def __init__(self):
super(trading_vix_env, self).__init__()
self.action_space = spaces.box.Box(
low=0, #no position
high=1, #all in stock
shape=(1, ),
dtype=np.float32)
high_observation = np.asarray([999, 999, 999, 999, 999, 999])
self.observation_space = spaces.box.Box(low=-1 * high_observation,
high=high_observation,
dtype=np.float32)
self.seed()
self.max_trajectory_length = 201
#load data
index_data = pd.read_csv("^VIX.csv")
index_data = index_data.rename(columns = {"Date":"Date",\
"Open":"index_open",\
"High":'index_high',\
'Low':'index_low',\
'Close':'index_close',\
'Adj Close':'index_adj_close',\
'Volume':'index_volume'})
vix_price_data = pd.read_csv('VIXY.csv')
vix_price_data = vix_price_data.rename(columns = {"Date":"Date",\
"Open":"vix_price_open",\
"High":'vix_price_high',\
'Low':'vix_price_low',\
'Close':'vix_price_close',\
'Adj Close':'vix_price_adj_close',\
'Volume':'vix_price_volume'})
total_data = pd.merge(index_data,
vix_price_data,
on="Date",
how='inner')
#build features
#compute the exponential moving average
mv_10 = total_data['index_adj_close'].ewm(span=10).mean()
mv_20 = total_data['index_adj_close'].ewm(span=20).mean()
mv_30 = total_data['index_adj_close'].ewm(span=30).mean()
mv_50 = total_data['index_adj_close'].ewm(span=50).mean()
mv_100 = total_data['index_adj_close'].ewm(span=100).mean()
spot_to_mv_10 = total_data['index_adj_close'] / mv_10
spot_to_mv_20 = total_data['index_adj_close'] / mv_20
spot_to_mv_30 = total_data['index_adj_close'] / mv_30
spot_to_mv_50 = total_data['index_adj_close'] / mv_50
spot_to_mv_100 = total_data['index_adj_close'] / mv_100
vix_measure = spot_to_mv_10 + spot_to_mv_20 + spot_to_mv_30 + spot_to_mv_50 + spot_to_mv_100
vix_measure_list = vix_measure.tolist()
index_feature_dataframe = pd.DataFrame()
index_feature_dataframe['vix_price_adj_close'] = total_data[
'vix_price_adj_close'][1:] #[1:] for matching counting_days
index_feature_dataframe['vix_adj_close'] = total_data[
'index_adj_close'][1:]
index_feature_dataframe['mv_ratio'] = vix_measure_list[1:]
threshold_list = [5, 6, 7]
for threshold in threshold_list:
counting_days = trading_vix_utils.day_counter_helper(
vix_measure_list, threshold)
index_feature_dataframe['days_since_' +
str(threshold)] = counting_days
index_feature_dataframe = index_feature_dataframe.iloc[
-1000:] #there may be a vix regime change in 2018/1??
index_feature_dataframe = index_feature_dataframe.reset_index(
drop=True)
self.index_feature_dataframe = index_feature_dataframe
#other variables
self.current_time_index = None
self.quantity = None
self.cash = None
self.min_transaction_value = None
self.buy_and_hold_stock_quantity = None
self.current_portfolio_value = None
self.current_trajectory_length = None
self.has_at_least_one_sell = None
def __init__(self, threshold_list=[5, 6, 7]):
seed_index = 0
np.random.seed(seed_index)
random.seed(seed_index)
#load data
index_data = pd.read_csv("^VIX.csv")
index_data = index_data.rename(columns = {"Date":"Date",\
"Open":"index_open",\
"High":'index_high',\
'Low':'index_low',\
'Close':'index_close',\
'Adj Close':'index_adj_close',\
'Volume':'index_volume'})
vix_price_data = pd.read_csv('VIXY.csv')
vix_price_data = vix_price_data.rename(columns = {"Date":"Date",\
"Open":"vix_price_open",\
"High":'vix_price_high',\
'Low':'vix_price_low',\
'Close':'vix_price_close',\
'Adj Close':'vix_price_adj_close',\
'Volume':'vix_price_volume'})
total_data = pd.merge(index_data,
vix_price_data,
on="Date",
how='inner')
#build features
#compute the exponential moving average
mv_10 = total_data['index_adj_close'].ewm(span=10).mean()
mv_20 = total_data['index_adj_close'].ewm(span=20).mean()
mv_30 = total_data['index_adj_close'].ewm(span=30).mean()
mv_50 = total_data['index_adj_close'].ewm(span=50).mean()
mv_100 = total_data['index_adj_close'].ewm(span=100).mean()
spot_to_mv_10 = total_data['index_adj_close'] / mv_10
spot_to_mv_20 = total_data['index_adj_close'] / mv_20
spot_to_mv_30 = total_data['index_adj_close'] / mv_30
spot_to_mv_50 = total_data['index_adj_close'] / mv_50
spot_to_mv_100 = total_data['index_adj_close'] / mv_100
vix_measure = spot_to_mv_10 + spot_to_mv_20 + spot_to_mv_30 + spot_to_mv_50 + spot_to_mv_100
vix_measure_list = vix_measure.tolist()
index_feature_dataframe = pd.DataFrame()
index_feature_dataframe['vix_price_adj_close'] = total_data[
'vix_price_adj_close'][1:] #[1:] for matching counting_days
index_feature_dataframe['vix_adj_close'] = total_data[
'index_adj_close'][1:]
index_feature_dataframe['mv_ratio'] = vix_measure_list[1:]
threshold_list = [5, 6, 7]
for threshold in threshold_list:
counting_days = trading_vix_utils.day_counter_helper(
vix_measure_list, threshold)
index_feature_dataframe['days_since_' +
str(threshold)] = counting_days
index_feature_dataframe = index_feature_dataframe.iloc[
-1000:] #there may be a vix regime change in 2018/1??
index_feature_dataframe = index_feature_dataframe.reset_index(
drop=True)
self.index_feature_dataframe = index_feature_dataframe
#other variables
self.current_time_index = None
self.quantity = None
self.cash = None
self.min_transaction_value = None
self.buy_and_hold_stock_quantity = None
self.current_portfolio_value = None