Pandas-Market-Predictor 1.0.6

Pandas Market Predictor, is a deep learning API written in Python on top of Panda that helping you predict future price (low and high), trend of Financial market assets.

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 :

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 :

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 ?

  Level = MyMarketPredictor.Support_Resistance_Estimation_Tool(Indicators)
  print("Support Level :",Level['Support'])
  print("Resistance Level :",Level['Resistance'])

Result :

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 ?

  
  # 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" )

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 ?

  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" )

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

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Support

You can ask questions and join the development discussion:

• Facebook page .

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