Test with Clairvoyance

clairvoyance.py

from clairvoyant import Backtest
from pandas import read_csv
from nsepy import get_history
from datetime import date

# Testing performance on a single stock

variables  = []     # Financial indicators of choice # "SSO", "SSC"
trainStart = '2013-03-01'       # Start of training period
trainEnd   = '2015-07-15'       # End of training period
testStart  = '2015-07-16'       # Start of testing period
testEnd    = '2016-07-16'       # End of testing period
buyThreshold  = 0.65            # Confidence threshold for predicting buy (default = 0.65)
sellThreshold = 0.65            # Confidence threshold for predicting sell (default = 0.65)
C = 1                           # Penalty parameter (default = 1)
gamma = 10                      # Kernel coefficient (default = 10)
continuedTraining = False       # Continue training during testing period? (default = false)



history = get_history(symbol="SBIN",
                      start=date(2013, 1, 1),
                      end=date(2017, 1, 1),
                      index=False)

history[['Open','High','Low','Close','Volume','Close']].to_csv("sbin.csv")



backtest = Backtest(variables, trainStart, trainEnd, testStart, testEnd)
data = read_csv("sbin.csv")      # Read in data
data = data.round(3)                    # Round all values
backtest.stocks.append("sbin")          # Inform the model which stock is being tested
for i in range(0,10):                   # Run the model 10-15 times
    backtest.runModel(data)