Dutch Algotrading
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Forgotten FrostAura strategies :-S
🕑 Added 2024-08-07 07:00:00 +0000 UTCFrostAura M21h and M31h strategies
Introduction
In my previous post I presented the FrostAuraM115m strategy. But shortly after posting those results I found another directory with two similar named, but different trading algos too. As a result, the outcome of these two strategies is also much different.
I did not want to keep these two different trading algo’s behind. So here are the result and let me get right down to the code of these two algorithms.
The strategy
First of all, both strategies have unknown origins, but the author was nice enough to leave some comments about the intentions of the algorithms.
The M21h version has the following comment:
They both have different take profit and stoploss settings too:
M21h
M31h
Now these are small differences. More noticeable is the use of the indicators, already mentioned in the comments section.
M21h
Buy & sell signals
As a result, the buy and sell signals are also different.
M21h
M31h
As an avid and experienced reverse engineer, you might already know what is happening here.
The only thing that was really different I noticed was the use of a minimum_coin_price as a factor for buying or not buying. Apparently, the author has the idea that there will be a dynamic pair list used for this algo (like the volume pair list).
If you are using a static pair list with a pair used that has a very low price, then that pair would ever be used according to this configuration.
Backtest results
M21h
Let me first show you the results of the FrostAuraM21hStrategy.
The equity curve of this version is very spikey to say the least.
It might respond well to bearish circumstances, but when the bears walk in, then the gained money can be easy lost as well.
This is also clearly visible in the profits and losses over the weeks. Where the mean profit drops steeply around the half of 2021.
M31h
Although there are also some remarkable things happening here too which do not make me comfortable using this strategy in real time.
To start with a positive thing here, the profits are taken, and the gains are kept. But if you look at the low number of trades there are, then you (or the trading bot you are using) would probably do not much most of the time. Which leads to opportunity costs.
The drawdown is relatively low but again, considering the low number of trades, there is not much to fear. This is better visible in the next plot where we can see an overview of the weeks that there used for trading.
In earlier tested algorithms, there were trades made every week. Whether they were successful or not. But here it’s clearly visible that the largest part of the time there is no action whatever.
Of course, it is not obligated to trade every day or every week and there can be periods when there are no trades made if your strategy demands it. But again, the lack of trades can also point to a strategy that is too strict and too risk averse. And scared money does not make money here.
Nonetheless my scores for this version are much better because of this reason.
But we know now that there are better strategies out there that can be profitable and have a low risk of losing it again to the market too.
So, these two strategies do not score the best and therefore also score low in the strategy league as well.
End
And also, for this Patreon blogpost only, the results are in for these two strategies that I found on GitHub.
You do not have to search for these Python files though, since I will add them to the files that are included in this post. Together with all the other output and logs.
As promised in earlier posts, I will keep the results and posts of strategies that score below average short and concise. So, to not waste your and my time. Extensively analyzing results that will probably never be used after that anyway.
You are always invited to optimize or use parts of this strategy if you like to. But I will continue searching for other, already available strategies and test their results.
Because I still have the feeling that other algorithms will provide us with better results than this one.
This is it for now. Thank you all for being a Patron and I will see you the next time.
Goodbye!
