# 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