Why I'll transform Reddit into a new online economy
Hi! I've been a Redditor since the great Digg migration and have been a Fintech & Crypto professional my entire career. My journey into tech started by discovering a post on Reddit about a new p2p cash payment system called Bitcoin in 2010. I was immediately a trader and miner, and taught myself to code in Python to create a trading algorithm in 2014. The algo became fairly successful and I decided to pursue a higher degree of education at Cornell Tech where I received an MBA but furthered my technical skills around data, systems engineering, and blockchain. I spent over two years innovating consumer fintech for CitiBank at Citi Ventures and enterprise fintech at JP Morgan, and in 2017 I left to start my own social crypto wallet called Mirian. I also part-time consulted on token design and economics for organizations including the Ethereum Foundation. Mirian was and still is ahead of its time, but it didn't grow to its potential after peaking at 1000+ users due to some personal mishaps along with some first-time founder mistakes I made. Nonetheless, I received an opportunity to move to Silicon Valley and work with a startup called Peernova, where I've spent my last year as a Sr. PM applying my deep crypto and data knowledge to construct new types of digital economies intertwined with data analytics. As I look for something new and exciting to tackle in my career and continue Redditing more than I'd like to admit, I can't think of a more suited opportunity to apply my skills than shaping the future of Paid Digital Goods at Reddit. I believe my experience in incentive and token design for consumer apps like Mirian or ones I've been working on for the World Bank at Peernova can be the catalyst Reddit is looking for to propel its Paid Goods strategy and foothold. I can't fathom how excited I'd be to dig into the digital goods data at Reddit and shape a roadmap around the behavioral patterns I discover on their use. I look forward to your review of my background and application. Many thanks for reading, Murat
My 10 Months Journey in Algo Trading - A trip down the rabbit hole. (And why you should be persistent)
Hello everyone, the following is my own story inside this market. Since i first heard about Crypto, i never again lost interest for it. I remember it was late 2014 when i first met a friend that was deep into Bitcoin, saying all kinds of crazy stuff about it like it would be the future of money, that it was a revolutionary tech and was going to be the reason why governments would no longer be so able to control your own money (Later he dropped out of college to work for one of the major exchanges today). Me, being your average college anarchist, thought that was absolutely amazing, and i became eager to understand what that new tech actually meant. To this day i don't completely remember why i never bought any BTC at the time, maybe it was because i didnt have any kind of spare money on me, and that was about it. It was only late 2017 that I first got around to having a good amount of money to finally be able to buy some BTC. Now, guys, if any of you was around the scenario at the time, you should remember that BTC was peaking... Days later it completely crashed. I bought it at $17.000... Sold it at $8.300. I was completely furious. That money took me a long time to save up!! I remember not telling that to anyone, and I was completely and utterly done with crypto! But oh boy... Was I wrong. I really left the community after that, without any willingness to come back again. It was only until Mid July 2019 that crypto finally picked up on my radar again, when another friend added me to his Telegram discussion group. People there seemed quite the bunch, of all ages and degree of knowledge, sharing everything they could find about news/articles/theories about Btc and Altcoins. And this my friends, is where the 10 Months journey actually begins. Seeing that absurd amount of information being shared, i felt it was time to study the market again and put my money on it AGAIN, but this time as an Altcoin Trader (I now know it was a stupid idea). Studied for months, developed strategies, paper tested them... Lost it all in 2 weeks. Not satisfied, I wrongly believed the mistake was my own, and if i really wanted to conquer financial freedom, i had to study more, perfect my strategy. I repeated this cycle About 4 of 5 times, losing everything at somepoint, everytime. One day, someone forwarded me a paper saying about 90%+ traders will completely fail in the long run, and i completely agreed with it, concluding that i was one of those. But, an excerpt said the following: "Most traders lose in the long run not because their strategy suddenly stops working, but because they get emotional on trades". And the conclusion on my head was just as simple as you can imagine: "then, Let's remove emotion". To shorten the story, i met a guy there who had developed some sort of market scanner for a specific exchange. The Market scanner was absolutely great, but he wasn't managing to draw a good strategy from it. Hearing that, I reached out to two awesome programmers i met on college, so they could help me with some kind of algo trading bot based on what the scanner was telling us, and they agreed to help. I was in charge of Data Analysis/strategy developing, and the other two managed