螺纹钢期货市场价格发现功能与量化交易策略实证

发布时间：2018-01-10 00:00

本文关键词：螺纹钢期货市场价格发现功能与量化交易策略实证　出处：《江西财经大学》2014年硕士论文　论文类型：学位论文

【摘要】：螺纹钢期货自2009年3月27日在上海期货交易所正式上市以来,倍受市场投资者青睐。然而,相对国内成熟期货品种(农产品期货,铜期货),螺纹钢期货的上市时间短,仍处于初期发展阶段。因此,研究其期货市场的功能能否有效地发挥具有现实意义。期货市场的基本功能分为两大类：套期保值功能和价格发现功能。价格发现功能是期货市场存在和发展的基础,是现货市场引导期货市场的基本前提。期货市场价格发现功能发挥的有效程度可以用来评估期货市场的运行效率。同时,我国在继菜籽油、棕榈油等商品期货上市之后推出金属期货,加强了期货市场和证券市场以及现货市场的互动。投资者既可以通过期货市场、证券市场和现货市场进行套期保值,也可以在期货市场进行风险投机。期货市场的迅速发展以及金融衍生品市场的扩张为量化交易提供了强而有力的市场基础。在期货市场利用量化交易将会是市场投资者,尤其是机构投资者的一个重要发展方向。本文实证研究分为两部分：第一部分,研究螺纹钢期货价格发现功能的有效性,检验我国上海期货交易所的螺纹钢期货市场价格发现功能；第二部分,建立螺纹钢期货5分钟数据的量化交易模型,应用Matlab仿真功能进行模型仿真分析,寻找最优的量化交易策略。其中,螺纹钢期货市场价格发现功能实证部分采用的研究方法包括：ADF单位根检验、向量自回归模型、协整检验、向量误差修正模型、EG两步法检验、格兰杰因果关系检验以及方差分解；实证工具为Eviews软件。选取的数据为螺纹钢期货每日收盘价数据,样本区间去掉螺纹钢上市后的五个月,从2009年9月1日至2014年3月10日共1056组数据。实证结果表明：(1)螺纹钢期货价格和现货价格是一阶单整的非平稳序列；(2)螺纹钢期货价格和螺纹钢现货价格存在协整关系,即长期均衡关系；(3)螺纹钢期货价格和现货价格存在双向引导关系,但期货市场比现货市场更具有信息优势；(4)期货价格处于主导地位,但其引导作用发挥力度不强,市场有待继续完善。量化交易采取短线交易模式。短线交易对时间没有明确定义,可以是几天、几小时或几分钟。本文限定为5分钟的短线交易。样本数据从2014年1月27日9：00到2014年3月11日15：00。实证采用的研究方法：K线分析技术法和技术指标法。技术指标法包含趋势型技术指标MACD和MA以及震荡型技术指标KDJ和RSI；实证使用工具为Matlab软件。策略设计思路分两步：第一步,双指标组合策略设计。对每一个指标的不同参数进行组合寻找最优参数组,例如,移动平均线MA有五日均线、十日均线、十五日均线等等；之后,对不同周期均线进行两两组合,比较各组合的盈利率、赢利情况等确定最佳参数。第二步,四指标组合策略设计。将第一步得到的最优参数组分别设定为各指标的默认参数,并对修改后的指标进行共振叠加操作。交易策略结果表明：指标组合的资金利用率以及资金回报率都要高于单个指标单独使用,且四指标组合策略在保持高盈利率的同时,能降低最大盈利率和最大亏损率,使得收益风险比率保持较高水平。
[Abstract]:Rebar futures since March 27, 2009 officially listed on the Shanghai futures exchange by market investors. However, the relatively mature domestic futures (agricultural futures, futures), steel futures listed in short time, is still in the early stages of development. Therefore, the study on the function of the futures market can effectively play is of practical significance.
The basic function of futures market is divided into two categories: the discovery function of hedging and price. The price discovery function is the basis for the existence and development of the futures market, the spot market is the basic premise to guide the futures market. The futures market price discovery effectiveness function can be used to evaluate the efficiency of the futures market. At the same time, China in the rapeseed oil, palm oil and other commodity futures market after the launch of metal futures, strengthen the futures market and stock market and spot market interaction. Investors can through the futures market, the stock market and spot market hedging can also risk speculation in the futures market. The market provides a strong foundation for the rapid development of the futures market and the expansion of the financial derivatives market for quantitative trading in the futures market. Using quantitative trading will be market investors, especially the machine An important direction for the development of investors.
This paper is divided into two parts: the first part, study on the rebar futures price discovery function of the validity test, the steel futures market price in China Shanghai futures exchange discovery; the second part quantitative trading model of steel futures 5 minutes of data, using Matlab simulation function model simulation analysis for quantitative trading the optimal strategy.
Among them, the steel futures market price discovery function includes study approaches: ADF unit root test, VAR model, cointegration test, vector error correction model, EG two step test, Grainger causality test and variance decomposition; empirical tool for Eviews software. The selected data for rebar futures daily the closing price data, the sample interval removed five months after the listing of thread steel, from September 1, 2009 to March 2014 10 a total of 1056 sets of data. The empirical results show that: (1) steel futures prices and spot prices is a single whole non-stationary sequence; (2) there is a cointegration relationship and steel rebar futures prices the spot price, namely the long-term equilibrium relationship; (3) there is a bi-directional leading relationship steel futures prices and spot prices, but the futures market has more advantages than the spot market information; (4) futures price is the main To guide the position, but its guiding role is not strong, the market needs to be continued to improve.
Quantitative trading to take short-term trading patterns. Short-term trading does not have a clear definition on time, can be a few days, a few hours or minutes. This paper is limited to 5 minutes of short-term trading. Methods from January 27, 2014 to March 11, 2014 by the 9:00 15:00. empirical sample data: K-line analysis technique method and technical index method. Technology index contains the trend type MACD and MA technical indicators and the shock type technical index of KDJ and RSI; the use of empirical tools for Matlab software. The strategy design is divided into two steps: the first step, two index strategy design. Combined to find the optimal parameters for different array parameters for each of the parameters such as the moving average MA five day moving average ten, on average, fifteen day moving average and so on; after 22 combinations in different period average, compared with each combination of profit rate, profit and determine the optimal parameters. The second step, four index The combination strategy design. The optimal parameters were obtained by the first step were set as the default parameters of each index, and resonance overlay operation on the revised index. The results show that the use of funds trading strategy index combination ratio and capital return rate is higher than the single indicator used alone, and the four index combination strategy to maintain high profit the interest rate at the same time, can reduce the maximum profit rate and the maximum loss rate, the income risk ratio remained at a high level.

【学位授予单位】：江西财经大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F224;F724.5

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