趋势网格

说明：  原创，布林通道的自动交易EA，运用布林线做了一个通道，价格上穿时卖出，价格下穿时买入，加入了几款过滤器(Originally, the automatic trading EA of Brin Channel, which uses Brin Line to make a channel, sells when the price goes up, buys when the price goes down, and adds several filters.)

计算20天平均价，高开低收价，一个单独的方框表示(Calculate the average price of 20 balances, raise the price lower and lower the price.)

ISO8583包（简称8583包）是一个国际标准的包格式，最多由128个字段域组成，每个域都有统一的规定，并有定长与变长之分。8583包前面一段为位图，用来确定包的字段域组成情况。(The ISO8583 package (8583 pack) is an international standard format, and up to 128 field domain, each domain has a unified, and the fixed length and variable length of. 8583 package in front of a bitmap, used to determine the composition of the field.)

MT4 Expert Advisor for auto trading

mt4ea,，自动交易程序,使用vps可以实现24小时不间断交易.(Mt4ea, automated trading program, use the VPS can realize 24-hour trading.)

说明：  只需要挂在美加一分钟就行 无需风控，系统根据两个货币的关系进行止损 止盈(It only needs to hang in the US and Canada for one minute without wind control. The system stops losses and stops earnings according to the relationship between the two currencies.)

说明：  MT4一款头i皮EA,单量大准确率高，不存在爆仓！！(MT4 is a scalp EA, with high accuracy and large volume, and no explosion!!)

自定义MACD指标，应用于外汇市场或者股票证券期货的技术指标。(The custom MACD index is applied to the technical indicators of the foreign exchange market or stock securities futures.)

GARCH模型的matlab程序，使用最大似然估计方法进行参数估计(The matlab program of the GARCH model uses maximum likelihood estimation to estimate the parameters.)

经验模态分解（Empirical Mode Decomposition，简称EMD))方法被认为是2000年来以傅立叶变换为基础的线性和稳态频谱分析的一个重大突破?，该方法是依据数据自身的时间尺度特征来进行信号分解，无须预先设定任何基函数。 该方法的关键是经验模式分解，它能使复杂信号分解为有限个本征模函数（Intrinsic Mode Function，简称IMF），所分解出来的各IMF分量包含了原信号的不同时间尺度的局部特征信号。经验模态分解法能使非平稳数据进行平稳化处理，然后进行希尔伯特变换获得时频谱图，得到有物理意义的频率。(The Empirical Mode Decomposition (EMD) method is considered as a major breakthrough in the linear and steady state spectrum analysis based on Fu Liye transform in 2000. The method is based on the time scale characteristics of the data itself to decompose the signal without setting any base functions in advance. The key of this method is the empirical mode decomposition, which can decompose the complex signal into a limited eigenmode function (Intrinsic Mode Function, for short, IMF), and the decomposed IMF components include the local characteristic signals of the different time scales of the original signal. The empirical mode decomposition method can smooth the non-stationary data, and then obtain the time-frequency spectrum by Hilbert transform to get the physical meaning frequency.)