the Database and coded the hard part of the integration with the scanner. The first test was a complete failure as well. The algo, after A LOT of work on our end, managed to nail the top and always buy on it, resulting in an absurd amount of losses. We obviously were very disappointed saying that so much time was wasted on something that was not even close from being profitable. So, stubborn as we are, we studied even more. We added several self-adjustable parameters within it, Studied LSTM Analysis to apply better filters and Pretty much devoured the Turtle Trading Book. Guess what? The both still managed to lose, only this time a bit slower. At this point, we already accepted our fate that we were never going to make something work, but we kept researching new methods just because they helped us understand and try out Python and Data analysis tools in a practical way. When Corona arrived, we decided to lock ourselves up together, to give it one last as well aimed shot at developing an Algo. This time, we actually allowed ourselves to be creative and try all sorts of crazy out-of-the-box techniques, while always remembering the motto "The difference between Losing and Winning is merely detail." Then a flash of brilliance came to us. We were interpreting the market the wrong way all along, making something statical read something ever-shifting like the crypto market. That was bound to lose us money in the long run. We finally got rid of several useless add-ons on the algo, and updated the parameters for entries based on what our theory was. And well, we finally did it! The new algo is running since the 14th of this month, with 93% Winrate on First Targets across all of the exchange's Pairs and 80% winrate on the second Target. We are at our most happy moment with this journey and completely sure we can further improve our new and working system! So, here goes some tips: - No matter at which point you are on your Code, never stop studying. News things pop up everyday, and there's always something out there that you can use, but do not know exists. - "The difference between losing and winning is merely detail" - Never be afraid to share the project with others. They are your greatest source of help - Be aware of commisions and pay attention to compound interest - Never make a strategy that doesn't adapt itself, or better bots will start to read it and completely crush it. - Be persistent :) TL;DR I built a good algo with the money i lost along the way
Hi, I am looking to use my novice Python skills to help me filter equities (though commodities and bitcoin are of interest too) prices as well as build up a database, which I can use once I have some algo ideas. Anyone can recommend a good data provider for a private individual, with a good trade-off between ease of access, price and reliability?
https://github.com/fxcm/RestAPI/blob/mastePython-Live-Trading-Examples/Bitcoin%20Breakout%20Strategy.py The algo looks to take advantage of Bitcoin’s volatility by getting into a breakout trade as soon as it occurs, using real time streaming tick data via WebSocket. This strategy buys the moment Bitcoin’s price breaks above the 24-hour high and sells the moment Bitcoin’s price breaks below the 24-hour low. Profit targets (limit orders) are set at 1.5x the distance between the 24-hour high and low. While no actual stop loss orders are set for each trade, the strategy automatically closes out a trade when an opposing signal occurs (i.e. closes buy trades when a sell breakout occurs, closes sell trades when a buy breakout occurs.) This effectively gives the strategy a built in trailing stop. Try it out and let me know your thoughts. (Losses can exceed deposits)
Any interest in a HFT and backtesting platform for GDAX?
I'm building out the tech infrastructure required for analyzing a GDAX bitcoin order book and executing/simulating trades based on it in real-time. Doing it for myself for now, as the only bots and data sets I found were for trading based on historical ticker price only, not with actual order book data. With a little more effort, I can expose the simulation engine through a web interface. I'm just hoping to gauge the interest before I do. Are there folks here who would like to test out some order book dynamics algos on GDAX markets? Edit: Some tech details
Trading and analysis strategies must be written in Scala (python possible in future).
Matching is done naively, as it doesn't take into account GDAX self-trade prevention. A caveat to keep in mind. But in my experience, most algorithms are not impacted by this in simulations.
Engine-to-exchange request latency is configurable for simulations (defaults to 20ms)
Happy to answer more questions as they come. Edit #2: Cool, looks like people would be interested in poking around! I'll get a Github repo up as soon as it's ready, along with a web interface to mess instantly try it out, Quantopian-style. In the meanwhile, plz continue posting or PMing if interested. Also, I'm full of questions for existing traders. I would love to hear about existing algo trading platforms ya'll have experience with. Any killer features, or limitations, you ran in to? Are there common APIs for strategy construction I should conform to? (For now, I've been using a simplified Zipline-like API) Edit #3 We started a Slack channel! Join here if you'd like to discuss further or collaborate.
