Tag Archives: S&P 500
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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Does the S&P 500 exhibit seasonality through the year?
Are there times of the year when returns are better or worse? Abnormal Returns prompted this question with “SAD and the Halloween indicator” in which it is claimed that the US market tends to outperform from about Halloween until April. Data The data consisted of 15,548 daily returns of the S&P 500 starting in 1950. … Continue reading
Predictability of kurtosis and skewness in S&P constituents
How much predictability is there for these higher moments? Data The data consist of daily returns from the start of 2007 through mid 2011 for almost all of the S&P 500 constituents. Estimates were made over each half year of data. Hence there are 8 pairs of estimates where one estimate immediately follows the other. … Continue reading
Beta and expected returns
Some pictures to explore the reality of the theory that stocks with higher beta should have higher expected returns. Figure 2 of “The effect of beta equal 1” shows the return-beta relationship as downward sloping. That’s a sample of size 1. In this post we add six more datapoints. Data The exact same betas of … Continue reading
Posted in Quant finance, R language
Tagged beta in finance, Capital Asset Pricing Model, CAPM, low volatility investing, S&P 500
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The indices understate the carnage
The first 6 trading days of August have been bad for the major indices, but how variable is that across portfolios? To answer that, two sets of random portfolios were generated from the constituents of the S&P 500. The trading days are 2011 August 1 — 5 and 8. The returns of the indices for … Continue reading
More S&P 500 correlation
Here are some additions to the previous post on S&P 500 correlation. Correlation distribution Before we only looked at mean correlations. However, it is possible to see more of the distribution than just the mean. Figures 1 and 2 show several quantiles: 10%, 25%, 50%, 75%, 90%. Figure 1: Quantiles of 50-day rolling correlation of … Continue reading
Posted in Quant finance, R language
Tagged correlations, equity correlations, jackknife, S&P 500, stock correlations
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On “Stock correlation has been rising”
Ticker Sense posted about the mean correlation of the S&P 500. The plot there — similar to Figure 1 — shows that correlation has been on the rise after a low in February. Figure 1: Mean 50-day rolling correlation of S&P 500 constituents to the index. For me, this post raised a whole lot more … Continue reading
Posted in Quant finance, R language
Tagged correlations, equity correlations, S&P 500, stock correlations
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Testing an S&P 500 prediction
If a particular prediction comes true, how surprised should we be? The prediction The page that sparked my curiosity tells of a prediction made a year ago that the S&P 500 would beat its historic high by the end of 2011. It says that at the point the prediction was made, the level of the … Continue reading
Again with Ledoit-Wolf and factor models
We come closer to a definitive answer on the relative merit of Ledoit-Wolf shrinkage versus a statistical factor model for variance matrices. Previously This post builds on the post entitled: A test of Ledoit-Wolf versus a factor model That post depended on some posts previous to it. New information Previously we generated random portfolios with … Continue reading
Posted in Quant finance, R language
Tagged covariance matrix, factor model, Ledoit-Wolf shrinkage, risk fraction, S&P 500, variance matrix
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A test of Ledoit-Wolf versus a factor model
Statistical factor models and Ledoit-Wolf shrinkage are competing methods for estimating variance matrices of returns. So which is better? This adds a data point for answering that question. Previously There are past blog posts on: the idea of variance matrices factor models of variance The data in this post are from the blog posts: “Weight … Continue reading
Posted in Quant finance, R language
Tagged covariance matrix, factor model, Ledoit-Wolf shrinkage, risk fraction, S&P 500, variance matrix
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