply chains Interesting
  6. Ethos unifyies all cryptos. Ethos is building a multi-cryptocurrency phone wallet. The team is also building an investment diversification tool and a social network
  7. Aion: Aion is the token that pays for services on the Aeternity platform.
  8. USDT: is no cryptocurrency really, but a replacement for dollar for trading After months of asking for proof of dollar backing, still no response from Tether.

Market 4 - Privacy

The 4th market are privacy coins. As you might know, Bitcoin is not anonymous. If the IRS or any other party asks an exchange who is the identity behind a specific Bitcoin address, they know who you are and can track back almost all of the Bitcoin transactions you have ever made and all your account balances. Privacy coins aim to prevent exactly that through address fungability, which changes addresses constantly, IP obfuscation and more. There are 2 types of privacy coins, one with completely privacy and one with optional privacy. Optional Privacy coins like Dash and Nav have the advantage of more user friendliness over completely privacy coins such as Monero and Enigma.
  1. Monero: Currently most popular privacy coin, though with a very high market cap. Since their privacy is all on chain, all prior transactions would be deanonymized if their protocol is ever cracked. This requires a quantum computing attack though. PIVX is better in that regard.
  2. Zcash: A decentralized and open-source cryptocurrency that hide the sender, recipient, and value of transactions. Offers users the option to make transactions public later for auditing. Decent privacy coin, though no default privacy
  3. Verge: Calls itself privacy coin without providing private transactions, multiple problems over the last weeks has a toxic community, and way too much hype for what they have.
  4. Bytecoin: First privacy-focused cryptocurrency with anonymous transactions. Bytecoin’s code was later adapted to create Monero, the more well-known anonymous cryptocurrency. Has several scam accusations, 80% pre-mine, bad devs, bad tech
  5. Bitcoin Private: A merge fork of Bitcoin and Zclassic with Zclassic being a fork of Zcash with the difference of a lack of a founders fee required to mine a valid block. This promotes a fair distribution, preventing centralized coin ownership and control. Bitcoin private offers the optional ability to keep the sender, receiver, and amount private in a given transaction. However, this is already offered by several good privacy coins (Monero, PIVX) and Bitcoin private doesn't offer much more beyond this.
  6. Komodo: The Komodo blockchain platform uses Komodo’s open-source cryptocurrency for doing transparent, anonymous, private, and fungible transactions. They are then made ultra-secure using Bitcoin’s blockchain via a Delayed Proof of Work (dPoW) protocol and decentralized crowdfunding (ICO) platform to remove middlemen from project funding. Offers services for startups to create and manage their own Blockchains.
  7. PIVX: As a fork of Dash, PIVX uses an advanced implementation of the Zerocoin protocol to provide it’s privacy. This is a form of zeroknowledge proofs, which allow users to spend ‘Zerocoins’ that have no link back to them. Unlike Zcash u have denominations in PIVX, so they can’t track users by their payment amount being equal to the amount of ‘minted’ coins, because everyone uses the same denominations. PIVX is also implementing Bulletproofs, just like Monero, and this will take care of arguably the biggest weakness of zeroknowledge protocols: the trusted setup.
  8. Zcoin: PoW cryptocurrency. Private financial transactions, enabled by the Zerocoin Protocol. Zcoin is the first full implementation of the Zerocoin Protocol, which allows users to have complete privacy via Zero-Knowledge cryptographic proofs.
  9. Enigma: Monero is to Bitcoin what enigma is to Ethereum. Enigma is for making the data used in smart contracts private. More of a platform for dapps than a currency like Monero. Very promising.
  10. Navcoin: Like bitcoin but with added privacy and pos and 1,170 tps, but only because of very short 30 second block times. Though, privacy is optional, but aims to be more user friendly than Monero. However, doesn't really decide if it wants to be a privacy coin or not. Same as Zcash.Strong technology, non-shady team.
  11. Tenx: Raised 80 million, offers cryptocurrency-linked credit cards that let you spend virtual money in real life. Developing a series of payment platforms to make spending cryptocurrency easier. However, the question is if full privacy coins will be hindered in growth through government regulations and optional privacy coins will become more successful through ease of use and no regulatory hindrance.

