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Fund ratios with lagged correlations

2 messages · Bengoechea Bartolomé Enrique (SIES 73), Dirk Eddelbuettel

Original
Bengoechea Bartolomé Enrique (SIES 73)
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Hi, I'm having a problem computing funds ratios such as alpha, beta, tracking error, etc, and maybe the list wisdom can be of help  :-)

I have daily NAVs and values of luxembourg funds and their benchmarks. Most funds investing in the US have a delay on its NAV of 1 day with respect to benchmarks such as S&P500. I find this easily using the ccf function, and then I just compute the ratios
of the delayed (returns of the) NAVs with respect to (returns of) the benchmark.

The problem is that with some markets (e.g. south american funds) the correlation between the fund and its benchmarks is splitted between the current day and the previous day. I find this by testing that none of the series exhibits significant serial
autocorrelation, but the cross-correlations are high for both the 0 and 1 lag (say 0.5 and 0.5, or 0.7 and 0.4). With products that trade continuously I can solve this problem by taking into account timezones and using prices at specific times of the day,
but with funds and many indexes only end-of-day values are available.

Has someone faced this problem? How do you adapt the beta/correlation/etc computations to handle this issue and come up with sensible estimates? Any paper dealing with this topic?

Thanks in advance!!!

Enrique
Dirk Eddelbuettel
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On 9 March 2006 at 15:43, Enrique Bengoechea wrote:
| Hi, I'm having a problem computing funds ratios such as alpha, beta, tracking error, etc, and maybe the list wisdom can be of help  :-)
| 
| I have daily NAVs and values of luxembourg funds and their benchmarks. Most funds investing in the US have a delay on its NAV of 1 day with respect to benchmarks such as S&P500. I find this easily using the ccf function, and then I just compute the ratios
| of the delayed (returns of the) NAVs with respect to (returns of) the benchmark.
| 
| The problem is that with some markets (e.g. south american funds) the correlation between the fund and its benchmarks is splitted between the current day and the previous day. I find this by testing that none of the series exhibits significant serial
| autocorrelation, but the cross-correlations are high for both the 0 and 1 lag (say 0.5 and 0.5, or 0.7 and 0.4). With products that trade continuously I can solve this problem by taking into account timezones and using prices at specific times of the day,
| but with funds and many indexes only end-of-day values are available.
| 
| Has someone faced this problem? How do you adapt the beta/correlation/etc computations to handle this issue and come up with sensible estimates? Any paper dealing with this topic?

I'd try the ccf() over longer return periods -- say two-day returns or
five-day returns.

Hope this helps,  Dirk