Posts Tagged ‘ Quant finance ’

A slice of S&P 500 kurtosis history

February 13, 2012
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A slice of S&P 500 kurtosis history

How fat tailed are returns, and how does it change over time? Previously The sister post of this one is “A slice of S&P 500 skewness history”. Orientation The word “kurtosis” is a bit weird.  The original idea was of peakedness — how peaked is the distribution at the center.  That’s what we can see, … Continue reading...

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The distribution of financial returns made simple

January 23, 2012
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The distribution of financial returns made simple

Why returns have a stable distribution As “A tale of two returns” points out, the log return of a long period of time is the sum of the log returns of the shorter periods within the long period. The log return over a year is the sum of the daily log returns in the year.  … Continue reading...

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How to search the R-sig-finance archives

January 19, 2012
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How to search the R-sig-finance archives

A not unusual part of a response on the R-sig-finance mailing list is: “Search the list archives.” In principle that makes sense.  In practice it might not be clear what to do.  Now it should be. The list The R-sig-finance mailing list deals with the intersection of questions about the R language and finance.  It … Continue reading...

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A slice of S&P 500 skewness history

January 16, 2012
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A slice of S&P 500 skewness history

How symmetric are the returns of the S&P 500? How does the skewness change over time? Previously We looked at the predictability of kurtosis and skewness in S&P constituents.  We didn’t see any predictability of skewness among the constituents.  Here we look at skewness from a different angle. The data Daily log returns of the … Continue reading...

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Sensitivity of risk parity to variance differences

January 9, 2012
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Sensitivity of risk parity to variance differences

Equal risk contribution of assets determines the asset weights given the variance matrix.  How sensitive are those weights to the variance estimate? Previously The post “Risk parity” gave an overview of the idea. In particular it distinguished the cases: the assets have equal risk contribution groups of assets have equal risk contribution A key difference … Continue reading...

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The top 7 portfolio optimization problems

January 5, 2012
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The top 7 portfolio optimization problems

Stumbling blocks on the trek from theory to practical optimization in fund management. Problem 1: portfolio optimization is too hard If you are using a spreadsheet, then this is indeed a problem. Spreadsheets are dangerous when given a complex task.  Portfolio optimization qualifies as complex in this context (complex in data requirements). If you are … Continue reading...

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Market predictions for years 2011 and 2012

January 2, 2012
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Market predictions for years 2011 and 2012

A review of market predictions and results for 2011, and a calibration for 2012 predictions (of 19 equity indices plus oil). Previously One year ago the post “Revised market prediction distributions” presented plots showing the variability of various markets assuming no market-moving forces. The follow-up post “Some market predictions enhanced some of those plots with … Continue reading...

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Volatility estimation and time-adjusted returns

December 15, 2011
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Volatility estimation and time-adjusted returns

Do non-trading days explain the mystery of volatility estimation? Previously The post “The volatility mystery continues” showed that volatility estimated with daily data tends to be larger (in recent years) than when estimated with lower frequency returns. Time adjusting One of the comments — from Joseph Wilson — was that there is a problem with … Continue reading...

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The volatility mystery continues

December 5, 2011
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The volatility mystery continues

How do volatility estimates based on monthly versus daily returns differ? Previously The post “The mystery of volatility estimates from daily versus monthly returns” and its offspring “Another look at autocorrelation in the S&P 500″ discussed what appears to be an anomaly in the estimation of volatility from daily versus monthly data. In recent times … Continue reading...

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Alpha decay in portfolios

November 30, 2011
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Alpha decay in portfolios

How does the effect of our expected returns change over time?  This is not academic  curiosity, we want to know in the context of our portfolio if we can.  And we can — we visualize the effect of expected returns in situ. First step The idea is to look at the returns of portfolios that … Continue reading...

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