Well, i`m a engeneering student and while i was trading bitcoins i found out that Algo Trading was a thing, and thats why im here. I found it extremely interesting, because it has my favourite things, like statistics, programming, economics, machine learning and, of cour$e, money! Anyway, i read a significant amount of posts and it seems to be extremely complicated and although i like it, i cant spend too much time studying it, as i am more compromised with robotics and stuff like that (i know that they both have stat and programming, but they are probably very different, idk) I know the basics of economics, linear algebra, calculus, C, and a bit of Python and Java. Well, my question is: can i learn a few things in a couple weeks and develop (or just get from someone) a trading algorithm to something small and specific, like bitcoin? I dont wanna get a server or smth big, could i just run a algo on my computer, learn some code, math and maybe dont lose money?
03-21 18:23 - '(FOR HIRE) Blockchain developers' (self.Bitcoin) by /u/Marekzvar removed from /r/Bitcoin within 82-92min
''' Hi everyone, We have free development capacity now. We are Blockchain and ML dev team based in San Francisco and Prague, CZ. We love cryptocurrencies, coding wallets, exchanges, we have experience with Pattern recognition, Algo trading, NLP, Artificial Intelligence and chatbots. Our Stack: Clojure, ClojureScript, Solidity, Python (TensorFlow, Pytorch, Django), JS, Node.Js, Angular, React Native, C#, AWS, MongoDB and many other technologies. Our Projects: [link]1 , [link]2 , [link]3 , [link]4 , [link]5 , Stealth startup - Machine Learning platform for forex trading. Now we work on [link]6 and [link]7 We are looking ideally for long-term project or cooperation. We can join your core team and help with the Machine Learning, Blockchain, web or mobile apps or develop the whole project from scratch. Here is some basic information about us: [link]8 Send PM If you would like to chat a bit or you can reach me here - [email protected] Cheers, Mark ''' (FOR HIRE) Blockchain developers Go1dfish undelete link unreddit undelete link Author: Marekzvar 1: www.status.im 2: www.foldapp.com 3: www.evolta.fi 4: www.trezor.io 5: www.discomelee.com 6: www.neureal.net 7: www.volentix.com 8: www.flexiana.com
[Sorry for the long post] So I've looked around this sub and I see a lot of high level or theoretical Algo discussions which I can appreciate but I'm kind of lost when it comes to practical applications and I don't even know if any service even exists that can meet my needs. Currently, I have a strategy that I think is a little profitable with 1 minute data intraday swing trading on USDJPY, it's very simple and written in Pinescript. I plug the pinescript into a 1 min chart on Tradingview and it spits out alerts for my trades. The alerts are picked up by a chrome addon called Autoview which sends the orders to 1broker using a special alert API. I hate it for many reasons: - Chrome with tradingview and Autoview must be running and checked frequently for glitches (sometimes alerts stop firing randomly) - Tradingview alerts are not meant to be used as orders so I lose any semblance of order management. Basically it fires alerts/orders for every entry point regardless of my current balance or positions. - Pinescript sucks. - 1broker uses bitcoins as currency, I like bitcoins but don't fully trust putting thousands of dollars into them when it could be rendered obsolete at any time without warning. So the reason I use it is because it meets all my needs. I'm just starting out and I have a fairly large income via my job (US) but it would take me at more than a year to save up 25k for a legit daytrading account. So I need to find a broker + automation combo with the following: - hedging within the same fund (is this not allowed in the US?) - can make unlimited day trades without needing $25,000 USD, low minimum account size - low or no fees - supports 24/5 forex or E-mini trading (options not required) - API for automation with somewhat low coding requirements. I am familiar with python but by no means am I an expert. I like looking at tradingview charts and backtest instantaneously via graphical interface but I realize this is probably not very common. I've spent a lot of time on both Quantopian and Quantconnect but neither of them can do intraday trading very well if at all. They are primarily focused on fundamental trading and I'm more into technical trading. I tried looking into Ninjatrader, metatrader, whatever but I found them very expensive, unnecessarily complicated, and beholden to the US's stupid trading laws. TL;DR - Can anyone tell me exactly how to implement my simple automated intraday FX strategy using a simple interface that doesn't require me to have a $25,000 US brokerage account and software that costs 1000's of dollars? P.S. If any other beginners are in the same situation as me you should look into 1broker.com + TradingView + Autoview, it's pretty sweet given the limitations it's working with.
