How Does High Frequency Risk Hedge Activity Have an Affect on Underlying Market?: Analysis by Artificial Market Model
Saki Kawakubo*, Kiyoshi Izumi*,**, and Shinobu Yoshimura*
*School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan
**CREST, Japan Science and Technology Agency (JST), 5-3 Yonbanchou, Chiyoda-ku, Tokyo 102-8666, Japan
The effect of option markets on their underlying markets has been studied intensively since the first option contract was listed. Despite considerable effort, including the development of theoretical and empirical approaches, we do not yet have conclusive evidence on this effect. We investigate the effect of option markets, especially that of dynamic hedging, on their underlying markets by using an artificial market. We propose a two-market model in which an option market and its underlying market interact. In our model, there are three types of agents, underlying local agents trading only on the underlying market, option local agents who trade only on the option market, and global agents who trade both on the underlying and the option market. In this simulation, we investigate the effect of hedgers, a global agent, to the underlying market. Hedgers who have option contracts trade the underlying asset to keep a delta neutral position. This hedge behavior is called dynamic hedging. We simulate two scenarios; one is the hedge with low frequency and the other is the hedge with high frequency that hedger can send hedge order anytime when hedge miss appears. We confirmed that dynamic hedging increases or decreases the volatility of the underlying market under certain conditions.
-  Y. Uno, “The relationship between futures market and underlying market in Japan: Does futures market takes a lead over underlying market?,” Bank of Japan Review, 2013 (in Japanese).
-  V. Darley and A. V Outkin, “A Nasdaq Market Simulation Insights on a Major Market from the Science of Complex Adaptive Systems,” World Scientific, 2007.
-  F. Black and M. S. Scholes, “The pricing of options and corporate liabilities,” J. of Political Economy, Vol.81, pp. 673-654, 1973.
-  R. Frey, “Market Illiquidity as a Source of Model Risk,” in Dynamic Hedging in R. Gibson (ed.), Model Risk (RISK Publications, London), 2000.
-  N. D. Pearson, A. M. Poteshman, and J. White, “Does option trading have a pervasive impact on underlying stock prices?,” Working paper, University of Illinois at Urbana-Champaign, 2007.
-  O. Baqueiro Espinosa,W. van der Hoek and P.McBurney, “The performance of op-tion-trading software agents: initial results,” Artificial Markets Modeling: Methods and Ap-plications, Lecture Notes in Economics and Mathematical Systems, Vol.599, pp. 113-125, 2007.
-  S. Ecca, M. Marchesi, and A. Setzu, “Modeling and Simulation of an Artificial Stock Option Market,” Computational Economics, Vol.32, No.1-2, pp. 37-53, 2008.
-  C.Wang, K. Izumi, T. Mizuta, and S. Yoshimura, “Investigating the Impact of Market Maker Strategies: a Multi-agent Simulation Approach,” Proc. of 4th World Congress on Social Simulation, 2012.
-  B. Frijns, T. Lehnert, and R. C. J. Zwinekls, “Behavioral heterogeneity in the option market,” J. of Economic Dynamics & Control, Vol.34, pp. 2273-2287, 2010.
-  C. Chiarella, G. Iori, and J. Perell, “The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows,” J. of Economic Dynamics and Control, Vol.33, No.525, pp. 525-37, 2009.