Beating mean-variance with stochastic dominance!

Mean-variance with stochastic dominance may sound like a foreign language to most, but for traders modelling and algorithms are central to helping gain an edge over their counterparts.

Today, mean-variance models are the preferred risk models as they are easy to understand and convenient from a computational point of view.  However, they mainly only use two statistics to characterise the portfolio return distribution and thus, may ignore important information.

A more general approach is stochastic dominance, which considers the entire distribution of a random variable and relies on expected utility theory. It assumes risk-averse investors maximising expected utility without the drawback of defining a specific utility function. So, it is appealing to a wide group of investors.

Second-order stochastic dominance particularly is broadly accepted as important principle in portfolio optimisation. Its approach, even though being computationally intensive, ensures that the cumulative portfolio return exceeds the return of a given benchmark.

It can reduce downside risk on one side, and increase upside potential on the other side.  And isn’t that what traders are looking for?  Beating mean-variance with stochastic dominance!

Built out of 10 years’ academic research and over 100 papers and studies, ALA’s financial analytics can offer a deeper and richer insight into market movements ahead of time.  Our financial analytics undertake pre-emptive, descriptive, and predictive edge analytics augmented with behavioural, sentiment and emotional analytics.  Data can be mined, processed and analysed using any internal or external source in real time.

Our financial analytics solution identifies and catches signs of bubbles, market trends, overconfidence in M&A deals, and other useful indicators, in any language, and across jurisdictions. Delivering accurate and predictive business intelligence, investment professionals can make more informed and better decisions throughout the investment cycle.

ALA believes that business driven decisions should be firmly rooted in advanced analytics, not instinct.
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