Market 5 - Currency Exchange Tool

Due to the sheer number of different cryptocurrencies, exchanging one currency for the other it still cumbersome. Further, merchants don’t want to deal with overcluttered options of accepting cryptocurrencies. This is where exchange tool like Req come in, which allow easy and simple exchange of currencies.
  1. Cryptonex: Fiat and currency exchange between various blockchain services, similar to REQ.
  2. QASH: Qash is used to fuel its liquid platform which will be an exchange that will distribute their liquidity pool. Its product, the Worldbook is a multi-exchange order book that matches crypto to crypto, and crypto to fiat and the reverse across all currencies. E.g., someone is selling Bitcoin is USD on exchange1 not owned by Quoine and someone is buying Bitcoin in EURO on exchange 2 not owned by Quoine. If the forex conversions and crypto conversions match then the trade will go through and the Worldbook will match it, it'll make the sale and the purchase on either exchange and each user will get what they wanted, which means exchanges with lower liquidity if they join the Worldbook will be able to fill orders and take trade fees they otherwise would miss out on.They turned it on to test it a few months ago for an hour or so and their exchange was the top exchange in the world by 4x volume for the day because all Worldbook trades ran through it. Binance wants BNB to be used on their one exchange. Qash wants their QASH token embedded in all of their partners. More info here https://www.reddit.com/CryptoCurrency/comments/8a8lnwhich_are_your_top_5_favourite_coins_out_of_the/dwyjcbb/?context=3
  3. Kyber: network Exchange between cryptocurrencies, similar to REQ. Features automatic coin conversions for payments. Also offers payment tools for developers and a cryptocurrency wallet.
  4. Achain: Building a boundless blockchain world like Req .
  5. Req: Exchange between cryptocurrencies.
  6. Bitshares: Exchange between cryptocurrencies. Noteworthy are the 1.5 second average block times and throughput potential of 100,000 transactions per second with currently 2,400 TPS having been proven. However, bitshares had several Scam accusations in the past.
  7. Loopring: A protocol that will enable higher liquidity between exchanges and personal wallets.
  8. ZRX: Open standard for dapps. Open, permissionless protocol allowing for ERC20 tokens to be traded on the Ethereum blockchain. In 0x protocol, orders are transported off-chain, massively reducing gas costs and eliminating blockchain bloat. Relayers help broadcast orders and collect a fee each time they facilitate a trade. Anyone can build a relayer.

Market 6 - Gaming

With an industry size of $108B worldwide, Gaming is one of the largest markets in the world. For sure, cryptocurrencies will want to have a share of that pie.
  1. Storm: Mobile game currency on a platform with 9 million players.
  2. Fun: A platform for casino operators to host trustless, provably-fair gambling through the use of smart contracts, as well as creating their own implementation of state channels for scalability.
  3. Electroneum: Mobile game currency They have lots of technical problems, such as several 51% attacks
  4. Wax: Marketplace to trade in-game items

Market 7 - Misc

There are various markets being tapped right now. They are all summed up under misc.
  1. OMG: Omise is designed to enable financial services for people without bank accounts. It works worldwide and with both traditional money and cryptocurrencies.
  2. Power ledger: Australian blockchain-based cryptocurrency and energy trading platform that allows for decentralized selling and buying of renewable energy. Unique market and rather untapped market in the crypto space.
  3. Populous: A platform that connects business owners and invoice buyers without middlemen. Invoice sellers get cash flow to fund their business and invoice buyers earn interest. Similar to OMG, small market.
  4. Monacoin: The first Japanese cryptocurrency. Focused on micro-transactions and based on a popular internet meme of a type-written cat. This makes it similar to Dogecoin. Very niche, tiny market.
  5. Revain: Legitimizing reviews via the blockchain. Interesting concept, though market not as big.
  6. Augur: Platform to forecast and make wagers on the outcome of real-world events (AKA decentralized predictions). Uses predictions for a “wisdom of the crowd” search engine. Not launched yet.
  7. Substratum: Revolutionzing hosting industry via per request billing as a decentralized internet hosting system. Uses a global network of private computers to create the free and open internet of the future. Participants earn cryptocurrency. Interesting concept.
  8. Veritaseum: Is supposed to be a peer to peer gateway, though it looks like very much like a scam.
  9. TRON: Tronix is looking to capitalize on ownership of internet data to content creators. However, they plagiarized their white paper, which is a no go. They apologized, so it needs to be seen how they will conduct themselves in the future. Extremely high market cap for not having a product, nor proof of concept.
  10. Syscoin: A cryptocurrency with a decentralized marketplace that lets people buy and sell products directly without third parties. Trying to remove middlemen like eBay and Amazon.
  11. Hshare: Most likely scam because of no code changes, most likely pump and dump scheme, dead community.
  12. BAT: An Ethereum-based token that can be exchanged between content creators, users, and advertisers. Decentralized ad-network that pays based on engagement and attention.
  13. Dent: Decentralizeed exchange of mobile data, enabling mobile data to be marketed, purchased or distributed, so that users can quickly buy or sell data from any user to another one.
  14. Ncash: End to end encrypted Identification system for retailers to better serve their customers .
  15. Factom Secure record-keeping system that allows companies to store their data directly on the Blockchain. The goal is to make records more transparent and trustworthy .

