import pandas as pd

import numpy as np

import requests

import math

from scipy.stats import percentileofscore as score

import xlsxwriter

from statistics import mean

from secrets import IEX_CLOUD_API_TOKEN

stocks = pd.read_csv('sp_500_stocks.csv')

symbol = 'AAPL'

api_url = f"https://sandbox.iexapis.com/stable/stock/{symbol}/stats?token={IEX_CLOUD_API_TOKEN}"

data = requests.get(api_url).json()

def chunks(lst, n):

for i in range(0, len(lst), n):

yield lst[i:i + n]

symbol_groups = list(chunks(stocks['Ticker'], 100))

symbol_strings = []

for i in range(0, len(symbol_groups)):

symbol_strings.append(','.join(symbol_groups[i]))

# make columns

my_columns = ['Ticker', 'Price', 'One-Year Price Return', 'Number of Shares to Buy']

# create empty dataframe with premade columns

final_dataframe = pd.DataFrame(columns = my_columns)

# call batch api to fill empty dataframe

for symbol_string in symbol_strings:

batch_api_call_url = F"https://sandbox.iexapis.com/stable/stock/market/batch?symbols={symbol_string}&types=price,stats&token={IEX_CLOUD_API_TOKEN}"

data = requests.get(batch_api_call_url).json()

for symbol in symbol_string.split(','):

final_dataframe = final_dataframe.append(

pd.Series(

[

symbol,

data[symbol]['price'],

data[symbol]['stats']['year1ChangePercent'],

'N/A'

],

index = my_columns),

ignore_index = True

)

# remove low-momentum stocks

# inplace modifies original dataframe

final_dataframe.sort_values('One-Year Price Return', ascending = False, inplace = True)

# resets index numbers to go from 0-49

final_dataframe.reset_index(inplace = True, drop = True)

def portfolio_input():

portfolio_size = input('Enter the size of your portfolio:')

portfolio_size = 1000000

position_size = float(portfolio_size)/len(final_dataframe.index)

for i in range(0, len(final_dataframe)):

final_dataframe.loc[i, 'Number of Shares to Buy'] = math.floor(position_size/final_dataframe.loc[i, 'Price'])

#print(final_dataframe[:50])

# identifying high quality momentum (hqm)

hqm_columns = [

]

hqm_dataframe = pd.DataFrame(columns = hqm_columns)

for symbol_string in symbol_strings:

batch_api_call_url = F"https://sandbox.iexapis.com/stable/stock/market/batch?symbols={symbol_string}&types=price,stats&token={IEX_CLOUD_API_TOKEN}"

data = requests.get(batch_api_call_url).json()

for symbol in symbol_string.split(','):

hqm_dataframe = hqm_dataframe.append(

pd.Series(

[

symbol,

data[symbol]['price'],

0.0,

data[symbol]['stats']['year1ChangePercent'],

0.0,

data[symbol]['stats']['month6ChangePercent'],

0.0,

data[symbol]['stats']['month3ChangePercent'],

0.0,

data[symbol]['stats']['month1ChangePercent'],

0.0,

0.0,

],

index = hqm_columns),

ignore_index = True

)

time_periods = [

]

# because some price return scores are None

for row in hqm_dataframe.index:

for time_period in time_periods:

change_col = f'{time_period} Price Return'

percentile_col = f'{time_period} Return Percentile'

if hqm_dataframe.loc[row, change_col] == None:

hqm_dataframe.loc[row, change_col] = 0.0

for row in hqm_dataframe.index:

for time_period in time_periods:

change_col = f'{time_period} Price Return'

percentile_col = f'{time_period} Return Percentile'

hqm_dataframe.loc[row, percentile_col] = score(hqm_dataframe[change_col], hqm_dataframe.loc[row, change_col])/100

for row in hqm_dataframe.index:

momentum_percentiles = []

for time_period in time_periods:

momentum_percentiles.append(hqm_dataframe.loc[row, f'{time_period} Return Percentile'])

hqm_dataframe.loc[row, 'HQM Score'] = mean(momentum_percentiles)

# creating HQM score column

hqm_dataframe.sort_values('HQM Score', ascending = False, inplace = True)

hqm_dataframe = hqm_dataframe[:50]

hqm_dataframe.reset_index(inplace = True, drop = True)

position_size = float(portfolio_size)/len(hqm_dataframe.index)

for i in hqm_dataframe.index:

hqm_dataframe.loc[i, 'Number of Shares to Buy'] = math.floor(position_size/hqm_dataframe.loc[i, 'Price'])

# making excel document

writer = pd.ExcelWriter('momentum_strategy.xlsx', engine = 'xlsxwriter')

hqm_dataframe.to_excel(writer, sheet_name = 'Momentum Strategy', index = False)

background_color = '#0a0a23'

font_color = '#ffffff'

# dictionaries for formatting

string_format = writer.book.add_format(

)

dollar_format = writer.book.add_format(

)

integer_format = writer.book.add_format(

)

percent_format = writer.book.add_format(

)

# dictionary for excel columns

column_formats = {

}

# formats excel sheet

for column in column_formats.keys():

writer.sheets['Momentum Strategy'].set_column(f'{column}:{column}', 25, column_formats[column][1])

writer.sheets['Momentum Strategy'].write(f'{column}1', column_formats[column][0], column_formats[column][1])

writer.save()