Publications by Pat
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 appear to be too small. The re...
3777 sym 8 img
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 have the constraints we want and also have a high expect...
7979 sym 16 img
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 ...
8132 sym 34 img 2 tbl
LondonR recap
The biggest and perhaps best meeting yet. The talks James Long: “Easy Parallel Stochastic Simulations using Amazon’s EC2 & Segue”. This was a lively talk about James’ package to use Amazon’s cloud to speed up a (huge) call to lapply. The good part is that if you want to use Amazon as your cloud provider, it is very easy. The downs...
3023 sym 2 img
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 probl...
5215 sym 20 img
R-specific review of blog year 2011
Most popular posts Two of the ten most popular posts during the year were completely about R: The R Inferno revised (number 6) Solve your R problems (number 9) R played a role in the other eight top ten, and many of the rest of the posts as well. R The R Inferno was revised in the spring. Amazingly, this blog got the world-wide scoop. Here is t...
1113 sym 2 img
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 enhan...
5353 sym 82 img
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 y...
10672 sym 2 img
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 ...
4534 sym 8 img
Physical books of “The R Inferno” and “S Poetry”
Hardcopy versions of both The R Inferno and S Poetry are now available for sale. Physical economy Buy The R Inferno (the version dated 2011 April 30) Buy S Poetry Discount The publisher, Lulu, has a coupon for a 25% discount off purchases (up to a maximum of $50) that is good until the end of January (US west coast time). The code is: LULUBOO...
2018 sym 6 img