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| A Theoretical and Empirical Analysis of Portfolio Hedging Strategy with Stock Index Futures under Ambiguity Aversion |
| ZHANG Jinqing, YIN Yiwen
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| School of Economics, Fudan University |
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Abstract Under high volatility, given the limited short selling opportunities in China's A-share market, futures and options products are essential to meet the strong investor demand for risk hedging. However, there are few studies on the type of risk hedging strategies or stock index futures that are suitable for China's A-share market. This paper studies one such optimal risk hedging strategy: trading open-end index funds (ETF) under ambiguity aversion and with transaction costs.
The goal of a hedging strategy is to improve investment performance by adjusting the risk exposure of a portfolio at low cost. Garleanu and Pederson (2013) analyze the liquidity cost of stock spot and futures trading and the impact of their differences on hedging strategies. Under the condition of investors' ambiguity aversion, Garleanu-Pederson identify novel characteristics that can improve investment performance and reduce transaction costs (Zhang et al., 2019). However, there are few studies of futures hedging strategies under ambiguity aversion.
The contributions of this paper are as follows. First, this paper introduces ambiguity aversion into the hedging strategy of stock index funds and examines the influence of ambiguity aversion on the optimal position of securities given restrictions on futures trading. Second, this paper distinguishes between the transaction costs of stock index futures and ETFs and considers the interaction of transaction costs and investors' ambiguity aversion within Garleanu-Pederson's model. It finds that ambiguity aversion reduces the transaction costs caused by wrong investment decisions and improves investment performance. Third, this paper separates the independent disturbance term of ETF yield from stock index futures, to further distinguish the effects of ambiguity aversion on the disturbance term and futures.
Ambiguity aversion and transaction costs are introduced into the Garleanu-Pederson framework to construct a theoretical model of the dynamic hedging of stock index funds. Then, the model is tested using a dataset of China's ETF portfolio and stock index futures. According to the model, if the estimations of ambiguity aversion and transaction cost parameters are reasonable, the performance of an investment portfolio based on a hedging strategy will be better than one based on a non-hedging strategy, the ratio of dynamic optimal trading volume to aim trading volume will be smaller, and the target trading volume will be more sensitive to the expected return predictor. This paper uses ETF and stock index futures data from China's A-share market from April 2010 to June 2021 to empirically test the above reasoning. There are three main results. First, a hedging strategy can significantly improve investment performance, and restrictions on stock index futures trading weaken this effect. Second, the decrease in transaction costs and the flexibility of target position adjustment are the main channels of investment performance improvement. Third, relative to previous studies, such as Garleanu and Pederson (2013) and Zhang et al. (2019), this paper's findings are more robust and highlight the characteristics of sensitivity.
The findings have implications for the development of China's derivatives market. First, continuously enriching the product series of stock index futures and stock index options should become the key issue of capital market infrastructure construction. Second, although using a risk hedging strategy on stock index futures to implement ETF produces better performance than using a non-hedging strategy, trading restrictions on stock index futures weaken this effect. Therefore, the reduction of transaction costs and arbitrage constraints should be promoted, so as to improve the ability of institutional investors, such as funds, to use derivatives to manage risk and create value.
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Received: 28 November 2019
Published: 01 June 2022
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