I searched and could not find these exact answers anywhere so I was hoping one of you could help me out. I am backtesting an automated trading program of my own design that I hired a programmer to create. I am backtesting over the S&P 500 and have been calculating 5 bp slippage. I have been told that 5 bp is reasonable for highly liquid stocks but to use 15 bp for illiquid stocks. Do any of you have any advice on what number to use? The scary thing to me is that I can show a healthy profit at 5bp, but usually a loss at 15bp.
Also, I am backtesing on 1 minute data from Reuters, but only have access to one years worth of data. If the program trades about 400 times per stock and shows a profit across all 500 (I have not tested on all 500 yet I am trying to optimize over 40 before I test on the entire S&P) any advice on whether or not it is possible to still be so overfit, because it is just one year of data, that my real results will be drastically different?
Any advice would be really appreciated.
Also, I am backtesing on 1 minute data from Reuters, but only have access to one years worth of data. If the program trades about 400 times per stock and shows a profit across all 500 (I have not tested on all 500 yet I am trying to optimize over 40 before I test on the entire S&P) any advice on whether or not it is possible to still be so overfit, because it is just one year of data, that my real results will be drastically different?
Any advice would be really appreciated.