Nifty200_top10_ranking_strategy

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import yfinance as yf

import pandas as pd

# Download historical data

df = yf.download(stocks.to_list(), start='2022-08-01')

df_close = df['Adj Close']

df_dret = df_close.pct_change()

df_wret = (df_dret + 1).resample('W').prod() - 1

df_mret = (df_dret + 1).resample('M').prod() - 1

# Calculate 12-month rolling returns

df_mret_12 = df_mret.rolling(12).apply(lambda x: (x + 1).prod() - 1).dropna()

print('month wise : \n',df_mret_12.iloc[:,0])

# Calculate 55 weeks rolling return

df_wret_55 = df_wret.rolling(55).apply(lambda x: (x + 1).prod() - 1).dropna()

print('week wise :\n',df_wret_55.iloc[:,0])

# Calculate 252-days rolling return

df_dret_252 = df_dret.rolling(252).apply(lambda x: (x + 1).prod() - 1)

print('day wise :\n',df_dret_252.iloc[:,0:2])

m_top10 = df_mret_12.iloc[-2:].apply(lambda row: row.nlargest(10), axis=1)

print('top 10 with date ',m_top10.index[0],'\n')

print(m_top10.iloc[0].sort_values(ascending=False).dropna(axis=0))

print('top 10 with date ',m_top10.index[1],'\n')

print(m_top10.iloc[1].sort_values(ascending=False).dropna(axis=0))

Result: