scorecalc.py

# The code in this file calculates the 'score' the algorithm attributes to each company
# based on a normal distribution curve. This data is then used by the 'main.py' file
# to make the decision on whether to buy the company or not

from math import exp, sqrt, pi
from quant import *
from apikeys import *

def standardized_normal_dist(x : float, std : float, mean : float):
    """Returns the normal place of x in a normal distribution curve whose standard
       variation and expected value are passed as parameters."""
    peak_val = (1/sqrt(2 * pi * (std**2))) * exp(-((mean - mean)**2/(2 * std**2)))
    return ((1/sqrt(2 * pi * (std**2))) * exp(-((x - mean)**2/(2 * std**2))))/peak_val

def liabilities_to_equity_score(balance_sheet : dict):
    """Returns the score attributed to a company's liabilities to equity ratio."""
    val = liabilities_to_equity(balance_sheet)
    return standardized_normal_dist(val, 0.425, 1.0)

def liabilities_to_capital_score(balance_sheet : dict):
    """Returns the score attributed to a company's liabilities to capital ratio."""
    val = liabilities_to_capital(balance_sheet)
    return standardized_normal_dist(val, 0.128, 0.45)

def assets_to_equity_score(balance_sheet : dict):
    """Returns the score attributed to a company's assets to equity ratio."""
    val = assets_to_equity(balance_sheet)
    return standardized_normal_dist(val, 0.5, 1.5)

def debt_to_ebitda_score(balance_sheet : dict, income_statement : dict):
    "Returns the score attributed to a company's debt to EBITDA ratio."
    val = debt_to_ebitda(balance_sheet, income_statement)
    return standardized_normal_dist(val, 0.425, 1)

def quick_ratio_score(balance_sheet : dict):
    """Returns the score attributed to a company's quick ratio."""
    val = quick_ratio(balance_sheet)
    return standardized_normal_dist(val, 0.213, 1.0)

def current_ratio_score(balance_sheet : dict):
    """Returns the score attributed to a company's current ratio."""
    val = current_ratio(balance_sheet)
    return standardized_normal_dist(val, 0.213, 1.0)

def ten_yr_opex_growth_score(income_statement : dict):
    """Returns the score attributed to a company's 10-year operating expenses growth"""
    val = ten_yr_operating_expenses_growth(income_statement)
    return standardized_normal_dist(val, 34, 120)

def ten_yr_assets_growth_score(balance_sheet : dict):
    """Returns the score attributed to a company's 10-year assets growth"""
    val = ten_yr_assets_growth(balance_sheet)
    return standardized_normal_dist(val, 150, 125)

def ten_yr_liabilities_growth_score(balance_sheet : dict):
    """Returns the score attributed to a company's 10-year liabilities growth"""
    val = ten_yr_liabilities_growth(balance_sheet)
    return standardized_normal_dist(val, 100, 95)

def ten_yr_cash_flow_growth_score(cash_flow : dict):
    """Returns the score attributed to a company's 10-year cash flow growth"""
    val = ten_yr_cash_flow_growth(cash_flow)
    return (standardized_normal_dist(val, 1000, 259.37)) / (7.7358 / (0.01 * val))

def ten_yr_share_count_growth_score(balance_sheet : dict):
    """Returns the score attributed to a company's 10-year share count growth"""
    val = ten_yr_share_count_growth(balance_sheet)
    return (standardized_normal_dist(val, 1000, 259.37)) / (7.7358 / (0.01 * val))