人工市場シミュレーションを用いたCFD市場に おける最適マーケットメイク戦略分析

抄録

With the increasing trading volume in the Japanese CFD (Contract for Difference) market, the strategy of market making in CFDs has become a significant issue. Unlike other quote-driven markets where market makers face the dilemma of maximizing profits and managing inventory risk, CFD market makers can hedge their risks using the underlying market. Therefore, effectively incorporating hedging strategies into market making becomes a crucial aspect of CFD market strategies. This study aimed to analyze the optimal market-making strategies in the CFD market. A multi-agent simulation model of a CFD market was constructed, simulating the environment of a prominent Japanese CFD exchange, ”Click kabu 365”. This model included an index market as the underlying asset market, along with investor agents and market maker agents. Through the analysis of market makers in the CFD market, we proposed a new market-making strategy that dynamically adjusts hedging intensity based on market volatility and trends, in addition to using the spread strategy from previous research. To evaluate the effectiveness of the proposed strategy, we conducted simulations under different market conditions. The first set of experiments compared the performance of different strategies in separate market environments. The results showed that the proposed strategy outperformed others in terms of profitability and risk management. The second set of experiments considered competition among market makers within the same market environment, confirming that the proposed strategy maintained superior overall performance, though its advantage was less pronounced in this competitive scenario. The study concludes that the proposed market-making strategy effectively balances inventory risk management and hedging costs. Additionally, it highlights the potential risk of presenting competitive quotes in adverse market conditions when combining spread and hedging strategies, which should be considered in practical applications.