Why OKCoin isn't faking volumes, and why volume is silly measurement on zero fee markets.
Hello Everyone, This is a post to answer many people's question, I don't think Zane Tackett really explained the root of the confusion with volume in his post. I saw a lot of posts complaining about Chinese exchanges faking volume, I'd like to contribute to this discussion by showing (from a neutral perspective) why OKCoin and Huobi do not fake their volume, and why the complaints about this topic are just plain useless, I am going to include a python bot which you can try out yourself to test my hypothesis. The Controversy Many people have accused Chinese exchanges of faking volume, mainly stating spread changes and quick order movements as their main backing reason, this has caused a lot of discussion. Essentially the main argument is that exchanges fake volume to make their credibility rise, pulling in more people so they can make money of CNY withdrawals. This has even led their manager of international operations to state why these claims are false. Why are 0% fees feasible? Because that's Just how China does it. There is a more competitive market on Chinese exchanges as most Chinese are in for immeadiete profit algo based trading. Americans & Europeans mainly buy Bitcoin as a long term investment expecting its value to rise over time, which means the 0.2% fee and the lack of a proper API are not really an issue for them. Chinese exchanges still make CNY off of their CNY withdrawal fees. OK, you mentioned this high frequency trading stuff, why does it matter? As someone who is using a VPS in Beijing at the same place OKcoin's datacenter is based, I am still getting one upped on orders, these guys do exist. Someone trading once a minute with 1 BTC volume everytime will have a total volume of over 1400BTC! OK, prove it! It is important to note that increased leverage oportunities exist for high volume traders in the form of OKCoin reward points. It only takes a few lines of code to make a bot that trades within the spread and makes no direct loss which fakes volume. I know this code is is not good, how bad I am at python just outlines how easy this is! This was done using this python wrapper https://github.com/trexmatt/OKCoin-API, I excluded imports and private key imports, pm me if you need help! Moved code to the edit! You should probably also create a balance fetcher and place buy and sells at the min volume from a list to avoid invalid balances, not including that here for the sake of keeping it short! PM me if you need help (optimally sleep 5 seconds, refetch, and then place altering orders after sleeping). Then what should I used instead of volume? Easy, spread and market depth. Not misleading, and the most relevant to trading! Edit: Turns out reddit is shitty for posting code, so I placed a simplified version here, PM me if you want a functional volume faker, and I will post a link to github here. (unless OKCoin is against that). Edit: Here is a bot that should give you a few million USD trading volume per day even if you just have 1BTC!, you may want to do some partial handling yourself, you can adjust the order depth you take by adjusting key values!
M = okcoin.MarketData() okcoin_sell_list = dict.items(M.get_depth('btc_cny').asks) lowest_sell = min(okcoin_sell_list) okcoin_lowest_sell_price_btc = lowest_sell okcoin_lowest_sell_volume_btc = lowest_sell okcoin_buy_list = dict.items(M.get_depth('btc_cny').bids) highest_buy = max(okcoin_buy_list) okcoin_highest_buy_price_btc = highest_buy okcoin_highest_buy_volume_btc = highest_buy """Get balances!""" bbb = okconf.get_info() okcoin_cny_balance = float(bbb['info']['funds']['free']['cny']) okcoin_btc_balance = float(bbb['info']['funds']['free']['btc']) """calculate min volume!""" min_volume1 = min(okcoin_highest_buy_volume_btc,okcoin_btc_balance) min_volume2 = min(okcoin_cny_balance/okcoin_lowest_sell_price,okcoin_lowest_sell_volume) """Now just trade one by one!""" if 0.01 < min_volume_1: okconf.trade('btc_cny', 'sell', okcoin_highest_buy_price_btc, min_volume_1) if 0.01 < min_volume_2: okconf.trade('btc_cny', 'buy', okcoin_lowest_sell_price_btc, min_volume2) time.sleep(5)
[SMT] Python script that will display my mining stats onto a RPi Char LCD Plate
I am sorry if this isn't the right subreddit to ask this. I did do a search but I only found C programmers for hire and a general for hire. If this isn't the right place, any point in the right direction would be greatly appreciated. I have always and still do have an interest in Python and would love to learn how to write said language. Usually, with the help of google I can make small projects happen by my lonesome. However, this time I cannot and I'd like to leave it to an expert because I'd like this working soon. So heres what I'm looking for; I need a script to run my 16x2 Character LCD plate that I have on my RPi B+ which is running Minera. Which if you're not familiar it is a BTC/LTC mining interface that keeps stats and such. I'd like the LCD to be able to show certain sections of criteria (hashrate, temp, rejected, accepted, runtime, etc) and be able to cycle through screens using the direction pad on the Pi's LCD plate. If I'm not completely wrong, that should all be able to be pulled from a local JSON file that displays every strings(?) value. So I'd like to think this wouldn't be a very challenging task for someone who knows a thing or two about Python. I have tried to use other scripts as references but I have yet to find anything familiar enough or anybody generous enough to help. I have analysed the PiMiner cgminer script that displays stats but its completely different as far as I can tell. I also don't want stats from just one mining script I need the stats as a whole that Minera shows. The JSON looks like:
Below is the format I suppose would be needed. I hope it makes sense, haha. I hope I'm somewhat close to accurately conveying what is in my mind. Hope this "format" makes sense :| Left/Right scroll below: Screen 1:
Top Row: Current time
Second Row: wlan0's local ip
Top Row: Accepted, Rejected, Errors.