Market 8 - Social network

Web 2.0 is still going strong and Web 3.0 is not going to ignore it. There are several gaming tokens already out there and a few with decent traction already, such as Steem, which is Reddit with voting through money is a very interesting one.
  1. Mithril: As users create content via social media, they will be rewarded for their contribution, the better the contribution, the more they will earn
  2. Steem: Like Reddit, but voting with money. Already launched product and Alexa rank 1,000 Thumbs up.
  3. Rdd: Reddcoin makes the process of sending and receiving money fun and rewarding for everyone. Reddcoin is dedicated to one thing – tipping on social networks as a way to bring cryptocurrency awareness and experience to the general public.
  4. Kin: Token for the platform Kik. Kik has a massive user base of 400 million people. Replacing paying with FIAT with paying with KIN might get this token to mass adoption very quickly.

Market 9 - Fee token

Popular exchanges realized that they can make a few billion dollars more by launching their own token. Owning these tokens gives you a reduction of trading fees. Very handy and BNB (Binance Coin) has been one of the most resilient tokens, which have withstood most market drops over the last weeks and was among the very few coins that could show growth.
  1. BNB: Fee token for Binance
  2. Gas: Not a Fee token for an exchange, but it is a dividend paid out on Neo and a currency that can be used to purchase services for dapps.
  3. Kucoin: Fee token for Kucoin

Market 10 - Decentralized Data Storage

Currently, data storage happens with large companies or data centers that are prone to failure or losing data. Decentralized data storage makes loss of data almost impossible by distributing your files to numerous clients that hold tiny pieces of your data. Remember Torrents? Torrents use a peer-to-peer network. It is similar to that. Many users maintain copies of the same file, when someone wants a copy of that file, they send a request to the peer-to-peer network., users who have the file, known as seeds, send fragments of the file to the requester., he requester receives many fragments from many different seeds, and the torrent software recompiles these fragments to form the original file.
  1. Gbyte: Byteball data is stored and ordered using directed acyclic graph (DAG) rather than blockchain. This allows all users to secure each other's data by referencing earlier data units created by other users, and also removes scalability limits common for blockchains, such as blocksize issue.
  2. Siacoin: Siacoin is decentralized storage platform. Distributes encrypted files to thousands of private users who get paid for renting out their disk space. Anybody with siacoins can rent storage from hosts on Sia. This is accomplish via "smart" storage contracts stored on the Sia blockchain. The smart contract provides a payment to the host only after the host has kept the file for a given amount of time. If the host loses the file, the host does not get paid.
  3. Maidsafecoin: MaidSafe stands for Massive Array of Internet Disks, Secure Access for Everyone.Instead of working with data centers and servers that are common today and are vulnerable to data theft and monitoring, SAFE’s network uses advanced P2P technology to bring together the spare computing capacity of all SAFE users and create a global network. You can think of SAFE as a crowd-sourced internet. All data and applications reside in this network. It’s an autonomous network that automatically sets prices and distributes data and rents out hard drive disk space with a Blockchain-based storage solutions.When you upload a file to the network, such as a photo, it will be broken into pieces, hashed, and encrypted. The data is then randomly distributed across the network. Redundant copies of the data are created as well so that if someone storing your file turns off their computer, you will still have access to your data. And don’t worry, even with pieces of your data on other people’s computers, they won’t be able to read them. You can earn MadeSafeCoins by participating in storing data pieces from the network on your computer and thus earning a Proof of Resource.
  4. Storj: Storj aims to become a cloud storage platform that can’t be censored or monitored, or have downtime. Your files are encrypted, shredded into little pieces called 'shards', and stored in a decentralized network of computers around the globe. No one but you has a complete copy of your file, not even in an encrypted form.

Market 11 - Cloud computing

Obviously, renting computing power, one of the biggest emerging markets as of recent years, e.g. AWS and Digital Ocean, is also a service, which can be bought and managed via the blockchain.
  1. Golem: Allows easy use of Supercomputer in exchange for tokens. People worldwide can rent out their computers to the network and get paid for that service with Golem tokens.
  2. Elf: Allows easy use of Cloud computing in exchange for tokens.

