Faculties and Research

Professor Stewart Hodges

Professor Emeritus of Finance

Faculty of Finance


Visit Stewart Hodges

Room BR5034, Bunhill Row


Postal Address

Cass Business School
106 Bunhill Row
United Kingdom


Stewart Hodges has spent extended periods first at the London Business School and subsequently at the University of Warwick where he established and directed both the Financial Options Research Centre and the MSc in Financial Mathematics. He has also taught at MIT and at UC Berkeley.
His research interests relate to the theory and practice of derivatives valuation, risk measurement and management, and also a number of topics in portfolio management. They span commodities and energy as well as fixed interest and equities. Besides being widely published in these areas, he has acted as a consultant on them to a variety of financial institutions and government organizations.
He is currently a director of a hedge fund managed by F&C Alternative Investments, a member of Barrie and Hibbert’s Technical Advisory Panel and Associate Editor, Journal of Derivatives, and Review of Futures Markets.


BSc, MSc (Maths)- Southamption and PhD (Econ)- London.


Primary Topics

  • Hedge Funds
  • Fund Management
  • Risk Management
  • Mathematical & Quantitative Methods
  • Portfolio Choice
  • Futures & Options
  • Financial Regulation
  • Mathematical Finance
  • Financial Markets
  • Derivatives
  • Fixed-Income Investments
  • Risk Modelling
  • Finance

Research Topics

The role of higher moments in hedging under transactions costs (with Miao Chen)
A local time analysis of delta hedginghunder transactions costs reveals that the higher moments of the probability distribution of the costs incurred influence the width of the hedging band.
The value of a storage facility
The paper derives the value of a facility to store a commodity whose exogenously defined price process has both seasonal and mean-reverting components. It provides an elegant new analytic continuous-time model of storage. Closed form solutions are obtained as functions of the underlying price (when there is no seasonality), and a local time analysis provides an even simpler unconditional formula which extends to the general case. An interesting feature is that both buy and sell transactions are triggered by a single critical price. The analysis provides insights into the profitability of storing under alternative price process assumptions.
Fixed odds bookmaking with stochastic betting demands (with Hao Lin)
This paper studies the fixed odds bookmaking in the market for bets in a British horse race. The bookmaker faces the risk of unbalanced liability exposures. Even random shocks in the noisy betting demands are costly to the bookmaker since his book could become less balanced. In our model, the bookmaker sets appropriate odds to influence the betting flow to mitigate the risk. The stylized fact of the favorite-longshot bias only arises from the model under specific assumptions. Our model offers insights into the complexity of managing a series of state contingent exposures such as options.
Hao Zhang
Oct 2008 – present, full-time
Thesis Title
Modelling liquidity effects
1st Supervisor

Chapters (3)

  1. Hodges, S.D. (2009). Good Deal Bounds. In Cont, R. (Ed.), Encyclopedia of Quantatitive Finance Wiley.
  2. Tompkins, R.G., Hodges, S.D. and Ziemba, W.T. (2008). The Favourite-Longshot Bias in S&P500 and FTSE 100 Index Futures Options: The Return to Bets and the Cost of Insurance. In Hausch, D.B. and Ziemba, W.T. (Eds.), Handbook of Sports and Lottery Markets (pp. 161–180). North Holland.
  3. Clewlow, L., Hodges, S.D. and Skiadopoulos, G. (2004). The Dynamics of Smiles. In Refenes, A.N. (Ed.), Quantitative Methods in Finance (pp. 119–153). Athens: Typothito Dardanos.

Conference Paper/Proceedings

  1. Hodges, S.D. and Lin, H. (2009). Fixed odds bookmaking with stochastic betting demands. EFMA 2009 Annual Meeting, June 24-27, 2009 Milan, Italy.

