Stochastic Control Approach to Futures Trading

The following sections are included:

• Dedication
• Preface
• About the Authors
• Contents
• List of Figures
• List of Tables

This chapter gives an overview of the futures market, followed by a discussion on futures price structure. This allows us to better under the price dynamics of futures and motivate a stochastic control approach to futures trading. An introduction to the subsequent chapters is also provided.

In this chapter, we discuss no-arbitrage pricing of futures contracts in a general stochastic framework. We propose a multifactor framework where the underlying asset price is driven by a multiple Gaussian diffusion processes. Our framework is flexible and practically useful for pricing futures contracts. The flexibility of multifactor models permits good fit to entire term structure as displayed in the market. These models also come with explicit formulas for the futures prices, so they are highly tractable and easy to implement. It can be viewed as a generalization of some existing factor models, such as the Schwartz (1997) two-factor model and central tendency Ornstein–Uhlenbeck (CTOU) model (see Mencia and Sentana (2013))…

The following sections are included:

• Introduction
• Optimal Dynamic Futures Portfolio
• Two-Factor Models
  • Schwartz model
  • CTOU model
• The Multiscale Central Tendency Ornstein–Uhlenbeck Model
  • Model formulation
  • Futures pricing and futures trading
• Numerical Illustration
• Conclusion

Asset price dynamics may depend on market regimes, which can change suddenly and persist for a period of time. The timing of regime switching is often unpredictable, thus making hedging and risk management very challenging. In this chapter, we discuss a general regime-switching model to capture such properties of market dynamics. Specifically, an exogenous continuous-time finite-state Markov chain is used to represent the stochastic market regime…

The following sections are included:

• Introduction
• Futures Price Dynamics
• Futures Portfolio Optimization
  • Utility maximization
  • Certainty equivalent
• Regime-Switching Geometric Brownian Motion
• Regime-Switching Exponential Ornstein–Uhlenbeck Model
  • Futures dynamics and utility maximization
  • Numerical implementation and examples
• Conclusion

In the previous chapters, the futures portfolios consist of multiple futures contracts written on the same underlying asset. A portfolio that has exposures to multiple underlying assets within the same asset class or across different asset classes offers more degrees of freedom in portfolio construction and certain diversification effects. Nevertheless, additional underlying assets and futures increase the dimension and complexity of the portfolio optimization problem…

The following sections are included:

• Bibliography
• Index