Market 12 - Stablecoin

Last but not least, there are 2 stablecoins that have established themselves within the market. A stable coin is a coin that wants to be independent of the volatility of the crypto markets. This has worked out pretty well for Maker and DGD, accomplished through a carefully diversified currency fund and backing each token by 1g or real gold respectively. DO NOT CONFUSE DGD AND MAKER with their STABLE COINS DGX and DAI. DGD and MAKER are volatile, because they are the companies of DGX and DAI. DGX and DAI are the stable coins.
  1. DGD: Platform of the Stablecoin DGX. Every DGX coin is backed by 1g of gold and make use proof of asset consensus.
  2. Maker: Platform of the Stablecoin DAI that doesn't vary much in price through widespread and smart diversification of assets.
EDIT: Added a risk factor from 0 to 10. The baseline is 2 for any crypto. Significant scandals, mishaps, shady practices, questionable technology, increase the risk factor. Not having a product yet automatically means a risk factor of 6. Strong adoption and thus strong scrutiny or positive community lower the risk factor.
EDIT2: Added a subjective potential factor from 0 to 10, where its overall potential and a small or big market cap is factored in. Bitcoin with lots of potential only gets a 9, because of its massive market cap, because if Bitcoin goes 10x, smaller coins go 100x, PIVX gets a 10 for being as good as Monero while carrying a 10x smaller market cap, which would make PIVX go 100x if Monero goes 10x.
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Acute Growth of Algorithm Trading Market Opportunity Assessments 2019-2023

Acute Growth of Algorithm Trading Market Opportunity Assessments 2019-2023
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Established Strategies You Can Use In Forex Trading

Both down market and up market patterns are visible, but one is more dominant. You should aim to select the trades based on the trends.

Adjust your position each time you open up a new trade, based on the charts you're studying. Traders often open in the same position and spend more than they should or not a sufficient amount. Vary your position depending on the trades above you if you want to be profitable in the market.

Some currency pairs have what is called an inverse relationship with another currency pair. What this means is that when one pair is trending upwards, the other trends downward (and vice-versa). The classic example is that of the EUUSD vs. the USD/CHF. This comes about because the Swiss economy is closely tied with the rest of the European economy. Additionally, there is the common factor of the US dollar in both pairs.

If you are just starting out in Forex and you are still hesitant about investing your own money, sign up for a demo account with a broker that will enable you to try out your Forex investment skills. Demo accounts allow you to trade with virtual money. It is a great way for you to practice without risking any real money.

You should try Forex trading without the pressure of real money. By practicing live trading under real market conditions, you can get a feel for the Forex market without using actual currency. You can also get some excellent trading advice through online tutorials. Gather as much information as you can, and practice a lot of trading with your demo account, before you move on to trading with money.

It may seem like it is you against the world sometimes when it comes to dealing with Forex trading. With the vast amount of information available online, it can be nearly overwhelming at first. This article will provide much helpful information for you to get started on the right path.

Begin as a Forex trader by setting attainable goals and sticking with those goals. Establishing goals, and deadlines for meeting those goals, is extremely important when you're trading in Forex. Keep in mind that the timetable you create should have room for error. If this is your first-time trading, you will probably make mistakes. Additionally, calculate a realistic amount of time that you can spend trading, and make sure to factor in time spent researching.

You should pay attention to the larger time frames above the one-hour chart. Technology can even allow you to track Forex down to 15-minute intervals. The thing is that fluctuations occur all the time and it's sometimes random luck what happens. You do not need stress in your life, stay with long cycles.

Be sure that you always open up in a different position based on the market. There are Forex traders who always open using the same position. They often end up committing more cash than they intended and don't have enough money. Learn to adjust your trading accordingly for any chance of success.

Learning about the currency pair you choose is important. It can take a long time to learn different pairs, so don't hold up your trading education by waiting until you learn every single pair. It's better to pick a pair in which you are interested, do your research, and understand how volatile the pair is. Follow and news reports and take a look at forecasting for your currency pair.

As a beginner in Forex, you will need to determine what time frames you will prefer trading in. To make plans for getting in and out of trades quickly, rely on the 15-minute and hourly charts to plan your entry and exit points. A scalper, for example, might refer to the five- and ten-minute charts to complete trades within a matter of minutes.

Utilize resources at hand, such as exchange market signals, to facilitate purchases or sell-outs. Forex Robots Software allows you to set alerts that sound once the market reaches a certain rate. Figure out your exit and entry points ahead of time to avoid losing time to decision-making.

