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.

Paying interest and the number e

Suppose I borrow a dollar from you and I’ll pay you 100% interest at the end of the year.  How much money will you have then? $1 * (1 + 1) = $2 What happens if instead the interest is calculated as  50% twice in the year? $1 * (1.5 * 1.5) = $2.25 After … Continue reading

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In the blogosphere this week: sunshine and Vegas

Gambling Falkenblog has a post called: Why Do People Gamble? This includes the often-stated “problem” that the same people both: pay for insurance pay to gamble Maybe I’m being thick, but I don’t see any problem.  I see both these activities as buying positive skewness: paying a little now for an uncertain but big positive … Continue reading

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Normal market accidents

We think of accidents as abnormal events, but there is “normal accident” theory.  We don’t think of accidents happening in markets, but they do.  That’s why it’s called a market crash. For normal accidents to come into play, two conditions need to hold: the system is complex the system is tightly coupled Certainly the financial … Continue reading

Posted in R language, Risk | Tagged , , , | 1 Comment

Elsewhere in the blogosphere this week

Markets Sex and statistics Marginal Revolution had the post Sex and Statistics or Heteroscedasticity is Hot which reports on the OkTrends post The Mathematics of Beauty. The summary is that conditional on their average beauty rating, the women with more variable ratings get more interest.  The post proposes a theory that there is less competition … Continue reading

Posted in Economics, Fund management in general | Tagged , , | 1 Comment

The number 1 novice quant mistake

It is ever so easy to make blunders when doing quantitative finance.  Very popular with novices is to analyze prices rather than returns. Regression on the prices When you want returns, you should understand log returns versus simple returns. Here we will be randomly generating our “returns” (with R) and we will act as if … Continue reading

Posted in Quant finance, R language | Tagged , | 26 Comments

Boris The Banker explains efficient markets

Amy Anyone: What is EMH? Boris The Banker: That’s the Efficient Market Hypothesis, or sometimes the Efficient Markets Hypothesis. Amy: What’s that? Boris: It says that all available and relevant information has been taken into account in the price of items in the market — a stock market for example. Amy: Does it have any … Continue reading

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Some market predictions

We look at a few forecasts for the year 2011 that we’ve run across, and compare them with the prediction distributions presented in Revised market prediction distributions. FTSE 100 There is a “range forecast” on an Interactive Investor page of 5350 to 6565.  It isn’t clear (to me at least) what this means, but I … Continue reading

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Revised market prediction distributions

This provides revised plots of the prediction distributions published yesterday.  The previous plots of prediction distributions should be ignored — they are not doing as advertised. We show the prediction distribution of levels of several equity indices (plus oil price) at the end of 2011 assuming nothing happens.  That is, we’ve taken out market trends … Continue reading

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Creating prediction distributions

Here we give details and code for the prediction distributions exhibited in yesterday’s blog post “Tis the season to predict”. [Revision: There was a problem with the plots published in that post.  For corrected plots and an explanation of the error, see Revised market prediction distributions.] Eight years of returns The equity indices use daily … Continue reading

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Tis the season to predict

I predict there will be a lot of predictions of markets for the coming year.  Here is a calibration of such predictions. We show the prediction distribution of levels of several equity indices (plus oil price) at the end of 2011 assuming nothing happens.  That is, we’ve taken out market trends and just left drift … Continue reading

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