Buy Side Risk Europe – “Avoiding crowds and modeling endogenous risk” Discussion Summary

Bénédicte Godet

BISAM was very pleased to sponsor last week’s Buy Side Risk Europe 2017 conference in London, to share views and discuss the latest operational and technology trends with the European asset management community. Boryana Racheva-Iotova, BISAM’s Global Head of Risk, took part in a panel discussion on Avoiding crowds and modeling “endogenous” risk. Here is an extract of the questions and key points expressed by the panelists.

Question: What do you think are the biggest risks in the market?
Answers from panelists: The biggest risks in the market right now are:

  • Too much concentration into specific asset classes
  • With markets becoming more and more complex, it has become increasingly difficult to separate all types of risks: political, market, credit, etc.
  • Some risk factors are non-quantifiable and, as such, difficult to incorporate in risk models

Despite these risks, opportunities for alpha may arise when markets are nervous and uncertainty is high.

Q: What are the shortcomings of conventional models?
A: The short answer is that there is no perfect model, they all work based on assumptions. When using a model, its specific assumptions need to be known and understood.

Conventional models work better in normal market conditions. When the markets are volatile, fat-tail modeling delivers a clearer and more efficient reading. A few things models should start considering:

  • Markets regime changes, i.e. conditioning “traditional models” on market state
  • Behavior description in stressed markets
  • Market turbulence caused by new type of risks factors including external shocks (i.e. political risk), market micro-structure factors, liquidity stress, crowding

What about smart beta strategies, can they cause crowding?
A: To the extent any strategy based on simplistic assumptions is widely used, smart betas based on similar model assumptions can create crowding risks.

However, smart beta strategy building is becoming further sophisticated and the correlation and dependency between strategies and top-level similar objectives are not necessarily high and they can have very different returns behavior.

What is the best way to predict extreme risk in portfolios without focusing on the last crisis?
A: To predict extreme risk, the focus should be on:

  • Turbulence analysis (turbulence meaning in some sense volatility of volatility)
  • Even in a low volatility regime, you can see signs of increasing turbulence. Understanding structure of the market and new types of risk factors that can lead to turbulence (market liquidity, trading intensity, concentration of assets, etc.)

What is the meaning when VIX is very low and skew very high?
A: Low VIX, and in general low volatility, and high positive skew can be potential indicators of crowding. Indicators for crowding are complex and multifaceted. Compare implied and realized levels on volatility and implied dividend, observing structural changes of the correlations structure and factor loadings, combined with understanding of asset flows, can point to crowded trades.

 State of the art Real World Risk Modeling


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