Tag Archives: variance compression
Volatility from daily or monthly: garch evidence
Should you use daily or monthly returns to estimate volatility? Does garch explain why volatility estimated with daily data tends to be bigger than if it is estimated with monthly data? Previously There are a number of previous posts — with the variance compression tag — that discuss the phenomenon of volatility estimated with daily … Continue reading
Posted in Quant finance, R language
Tagged garch simulation, variance compression, volatility
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Three talks from CFE
The Computational and Financial Econometrics conference was just held in London. Here are three talks from the large menu. Lars Helge Hass The objective is to find a way to do an asset allocation optimization that includes private equity. A problem of course is that private equity is seriously opaque. To highlight that, using one … Continue reading
Posted in Quant finance
Tagged portfolio optimization, regime switching model, variance compression
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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
Posted in Quant finance, R language
Tagged S&P 500, time-adjusted returns, variance compression, volatility
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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
Posted in Quant finance, R language
Tagged autocorrelation, S&P 500, variance compression, volatility
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Another look at autocorrelation in the S&P 500
Casting doubt on the possibility of mean reversion in the S&P 500 lately. Previously A look at volatility estimates in “The mystery of volatility estimates from daily versus monthly returns” led to considering the possibility of autocorrelation in the returns. I estimated an AR(1) model through time and added a naive confidence interval to the … Continue reading
Posted in Quant finance, R language
Tagged autocorrelation, mean reversion, S&P 500, variance compression
5 Comments
The mystery of volatility estimates from daily versus monthly returns
What drives the estimates apart? Previously A post by Investment Performance Guy prompted “Variability of volatility estimates from daily data”. In my comments to the original post I suggested that using daily data to estimate volatility would be equivalent to using monthly data except with less variability. Dave, the Investment Performance Guy, proposed the exquisitely … Continue reading
Posted in Quant finance, R language
Tagged annualize, autocorrelation, S&P 500, variance compression, volatility
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