def calculate_columns(indicator_client: Indicators, owned: bool, trading_symbol: str,
bot_account: dict):
"""Sets buy/sell/hold signals for the conf_val strategy"""
indicator_client.ema(period=20, column_name='ema_20').dropna(inplace=True)
indicator_client.ema(period=200, column_name='ema_200').dropna(inplace=True)
indicator_client.rsi(period=14).dropna(inplace=True)
indicator_client.macd().dropna(inplace=True) # Defaults to fast: 12, slow: 26, column_name: macd
# Calculate the current % gap between the open and current ema_20
# This will be used to prevent a buy signal from happening if the open just barely
# goes over the ema_20.
v1 = indicator_client.price_data_frame['open']
v2 = indicator_client.price_data_frame['ema_20']
v3 = indicator_client.price_data_frame['ema_200']
indicator_client.price_data_frame['open_ema_20_percent_diff'] = \
((v1 - v2) / abs(v2)) * 100
indicator_client.price_data_frame['ema_20_ema_200_percent_diff'] = \
((v2 - v3) / abs(v3)) * 100
indicator_client.price_data_frame['signals'] = indicator_client.price_data_frame.apply(lambda row: calc_sig(row, owned), axis=1)
print("break")
indicator_client.ema(period=50)
# Add the Bollinger Bands.
indicator_client.bollinger_bands(period=20)
# Add the Rate of Change.
indicator_client.rate_of_change(period=1)
# Add the Average True Range.
indicator_client.average_true_range(period=14)
# Add the Stochastic Oscillator.
indicator_client.stochastic_oscillator()
# Add the MACD.
indicator_client.macd(fast_period=12, slow_period=26)
# Add the Mass Index.
indicator_client.mass_index(period=9)
while True:
# Grab the latest bar.
latest_bars = trading_robot.get_latest_bar()
# Add to the Stock Frame.
stock_frame.add_rows(data=latest_bars)
# Refresh the Indicators.
indicator_client.refresh()