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1.01 经典模型之 - SMA移动平均&双均线模型.ipynb
1.01 经典模型之 - SMA移动平均&双均线模型.ipynb
 
 
1.02 经典模型之 - 动量策略.ipynb
1.02 经典模型之 - 动量策略.ipynb
 
 
1.03 经典模型之 - 反转策略.ipynb
1.03 经典模型之 - 反转策略.ipynb
 
 
1.04 经典模型之 - 配对交易Pair Trading - Time Series Stationary.ipynb
1.04 经典模型之 - 配对交易Pair Trading - Time Series Stationary.ipynb
 
 
2.01 基于经典技术分析指标CCI的交易策略.ipynb
2.01 基于经典技术分析指标CCI的交易策略.ipynb
 
 
2.02 基于经典技术分析指标Bollinger Band布林带的交易策略.ipynb
2.02 基于经典技术分析指标Bollinger Band布林带的交易策略.ipynb
 
 
2.03 基于双技术指标SMA+CCI过滤器交易系统.ipynb
2.03 基于双技术指标SMA+CCI过滤器交易系统.ipynb
 
 
2.04 基于K线形态锤子线的趋势跟踪策略及各类改进（TBD）.ipynb
2.04 基于K线形态锤子线的趋势跟踪策略及各类改进（TBD）.ipynb
 
 
2.05 基于KDJ指标交易比特币.ipynb
2.05 基于KDJ指标交易比特币.ipynb
 
 
3.01 趋势跟踪系统之 CTA_交易系统(Aberration)股票修改版.ipynb
3.01 趋势跟踪系统之 CTA_交易系统(Aberration)股票修改版.ipynb
 
 
3.02 趋势跟踪系统之 CTA_交易系统(Aberration)股票修改版-Modified on'601688'.ipynb
3.02 趋势跟踪系统之 CTA_交易系统(Aberration)股票修改版-Modified on'601688'.ipynb
 
 
3.03 对比均值回归_Mean Reverting Strategy on '601688'.ipynb
3.03 对比均值回归_Mean Reverting Strategy on '601688'.ipynb
 
 
4.01 机器学习算法基础-常用模型.ipynb
4.01 机器学习算法基础-常用模型.ipynb
 
 
4.02 机器学习策略V1.0—逻辑回归预测股市涨跌(算法转换：SVM) .ipynb
4.02 机器学习策略V1.0—逻辑回归预测股市涨跌(算法转换：SVM) .ipynb
 
 
4.03 机器学习策略V2.0—基于SVM回归算法预测股市收益率.ipynb
4.03 机器学习策略V2.0—基于SVM回归算法预测股市收益率.ipynb
 
 
5.01 Time bar, tick bar, volumn bar, dollar bar, imbalance bar, and dollar imbalance bars.ipynb
5.01 Time bar, tick bar, volumn bar, dollar bar, imbalance bar, and dollar imbalance bars.ipynb
 
 
5.011 fast_ewma.py
5.011 fast_ewma.py
 
 
5.02 Tick, Volume, Dollar Volume Bars- Exercised.ipynb
5.02 Tick, Volume, Dollar Volume Bars- Exercised.ipynb
 
 
Preq: 基本金融数据分析和处理.ipynb
Preq: 基本金融数据分析和处理.ipynb
 
 
README.md
README.md
 
 
data_merged.h5
data_merged.h5
 
 
index_data.csv
index_data.csv
 
 
north_data.csv
north_data.csv
 
 
result_df.csv
result_df.csv
 
 
北上资金布林带择时策略(Final).ipynb
北上资金布林带择时策略(Final).ipynb
 
 
北上资金布林带择时策略.ipynb
北上资金布林带择时策略.ipynb
 
 

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quantfinance

Quantitative finance and trading system development

Preq: Finantial data collection, storage, data cleaning, data preperation fundamentals

1.0s Classic models: SMA, Momentum, Reversal, Pair Trading Strategy

2.0s Technical Analysis Trading Systems: CCI, Bollinger Bands, Conbination of SMA & CCI, Hammer Shape Trading Systems(EMA MACD, KDJ etc.)

3.0s Trend Following System: A CTA modified Stock Aberration Trading System; Stock Universe:Trend Following VS Mean Reversal

4.0s Big Data & Machine Learning: NLP, Logistic, SVM, Random Forest, XGboost, CNN, etc.

5.0s Advances in Financial Machine Learning, Marcos Lopez de Prado Practices & Notes

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everything quantitative finance related

github.github.io/quantfinance

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