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As I mentioned earlier it went well. So I scaled up from $20k to $40k. That is, I deposited an additional $20k. So profit is now $1.82k.

That's why I provided the Sharpe ratio. It's a better metric since the capital base changed over time. The total money placed in the account is $40k. Total balance is now $41.82k. So profit is currently $1.82k.

It's very simple stuff. Usually just a few lines of numpy. The most complex parts are pulling price data from quandl automatically and stitching the futures.

It's been a while. Thought I'd post a quick update. I've increased my account to $40k and scaled the positions accordingly. Current account value is $41.53k. Sharpe ratio since I started trading is 1.12. Current positions: AUD 2016-03 -1 EDOLLAR 2017-12 2 TU 2016-01 1...

This is pretty interesting. Any reason you're selecting individual stocks versus just buying into an index fund?

Thanks for the interest. I'm using Python for everything, from stitching futures prices through to backtesting, portfolio analysis and trade generation. I pull prices from quandl with a cron job on my mac and have Python email me once a day with any necessary trades using Postmark which provides...

Not much new on this front. No new trades. Portfolio is back up to $19,673. I've automated everything except execution so now I just receive an email once per day with directions on what trades to make.

Thanks for sharing your current status. It's comforting to know that I'm not the only one in drawdown right now. I'm 5% below high water mark. Janet's recent statements really hurt 2 year treasuries and Eurodollar contracts.

Today was an interesting day. Thanks Janet :) I closed my AUD position for about $184 profit. Still continuing to hold ED and TU. Account value: $19,801, down 2.3% from high water mark.

Yeah but the daily resets will make holding positions for the long term complex. As I understand it leveraged ETFs are good for day traders, but not so good for interday. I hold for weeks at a time, so I'm not sure they'll work for my case. On top of that there's the additional tax to deal with.

Yeah. The difficulty is that leverage with ETFs is much more limited and spread is higher. Most ETFs only have a volatility of around 10%, which means I'd have to leverage up at least 2x to hit my volatility target. That would make margin calls a real risk, plus you have to pay interest on the...

I've decided to diversify a little and add corn to the portfolio. Here's the new weighting: AUD 2015-12 25% EDOLLAR 2017-12 12.5% TU 2015-12 12.5% NK225M 2015-12 25% ZC 2015-12 25% First trade -1 ZC at 378 3/4.

No trades today. 2015-10-27 account value: 20275.00 GE (ED) contract: EDZ2017 settle: $98.6350 volatility: $124.42 target volatility: $53.86 previous position: 1 new position: 1 action: none ZT (TU)...

No. As I said I'd be happy to achieve a post-cost Sharpe of 0.5 and getting 0.6 would be fantastic. You're probably confusing the Sharpe ratio with the information ratio. Yes.

This is a small account so I don't have a significant amount of diversification. For this reason I don't think I'll get a post-cost Sharpe ratio much higher than 0.5. With a target volatility of 25% that will give a return of 12.5%. If this works well I'll scale the account up and trade a more...

No trades today. 2015-10-26 account value: 20117.00 GE (ED) contract: EDZ2017 settle: $98.59 volatility: $126.20 target volatility: $53.44 previous position: 1 new position: 1 action: none N225M (NK) contract...

A quick update: Account balance: $20,000.00 Target volatility: $5,000.00 Expected volatility: $5,062.88 Trades -1 AUD 0.72386 +1 EDOLLAR 98.590 +1 TU 109.555 0 NK225M Positions -1 AUD +1 EDOLLAR +1 TU 0 NK225M

So I've setup my portfolio which is weighted as follows: AUD 2015-12 33% EDOLLAR 2017-12 17% TU 2015-12 17% NK225M 2015-12 33% I'm limited here to the smaller contracts because I'm trading a small account initially and have a low target volatility. Today's trades are...

Any online learning system should be capable of doing this e.g. stochastic gradient descent. What you describe in terms of combining the predictions from the individual strategies is referred to as boosting in the machine learning field. You might find this interesting to read into. You could...

Its been almost a month since my last post. How time flies. In the mean time I've been busy coding up a systematic trading environment in Python with futures stitching, backtesting at the portfolio level and bootstrapping to measure statistical significance. I've been reading through Systematic...