Second Row: Frequency, Shares
Top Row: Local hashrate, pool hashrate
Second Row: Sysuptime, Temp
Also, the up/down on the directional pad to display/cycle through; Up/Down Scroll Loop: * Top: Litecoin Balance * Bottom: #Balance# Down/Up Scroll Loop: * Top: Dogecoin Balance * Bottom: #Balance# I hope I'm making sense but if you need me to be more specific, ask me. If could maybe afford to pay a little to get this done so if its something you think you could help me out with please give me a shout! :)
Well, the Automated Trading Using Python Algo Stock Trading course is right here for you! The goal of the course: to go the way from beginner to algorithmic trader. It means that by the end of this guide you will be able to use what you’ve learned and create Algo trading that execute whatever strategy you can come up with. AlgoTrader is the world’s first professional algorithmic trading solution to support automated Cryptocurrency trading. AlgoTrader has direct exchange adapters to Binance, Bitfinex, BitFlyer, Bithumb Pro, BitMex, BitStamp, Coinbase Pro, Deribit, Huobi spot, Kraken spot, OkEx / OkCoin, RFQ adapters to B2C2 and Tilde/Grasshopper, historical data adapters to CoinAPI and CoinMarketCap, as well as Cryptocurrency / Bitcoin Trading Bots in Python Algo / Automated Cryptocurrency Trading with Python-Based Open Source Software Guides and Instructional YouTube Videos by @BlockchainEng Joaquin Roibal focusing on crypto trading strategies such as Triangular Arbitrage, Market Making, etc. Interactive Brokers (IB) is a trading brokerage used by professional traders and small funds. If you want to learn how to build automated trading strategies on a platform used by serious traders, this is the guide for you. Table of Content What is the Interactive Brokers Python native API? Why should I learn the IB […] 5. Simulated Trading and Trade Tracking. 5.1. Bitcoin as a Benchmark. Given the rules when to open and when to close each trade, in the following simulation of intraday algo-trading, let’s assume we invest every time 1000 USD in each trade (again, no fee structure applied here). To begin, we can analyse what-if we were trading Bitcoin only.
How to do Automated Bitcoin Algo Trading via BTC-e Trade ...
This is the first part of the "algorithmic cryptocurrencies trading" video series, where I take you through the implementation of a crypto trading bot in python. In this video we're writing a ... Algorithmic Cryptocurrency Trading Strategies in Python Quantra by QuantInsti ... let us create and backtest a trading strategy on the day of the week anomaly on the Bitcoins. It is the anomaly ... In this tutorial, you are shown how to use Python to communicate with a bitcoin trade API. In this case, we are using BTC-e's Trade API, though the trade API... 24/7 Live Bitcoin Algo Trading on Deribit Exchange (DeriBot) Bitcoin Trading Robots 298 watching Live now How to Trade Simple Moving Averages - Python Automation Tutorial - Duration: 8:06. I explain the reason why Bitcoin is huge with the black box bots out there. ... Overview of my Python 3 Algo Trading with Cyrpto Curcency like Bitcoin ... Start with and stick with Python. It is ...