From Theory to Application - Need Input

[ronblack]

Quote from Occam:

Which instruments?

If it includes US equities, reported trades could be "internalized" or otherwise reported late, making a seemingly profitable strategy actually impossible in certain cases. For many US stocks, dark/internalized trades exceed 50% of total volume. So to be more sure, you need to use trade data that has these flagged, as well as late reported trades and busts. All of these need to be filtered out, as they otherwise might show a lot of "profit" that doesn't actually exist.

Also, for AAPL and other high-priced stocks, unless you're using direct exchange data from every exchange, you're probably missing the odd-lot trades until later in December, when it's finally going to be reported. That may help or hinder (but far more likely to help, IMO).

Maybe you're already considering these things, but I just thought I'd let you know. You probably won't really know the whole story until you start trading live, anyway. It never works out exactly the way it does in a simulation.

Excellent post.

I'd also like to add that most intraday backtests are not realistic because slippage is too high. HF robots know when you are placing an order and move the market their way.

If the OP would like to report the profit factor and Sharpe ratio along with avg. win to avg. loss and win rate maybe those will offer a better indication of his strategy dynamics.

 

[wfeagin3]

Quote from ronblack:

Excellent post.

I'd also like to add that most intraday backtests are not realistic because slippage is too high. HF robots know when you are placing an order and move the market their way.

If the OP would like to report the profit factor and Sharpe ratio along with avg. win to avg. loss and win rate maybe those will offer a better indication of his strategy dynamics.

I'm sorry that I am just responding. I've been busy over the holiday break. I have the metrics that you suggest I post.

Win rate = 68%
Profit Factor = 1.42

avg win = 0.33 of stock price
avg loss = 0.48 of stock price

annualized sharpe ratio = 6.3

What can you deduct from these metrics about the dynamics of my strategy? I was hoping that the avg win would catch more of the price movent. But 0.33 doesn't sound too small to me.

Thanks for your post!

 

[wfeagin3]

Quote from pick:


The correct way to backtest your strategy is to assume your buy price is the current asking price at the time you get the close for the tick bar. Conversely, your selling price will be the current bid price once you have all information needed for making your sell decision. In practice, you will have a bit of a time delay beyond that, but that is probably not that important unless you're trying to grab very rapidly moving markets.

I am working towards this now for comparison. I will only be able to compare the last 20 days of trading for the bid ask prices. I have only been saving the market trades.
I have not been intentionally trying to capture any of the bid ask spread. I was only assuming that I could buy and sell at market with a small order size in a high volume stock.
I had not planned on using limit orders in fear that some of them would not get filled. My intention is to use market orders. I am assuming that the market would move in my favor and not in my favor about equally. Therefore, I do not consider it in my backtests. Is that an unreasonable assumption?

Thanks for the post!