Quantitative Ramblings

This post is an opportunity to play with a few ideas buzzing in my head this afternoon.

Here is some data on the hedge fund industry taking from the EDHEC dataset. See website for more details: http://www.edhec-risk.com/

Here is an overview of monthly performance from 1 Jan 1997 – 31 Dec 2014.



On a risk adjusted basis the Equity Market Neutral returns are the clear star performer.






Now let us have a look at how some of these returns look from the lens of a normal distribution.

Rplot16 Rplot15 Rplot14 Rplot13





There is a very strong argument that the markets are random. If this is the case then fund managers should not be able to demonstrate any consistent pattern of returns. One of the ways to determine if there is a persistence of performance is to test for auto-correlation. In essence auto-correlation is a process whereby you test the correlation of a time series by itself but create a series of lags. Naturally the 0 lag will have a perfect correlation of 1 (100%) what you are looking to see is if the lags produce a statistically significant correlation by piercing the horizontal dashed lines. If there is a  statistically significant auto-correlation after many lags, I think we can dismiss this as spurious we are looking for significance after few lags.

I wasn’t surprised to find that the only strategy to produce auto-correlation was the Equity Market Neutral strategy.  L/S Equity was also able to produce auto-correlation.


Rplot18 Rplot19 Rplot20


To conclude this post is just me rambling along while watching some news. I will do more in depth analysis some time in the future but I think from the data presented there is certainly a strong argument to be made for managers that try and take out market direction in their trading behaviour. I think this makes a lot of sense, if forecasting the markets is random as many suggest, then the best chance of producing alpha as a manager is if you see the investing world within the relative scope of a market neutral environment.


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