MT4编程手册技术大全

说明：  很出名的交易系统，原理是利用价格超卖超买和最近最高最低价格来进行判断交易信号，同时再入场的信息也可以自己设置，我附上了源码，大家也可以在源码中增加自己的交易筛选信号提高正确率和盈利率。(Well-known trading system, the principle is to use price oversold and overbought and the latest highest and lowest price to judge the trading signal, while re-entry information can also be set by itself, I attached the source code, you can also add their own trading screening signal in the source code to improve the accuracy and profitability.)

说明：  建议参数调成10，我主要用这个指标配合MAcD和均线做恒指，效果挺好。(It is suggested that the parameter be adjusted to 10. I mainly use this index with MAcD and mean line as the constant finger. The effect is good.)

银行使用的8583算法，使用者可以直接使用(8583 algorithms used by banks)

说明：  平台：Metatrader4 货币对：EURUSD 、GBPUSD 时间范围：30分 资金起点只要1000美金就可以跑，有实盘记录10个月竟然没有爆仓,以3.5%的超低回撤率，净盈利200%，月均收益20%，,实属罕见的马丁EA无需绑定任何VPS，不限电脑账号和时间。 在附件，由2019.01.01到2020.09.01的20个月EurUsd交易回测当中，可发现营利超过 180%，平均月营利约有 9% 以上，但在新冠肺炎疫情期间，有如金融风暴海啸的冲击，浮动亏损也相当大。建议使用者在重大天灾地变事件期间，最好停止运营，以策安全。(Platform: metatrader4 Currency pairs: EURUSD, GBPUSD Time frame: 30 minutes The starting point of capital is only 1000 US dollars. There is a record of real offer, but there is no position explosion in 10 months. With an ultra-low withdrawal rate of 3.5%, the net profit is 200%, and the average monthly income is 20%. Martin EA is really rare. It does not need to bind any VPS, and does not limit computer account and time. In the annex novel coronavirus pneumonia transaction from 2019.01.01 to 2020.09.01, 20 months of EurUsd trading return test revealed that profits were over 180%, and average monthly profit was more than 9%. However, during the new crown pneumonia outbreak, there was a large floating loss as a result of the financial storm and tsunami. It is suggested that users should stop operation during major natural disasters to ensure safety.)

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

stata命令，一般主成分分析均使用SPSS，很少有人使用功能更为强大的stata进行，主要是因为对于经管类学生来说，编程是一件不太容易的事情，本文档可以直接替换研究所使用的变量，即可得到主成分分析结果。(Stata command, general principal component analysis using SPSS, few people use a more powerful Stata, mainly because for the management class, programming is a difficult thing, this document can directly replace the variable used by the research, can get the result of the principal component analysis.)

波动率追踪, 数据储存读取，多种模型计算历史波动率等等， GARCH模型应用(Volatility tracker, Historical volatility calculation, Garch model application)

vs2017 MFC 期货 CTP API 开发示例， 带界面(vs2017 MFC CTP API CTP API)

实现简单的存取功能，代码精炼，值得研究自编，大家支持一下(To achieve a simple access, self-compiled, we support what)

在EVIEWS中用GARCH模型算VaR(在值风险)，计算failure rate，和做LRuc检测。(Var failure rate LRuc)