Risk Management, Kurtosis, Skewness & Extreme Value Theory

My article at SeekingAlpha.com was published as a full-fledged article - and I am now an official "Contributor" at their website. Someone asked a few good questions that I answered on the website. I also copied it below, since I thought it was good information.

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More realistic estimate of probabilities: I like semi-deviation as an easy-to-explain measure (volatility and risk to the downside). Additional measures that help describe return distributions -- would involve calculating additional "moments" such as skewness and kurtosis (the fat-tailed distributions that many investment strategists strive for = minimize losses, fattening profits).

More on Semi-Correlation: Semi-correlation is somewhat similar to correlation, except it studies periods where certain assets decline. This can give a "true" measure of diversification during financial crises.

There is also a branch of statistics that studies the probability of big dislocations such as crashes in markets (Extreme Value Theory) - which is very interesting...

Stock Market Outlook

With the sharp decline, and bounce, our stock market models are turning bullish. The long-term model remains moderately bullish. The overbought/oversold indicators have turned from moderately short to moderately long.

In addition, barring wild market action, a look-ahead at the model's signals shows that they will turn from moderately bullish to a medium long signal. Perhaps the summer rally is getting set to start in earnest.

My Article at SeekingAlpha - Portfolio Optimization and Rising Correlations

Here's a link to my article at SeekingAlpha.com.

In particular, it talks about "true" diversification amidst rising correlations and the evolving world -- and some implications for portfolio optimization. I show a tool I developed that I call semi-correlation. This statistic can show which asset classes offer more "true diversification" when many assets start moving together in a financial crisis.

http://seekingalpha.com/article/215457-portfolio-optimization-with-rising-correlations-and-an-evolving-world

Quick Twit: have you signed up for our Twitter?

16 July 345pm - With today's drop, our indicators remain neutral. The overbought / sold indicators will remain bearish for a few more days.

Our twitter is: z_trader (underscore).

If signals don't change, we may only do a Quick Twitter. If models flash a change in signals, we will normally make a blog post.

Have a good weekend.

Long-Term Systems Flip to Moderately Bullish

With today's rally, our long-term stock models are flipping to moderately bullish at the close today (from their moderately bearish stance). Our overbought (intermediate) stock market indicators remain moderately bearish.

The short-term trend upwards today kept us flat to slightly long overall. Remember to keep all three time-frames in mind if you are a trader.

Stock Systems Wary

Our long-term stock market indicators are moderately bearish. The market has bounced, but not very strongly. The indicator will hold on to it's bearish stance for a few more days, based on market action.

Interestingly, our intermediate indicators are also moderately bearish right now. The intermediate and long-term indicators have been countering each other a bit recently, but both are now moderately bearish due to the market bounce. They are calling it a dead-cat bounce -- at least for a few more days.

We'll keep you posted with any changed in the stock market indicators.

My Article at SeekingAlpha - Semi-Deviation & Semi-Correlation

http://seekingalpha.com/instablog/677712-carlton-chin-cfa/79376-post-modern-portfolio-theory-semi-deviation-semi-correlation

The popular mean-variance approaches are well-documented methods of improving a portfolio’s risk-reward characteristics. The fact that Markowitz’s contributions to Modern Portfolio Theory have stood the test of time – more than fifty years later – shows the power of these methods. Over the years, additional models have been developed, that, for example, help investors establish reasonable assumptions and optimizer inputs such as expected returns, volatility (standard deviation), and correlations amongst asset classes.

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Summary

It is important to study and measure true downside risk and the inter-relationships amongst various asset classes. More specifically, determine which particular asset classes may help when certain assets are declining in value. Semi-correlation as well as semi-deviation have proven to provide a more accurate picture – when applying portfolio diversification models.

In addition to improved risk measures and correlation studies, a variety of tools (such as Monte Carlo analysis) form a strong foundation for enhanced portfolio optimization and Post-MPT. On top of a “risk-management portfolio optimization engine,” robust alternative investment strategies add meaningful diversification and greatly improve expected risk/return characteristics to a portfolio.

Carlton Chin, CFA, is a specialist in strategic asset allocation, quantitative investment strategies, and alternative assets. Carlton has worked with institutional investors on asset allocation and is a fund manager. He holds both undergraduate and graduate degrees from MIT.