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A simple portfolio optimization problem is used to look at several R functions that use randomness in various ways to do optimization. Orientation Some optimization problems are really hard. In these cases sometimes the best approach is to use randomness to get an approximate answer. Once you decide to go ... [Read more...]

Portfolio diversity is a balancing act. Previously The post “Portfolio diversity” talked about the role of the correlation between assets and the portfolio.  The current post fills a hole in that post. The 2 dimensions asset-portfolio correlation Each asset in the universe has a correlation with the portfolio.  If there are ... [Read more...]

We look at volatility clustering, and some aspects of modeling it with a univariate GARCH(1,1) model. Volatility clustering Volatility clustering — the phenomenon of there being periods of relative calm and periods of high volatility — is a seemingly universal attribute of market data.  There is no universally accepted explanation of it. ... [Read more...]

What is the difference between Monte Carlo — as it is usually defined in finance — and random portfolios? The meaning of “Monte Carlo” The idea of “Monte Carlo” is very simple.  It is a fancy word for “simulation”. As usual, it is all too possible to find incredibly muddied explanations of ... [Read more...]

Two books were recently published that are sure to help R grow even faster. R has a reputation, partially deserved, for being hard to learn.  These books will help.  The first makes learning easier, the second can make learning less necessary for initiates. I have not yet touched either book. ... [Read more...]

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A look at a simplistic measure of stock-picking opportunity. Motivation The interquartile range (the spread of the middle half of the data) has recently been added to the market portrait plots.  Putting those numbers into historical context was the original impulse. However, this led to thinking about change in stock-picking ... [Read more...]

Maximum drawdown is blazingly variable. Psychology Probably the most salient feature that an investor notices is the amount lost since the peak: that is, the maximum drawdown. Just because drawdown is noticeable doesn’t mean it is best to notice. Statistics The paper “About the statistics of the maximum drawdown ... [Read more...]

In this video tutorial, it will show you how to make R analysis Modules just like MS Excel Templates using the Building Derivative Calculator app as study case. Let’s say we wanted to know the derivative of tan(x^2 + 3), commonly, we will use th... [Read more...]

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A look at return variability for portfolio changes. The problem Suppose we make some change to our portfolio.  At a later date we can see if that change was good or bad for the portfolio return.  Say, for instance, that it helped by 16 basis points.  How do we properly account ... [Read more...]

I’m using the Twitter Listening Robot to know what people is talking Najib Razak, Malaysia Prime Minister. Apparently,  23-27 are the Malaysia Youth Day 2012.  There were many funny retweets (more than 50 times) by the public: RT @Faizrawrr: Be... [Read more...]

On the way to another destination, I found some curious behavior with average correlations. The data Daily log returns from almost all of the constituents of the S&P 500 for years 2006 through 2011. The behavior Figure 1 shows the actual mean correlation among stocks for the set of years and the mean ... [Read more...]

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All models are wrong, some models are more wrong than others. The streetlight model Exponential decay models are quite common.  But why? One reason a model might be popular is that it contains a reasonable approximation to the mechanism that generates the data.  That is seriously unlikely in this case. ... [Read more...]

Here is a simple application to transform text into a beautiful word cloud, Text Mining to WordCloud. The purpose is to find out the highest frequency word in a certain text. It is an app built with R language, the source code is attached at the end of... [Read more...]

How many baskets are your eggs in? Meucci diversity Attilio Meucci directly addresses the adage: Don’t put all your eggs in one basket. His idea is to think of your portfolio as a set of  subportfolios that are each uncorrelated with the rest.  If your portfolio can be configured ... [Read more...]

Not quite expected behavior of skewness and kurtosis. The question In each time period the returns of a universe of stocks will have some distribution — distributions as displayed in “Replacing market indices” and Figure 1. Figure 1: A cross-sectional distribution of simple returns of stocks. In particular they will have values for ... [Read more...]