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# dir
DATA_SAVE_DIR = "datasets"
TRAINED_MODEL_DIR = "trained_models"
TENSORBOARD_LOG_DIR = "tensorboard_log"
RESULTS_DIR = "results"
# date format: '%Y-%m-%d'
TRAIN_START_DATE = "2014-01-01"
TRAIN_END_DATE = "2020-07-31"
TEST_START_DATE = "2020-08-01"
TEST_END_DATE = "2021-10-01"
TRADE_START_DATE = "2021-11-01"
TRADE_END_DATE = "2021-12-01"
# stockstats technical indicator column names
# check https://pypi.org/project/stockstats/ for different names
INDICATORS = [
"macd",
"boll_ub",
"boll_lb",
"rsi_30",
"cci_30",
"dx_30",
"close_30_sma",
"close_60_sma",
]
# Model Parameters
A2C_PARAMS = {"n_steps": 5, "ent_coef": 0.01, "learning_rate": 0.0007}
PPO_PARAMS = {
"n_steps": 2048,
"ent_coef": 0.01,
"learning_rate": 0.00025,
"batch_size": 64,
}
DDPG_PARAMS = {"batch_size": 128, "buffer_size": 50000, "learning_rate": 0.001}
TD3_PARAMS = {
"batch_size": 100,
"buffer_size": 1000000,
"learning_rate": 0.001,
}
SAC_PARAMS = {
"batch_size": 64,
"buffer_size": 100000,
"learning_rate": 0.0001,
"learning_starts": 100,
"ent_coef": "auto_0.1",
}
ERL_PARAMS = {
"learning_rate": 3e-5,
"batch_size": 2048,
"gamma": 0.985,
"seed": 312,
"net_dimension": 512,
"target_step": 5000,
"eval_gap": 30,
}
RLlib_PARAMS = {"lr": 5e-5, "train_batch_size": 500, "gamma": 0.99}
# Possible time zones
TIME_ZONE_SHANGHAI = "Asia/Shanghai" # Hang Seng HSI, SSE, CSI
TIME_ZONE_USEASTERN = "US/Eastern" # Dow, Nasdaq, SP
TIME_ZONE_PARIS = "Europe/Paris" # CAC,
TIME_ZONE_BERLIN = "Europe/Berlin" # DAX, TECDAX, MDAX, SDAX
TIME_ZONE_JAKARTA = "Asia/Jakarta" # LQ45
TIME_ZONE_SELFDEFINED = "xxx" # If neither of the above is your time zone, you should define it, and set USE_TIME_ZONE_SELFDEFINED 1.
USE_TIME_ZONE_SELFDEFINED = 0 # 0 (default) or 1 (use the self defined)
# parameters for data sources
ALPACA_API_KEY = "xxx" # your ALPACA_API_KEY
ALPACA_API_SECRET = "xxx" # your ALPACA_API_SECRET
ALPACA_API_BASE_URL = "https://paper-api.alpaca.markets" # alpaca url
BINANCE_BASE_URL = "https://data.binance.vision/" # binance url
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