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Custom v. Standardized Risk Models

Author

Listed:
  • Zura Kakushadze

    (Quantigic Solutions LLC, 1127 High Ridge Road #135, Stamford, CT 06905, USA
    Business School & School of Physics, Free University of Tbilisi, 240, David Agmashenebeli Alley, Tbilisi 0159, Georgia)

  • Jim Kyung-Soo Liew

    (The Johns Hopkins Carey Business School, 100 International Drive, Baltimore, MD 21202, USA)

Abstract

We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: (1) longer horizon risk factors (value, growth, etc.) increase noise trades and trading costs; (2) arbitrary risk factors can neutralize alpha; (3) “standardized” industries are artificial and insufficiently granular; (4) normalization of style risk factors is lost for the trading universe; (5) diversifying risk models lowers P&L correlations, reduces turnover and market impact, and increases capacity. We discuss various aspects of custom risk model building.

Suggested Citation

  • Zura Kakushadze & Jim Kyung-Soo Liew, 2015. "Custom v. Standardized Risk Models," Risks, MDPI, vol. 3(2), pages 1-27, May.
    • Handle: RePEc:gam:jrisks:v:3:y:2015:i:2:p:112-138:d:49868
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    Cited by:

    1. Zura Kakushadze & Willie Yu, 2022. "ETF Risk Models," Bulletin of Applied Economics, Risk Market Journals, vol. 9(1), pages 1-17.

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