Abstract

This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures.

Highlights

  • On April 16, 2010, CSI 300 futures succeeded in listing on the China Financial Futures Exchange

  • Due to its leverage properties and the hedging strategies, it may lead to market shocks and increase the systematic risk effectively managing the risk of the stock index futures market and cross-market to prevent excessive volatility and stabilize the market is critically important for financial market stability

  • This study focuses on the effects of price limits on the CSI 300 stock index futures market through changing the price-limit level in an artificial financial market, which is similar to the real Chinese stock market and the stock index futures market

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Summary

Introduction

On April 16, 2010, CSI 300 futures succeeded in listing on the China Financial Futures Exchange. Paper [16] adopted an artificial stock market to analyze price limits in China and found that reasonably enlarged existing price limits could moderate the volatility of stock returns without considering some factitious factors These studies show important research findings on the effectiveness of price limits. To overcome the limitations of previous studies, this paper adopts an agent-based computational modeling method, which provides a new perspective in analyzing complex cross-market transactions. We adopt an agentbased computational model set based on a previous study by our academic research team [20] It is a spot-future cross-market structure that coincides with the main characteristics of the Chinese stock market and the CSI 300 futures market. This almost coincides with the existing trading mechanisms of the Chinese stock market and the CSI 300 futures market

Assets
Markets
Investors’ Structure and Behaviors
Parameter Settings
Liquidity Indicators
Volatility Indicator
Liquidity Analysis
Volatility Analysis
Conclusion

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