基于技术分析的流动性提供与高频交易策略研究
发布时间：2018-12-15 07:10
【摘要】：技术分析是一种在金融投资实务领域被广为使用的方法,有关技术分析的现有研究主要集中在价格变化趋势的预测方面。近年来,随着市场微观结构理论的不断发展,一些学者研究发现,使用技术分析方法还有助于预测市场流动性的变化。本文通过考察中国股票市场上技术分析指标与流动性指标之间的内在关系,研究技术分析是否有助于探测市场流动性的变化模式,考察技术分析能否为流动性提供者制定合适的订单提交策略提供有用的信息,并进一步探讨基于流动性的变化模式来构造高频交易策略的可行性。 首先,本文基于上证50与深证成指指数成分股的高频交易数据,实证考察了阻力线(支撑线)与市场流动性指标之间的关系,发现价格越靠近阻力线(支撑线)卖方(买方)深度越大；并且大量限价订单在某些价位上的聚集更有可能是阻力线(支撑线)形成的Granger原因而不是相反。进一步研究发现,在阻力线(支撑线)形成前提交的限价订单倾向于集中在某些接近于随后的阻力线(支撑线)的价位上,而阻力线(支撑线)形成之后,限价订单的分布相对分散；这意味着流动性提供者倾向于在略低于(高于)阻力线(支撑线)的价位处提交限价卖单(买单),在尽可能规避逆向选择风险的同时,也避免了大量订单聚集在阻力线(支撑线)上而无法成交的风险。 其次,由于流动性提供者提交限价订单时,需在逆向选择风险和订单不能执行的风险之间进行权衡,本文估测出在阻力线(支撑线)下方(上方)不同价格区间内提交限价卖单(买单)的成交概率,以衡量订单不能执行的风险。将交易对手的最优报价(不能执行的风险为0,但逆向选择风险最大)作为基准价格,再根据相对基准价格的期望收益(或价格改进)最大化的原则来确定最优的限价订单提交价格。基于该方法,本文构造出相应的指标来为流动性提供者选择出最优的限价订单提交价格。 最后,本文进一步探讨基于流动性的变化模式来构造高频交易策略的可行性。利用价格在阻力线和支撑线之间的振荡提出了高频交易策略(假定T+1的交易制度限制不存在的情况下所做的假想策略),并采用上证50指数成分股中波动最大的前10只股票的分笔交易数据,对基于阻力线和支撑线的高频交易策略的获利性进行了考察。
[Abstract]:Technical analysis is a widely used method in the field of financial investment. The existing research on technical analysis mainly focuses on the prediction of price trends. In recent years, with the development of market microstructure theory, some scholars have found that the use of technical analysis method can also help to predict the changes of market liquidity. By investigating the relationship between the technical analysis index and the liquidity index in the Chinese stock market, this paper studies whether the technical analysis can help to detect the changing pattern of the market liquidity. This paper investigates whether the technical analysis can provide useful information for liquidity providers to formulate appropriate order submission strategies, and further discusses the feasibility of constructing high-frequency trading strategies based on liquidity change patterns. First of all, based on the high-frequency trading data of Shanghai Stock Exchange 50 and Shenzhen Stock Exchange Index, this paper empirically investigates the relationship between resistance line (support line) and market liquidity index. The closer the price is to the resistance line (support line), the deeper the seller (buyer) is found; And the accumulation of large price limit orders at some prices is more likely to be the Granger cause of resistance lines than the opposite. Further studies show that the price limit orders submitted before the formation of the resistance line (support line) tend to concentrate on some prices close to the subsequent resistance line (support line), and after the resistance line (support line) is formed, The distribution of price limit orders is relatively scattered; This means that liquidity providers tend to submit price limit orders at prices slightly below (above) the resistance line (support line), while avoiding the risk of adverse selection as much as possible. Also avoid a large number of orders on the resistance line (support line) and can not close the risk. Second, because liquidity providers have to weigh the risk of adverse selection against the risk that the order cannot be executed when submitting a price limit order, This paper estimates the probability of submitting a price limit order (paying the bill) in different price ranges under the resistance line (support line) to measure the risk that the order cannot be executed. Take as the benchmark price the optimal quotation of the counterparty (the risk that cannot be executed is 0, but the risk of adverse selection is the greatest), According to the principle of maximization of the expected return (or price improvement) of the relative benchmark price, the optimal limit price order submission price is determined. Based on this method, this paper constructs the corresponding index to select the optimal price limit price for the liquidity provider. Finally, this paper discusses the feasibility of constructing high-frequency trading strategy based on liquidity change model. Using the oscillation of price between resistance line and support line, a high-frequency trading strategy (hypothetical strategy under the assumption that the trading system restriction of T1 does not exist) is proposed. The profit-making of high-frequency trading strategy based on resistance line and support line is investigated by using the data of the top 10 stocks in Shanghai 50 Index.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F830.59
本文编号：2380212
[Abstract]:Technical analysis is a widely used method in the field of financial investment. The existing research on technical analysis mainly focuses on the prediction of price trends. In recent years, with the development of market microstructure theory, some scholars have found that the use of technical analysis method can also help to predict the changes of market liquidity. By investigating the relationship between the technical analysis index and the liquidity index in the Chinese stock market, this paper studies whether the technical analysis can help to detect the changing pattern of the market liquidity. This paper investigates whether the technical analysis can provide useful information for liquidity providers to formulate appropriate order submission strategies, and further discusses the feasibility of constructing high-frequency trading strategies based on liquidity change patterns. First of all, based on the high-frequency trading data of Shanghai Stock Exchange 50 and Shenzhen Stock Exchange Index, this paper empirically investigates the relationship between resistance line (support line) and market liquidity index. The closer the price is to the resistance line (support line), the deeper the seller (buyer) is found; And the accumulation of large price limit orders at some prices is more likely to be the Granger cause of resistance lines than the opposite. Further studies show that the price limit orders submitted before the formation of the resistance line (support line) tend to concentrate on some prices close to the subsequent resistance line (support line), and after the resistance line (support line) is formed, The distribution of price limit orders is relatively scattered; This means that liquidity providers tend to submit price limit orders at prices slightly below (above) the resistance line (support line), while avoiding the risk of adverse selection as much as possible. Also avoid a large number of orders on the resistance line (support line) and can not close the risk. Second, because liquidity providers have to weigh the risk of adverse selection against the risk that the order cannot be executed when submitting a price limit order, This paper estimates the probability of submitting a price limit order (paying the bill) in different price ranges under the resistance line (support line) to measure the risk that the order cannot be executed. Take as the benchmark price the optimal quotation of the counterparty (the risk that cannot be executed is 0, but the risk of adverse selection is the greatest), According to the principle of maximization of the expected return (or price improvement) of the relative benchmark price, the optimal limit price order submission price is determined. Based on this method, this paper constructs the corresponding index to select the optimal price limit price for the liquidity provider. Finally, this paper discusses the feasibility of constructing high-frequency trading strategy based on liquidity change model. Using the oscillation of price between resistance line and support line, a high-frequency trading strategy (hypothetical strategy under the assumption that the trading system restriction of T1 does not exist) is proposed. The profit-making of high-frequency trading strategy based on resistance line and support line is investigated by using the data of the top 10 stocks in Shanghai 50 Index.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F830.59
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