Category Archives: Quant finance
Jackknifing portfolio decision returns
A look at return variability for portfolio changes. The problem Suppose we make some change to our portfolio. At a later date we can see if that change was good or bad for the portfolio return. Say, for instance, that it helped by 16 basis points. How do we properly account for variability in that … Continue reading
Posted in Performance, Quant finance, R language
Tagged jackknife, statistical bootstrap
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Correlations and postive-definiteness
On the way to another destination, I found some curious behavior with average correlations. The data Daily log returns from almost all of the constituents of the S&P 500 for years 2006 through 2011. The behavior Figure 1 shows the actual mean correlation among stocks for the set of years and the mean correlation with … Continue reading
Posted in Quant finance, R language
Tagged BurStFin, Ledoit-Wolf shrinkage, positive definite, variance estimation
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Random portfolios: 6 steps to a better fund management industry
Only puny secrets need protection. Big discoveries are protected by public incredulity. — Marshall McLuhan Random portfolios have the power to improve the practice of asset management in several ways. Here are six. 1) Measure active managers There is no convincing evidence that more than a handful of funds have consistently outperformed. This should tell … Continue reading
Posted in Performance, Quant finance, Random portfolios, Risk
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Asset correlations with minimum variance portfolios
The minimum variance portfolios have slightly reduced correlations to assets in weight-constrained portfolios. Previously “Portfolio diversity” introduced the topic of asset-portfolio correlations. It also generated four sets of long-only random portfolios as of the start of 2011 using constituents of the S&P 500: exactly 20 names, weights between 1% and 10% exactly 200 names, weights … Continue reading
Posted in Quant finance
Tagged asset-portfolio correlation, minimum variance portfolio, S&P 500
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Diverse US portfolios did well in 2011
Constraining the maximum asset-portfolio correlation gave bigger returns and smaller volatility. Previously “Portfolio diversity” introduced the topic of asset-portfolio correlations. It also generated four sets of long-only random portfolios as of the start of 2011 using constituents of the S&P 500: exactly 20 names, weights between 1% and 10% exactly 20 names, maximum asset-portfolio correlation … Continue reading
Posted in Quant finance
Tagged asset-portfolio correlation, diversification, portfolio diversity, S&P 500
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Portfolio diversity
How many baskets are your eggs in? Meucci diversity Attilio Meucci directly addresses the adage: Don’t put all your eggs in one basket. His idea is to think of your portfolio as a set of subportfolios that are each uncorrelated with the rest. If your portfolio can be configured to have a lot of roughly … Continue reading
Posted in Quant finance, R language
Tagged asset-portfolio correlation, diversification, portfolio diversity, S&P 500
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Cross-sectional skewness and kurtosis: stocks and portfolios
Not quite expected behavior of skewness and kurtosis. The question In each time period the returns of a universe of stocks will have some distribution — distributions as displayed in “Replacing market indices” and Figure 1. Figure 1: A cross-sectional distribution of simple returns of stocks. In particular they will have values for skewness and … Continue reading
A variance campaign that failed
they ought at least be allowed to state why they didn’t do anything and also to explain the process by which they didn’t do anything. First blush One of the nice things about R is that new statistical techniques fall into it. One such is the glasso (related to the statistical lasso) which converts degenerate … Continue reading
Three things factor models do
Factor models are heavily used in finance to create variance matrices. Here’s why. Factor models: Provide non-degenerate estimates Save space Quantify sources of risk Non-degenerate estimates First off, what does this mean? The technical term is that you want your estimate of the variance matrix to be positive definite. In practical terms what that means … Continue reading
Posted in Quant finance
Tagged factor model, Ledoit-Wolf shrinkage, statistical factor model
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Betas of the low vol cohorts
How did the constraints affect portfolio betas, and how did the betas change over time? Previously “Low (and high) volatility strategy effects” created 6 sets of random portfolios — the so-called low vol cohorts — as of 2007 and showed their performance up to about a month ago. “Rebalancing the low vol cohorts” looked at … Continue reading
Posted in Quant finance, R language, Random portfolios
Tagged beta in finance, low volatility investing
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