| Config |
Explanation |
| Start date |
The beginning date for your backtest period |
| End date |
The ending date for your backtest period |
| Exchange |
The exchange to simulate trading on |
| Maker fee |
Fee charged when you add liquidity to the order book (limit orders) |
| Taker fee |
Fee charged when you remove liquidity from the order book (market orders) |
| Coin |
The trading pair/symbol to backtest (e.g. BTCUSDT) |
| Main candle interval |
Primary timeframe for strategy execution (e.g. 1m, 5m, 15m, 1h) |
| Support candle intervals |
Additional timeframes available for analysis. Example: If your strategy run on 5m time frame but you only want to buy when 1h time frame is bullish, you should add 1h interval here |
| BTC.Dom candle intervals |
Bitcoin dominance chart intervals (Binance Futures only) |
| Config |
Explanation |
| Bot name |
Name of the bot |
| Bot path |
The address of the bot client (e.g. localhost:8888 or host.docker.internal:8888) |
| Prefetch bar |
Number of bars to prefetch (e.g. If your algorthim will buy when rsi(14) > 70, you should set this value to be greater than 14) |
| Initiation balance |
Initial fiat balance for the bot (e.g. 1000USDT ) |
| Number worker allocate to this backtest |
How many threads to run the backtest, please keep in mind that the more threads you use, the more memory and CPU it will consume |
| Indicator params |
Indicator parameters (e.g. period, source) . The BotClient will receive this params as parameter in init method. example :
def init(self, config: Dict[str, str]) -> None:
self.short_ema_period = int(config.get('s_ema'))
self.long_ema_period = int(config.get('l_ema'))
self.adx_period = int(config.get('adx'))
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