Tag Archives: drawdown

Monday was a massive #drawdown for #hedgefund

Monday was a massive for

[igp-video src=”” poster=”https://quantlabs.net/blog/wp-content/uploads/2015/07/Monday-was-a-massive-drawdown-for-hedgefund.jpg” size=”large”]
Monday was a massive #drawdown for #hedgefund

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24% return with SU.TO CP IBB low drawdown

24% return with SU.TO CP IBB low drawdown

24 pc expected return with SU.TO CP IBB low drawdown

20 return

This is decent little portfolio to start with as described in this short video.

I also got a 20 minute tutorial how to set this up. This Matlab project should be part of your arsenal

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How to use performance metric like Sharpe Ratio to reduce your drawdown in your trading?

How to use performance metric like Sharpe Ratio to reduce your drawdown in your trading?

Again, thank to my NYC source for providing this

http://www.stat.cmu.edu/~abrock/algotrading/page9.html

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Webinar coming on charting, max drawdown, Beta estimating with CAPM, and Sharpe Radtio

HI there
I have now completed the analysis with Matlab’s Financial Toolbox. I am even doing an EXCLUSIVE online event for taking questions from my  QuantLabs.net Premium members on this and the Econometrics toolbox.


–> JOIN NOW TO GET ACCESS <–

Get in on this event which happen this Monday Mar 18 at 7PM EST!
I have posted a video on all this and the direction the Membership is going|:
Youtube video on Analyzed Matlab Finance toolbox but now analyzing Stats PDE and Math
https://quantlabs.net/blog/2013/03/youtube-video-on-analyzed-matlab-finance-toolbox-but-now-analyzing-stats-pde-and-math/
The other recent Financial Toolbox topics for my Members include:
High Low Close and Bollinger Chart Demo
Performance metrics with Sharpe Ratio, risk adjusted return, Lower Partial Moments
Calculate max drawdown and expected max drawdown
Using CAPM to estimate Beta in portfolio
So if you want to start learning some of these topics listed above, get in on the party action now? Also, jump on the opportunity now for this Monday’s EXCLUSIVE LIVE online event? for QuantLabs.net Premium Members.
–> JOIN NOW TO GET ACCESS <–
Several other membership benefits listed here
Thanks Bryan

HOW DO YOU START A PROFITABLE TRADING BUSINESS? Read more NOW >>>

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Strategy out of an academic paper. 16.5 % return at 2.36 sharpe, max drawdown 6.9% through 1999-2010. Is this good, medium or bad?

Strategy out of an academic paper. 16.5 % return at 2.36 sharpe, max drawdown 6.9% through 1999-2010. Is this good, medium or bad? Equity curve, year by year statistics and relative performance here

Powered by Google Docs docs.google.com

 

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Looks ok, but really these 2 pages does not give much information.

Hss this been verified by independent auditors, or is this backtest results? if this is backtest results, then I have seen a lot like it.
You say this is an academic paper. Is this present and open source?

Nice graph though 🙂

 

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The strategy (implemented out of sample) above is based on the two papers below

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1340879http://www.futuresmag.com/Issues/2011/May-2011/Pages/Capturing-backwardation.aspx?page=1

Adding the dynamic S&P strategy to the dynamic commodity strategies results in a significant reduction in volatility.

 

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You are right the 2 pages give much information. What else would you like to know?

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I skimmed through the above article and would say that your results seem pretty realistic. I missed the part in the paper where you have a sharpe of 2.36 not sure if that was for all ten years or your best year. Looks to me like for an active strategy applied to a particular commodity the sharpes are between 1 an 1.5. Incidentally I have an intermediate strategy for ETFs that produces somewhat similar results ie active management does better than long only posns and sharpes in the same range as you. What happens if you toss out your most volatile commodities from the mix and instead of having ten use say the least volatile 5-7. Just curious I am going to review your paper more closer it looks pretty good.

 

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sorry i did not read the google docs paper first so now i see where the 2.36 comes from
(a) how were the weights chosen
(b) if you are shorting assets do you adjust the sharpes in any way to account for the short position ie is sharpe still appropriate measure for a long/short basket as opposed to long only or would you use an adjusted sharpe.

Initially I skimmmed your other papers

 

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Thanks for your interest

(a). The strategy is a combination of 3 equally weighted strategies (2 for commodities, 1 – S&P 500). Weights are chosen on equal weighting principles rather using mean-variance optimization on historical data.

(b). Our sharpes are simply calculated as the ratio of (Mean return – risk free) and (sigma of return). I see your point about sharpe for shorts, because return (or more specifically ROI in this case) would change for a short position.

Other statistics of our strategy is that for the 11 year period, it the maximum weekly loss was -2.39 percent and there were only 4 occasions when return was less than -2%. And also only 25 weeks when return was greater than 2%.

the papers you posted were very interesting. Thank you for posting them.

 

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For some reason I can’t view\download the pdf from Google Docs. Any way, to be concrete, On a simple scale of bad, fair, good then 6.9% is good, 16.5% is fair and 2.36 sharpe is also fair (that is, if you’re after setting up your own hedge fund).

 

Thanks for the reply.Wonder why arent you able to access the google docs document. I can email it you if you like?

 

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The results are too good to be true. The Devraj Basu and Alexander Stremme paper uses data from 1993-2007 to find a suitable model and the uses 1993-1998 to estimate the predictive model and then used the 1999-2007 as out of sample data. It is like not having any out of sample data at all. I wonder what was the performance during 2008-2011.
From my experience strategies that uses linear regressions would show performance with long periods of really good and really bad performances.

 

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The performance of the backtest over 2008-2010 is given in the document attached to the comment. The Sharpe ratios were 2008: 1.80, 2009:4.71 2010:2.02. For 2011 the strategy was up around 5% until the end of June. THe statement that the Basu and Stremme paper used data from 1993-2007 to find an appropriate model is not entirely accurate. An unconditionally efficient portfolio strategy was chosen ahead of time and the in-sample period was used for parameter estimation via the predictive regression and the fitted model was then evaluated out of sample.In

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Sorry I wasn’t clear enough. I would like to see the performance of the strategy only for SP500 during 2008-2011. You are right my statement is not entirely accurate but I see an issue related to variable selection (Why COT+VIX ?) using the entire sample.

 

HOW DO YOU START A PROFITABLE TRADING BUSINESS? Read more NOW >>>

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!