In fact, sometimes - even when you're trading the actual system - your results will vary from the model. One of the ways I monitor my execution is to run the model at the end of each month. Then I take the model trades (the ones produced by the backtester for the past month) and compare them with my actual trades. Why wouldn't they match perfectly? Well, they don't always and there are a host of reasons... here are a few:
Commissions: I normally include commissions when I run my backtests, particularly when I have a system at the final stages of development. My commission rate through Interactive Brokers is $0.005 per share (half penny per share). That's the rate I use, but you may have a completely different rate.
Sequencing: A few times of year something happens that almost assures variance from the model. Each day I scan for signals and enter orders accordingly. Normally, it's just a few orders and even if they all triggered - a rare occurrence - I would have enough equity in my account to cover the orders. On rare occasion, MANY signals are returned... sometimes 40 or 50 or more. When they happens it is likely that I would not have enough equity to cover all the trades, so I will buy the first few that trigger in the order that they trigger. ... end of day data... etc.
Liquidity: Every once in a while there is a very fine line between reality and modeling (aka. backtesting). Trades that look like they should work in a backtest, don't quite work in the real world. For example, I might have an order to buy at a price... call it $20.00. The low of the day was indeed $20; right at the price of my limit order. The problem is that it was the extreme low for the day, didn't stay there long, and didn't trade much volume at that level. I had a similar circumstance about two weeks ago. My order triggered and partially filled, but that was it. The price never went back and I never got the complete fill. In backtesting it looks just fine, but in the real world it didn't work out that way.
Mistakes: While I make every effort to follow the trading parameters precisely, occasionally I just mess it up. Mistakes are tracked and measured to determine their impact, and how to avoid them in the future. Trading automation is employed for several steps of the trading process, which reduces many errors, but mistakes still happen. Each month I compare my actual trades to the trades of the model. Rarely are there variances, but in the event of a mistake it shows me exactly where I didn’t follow the model precisely.
Generally, these four types of variances are fairly subtle and rare, although they do happen. Real world results don't match exactly, but they should always be directionally correct.