import pandas as pd
import pandas_datareader.data as web
import datetime

def returns(prices):
    """
    Calulates the growth of 1 dollar invested in a stock with given prices
    """
    return (1 + prices.pct_change(1)).cumprod()

def drawdown(prices):
    """
    Calulates the drawdown of a stock with given prices
    """
    rets = returns(prices)
    return (rets.div(rets.cummax()) - 1) * 100

def cagr(prices):
    """
    Calculates the Compound Annual Growth Rate (CAGR) of a stock with given prices
    """
    delta = (prices.index[-1] - prices.index[0]).days / 365.25
    return ((prices[-1] / prices[0]) ** (1 / delta) - 1) * 100


def sim_leverage(proxy, leverage=1, expense_ratio = 0.0, initial_value=1.0):
    pct_change = proxy.pct_change(1)
    pct_change = (pct_change - expense_ratio / 252) * leverage
    sim = (1 + pct_change).cumprod() * initial_value
    sim[0] = initial_value
    return sim

start = datetime.datetime(1977, 1, 1)
end = datetime.datetime(2020, 1, 1)

vfinx = web.DataReader("VFINX", "yahoo", start, end)["Adj Close"]
#upro = web.DataReader("UPRO", "yahoo", start, end)["Adj Close"]
upro_sim = sim_leverage(vfinx, leverage=3.0, expense_ratio=0.02).rename("UPRO Sim")

print("CAGRs")
print(f"SPY: {cagr(vfinx):.2f}%")
#print(f"UPRO: {cagr(upro):.2f}%")
print(f"UPRO_SIMULATED: {cagr(upro_sim):.2f}%")