import React, { useState, useEffect } from 'react'; import Sidebar from '../components/dashboard/Sidebar'; import Header from '../components/dashboard/Header'; import { Card, CardContent, CardDescription, CardHeader, CardTitle } from "@/components/ui/card"; import { Badge } from "@/components/ui/badge"; import { Progress } from "@/components/ui/progress"; import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"; import { CheckCircle, AlertTriangle, Database, Shield, RefreshCw, TrendingUp } from 'lucide-react'; import { useToast } from "@/components/ui/use-toast"; const CryptoEngine = () => { const [loading, setLoading] = useState(true); const { toast } = useToast(); useEffect(() => { // Simulate loading time const timer = setTimeout(() => { setLoading(false); }, 800); return () => clearTimeout(timer); }, []); const handleTrainModel = () => { toast({ title: "Training Initiated", description: "Crypto trader model training has started. Estimated completion time: 15 minutes.", }); }; return (

Crypto Engine

Real-time reinforcement learning for cryptocurrency trading strategies

Market Data Feeds Exchange API connections status {loading ? (
{Array(3).fill(0).map((_, idx) => (
))}
) : ( <>
Order Books
Level 2 data
Online
Trade Data
Executed transactions
86 tps
Sentiment Data
Social feeds
Delayed
)}
RL Training Status Reinforcement learning pipeline {loading ? (
{Array(3).fill(0).map((_, idx) => (
))}
) : ( <>
Last Training 35 minutes ago
crypto_trader v3.7.2
Trades since last run 651 / 1,000
Training Schedule Hourly
Every hour or after 1,000 new market trades
)}
Risk Controls Trading limits and performance metrics {loading ? (
{Array(3).fill(0).map((_, idx) => (
))}
) : ( <>
Max Drawdown 2.1% / 5.0%
Current / Limit
Position Sizing 1.8% / 2.0%
Current / Limit
Sharpe Ratio 1.42
Above 1.0 threshold (good)
)}
RL Algorithm Performance Recent Trades TD3 Reinforcement Learning Twin Delayed Deep Deterministic Policy Gradient implementation

Algorithm Configuration

Actor Network

3 layers, 256 units

Critic Networks

Twin Q-networks

Update Frequency

Every 2 steps

Target Update

Soft, τ=0.005

Exploration

Gaussian noise

Batch Size

256 trades

State Vector

Price Features

Moving averages (7 timeframes), Bollinger bands, RSI

Volume Features

VWAP, OBV, volume profile by price level

Sentiment Features

Social sentiment score, news sentiment, fear & greed

Hierarchical RL Structure

{/* Meta-controller */}

Meta-Controller

Market regime classifier

{/* Connector lines */}
{/* Sub-agents container */}
{/* Sub-agent 1 */}

Trend Agent

Long timeframes

{/* Sub-agent 2 */}

Range Agent

Consolidation

{/* Sub-agent 3 */}

Volatility Agent

News events

{/* Action space */}

Continuous Action Space:

Position Size

0-2% of capital

Direction

-1 (short) to +1 (long)

Trading Performance Key metrics from the reinforcement learning model

Returns

+8.3%

Last 30 days

Sharpe Ratio

1.42

Risk-adjusted return

Max Drawdown

-2.1%

Within target range

Performance Breakdown

Metric Value Target Status
Sharpe Ratio 1.42 ≥ 1.0 ✓ Pass
Max Drawdown -2.1% ≤ 5.0% ✓ Pass
Win Rate 58.3% ≥ 55.0% ✓ Pass
Profit Factor 1.83 ≥ 1.5 ✓ Pass
Avg Win / Avg Loss 1.31 ≥ 1.0 ✓ Pass
Recent Trading Activity Trades executed by the reinforcement learning agent
{loading ? ( <> {Array(5).fill(0).map((_, idx) => ( ))} ) : ( <> )}
Time Symbol Action Price Size P/L Strategy
14:32:15 BTC/USD Buy $61,245.30 0.082 BTC +$137.62 Trend Agent
14:05:52 ETH/USD Sell $3,128.75 1.5 ETH +$78.45 Range Agent
13:48:07 SOL/USD Buy $146.82 10.5 SOL -$42.20 Volatility Agent
13:22:34 XRP/USD Sell $0.5231 1,500 XRP +$28.35 Range Agent
13:01:15 BNB/USD Buy $572.45 2.1 BNB +$64.80 Trend Agent
Training History Past reinforcement learning model versions
{loading ? ( <> {Array(5).fill(0).map((_, idx) => ( ))} ) : ( <> )}
Version Date Sharpe Win Rate Status
v3.7.2 2025-05-09 13:00 1.42 58.3% Active
v3.7.1 2025-05-09 12:00 1.39 57.9% Archived
v3.7.0 2025-05-09 11:00 1.36 57.2% Archived
v3.6.9 2025-05-09 10:00 1.34 56.8% Archived
v3.6.8 2025-05-09 09:00 0.98 54.3% Failed
); }; export default CryptoEngine;