Category Archives: Blog

The ultimate aim of the Portfolio Probing blog is to help make fund management more effective, to make savings safer through better tools and better methods. Patrick Burns, the founder of Burns Statistics, offers a unique mix of experience in quantitative finance, statistics, computing and writing.

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

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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

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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

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Popular posts 2012 August

Most popular posts in 2012 August Highlights of R in Finance 2012 A comparison of some heuristic optimization methods A practical introduction to garch modeling Another comparison of heuristic optimizers A tale of two returns (posted in 2010) A bug at Knight The top 7 portfolio optimization problems garch and long tails R Inferno-ism: order … Continue reading

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garch and long tails

How much does garch shorten long tails? Previously Pertinent blog posts include: “A practical introduction to garch modeling” “The distribution of financial returns made simple” “Predictability of kurtosis and skewness in S&P constituents” Induced tails Part of the reason that the distributions of returns have long tails is because of volatility clustering.  It’s not really … Continue reading

Posted in Quant finance, R language | Tagged , , | 3 Comments

Another comparison of heuristic optimizers

A herd of heuristic algorithms is compared using a portfolio optimization. Previously “A comparison of some heuristic optimization methods” used two simple and tiny portfolio optimization problems to compare a number of optimization functions in the R language. This post expands upon that by using a portfolio optimization problem that is of a realistic size … Continue reading

Posted in optimization, R language | Tagged , , , | 3 Comments

Highlights of R in Finance 2012

I unfortunately was not there, but we can vicariously enjoy it via the presentations that are posted on the conference website. Below is my take on the highlights (in chronological order). Peter Carl and Brian Peterson “Constructing Strategic Hedge Fund Portfolios” is wonderful from my perspective.  Promoting random portfolios is sure to win my heart.  … Continue reading

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A bug at Knight

Some speculation and a vision of how to make finance safer. What I know Something horrible happened Adequate testing did not occur Either there was no fire alarm for the event “hemorrhaging money” or the fire brigade was asleep Regarding the last point, the New York Times reports — essentially — that there was no … Continue reading

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Popular posts 2012 July

Most popular posts in 2012 July A practical introduction to garch modeling A comparison of some heuristic optimization methods Random portfolios versus Monte Carlo The top 7 portfolio optimization problems A tale of two returns (posted in 2010) 2 dimensions of portfolio diversity Alpha alignment R Inferno-ism: order is not rank Market predictions for years … Continue reading

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Returns with negative net asset values

How are returns calculated when net asset value goes negative? Previously In “A tale of two returns” we highlighted the similarities and differences of log returns versus simple returns. Positive valuation We create — in R — an example of net asset value at four times: > nav1 <- c(1000, 900, 950, 1010) > nav1 … Continue reading

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