First time posting here and I'm not sure if this is the right category; apologies if it is. I've been interested in trading (primarily Forex) for a number of years and I just became serious about making it a career. I've been backtesting a system that I think is pretty good, but I would like some other opinions on the results. Below are some of the results; any input is very much appreciated!
2005-2017
- Annualized Return: 46.26%
- Win Rate: 55.54%
- Number of Trades: 2,618
- Max Drawdown: -28.68%
- Avg. Max Annual Drawdown: -18.26%
- CALMAR Ratio: 1.61
- Sterling Ratio: 1.64
- Sharpe Ratio: 1.73
2015-2017 (last 3 years)
- Annualized Return: 60.46%
- Win Rate: 56.36%
- Number of Trades: 621
- Max Drawdown: -26.46%
- Avg. Annual Drawdown: -19.78%
- CALMAR Ratio: 2.28
- Sterling Ratio: 2.03
- Sharpe Ratio: 2.60
no hard and fast rules but some ballparks.. 1 M in pnl with hope can grow beyond that if it's going takes some tech work and doesn't net with current stuff.
if hiring someone that's bringing it along and they want to be directly tied to pnl then 5 M pnl and uncorrelated to existing book
if something I came up with and can net with existing stuff then as long as it lowers turn or raises sharpe then it'll be thrown into the mix (or I'll just throw it in to avoid cherry picking/overfitting), so for example not trading the 4 sharpe low capacity thing but do have 1 sharpe low turn/uncorrelated signals that are traded in the book
currently running a book at a multi-manager hedge fund with payout based on sharpe so ultimately look at impact on payout
find alpha (the hard part), run optimization to neutralize/constrain risk factors while taking into account market impact/tcost/etc so one hopefully is putting on trades that actually make money, and then execute
the shorter termthe alpha the less the risk factors matter but the harder to execute (especially with the likes of virtu who probably have more invested in tech infrastructure than a lot funds have in capital) ' the longer term the alpha (especially overnight to days) then controlling risk becomes incredibly important since if you don't gonna end up trading things one doesn't intend to
so overall rather simple but devil is in the details and there isn't any literature that goes into sufficient detail to do it from scratch and most stuff out there is borderline useless
but a few books that are mildly helpful: Active Portfolio Management by Grinold/Kahn, Quantitative Equity Portfolio Management by Chincarini/Kim, Advances in Financial Machine Learning by Prado