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Contribution Details

Type Master's Thesis
Scope Discipline-based scholarship
Title Alternative Portfolio Optimization - Monetizing Volatility Risk with Variance Swaps
Organization Unit
Authors
  • Florian Vetters
Supervisors
  • Thorsten Hens
  • Alexandre Ziegler
Language
  • English
Institution University of Zurich
Faculty Faculty of Business, Economics and Informatics
Number of Pages 88
Date April 2017
Abstract Text This thesis analyzes the implied volatility and realized volatility characteristics and their comparable dynamic in combination with trading strategies involving variance swaps. The basics on valuation and construction of variance swaps follow the framework provided by Demeterfi et al. (1999). Different approaches are taken to evaluate whether variance swaps are better used to hedge a portfolio of underlying equities or better used for diversification of yield-generation in an equity portfolio. Firstly, the variance swaps returns using 1-month maturities are computed and analyzed using pure vega returns in order to conclude whether variance swaps can serve as an effective hedge or whether they provide excess returns to make up for the large drawdown potential. Following the conclusion on isolated strategy results the strategy is examined in a portfolio context. The author finds that variance swaps, while providing a decent hedge for large, past pace drawdowns, are too expensive due to convexity premia. The best returns (on a risk adjusted basis), consistent across equity indices, are provided by selling variance swaps with a fixed notional and earning the “insurance”-premium. The introduction of a conditional short-long strategy only enhances returns and portfolio stability in the case of the S&P500 equity index as an underlying. The short variance strategy seems to provide the best diversified returns of all strategies in the portfolio context examined with the drawdown of pro-cyclicality leading to exacerbated portfolio drawdowns and thereby implying that this strategy needs high risk tolerance.
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