def all_alpaca_assets(client: alpaca_trade_api.REST) -> list:
return [_.symbol for _ in client.list_assets()]
def select_day_trade_stocks(event, context):
# Get Alpaca API key and secret
storage_client = storage.Client()
bucket = storage_client.get_bucket('derek-algo-trading-bucket')
blob = bucket.blob('alpaca-api-key.txt')
api_key = blob.download_as_text()
blob = bucket.blob('alpaca-secret-key.txt')
secret_key = blob.download_as_text()
base_url = 'https://paper-api.alpaca.markets'
api = REST(api_key, secret_key, base_url, 'v2')
# Get all stocks
assets = api.list_assets('active')
symbols = [asset.symbol for asset in assets if asset.tradable]
# Get past 50 days data for all stocks
data = {}
symbols_chunked = list(chunks(list(set(symbols)), 200))
for symbol_group in symbols_chunked:
print(f'Retrieving {len(symbol_group)} symbol data')
data_group = api.get_barset(','.join(symbol_group), '1D', limit=50).df
for symbol in symbol_group:
data[symbol] = data_group[symbol]
result_df = pd.DataFrame()
for symbol in data.keys():
df = data[symbol]
df = df.loc[df['close'] > 0]
if len(df.index) >= 50:
# Calculate day change percent
dayChange = []
for i in df.index:
try:
high = df['high'][i]
low = df['low'][i]
if low and low > 0:
dayChange.append(round(((high - low) / low) * 100, 2))
else:
dayChange.append(0)
except KeyError:
dayChange.append(0)
# Calculate averages
df['dayChange'] = dayChange
df['averageDayChange10'] = df['dayChange'].ewm(span=10).mean()
df['averageVolume50'] = df['volume'].ewm(span=50).mean()
df['averageVolume10'] = df['volume'].ewm(span=10).mean()
df['symbol'] = symbol
# Add most recent row
i = len(df.index) - 1
result_df = result_df.append(df.iloc[i])
# Filter stocks by high volatility criteria
filtered_df = result_df.query(
'averageDayChange10>4.5 & averageVolume50>4000000 & averageVolume10>4000000 & close>=5'
)
# Sort descending by averageDayChange10
sorted_df = filtered_df.sort_values('averageDayChange10', ascending=False)
# Grab top 5 stocks
selected_stocks = sorted_df[:5]
print(selected_stocks)
symbols = list(selected_stocks['symbol'].values)
print(symbols)
# Store them in Alpaca watchlist
watchlist = api.get_watchlist_by_name('day-trade-stocks')
api.update_watchlist(watchlist.id, symbols=symbols)
print('Success')