Many traders make careless decisions when they start making money based upon greed and excitement. Consequently, not having enough confidence can also cause you to lose money. Work hard to maintain control of your emotions and only act once you have all of the facts - never act based on your feelings.

If you are new to the trading market, you should begin your account with a small initial deposit. This minimizes your losses if you were to lose your money. Instead of depositing more money, you should try to make gains through the money that you initially invested, and then place the money into further investments.

Be sure that your account has a Stop-loss in place. Stop-losses are like free insurance for your trading. If you do not set up any type of Stop-loss order, and there happens to be a large move that was not expected, you can wind up losing quite a bit of money. Your capital can be preserved with Stop-loss orders.
submitted by forexrobotspro to u/forexrobotspro [link] [comments]

Looking for FOREX Forecasting Software

Hello good people
I am looking for a FOREX Software that can forecast exchange rates for at least a year ahead. Free or expensive doesn't matter, I am doing this as a report and any thing that you guys know works would be appreciated. Thanks!
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Hidden Scalping Code Download Making $4,000 $7,000 $9,000 everyday

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now we understand the most significant aspects of Currency Forex Robotic; it is a mainly grid hedge trading robot, functioning 24/5, uses the M30 timeframe and the pairs additionally working yet not officially supported are AUDJPY, GBPJPY, CHFJPY and EURJPY. We see plenty of trading pairs here, is it possible?
They started guide is somewhat not much information but their member area does absolutely fill this gap. I see a lot of stuff in there included extra downloads, extra tutorials and updated set files frequently as they promise. In addition, as you’ll see, they provide 4 extra daily trading signals on the EA official website. I don’t use the forecasting signals so cannot have any comments about the signals.
More couple of realities relating to this EA should be known, I will attempt to list them immediately. It is most likely not an excellent theory to manually configure each pair SL and TP although you can. The EA gets its set ups upgraded from the stifles after authorized gain access to configuring each pair preset values; each setting has its own stop loss and take profit so I cannot list all in here. Just an example, the stop loss ranges from 180 pips on EURUSD and GBPUSD to as high as 300 on, and so on. The stop loss is rarely reached, though – by deeper analyzing the backrests. It’s additionally an ability to choose gains early prior to the choose take profit target is hit by its positions. I am quite happy with the way it open extra positions when the market move in not favorable direction. Some secret ways in here that I cannot understand that lower the drawdown (and risk) when the robot scales in to positions.
The strategy itself is pretty complicated that you have to be careful to read their instructions or using set files on official site only; a few signs which are provided with Metatrader are affected in an ingenious approach, so the entry signals are identified. It’s retry iterations for opening/closing orders, signifying a particular amount of expertise with automatic trading in live. Instead the DLL programming is sometimes a hurdle for EAs working on multiple pairs with the identical DLL, in this situation it appears to be entirely threaded safe.
Hidden Scalping Code is the best forex trading solution to avoid trading during any uncertain market periods. Hidden Scalping Code does it’s works This will help you sell better on the foreign exchange market and make more money. This program will analyze all the graphics for you every second! So, you get the best trend of the pair and time frame, at any time you want. Hidden Scalping Code Free Download This Hidden Scalping Code software is less expensive compared to other forex software. You need a computer with an internet connection. All setup information is provided in the Hidden Scalping Code user’s guide. Hidden Scalping Code Software Reviews 
Hidden Scalping Code: This is a special trend indicator that is available only on the official website. Absolutely no repaint! It is designed to work on M15, M30, H1, H4 and D1 timeframes. Works for all currency pairs, but best on: EUUSD, GBP/USD, USD/JPY, EUJPY, GBP/JPY, USD/CHF and USD/CAD.
"Hidden Scalping Code" can also inform you of every new signal via review, pop up sound or push alerts. It's very convinient. The special informer that is implemented in this indicator shows trend strength, time left until next candle, last generated signal etc. This will make your trading even more simple and profitable!
"Hidden Scalping Code" is designed for MT4 platforms. It is NOT an EA or Robot, but a powerful buy/sell signal arrows scalping indicator software. You get smart signals, use them and make profit. I highly recommend you try "Hidden Scalping Code" right now
I have just downloaded the Brand New "Hidden Scalping Code" It's absolutely fantastic! The signals are VERY fast! I already opened two trades and both are currently over 150 pips profit.
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submitted by abcxyz01 to hiddenscalpingcode [link] [comments]

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

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

Top Submitters' Top Submissions

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

Top Commenters

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

Top Submissions

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

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
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