Dynamic derivative strategies

Abstract

Quantitative Investment Models deal with investment in stock and bond and generally leave derivative securities aside. These Investment models argue that since derivatives can be replicated using stock and bonds they help us span no risk factors which we can’t other wise span using stocks and bonds only. This make derivative securities redundant. In this Thesis we argue otherwise and provide evidence for the existence or risk factors other than the ones which stock and bond span. We start with examining the jump risk and variance risk premiums, and then using elegant stochastic optimal control based models explain the theoretical need for investment in derivatives. Here we find from a theoretical point of view that investment in derivatives saves investors from bankruptcy risk and risk of time varying stochastic volatility. This theoretical model is important as many practitioners still do not invest in derivatives considering them to be redundant securities. We create Term Structure models for investment in variance swaps and show that a two factor term structure model best fits our data set. The price of variance swap under a general Affine term structure model is found and this for formula is valid for arbitrary number of factors. With a better understanding of variance risk, we suggest the use of both short term and long term variance swaps in portfolio management. In particular, we find selling short term variance swaps and buying long term variance improves provides a significant improvement in investment outcomes i.e sharp ratio etc.

Date of Award	2022
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Daniel PEREZ PALOMAR (Supervisor)