How to know in advance when stock market analysts are wrong?


In one of my previous posts I show how simple averaging of opinions of analysts about future stock returns could significantly improve their predictions of market behavior. Still, much space for errors left, and almost all of it concentrated around market crashes. The latter is hard to predict, although there are some interesting approaches. Today I’ll use The CBOE Volatility Index (VIX®) to predict analyst error itself.
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Who was the best in 2014 Winter Olympics: benchmarking in ‘The Economist’ and Tolstoy style

As a late followup to all the press, summarizing results of 2014 Winter Olympics, I decided to apply data envelopment analysis to find most efficient teams on 2014 Winter Olympics. I’ll use Benchmarking package to estimate efficiencies and ggplot2 + ggthemes to visualize it.Rplot07

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When do financial analysts make mistakes?

While helping one of my students, Oleg Karapaev, in his struggle with a paper on determinants of divergence between “fair” and observed prices in stocks (written as a part of his bachelor research project), I’ve made some observations perhaps worth sharing with blogosphere. I used some R code and ggplot2ggthemes by Jeffrey Arnolds to represent findings visually (important: to replicate code in full you should have an access to Bloomberg and Rbbg package to download data).

Historical vs. Predicted price for Microsoft shares

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