I am working on a program to backtest it. Honestly, I still have much to learn. I do things visually. So I take the little fib retracement chart tool in trading view and make the anchor at the beginning of a price movement and align the lines to the closing prices of significant support/resistance (defined mathematically as any 5 bars such that the the middle bar has the lowest low or highest high in like pyramid form.) If I see at least 3 lines of the fib retracement align, I consider the market to be demonstrating that pattern and I make a bet the market will reverse when it hits the highest fib line. This is much easier to see btw and I have a website where I’m going to write this out if you’re interested: https://seanneilan.com/ I have corresponding Python code that automates this strategy too that I intend to post once it’s ready.
No hate. But just remember that when you think that something is a good BUY, the other side (the seller) think that it is a good SELL. Hence, before trading in the stock market (or in any other market which is a zero sum game, e.g. used cars, NFT), you must be sure that you have more information than the seller.
Do you know of any studies or articles that shows why backtesting actually works or is useful? I have been reading up on automated and systematic trading, but I do not yet understand how backtesting gives one anything more than warm fuzzies.
For backtesting to work, wouldn't one need to re-run (i.e., playback and not simulate) all inputs from what the real data was (instrument pricing, the weather, social media sentiment, whatever) at a time resolution finer than what your algorithm operates on? If so, that's a massive amount of data that may even be impossible to get.
I'm not sure. I haven't found much on whether or not backtesting works in general. It definitely has its caveats. I think it really depends on what you're backtesting.
Backtesting definitely reveals ways in which trading algorithms can fail though. It can reveal more scenarios than one would initially consider which is super helpful.
Evidence-Based Technical Analysis is a starting point (book), but iirc it was able to show most common indicators aren't able to reject the null hypothesis.
I will also admit I am perhaps overconfident about my strategy. It accurately lined up to when the omicron announcement happened and then I sold my shares in the market and bought them back once I "felt" the market had finished pricing in the information. So I have half a strategy right now. My buy back strat is not great but my timing to short the S&P 500 was absolutely impeccable. And that's why I'm inspired to work on this now.
sneilan1|4 years ago
streetcat1|4 years ago
vasco|4 years ago
bmitc|4 years ago
For backtesting to work, wouldn't one need to re-run (i.e., playback and not simulate) all inputs from what the real data was (instrument pricing, the weather, social media sentiment, whatever) at a time resolution finer than what your algorithm operates on? If so, that's a massive amount of data that may even be impossible to get.
sneilan1|4 years ago
Backtesting definitely reveals ways in which trading algorithms can fail though. It can reveal more scenarios than one would initially consider which is super helpful.
smrtinsert|4 years ago
sneilan1|4 years ago