Selected Research Methods

Abstract

The purpose of this section on research methods and designs is to analyze the contemporary literature in the field of quantitative finance. Fifteen selected research articles were compared and contrasted on how to analyze hedging and price methods for financial assets. In addition, an investigation and evaluation of recent trends with research designs for the use in quantitative finance to develop and establish hedging and pricing techniques will be conducted.

The first article investigates modeling asymmetric volatility in the context of research methods explored by Hassan. The second research study involves oil future prices and term structures, whereby understanding the permanent and transitory shocks in oil futures can be accomplished via a structural vector auto-regression model by Zha. The third article of inquiry is by Cao and Guo which involved delta hedging performance methodologies. In the fourth research study, Ankirchner and Heyne suggested how to use research methods using cross hedging with stochastic correlations. In the fifth article, Srinvasan investigated stock market volatility and used different volatility models that are GARCH-types. The sixth peer-review study investigated is by Menkhoff, which involves currency momentum and the use of moving averages. The seventh research article was about how to price currency options and the methods used to determine which volatility model performed the best proposed was by Manzur, Hoque, and Poitras. The eighth scholarly study, which was authored by Jiang, involves foreign exchange markets and the use of a vector error correction model.

The ninth intellectual inquiry investigated was on tail risk management and some of the methodologies used when modeling with Value-at-Risk and conditional Value-at-Risk by Kayan, Lee, and Pornrojnangkool. The tenth article explores the hydroelectric power industry and how to incorporate a hedging strategy and test for performance by Fleten, Brathen, and Nissen-Meyer. The eleventh research study investigated was by Frikha and Lemaire involved the gas and electricity spot price using a multi-factor model that can present higher volatility markets. The twelfth scholarly article proposed was by Hinnerich which explores equity swaps and demonstrates how to incorporate a jump diffusion model to capture price dynamics. The thirteenth study relates to derivative pricing using a close-form approximation relying on series expansions by Kristensen and Mele. The fourteenth study in this section involves how to build a trading algorithm system by Moldovan, Moca, and Nitchi. The last article reviewed was by Viebig and Poddig, whereby extreme value theory and copula theory was considered as a way to model multivariate daily return distributions of hedge funds.

In the conclusion section of this Depth component a discussion on the synthesis of the relevant research related to research design used in quantitative finance was conducted. Comments on how to approach the research design with a focus on establishing hedging and pricing strategies of financial assets was shown. The intent of this section was to explore some of the tools developed in statistical analysis that enable researchers in quantitative finance to evaluate different hedging and pricing strategies. With a better research design and the use of advanced statistical methods researchers and practitioners can evaluate their financial modeling performance more accurately.

Within the conclusion section each of the fifteen research articles mentioned above will be summarized in the framework of research methods that can promote social change. In addition to the summary of these research studies, some questions are explored to provide possible investigational paths.

Keywords: Volatility, Term Structure, Oil Futures, Delta Hedging, Stochastic Correlation, Currency, Option Pricing, Tail Risk, Electricity, Natural Gas, Swaps, Derivatives, Extreme Value Theory

JEL Classification: C10, C49, C5, C53, C63, E17, E30, F47