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Portfolio Optimisation And Risk Management

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database and may not be available.

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  • Full or part time
    Dr Tan
  • Application Deadline
    Applications accepted all year round

Project Description

This project mainly focuses on employing advanced robust portfolio optimization techniques and quantitative risk models to construct portfolios with better performance through empirical studies of broad asset classes such as commodities, currencies, equities and fixed incomes etc. It would also contribute to develop the design of trading strategies and methods of estimation of expected returns, volatilities and risks, which are three important parameters inputted in asset allocation. In terms of performance evaluation, the project would contribute to enhance performance measures to better fitting features of financial assets in the portfolio.

Specifically, the recent research topic for this project is Investment Strategies in Commodity Futures Market. Commodity futures have become commonly used for strategic and tactical asset allocations due to their equitylike return, role of inflation-hedging and risk diversifiers (Bodie and Rosansky, 1980; Erb and Harvey, 2006; Gorton and Rouwenhorst, 2004; Chong and Miffre, 2010). Bessler and Wolff (2015) investigate if commodities could add value in multi-asset portfolios for different investment strategies, and find that the portfolio gains greatly vary between different types of commodities and sub-periods. Commodity futures have also been proved to generate abnormal returns by using momentum, term structure signals and trend following (Erb and Harvey, 2006; Miffre and Rallis, 2007; Fuertes et al., 2010; Clare et al., 2012; Narayan et al., 2014; Bianchi et al., 2015). Rachev et al. (2007) demonstrate that momentum strategies based on reward-risk criteria could show better risk-adjusted performance with acceptable lower tail risk. Gorton and Rouwenhorst (2004) find that the distribution of commodity returns has positive skewness and positive excess kutosis reflecting fat tails relative to normal distribution. Therefore, there is motivation to examine what type of investment strategies could be used in commodities to improve portfolio performances.

For informal enquiries about this project, please contact: Dr Linzhi Tan: [email protected]


BODIE, Z. & ROSANSKY, V. I. (1980) Risk and return in commodity futures. Financial Analysts Journal, 27-39.
BESSLER, W., and WOLFF, D., 2015. Do commodities add value in multi-asset portfolios? An out-of-sample
analysis for different investment strategies. Journal of Banking & Finance, 60, 1-20.
BIANCHI, R.J., DREW, M.E. and FAN, J.H., 2015. Combining momentum with reversal in commodity
futures. Journal of Banking & Finance, 59, 423-444.
CHONG, J. & MIFFRE, J. (2010) Conditional correlation and volatility in commodity futures and traditional asset
markets. The Journal of Alternative Investments, 12, 061-075.
CLARE, A., SEATON, J., SMITH, P. N. & THOMAS, S. (2012) Trend Following, Risk Parity and Momentum in
Commodity Futures.
ERB, C. B. & HARVEY, C. R. (2006) The strategic and tactical value of commodity futures. Financial Analysts
Journal, 69-97.
FUERTES, A.-M., MIFFRE, J. & RALLIS, G. (2010) Tactical allocation in commodity futures markets: Combining
momentum and term structure signals. Journal of Banking & Finance, 34, 2530-2548.
GORTON, G. & ROUWENHORST, K. G. (2004) Facts and fantasies about commodity futures. National Bureau of
Economic Research.
MIFFRE, J. & RALLIS, G. (2007) Momentum strategies in commodity futures markets. Journal of Banking &
Finance, 31, 1863-1886.
NARAYAN, P.K., AHMED, H.A. and NARAYAN, S., 2014. Do Momentum-Based Trading Strategies Work in the
Commodity Futures Markets? Journal of Futures Markets, doi: 10.1002/fut.21685.
RACHEV, S., JASIC, T., STOYANOV, S. & FABOZZI, F. J. (2007) Momentum strategies based on rewardrisk stock
selection criteria. Journal of Banking & Finance, 31, 2325-2346.

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