Author Archives: Pat
Variability of garch estimates
Not exactly pin-point accuracy. Previously Two related posts are: A practical introduction to garch modeling garch and long tails Experiment 1000 simulated return series were generated. The garch(1,1) parameters were alpha=.07, beta=.925, omega=.01. The asymptotic variance for this model is 2. The half-life is about 138 days. The simulated series used a Student’s t distribution … Continue reading
Horses and volatility
Two items struck me as being connected. Maybe they are. The items: Payoff of betting on horses versus the odds The Missing Risk Premium by Eric Falkenstein As you can see there is a unicorn on the cover, but that is not the horse connection I had in mind. Horses The post at Thinking in … Continue reading
Review of “Numerical Methods and Optimization in Finance” by Gilli, Maringer and Schumann
Previously This book and the associated R package were introduced before. Executive Summary A very nice — and enlightening — discussion of a wide range of topics. Principles The Introduction to the book sets out 5 principles. This is probably the most important part of the book. The principles are: We don’t know much in … Continue reading
Posted in Book review, Quant finance, R language
Tagged heuristic optimization, simulation
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Not fooled by randomness
The paper is “Not Fooled by Randomness: Using Random Portfolios to Analyze Investment Funds” by Roberto Stein. Here is an explanation of the idea of random portfolios. Favorite sentence The real question here is whether we’re actually measuring skill, or these are still measures of performance, so influenced by extraneous factors that the existence of … Continue reading
US market portrait 2012 week 37
US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used The initial post was “Replacing market indices” The R code is in marketportrait_funs.R
Sharpe ratios, replacing managers and random portfolios
Two articles in the August issue of Journal of Asset Management discuss topics that relate to random portfolios. Sharpe ratios The first article is “The Sharpe ratio’s market climate bias: Theoretical and empirical evidence from US equity mutual funds” by Sebastian Krimm, Hendrik Scholz and Marco Wilkens (abstract). SSRN claims a version of the paper is downloadable, but … Continue reading
Posted in Performance, Random portfolios
Tagged Monte Carlo in finance, Sharpe ratio
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Thalesians, and other events
Featured Thalesians, London 2012 September 12. Chia Tan on “Practical Financial Modeling”. Abstract: Financial modelling is not a competition in the mastery of complexity. Rather, the aim is to come up with the simplest models adequate to capture salient market features of traded products. There exists a wide gulf between material covered by traditional books … Continue reading
Posted in Events, R language
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A look at Bayesian statistics
An introduction to Bayesian analysis and why you might care. Fight club The subject of statistics is about how to learn. Given that it is about the unknown, it shouldn’t be surprising that there are deep differences of opinion on how to go about doing it (in spite of the stereotype that statisticians are accountants … Continue reading
US market portrait 2012 week 36
US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used The initial post was “Replacing market indices” The R code is in marketportrait_funs.R
