Right, it's just a drastic shift in the amount of training data, from 4 years to 1 month. I don't think it's reasonable to train a strategy on just 1 month of data, even as a test of robustness. I could be wrong!
It should affect strategies that are delta netural less. Are your automated strategies all breakouts of some sort
Through the years, i have spent thousands of hours back testing. Every strategy that i trade go through the same process. 1. Theory. 2. Back test and collect as many samples as you can or until you feel that the sample size is statistically relevant. 3. Forward test and trade a small amount relative to normal trading size. 4. If its proven profitable increase trading size based on your overall profits. So i'm sorry, i have to strongly disagree with this statement. I have a system that i'm trading now that is extremely systematic where there's hardly any thinking involved. If the numbers add up you hold/buy and if it doesn't add up you exit/short. I would be willing to go as far as saying the money that i make is through back testing and not live trading, because in live trading all i'm doing is pushing buttons.
My experience is more in the market making sector so these trump tweets are a bit of a disaster for a some strategies running in fpga code
It's a pain to put new code up there. Things that have been working for decades start making losses because of trump tweets. We don't run code on servers, we run it on FPGA
There are too few trades for the backtest and optimization. Typically you need 2k-3k of data points for a backtest. if you don't have this many trades, then trade more instruments using the same rules, or break down your trades into daily P&L to increase sample size. the optimization needs a lot more trades too.