【作者】 朱鹏；

【导师】 杨学伟；

【作者基本信息】 南京大学 ， 金融（专业学位）， 2020， 硕士

【摘要】 价格发现是市场的基本功能之一,而实现这一功能则涉及交易规则、交易机制、市场多方主体及其相互作用的复杂过程。从市场微观角度出发研究资产价格的形成与发现,成为揭示市场上价格形成的“黑箱过程”的可行之路。对于交易资产价格具有较大不确定性的比特币市场而言,上述研究路径显得更有价值,在市场标的价值的高波动背景之下,从微观角度出发研究价格形成与发现过程具有现实意义。本文以传统金融市场微观结构研究中的订单簿研究为基础,利用全球最大数字货币交易所主力品种的逐笔交易与订单簿快照的超高频数据,对订单簿不平衡现象蕴含的交易行为模式与其对价格形成的影响进行了实证研究。研究结论表明:订单不平衡与市场的趋势追踪行为相关,这种趋势追踪具有明显的方向差异,订单不平衡对价格变动具有正向影响,各类订单不平衡指标联合起来可以解释45%的价格变动(高于传统市场研究中15%-30%的水平)。基于订单不平衡指标的价格预测力,本文分别以简单信号和机器学习模型为基础,构建了两类量化交易策略,样本外回测结果表明策略能够实现稳定盈利,策略回撤能控制在较小的范围,风险收益表现整体较好。随着比特币市场的飞速发展,对于比特币市场微观层面的研究,有助于揭示该市场的价格形成过程,本文的研究内容拓展了市场微观结构的研究对象领域,填补了数字货币市场相关研究的空白。同时,本文的研究结果对比特币市场投资业界的高频交易、量化策略构建具有重要参考意义。更多还原

【Abstract】 Price discovery is one of the basic functions of the market,and the realization of this function involves the complex process of trading rules,trading mechanisms,market multi-party entities and their interaction.Studying the formation and discovery of asset prices from a market micro perspective has become a feasible way to reveal the "black box process" of price formation on the market.For the bitcoin market where trading asset prices are highly uncertain,the above research path appears to be more valuable Under the high volatility of market target value,it is of practical significance to study the price formation and discovery process from a micro perspectiveBased on the order book research in the study of the microstructure of traditional financial markets,using the UHF data of the world’s largest digital currency exchange’s major transactions and the order book snapshots,this paper conduct an empirical study on the imbalance of the order book and its impact on price formation.The conclusion of the study shows that the order imbalance is related to the market trend tracking behavior.This trend tracking has obvious direction differences.The order imbalance has a positive effect on price changes.The combination of various order imbalance indicators can explain 45%of the price.Change(higher than the 15%-30%level in traditional market research).Based on the price predictive power of order imbalance,this paper builds two types of quantitative trading strategies based on simple signals and machine learning models.The out-of-sample back test results show that the strategy can achieve stable profitability and the strategy retracement can be controlled at a small The scope of risk and return performance is generally betterWith the rapid development of the bitcoin market,research on the micro-level of the bitcoin market will help reveal the market’s price formation process.The research content of this article expands the research object field of the market microstructure and fills the related research gaps of the digital currency market.At the same time,the research results of this paper have important reference significance for the high-frequency trading and quantitative strategy construction of the Bitcoin market investment community.更多还原