Category Archives: Quant finance
Review of “Models. Behaving. Badly.” by Emanuel Derman
Why confusing illusion with reality can lead to disaster, on Wall Street and in life. Note that the cover is more clever than you might at first notice. Ceci n’est pas une pipe. You might also have a guess at the reason for the punctuation in the title. Executive summary Non-quants should embrace models more, … Continue reading
Posted in Book review, Quant finance
Tagged efficient market hypothesis, efficient market model
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The distribution of financial returns made simple
Why returns have a stable distribution As “A tale of two returns” points out, the log return of a long period of time is the sum of the log returns of the shorter periods within the long period. The log return over a year is the sum of the daily log returns in the year. … Continue reading
How to search the R-sig-finance archives
A not unusual part of a response on the R-sig-finance mailing list is: “Search the list archives.” In principle that makes sense. In practice it might not be clear what to do. Now it should be. The list The R-sig-finance mailing list deals with the intersection of questions about the R language and finance. It … Continue reading
A slice of S&P 500 skewness history
How symmetric are the returns of the S&P 500? How does the skewness change over time? Previously We looked at the predictability of kurtosis and skewness in S&P constituents. We didn’t see any predictability of skewness among the constituents. Here we look at skewness from a different angle. The data Daily log returns of the … Continue reading
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 A key difference … Continue reading
Posted in Quant finance, R language
Tagged equal risk contribution, factor model, Ledoit-Wolf shrinkage, risk parity
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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 you are … Continue reading
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 enhanced some of those plots with … Continue reading
Posted in Quant finance, R language
Tagged 2011 market prediction, 2012 market prediction, market prediction
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Three talks from CFE
The Computational and Financial Econometrics conference was just held in London. Here are three talks from the large menu. Lars Helge Hass The objective is to find a way to do an asset allocation optimization that includes private equity. A problem of course is that private equity is seriously opaque. To highlight that, using one … Continue reading
Posted in Quant finance
Tagged portfolio optimization, regime switching model, variance compression
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Portfolio optimization inside out
A possible way to search for constraints that improve optimization. The perspective The usual way of thinking about portfolio optimization is to first consider the utility and then restrict to where the constraints are satisfied. A perfectly reasonable view. We use random portfolios to get a different point of view: first ensure that the constraints … Continue reading
There’s news and there’s news
Two recent posts included the word “news”, but in different senses. Events “News” in the sense of reports on events was discussed in “News analytics”. We can think of this as an approximation to objective reality. Market moves The post “Volatility estimation and time-adjusted returns” used “news” in the sense of “that which moves market … Continue reading
