def run():
config = ConfigParser()
config.read('./config.ini')
API_KEY = config['ALPACA']['API_KEY']
SECRET_KEY = config['ALPACA']['SECRET_KEY']
api = REST(key_id=API_KEY, secret_key=SECRET_KEY)
GOOGLE_SA_PATH = './service_account.json'
assert os.path.exists(
GOOGLE_SA_PATH
), "Unable to locate Google Sheets service account credentials"
#Google Sheets Auth
gs = auth(GOOGLE_SA_PATH)
#Get params from Sheets
params = {
row[0]: row[1]
for row in
get_range(gs, config['SHEETS']['SPREADSHEET_ID'], config['SHEETS']
['PARAM_SHEET'], config['SHEETS']['PARAM_RANGE'])
}
#Read params into variables
POWER = try_cast(params['POWER'], float, 1 / 3)
PERCENT_HOLD = try_cast(params['PERCENT_HOLD'], float, 1 / 20)
df = pd.DataFrame(get_range(gs, config['SHEETS']['SPREADSHEET_ID'],
config['SHEETS']['STOCK_SHEET'],
config['SHEETS']['STOCK_RANGE']),
columns=['Symbol', 'Name', 'Price', 'Market Cap'])
#Convert string numbers into floats
df['Price'] = df['Price'].str.replace(',',
'').str.replace('$',
'').astype(np.double)
df['Market Cap'] = df['Market Cap'].str.replace(',', '').str.replace(
'$', '').astype(np.double)
#Get cash available to trade
buying_power = get_buying_power(api) * (1 - PERCENT_HOLD)
#Get currently held positions
positions = get_positions(api)
df = df.merge(positions, on='Symbol',
how='left').fillna('0').astype({'Total Value': np.double})
df['Derived Percentage'] = np.power(df['Market Cap'], POWER) / np.power(
df['Market Cap'], POWER).sum()
df['Current Percentage'] = df['Total Value'] / df['Total Value'].sum()
df['Transaction Percentage'] = df['Derived Percentage'] - df[
'Current Percentage']
df = df[df['Transaction Percentage'] > 0]
df['Purchase Value'] = (df['Transaction Percentage'] /
df['Transaction Percentage'].sum()) * buying_power
api.cancel_all_orders()
for r in df[df['Purchase Value'] > 5].to_dict(orient='records'):
put_fractional_order(api, r['Symbol'], r['Purchase Value'], 'buy')
df = df.merge(positions, on='Symbol',
how='left').fillna('0').astype({'Total Value': np.double})
df['Derived Percentage'] = np.power(df['Market Cap'], POWER) / np.power(
df['Market Cap'], POWER).sum()
df['Current Percentage'] = df['Total Value'] / df['Total Value'].sum()
df['Transaction Percentage'] = df['Derived Percentage'] - df[
'Current Percentage']
df = df[df['Transaction Percentage'] > 0]
df['Purchase Value'] = (df['Transaction Percentage'] /
df['Transaction Percentage'].sum()) * buying_power
print_df(df)
if MAKE_TRADES:
api.cancel_all_orders()
for r in df[df['Purchase Value'] > 1].to_dict(orient='records'):
print(r['Symbol'])
data = {
"symbol": r["Symbol"],
"notional": r["Purchase Value"],
"side": "buy",
"type": "market",
"time_in_force": "day"
}
# r = api._request('POST', '/orders', data=data)
if LOG_POSITIONS:
df['Date'] = date.today()
# log_positions_to_s3(positions, S3_BUCKET_NAME, LOGGING_PATH, overwrite=True)