Pandas_Market_Predictor-1.0.6.tar.gz

# Pandas Market Predictor  Pandas Market Predictor, is a deep learning API written in Python on top of Panda that helping you predict future price (low and min), trend of Financial market assets. ## About Pandas Market Predictor Pandas Market Predictor , is a Technical Analysis API written in Python. It was developed with a focus on enabling fast experimentation. *Being able to go from idea to result as fast as possible is key to doing good research.* Pandas Market Predictor is: - **Simple** - **Flexible** - **Powerful** ## First contact with Pandas Market Predictor The core data structures of Pandas Market Predictor are __Historical Market Data__ and __Technical Indicator__ . A sample Data Set should be : | Open | High | Low | Close | Volume | Indicator1 | Indicator2 | |-----:|------:|----:|-----:|-------:|-----------:|-----------:| |0.93767|0.93791|0.93618|0.9363|69414.0|0.9363860952540013|0.9365316260340849| |0.9363|0.93764|0.93566|0.93666|23461.0|0.936477396836001|0.9365549667551604| |0.93666|0.93798|0.93561|0.93724|26907.0|0.9367315978906674|0.936679518254222| You can build your data set by using Pandas-TA lib : https://github.com/twopirllc/pandas-ta For installation run : ``` pip install Pandas-Market-Predictor ``` ## About Feature ### I.Trend Detection The trend detection purpose is to help you find the most probable Future Market Trend on basis of your indicator : ````python from Pandas_Market_Predictor import Pandas_Market_Predictor import pandas as pd if __name__ == "__main__" : # Firt we read the specified data using pandas df = pd.read_csv('dataset.csv') df = df.dropna(axis=0) # Data cleaning # Create predictor MyMarketPredictor = Pandas_Market_Predictor(df) # Predict Trend Indicators = ["Indicator1","Indicator2"] TREND = MyMarketPredictor.Trend_Detection(Indicators,10) # 10 is the percentage of standard Deviation to detect print(MyMarketPredictor.PERCENT_STD) # Print the value of standard deviation percentage #Printing the result print("Buy Trend :",TREND['BUY']) print("Sell Trend :",TREND['SELL']) ```` Result : ```console foo@bar:~$ python test.py Buy Trend : 0 Sell Trend : 0 ``` ### II.The Support Resistance Estimation Tool The Support Resistance Estimation Tool is as his name indicate permit to estimate the Low and High of an asset The question is : What is the standard deviation for an up or down trend given the level of indicator that we have for the current period ? ````python Level = MyMarketPredictor.Support_Resistance_Estimation_Tool(Indicators) print("Support Level :",Level['Support']) print("Resistance Level :",Level['Resistance']) ```` Result : ```console Support Level : 146.42515227768754 Resistance Level : 147.38794619755853 ``` #### UPTREND EXEMPLE  ### III.The RISK MANAGEMENT TOOL Even if you make very good prediction and having right 99% of time. The 1% Risk could append a day and reduce all your profit to néant so you need to have a good risk reward management. Risk is about 2 things : #### 1. Determine at witch price your setup is invalide ? ````python # Risk Reward Ratio 1 / 3 mean i need to won 1 trade over 3 for being profitable RISK_REWARD_RATIO = 1 / 3 # Stop Loss Calculation Exemple for Up & Down Trend Stop_Loss_Up = MyMarketPredictor.STOP_LOSS_CALCULATOR("UP",Level['Support'],Level['Resistance'],RISK_REWARD_RATIO ) # For Up Trend Stop_Loss_Down = MyMarketPredictor.STOP_LOSS_CALCULATOR("DOWN",Level['Support'],Level['Resistance'],RISK_REWARD_RATIO ) # For Up Down # Printing Result print("The Stop Loss Level for up Trend is", Stop_Loss_Up , "for",RISK_REWARD_RATIO ,"RISK_REWARD_RATIO" ) print("The Stop Loss Level for down Trend is", Stop_Loss_Down , "for",RISK_REWARD_RATIO ,"RISK_REWARD_RATIO" ) ```` ```console The Stop Loss Level for up Trend is 146.10422097106388 for 0.3333333333333333 RISK_REWARD_RATIO The Stop Loss Level for down Trend is 147.7088775041822 for 0.3333333333333333 RISK_REWARD_RATIO ``` #### 2. Determine at witch price to exit ? ````python Trade_Efficiency_Factor = 1 - RISK_REWARD_RATIO Take_Profit_Up = MyMarketPredictor.Take_Profit_CALCULATOR("UP",Level['Support'],Level['Resistance'],Trade_Efficiency_Factor) Take_Profit_Down = MyMarketPredictor.Take_Profit_CALCULATOR("UP",Level['Support'],Level['Resistance'],Trade_Efficiency_Factor) print("The Take Profit Level for up Trend is", Take_Profit_Up , "for",Trade_Efficiency_Factor ,"Trade_Efficiency_Factor" ) print("The Take Profit Level for down Trend is", Take_Profit_Down , "for",Trade_Efficiency_Factor ,"Trade_Efficiency_Factor" ) ```` ```console The Take Profit Level for up Trend is 147.06701489093487 for 0.6666666666666667 Trade_Efficiency_Factor The Take Profit Level for down Trend is 147.06701489093487 for 0.6666666666666667 Trade_Efficiency_Factor ``` --- ## Support You can ask questions and join the development discussion: - [Facebook page](https://www.facebook.com/globalanalysistech) . ---