Abstract
We present a novel agent-based approach to simulating an over-the-counter (OTC) financial market in which trades are intermediated solely by market makers and agent visibility is constrained to a network topology. Dynamics, such as changes in price, result from agent-level interactions that ubiquitously occur via market maker agents acting as liquidity providers. Two additional agents are considered: trend investors use a deep convolutional neural network paired with a deep Q-learning framework to inform trading decisions by analysing price history; and value investors use a static price-target to determine their trade directions and sizes. We demonstrate that our novel inclusion of a network topology with market makers facilitates explorations into various market structures. First, we present the model and an overview of its mechanics. Second, we validate our findings via comparison to the real-world: we demonstrate a fat-tailed distribution of price changes, auto-correlated volatility, a skew negatively correlated to market maker positioning, predictable price-history patterns and more. Finally, we demonstrate that our network-based model can lend insights into the effect of market-structure on price-action. For example, we show that markets with sparsely connected intermediaries can have a critical point of fragmentation, beyond which the market forms distinct clusters and arbitrage becomes rapidly possible between the prices of different market makers. A discussion is provided on future work that would be beneficial.
Abstract (translated)
我们提出了一个新颖的基于代理的模拟超额交易金融市场的算法，其中交易仅由市场制造商代理进行中介，代理的可见性受到网络拓扑结构的限制。动态，如价格变化，源于市场制造商代理作为流动性提供者普遍发生的代理水平相互作用。我们还考虑了两个额外的代理：趋势投资者使用深度卷积神经网络与深度 Q-学习框架分析价格历史来告知交易决策；价值投资者使用静态价格目标来确定他们的交易方向和规模。我们证明了在我们的新颖加入市场拓扑结构与市场制造商的情况下，可以探索各种市场结构。首先，我们介绍了模型及其工作原理。其次，我们通过与现实世界的比较验证了我们的研究结果：我们证明了价格变化具有脂肪尾分布，自相关波动，市场制造商位置的 skew 负相关，可预测的价格历史模式以及更多。最后，我们证明了基于网络的模型可以揭示市场结构对价格行动的影响。例如，我们证明了稀疏连接的中介市场中，市场可能会出现临界点，超过这个临界点，市场将形成明显的簇，套利在不同的市场制造商价格之间变得迅速可能。我们还提供了未来工作的讨论。
URL
https://arxiv.org/abs/2405.02480
