feat: implement BTC/ETH correlation features for improved model accuracy

- Added a new design document outlining the integration of BTC/ETH candle data as additional features in the XRP ML filter, enhancing prediction accuracy.
- Introduced `MultiSymbolStream` for combined WebSocket data retrieval of XRP, BTC, and ETH.
- Expanded feature set from 13 to 21 by including 8 new BTC/ETH-related features.
- Updated various scripts and modules to support the new feature set and data handling.
- Enhanced training and deployment scripts to accommodate the new dataset structure.

This commit lays the groundwork for improved model performance by leveraging the correlation between BTC and ETH with XRP.

tests/test_bot.py

@@ -35,6 +35,19 @@ def sample_df():
     })
 
 
+def test_bot_uses_multi_symbol_stream(config):
+    from src.data_stream import MultiSymbolStream
+    with patch("src.bot.BinanceFuturesClient"):
+        bot = TradingBot(config)
+    assert isinstance(bot.stream, MultiSymbolStream)
+
+def test_bot_stream_has_btc_eth_buffers(config):
+    with patch("src.bot.BinanceFuturesClient"):
+        bot = TradingBot(config)
+    assert "btcusdt" in bot.stream.buffers
+    assert "ethusdt" in bot.stream.buffers
+
+
 @pytest.mark.asyncio
 async def test_bot_processes_signal(config, sample_df):
     with patch("src.bot.BinanceFuturesClient") as MockExchange: