Time for another thread on algo trading basics as I've been getting many DM's on where to start:

1. Start with trading manually and finding what works for you, what trading style, indicators, R/R, etc.
2. If you know how to use Pine script on Tradingview start there to backtest
2/ If you are not familiar, Python is usually the best/easy language to do algo/quant research in (with some R/Matlab for low level). This is a good course to begin with https://www.udemy.com/course/python-for-finance-and-trading-algorithms/

You'll need to understand dataframes in pandas to be able to analyze candle data.
After that, you want to choose the right backtester. There is a quite a few out there, but for crypto and @QuantumLabs1 we built our own in-house. We even have ML/Evolutionary based optimizer to churn out variations of backtests/parameters so we aren't tweaking manually all day.
The biggest issue I see with new algo devs is they dont apply slippage/fees in their backtest and assume unlimited liquidity. You also want a strategy that has the least amount of negative months rather than being fixated on getting 100-200x returns. For reference..
We have a strategy that does 200x returns in a 3.5 year period with 1x leverage. However, if you had started in year 2, you may not get the full 200x returns. You'd have to start from Day 0 and hold until 3.5 years is up. This is not practical.
The ultimate goal is to have a decent sharpe above 1.75, sortino above 2.0, and have no more than 3 neg months in a 12 month period. That way if an investor/client uses your algo and they come in on a random month, you can assure they will have smooth returns.
Initially, we had algos that would theoretically return 200x+ returns but most of those returns were done in a few months time (think Nov 2017-Jan 2018) so if you came in on Feb 2018 your 200x is probably more like 2-5x returns. Timing is key, smooth returns is key, call it IRR.
@CanteringClark Tagging you as I thought you might find this interesting as I've seen you're interested in learning Python/algo/etc.
You can follow @usgoose.
Tip: mention @twtextapp on a Twitter thread with the keyword “unroll” to get a link to it.

Latest Threads Unrolled:

By continuing to use the site, you are consenting to the use of cookies as explained in our Cookie Policy to improve your experience.