1) the graph is not vol adjusted, but shows the contribution of each trading rule to total profits. Breakout has a higher weight, so contributes more. Having said that breakout does seem to be more profitable than ewmac [remember something can be correlated, but still have a higher average return]. 2) carry is done on each instrument, relative carry within asset class 3) the former is ewmac on the price, the latter ewmac on the cumulative vol normalised returns 4) the former looks at the entire asset class, the latter just each instrument 5) it's mean reversion within asset class ;if CAC has outpaced AEX then I'd buy the latter I'll be releasing python code for all these at some point GAT
In case I missed it, could you please give one more time exact definitions of 'breakout' & 'momentum'?
"momentum" is an exponentially weighted moving average crossover "breakout" is as defined on my blog GAT
Did you ever get around to testing this? I have to admit to being really impressed by the performance of such a simple algo. All of the fancy crap my broker uses can't hold a candle to it (not an apples to apples comparison, but still).
No not yet. Refactoring takes second place to finishing my book for an end of year deadline. Are these algos for equities? My impression is that it's harder to get decent execution in equities (market rules, more HFT predators, more fragmented markets). GAT
Yes. That comment wasn't fair and said out of frustration. I wouldn't expect futures vs. stock execution quality to be anything close to the same animal. However, I've seen major degradation in my fill quality over the last few years. Just to give a few stats that will make you glad you've chosen to focus on futures, here are slippage numbers (normalized by %ADV) by year for one model (~5k trades per year): 2013: 45 bps 2014: 60 bps 2015: 69 bps 2016: 74 bps I've analyzed the data a million different ways and the only conclusion I can come up with is that HFT algos are evolving faster than my broker's smart router. Anyway, appreciate your contributions here and elsewhere. Trading is my primary income source, so I don't think the slower pace would be a match for me...but you've certainly got me thinking about implementing similar concepts on much smaller time frames.
The impressive thing is the lack of draw-downs out of the gate. Every system I've ever run begins with losses, as most smart algos narrow down to some variation on the dump-losers-first-let-winners-run theme. You do not seem to have this problem. I have never seen this not to be the case. PS You're using a Unix platform. I like you.
I'm really looking forward to reading another book by you. Your first book honestly revolutionized how I view trading and dramatically helped me refine my own strategies. What is the topic of your new book? Is there any more information you're able to share? I'd be happy to help with proof-reading ;-)
Does anyone have any advice on where to receive realtime data feeds? I have a lot of historical data and am now in the process of monitoring things realtime. I am aware of CSIdata, but they are end of day only. Are there any other data sources available (with a high degree of accuracy) for e.g., at least hourly futures data for a reasonable price?
I have used both Interactive Brokers API for receiving real time data and IQFeed. IB is cheaper if you are already using them as a broker. IQFeed is more expensive, but can get cheaper if you use their fee waiver program for GLOBEX futures. For IQFeed you may need to pay like 300$ for their developer license if you want to get their API documentation or you can use some open source library to connect to them.