Journal Articles (17)

  1. Hodges, S., Lin, H. and Liu, L. (2013). Fixed Odds Bookmaking with Stochastic Betting Demands. European Financial Management, 19(2), pp. 399–417. doi:10.1111/j.1468-036X.2012.00601.x.
  2. Zhao, B. and Hodges, S.D. (2013). Parametric modeling of implied smile functions: A generalized SVI model. Review of Derivatives Research, 16(1), pp. 53–77. doi:10.1007/s11147-012-9077-x.
  3. Parekh, N., Hodges, S.D., Pollock, A.M. and Kirkwood, G. (2012). Communicating the risk of injury in schoolboy rugby: Using Poisson probability as an alternative presentation of the epidemiology. British Journal of Sports Medicine, 46(8), pp. 611–613. doi:10.1136/bjsports-2011-090431.
  4. Bedendo, M. and Hodges, S.D. (2009). The dynamics of the volatility skew: A Kalman filter approach. Journal of Banking and Finance, 33(6), pp. 1156–1165. doi:10.1016/j.jbankfin.2008.12.014.
  5. Hodges, S.D. and Parekh, N. (2006). Term-Structure Slope Risk: Convexity Revisited. Journal of Fixed Income, 16(3), pp. 54–59. doi:10.3905/jfi.2006.670094.
  6. Ribeiro, D.R. and Hodges, S.D. (2005). A contango-constrained model for storable commodity prices. Journal of Futures Markets, 25(11), pp. 1025–1044. doi:10.1002/fut.20180.
  7. Anagnou, I., Bedendo, M., Hodges, S.D. and Tompkins, R.G. (2005). Forecasting Accuracy of Implied and GARCH-Based Probability Density Functions. Review of Futures Markets, 14(1), pp. 41–66.
  8. BEDENDO, M.A.S.C.I.A. and HODGES, S.T.E.W.A.R.T.D. (2004). A PARSIMONIOUS CONTINUOUS TIME MODEL OF EQUITY INDEX RETURNS: INFERRED FROM HIGH FREQUENCY DATA. International Journal of Theoretical and Applied Finance, 07(08), pp. 997–1030. doi:10.1142/S0219024904002773.
  9. Noceti, P., Smith, J. and Hodges, S. (2003). An evaluation of tests of distributional forecasts. Journal of Forecasting, 22(6-7), pp. 447–455. doi:10.1002/for.876.
  10. Wong, M.C.W. and Hodges, S.D. (2002). Pricing Defaultable Coupon Bonds Under a Jump-Diffusion Process. The Journal of Fixed Income, 12(1), pp. 51–64. doi:10.3905/jfi.2002.319318.
  11. Neuberger, A. and Hodges, S. (2002). How Large Are the Benefits from Using Options? The Journal of Financial and Quantitative Analysis, 37(2), pp. 201–201. doi:10.2307/3595003.
  12. Hodges, S.D. and Tompkins, R. (2002). Volatility Cones and Their Sampling Properties. The Journal of Derivatives, 10(1), pp. 27–42. doi:10.3905/jod.2002.319188.
  13. Skiadopoulos, G. and Hodges, S. (2001). Simulating the Evolution of the Implied Distribution. European Financial Management, 7(4), pp. 497–522. doi:10.1111/1468-036X.00168.
  14. Skiadopoulos, G., Hodges, S. and Clewlow, L. (2000). The Dynamics of the S&P 500 Implied Volatility Surface. Review of Derivatives Research, 3(3), pp. 263–282.
  15. Clewlow, L. and Hodges, S. (1997). Optimal delta-hedging under transactions costs. , 21(8-9), pp. 1353–1376.
  16. Hodges, S. and Carverhill, A. (1993). Quasi Mean Reversion in an Efficient Stock Market: The Characterisation of Economic Equilibria which Support Black-Scholes Option Pricing. The Economic Journal, 103(417), pp. 395–405.
  17. Hodges, S. and Neuberger, A. (1989). Optimal Replication of Contingent Claims under Transaction Costs. Review of Futures Markets, 8(2), pp. 222–242.

Consultancy (2)

  1. Barrie and Hibbert (Private Sector) (2006 – present)
    Member of their Technical Advisory panel
  2. F&C Alternative Investments (Private Sector) (2002 – present)
    Director of Sapphire hedge fund

Editorial Activities (2)

  1. Review of Futures Markets, Associate Editor, 2005 – present.
  2. Journal of Derivatives, Associate Editor, 1994 – present.


  1. EFMA 2009 Annual Meeting, June 24-27, 2009. (Conference) Milan, Italy (2009).
    Paper: Fixed odds bookmaking with stochastic betting demands
    Author: Hodges S D
    Co-authors: Lin, Hao

Media Appearances (2)

  1. Looking for solutions to our pension crisis. (2013) The Times (newspaper).
  2. Qunats Fight Back. (2009) eFinancial Careers (website).