(T_S_R)range2-

mt4版 新版黄蝴蝶 源码 参考文档设置(MT4 version of the new yellow butterfly source code)

股票数据与matlab环境接口构建，主要用于数据处理(Stock data interfaces with the matlab environment to build, mainly for data processing)

美亚式期权定价 使用蒙特卡洛数值模拟方法，对美亚式期权进行定价(Asian option pricing)

在MT4软件统计历史交易盈亏情况的脚本，比较实用的小功能(In the MT4 trading profit and loss situation software statistical history of the script, more practical small features)

使用财务工具箱产生列联表，小范例以矩阵表示(The use of financial toolbox generate contingency table, the small sample to matrix)

模拟ATM取款机，单机版的，自己做的小程序 希望对大家又帮助(Simulation standalone ATM machines)

增加excel表中股票代码导入文本代码与行情功能(The increase of Excel stock code table import text code and market function )

多因子模型构建。多因子模型是量化选股中最重要的一类模型，其基本思想就是找到某些和收益率最相关的指标。并根据该指标，构建一个股票组合，期望该组合在未来的一段时间跑赢或者跑输指数。如果跑赢，则可以做多该组合，同时做空期指，赚取正向阿尔法收益；如果是跑输，则可以做多期指，融券做空该组合，赚取反向阿尔法收益。多因子模型的关键是找到因子与收益率之间的关联性。(Multi-Factor Model. Multi-factor stock selection model is to quantify the most important class of models, the basic idea is to find some of the most relevant and profitability indicators. And based on the index, to build a stock portfolio, expect the combination index outperformed or underperformed for some time in the future. If outperform, you can do more than this combination, but short of that, to earn positive alpha income if it is underperforming, you can do more than futures, short selling short the combination to earn a reverse alpha returns. Key multi-factor model is to find correlation between factors and yields.)

说明：  利用Python进行量化投资详细教程，从Python基础知识到经典量化投资策略与量化模型。(Use Python for a detailed tutorial on quantitative investment, from Python basic knowledge to classic quantitative investment strategies and models.)

做时间序列预测的svm程序,matlab编的，多种时间序列预测模型(Time series prediction svm program, matlab code, and a variety of time-series forecasting model )