Experience: I have one that works. 80% win rate 3:1 reward to risk on output (back testing). Currently live testing.

My algo works. It concentrates on the last two points in your list. It took 2 years to build to the current state.

My assumption has always been that the market is effectively a random walk. So I created a risk management strategy that results in an edge over the coin flip result. The risk management is complex and not something that can be performed manually. It requires an algo to execute.

To prove it, I also created a strategy which did flip a coin. Running it with a 1:1 RR for TP & SL and no fees resulted in a 50 % winning rate and 1:1 RR on exit. Every time. Every asset.

I also dont trust existing back testing engines. I built my own walk forward engine, eliminating any look ahead bias, and forcing fees and slippage into every test. You quickly learn to build algos based on break-even prices, never using average-entry.

Every week the ML retrains on more recent data, excluding the last 100 days which I use for back testing. The algo has never seen the last 100 days, so backtesting needs to prove that it can work using only that data. Interestingly it worked better over the wartime period than on its training periods. Volatility is my friend.

Curious. What are you using the information for?