import pandas as pd
import numpy as np

# FILE_LIST = ["aapl", "amgn", "ba", "dis", "intc", "ko", "mcd", "msft", "trv", "v"]
# for file in FILE_LIST:
df = pd.read_csv('OriginalData\\' + 'adx_balance.csv')

# 计算每日收益率 r_t = (P_t - P_{t-1}) / P_{t-1}
df['daily_return'] = df['balance_hybrid_without_adx'].pct_change()
print(df['daily_return'][0:500])

df = df.dropna()

def sharpe_ratio(returns, risk_free_rate=0.1):
    mean_return = np.mean(returns)
    print(mean_return)

    std_return = np.std(returns)
    print(std_return)
    sharpe_ratio = (mean_return - risk_free_rate) / std_return
    return sharpe_ratio

returns = df['daily_return'][0:500].values

risk_free_rate = 0.01

sharpe = sharpe_ratio(returns, risk_free_rate)

print(f"夏普率: {sharpe}")