Category Archives: R language
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
Posted in Quant finance, R language, Random portfolios
Tagged alpha decay, expected returns, MACD, realized alpha
5 Comments
Asynchrony in market data
Be careful if you have global daily data. The issue Markets around the world are open at different times. November 21 for the Tokyo stock market is different from November 21 for the London stock market. The New York stock market has yet a different November 21. The effect The major effect is that correlations … Continue reading
Posted in Quant finance, R language
Tagged asynchronous data, asynchrony, multivariate moving average
3 Comments
Performance measurement is about decisions
The return of a hypothetical fund was 17.9% in 2010. We want to know if that is good or bad. The benchmark method The assets in the portfolio are constituents of the S&P 500, so we can compare our fund return to the return of the index. Figure 1: 2010 returns of: the fund and … Continue reading
Posted in Performance, R language, Random portfolios
Tagged investment performance measurement, luck versus skill
4 Comments
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
18 Comments
Variability of volatility estimates from daily returns
Investment Performance Guy has a post “Periodicity of risk statistcs (and other measures)” in which it is wondered how valid volatility estimates are from a month of daily returns. Here is a quick look. Figure 1 shows the variability (and a 95% confidence interval (gold lines) from a bootstrap) of the volatility estimate (black line) … Continue reading
Risk parity
Some thoughts and resources regarding a popular fund management buzzword. The idea Given asset categories (like stocks, bonds and commodities) create a portfolio where each category contributes equally to the portfolio variance. Two operations There are two cases in creating a risk parity portfolio: the universe is the asset categories the universe is the assets … Continue reading
Posted in Fund management in general, Quant finance, R language
Tagged equal risk contribution, risk parity
7 Comments
Introduction to “Numerical Methods and Optimization in Finance”
The book is by Manfred Gilli, Dietmar Maringer and Enrico Schumann. I haven’t actually seen the book, so my judgement of it is mainly by the cover (and knowing the first two authors). The parts of the book closest to my heart are optimization, particularly portfolio optimization, and particularly particularly portfolio optimization via heuristic algorithms. … Continue reading
How to compute portfolio returns badly
For those who naturally compute portfolio returns correctly here are some lessons in how to do it wrong. The data Random portfolios were generated from constituents of the S&P 500 with constraints: long-only exactly 20 assets in the portfolio no more than 10% weight for any asset (just for fun) the sum of the 5 … Continue reading
Posted in Quant finance, R language
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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
