搜索资源列表
BP_ZXF
- Stock data prediction model based on three layer BP neural network
股票预测
- 基于神经网络的股票价格预测的MATLAB实现，经网络的在实际预测模型中的问题(MATLAB implementation of stock price prediction based on neural network and problems in the actual forecasting model via network)
基于MATLAB的股票指数预测算法仿真
- 这个是基于MATLAB的股票指数预测算法仿真，里边含有实例和coding(This is a MATLAB based simulation of the stock index prediction algorithm, which contains an instance and a coding)
Forecast and Stock_timeSeries
- 利用灰色预测公司的利润；基于时间序列的股票价格预测(Profit from the grey Forecast Ltd; stock price prediction based on time series)
基于SVM的回归预测分析——上证指数开盘指数预测
- 基于SVM的回归预测分析——上证指数开盘指数预测(SVM Based Regression Prediction Analysis - Shanghai Stock Exchange Index Opening Index Forecast)
基于MATLAB神经网络的股票价格预测
- 基于MATLAB做的神经网络的股票价格预测算法。(Stock price prediction algorithm based on MATLAB neural network.)
08神经网络逼近股票收盘均价2
- python演示神经网络来逼近股价走势的预测，基于时间序列的预测(Python demonstrates neural network to approximate the prediction of stock price trend, based on time series prediction)
arima
- 通过一段ARIMA模型程序来预测股票上证指数(Prediction of Shanghai Stock Index by an ARIMA Model Program)
R
- 金融时间序列分析上证指数的GARCH模型R语言代码，可用于研究股票的波动性和预测。(The GARCH model R language code of the Shanghai Stock Exchange Index for financial time series analysis can be used to study the volatility and prediction of stocks.)
dlstock_predict
- 预测股票价格与成交价格 等多种因素的关系，通过python和神经网络实现预测(prediction the stock price)
小波变换和混沌理论在股市预测中的应用
- 应用小波变换和混沌理论相结合的方法对股票市场进行预测 ,即先对股指时序进行小波分解 ,然后对分解得到的高、低频部分分别进行混沌预测 ,再将预测的结果进行小波重构 ,得到原时序的预测结果。 在此基础上应用小波和混沌理论提出进一步提高预测精度的方法 ,即通过对高频部分再进行小分解、混沌预测和小波重构而使高频部分的预测精度得以提高 ,进而提高原始时序的预测精度。(The method of combining wavelet transform and chaos theory is used to
VaR
- 主要是用来风险预测评估，对于股票的收益率的趋势进行一个估计(It is mainly used for risk prediction and evaluation, and for estimating the trend of stock return)
股票市场预测
- LSTM 作为预测模型，使用贝叶斯优化算法来实现股票预测的功能(LSTM as a prediction model, uses Bayesian optimization algorithm to achieve the function of stock forecasting)