raposatech

class MultiSignalStarterSystem:
  '''
  Upgraded Start System using multiple entry rules. Adapted from Rob Carver's
  Leveraged Trading: https://amzn.to/3C1owYn
  '''
  def __init__(self, ticker: str, signals: dict, target_risk: float = 0.12,
               stop_loss_gap: float = 0.5, starting_capital: float = 1000,
               margin_cost: float = 0.04, short_cost: float = 0.001,
               interest_on_balance: float = 0.0, start: str = '2000-01-01', 
               end: str = '2020-12-31', shorts: bool = True, weights: list = [],

raposatech

# MultiSignalStarterSystem available here: 
# https://gist.github.com/raposatech/2d9f309e2a54fc9545d44eda821e29ad#file-starter_system_mult_sigs-py

class ContinuousStarterSystem(MultiSignalStarterSystem):
    '''
    Carver's Starter System without stop losses and multiple entry rules.
    Adapted from Rob Carver's Leveraged Trading: https://amzn.to/3C1owYn
    '''
    def __init__(self, ticker: str, signals: dict, target_risk: float = 0.12,
                starting_capital: float = 1000, margin_cost: float = 0.04,

raposatech

class ForecastStarterSystem(ContinuousStarterSystem):
    '''
    Carver's Starter System without stop losses, multiple entry rules, and
    a forecast for position sizing and rebalancing.
    Adapted from Rob Carver's Leveraged Trading: https://amzn.to/3C1owYn
    
    ContinuousStarterSystem class defined here:
    https://gist.github.com/raposatech/49ccc66f5c312f939f8826251c55a676
    '''
    def __init__(self, ticker: str, signals: dict, target_risk: float = 0.12,

raposatech

class DiversifiedStarterSystem(MultiSignalStarterSystem):
    '''
    Carver's Starter System without stop losses, multiple entry rules,
    a forecast for position sizing and rebalancing, and multiple instruments.
    Adapted from Rob Carver's Leveraged Trading: https://amzn.to/3C1owYn
    
    Code for MultiSignalStarterSystem available here:
    https://gist.github.com/raposatech/2d9f309e2a54fc9545d44eda821e29ad    
    '''
    def __init__(self, tickers: list, signals: dict, target_risk: float = 0.12,

raposatech

class AlpacaStarterSystem(DiversifiedStarterSystem):
    '''
    Carver's Starter System without stop losses, multiple entry rules,
    a forecast for position sizing and rebalancing, and multiple instruments.
    Adapted from Rob Carver's Leveraged Trading: https://amzn.to/3C1owYn
    
    Allows live trading via the Alpaca API.
    
    DiversifiedStarterSystem found here:
    https://gist.github.com/raposatech/d3f10df41c8745b00cb608bd590a986d

raposatech

from argparse import ArgumentParser
from decouple import config

from starter_system import AlpacaStarterSystem

# Import Keys
KEY = config('ALPACA_PAPER_API_KEY')
SECRET = config('ALPACA_PAPER_SECRET')
URL = config('ALPACA_PAPER_URL')

raposatech

# A few helper functions
def calcReturns(df):
  # Helper function to avoid repeating too much code
  df['returns'] = df['Close'] / df['Close'].shift(1)
  df['log_returns'] = np.log(df['returns'])
  df['strat_returns'] = df['position'].shift(1) * df['returns']
  df['strat_log_returns'] = df['position'].shift(1) * \
    df['log_returns']
  df['cum_returns'] = np.exp(df['log_returns'].cumsum()) - 1
  df['strat_cum_returns'] = np.exp(

raposatech

from collections import deque

class PSAR:
  '''
  Calculates the Parabolic Stop-and-Reverse (PSAR) indicator for trading.
  Find the full explanation here:
  https://raposa.trade/blog/the-complete-guide-to-calculating-the-parabolic-sar-in-python/
  '''

  def __init__(self, init_af=0.02, max_af=0.2, af_step=0.02):