The latest articles on DEV Community by Stefano viana (@stefano_viana_dda882cfae5). https://dev.to/stefano_viana_dda882cfae5 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3867021%2F4ce2be1b-7eae-4c3f-abde-ff9771444aa8.jpg https://dev.to/stefano_viana_dda882cfae5 en Stefano viana Wed, 08 Apr 2026 20:30:15 +0000 https://dev.to/stefano_viana_dda882cfae5/deepalpha-v60-ai-trading-report-2026-04-08-1hmn https://dev.to/stefano_viana_dda882cfae5/deepalpha-v60-ai-trading-report-2026-04-08-1hmn <h1> DeepAlpha v6.0 — AI Trading Report (2026-04-08) </h1> <h2> Market </h2> <ul> <li> <strong>BTC</strong>: $71,336 (-0.8%)</li> <li> <strong>ETH</strong>: $2,213 (-1.2%)</li> <li> <strong>SOL</strong>: $83 (-2.7%)</li> </ul> <h2> Performance </h2> <ul> <li>Return since launch: <strong>-1.9%</strong> </li> <li>Open positions: 2</li> <li>AI model accuracy: 0.0% (walk-forward validated)</li> </ul> <h2> How it works </h2> <p>DeepAlpha is an AI-powered trading system running on Hyperliquid L1 perpetuals. It uses:</p> <ul> <li>LightGBM + XGBoost ensemble trained on 7M+ samples (5 years of data)</li> <li>38 features including RSI, ATR, OBI proxy, CVD, BTC correlation</li> <li>Walk-forward validation (no overfitting)</li> <li>BTC SMA20 regime filter</li> <li>Conservative risk: 5x leverage, 3% equity per trade, ATR-based trailing stops</li> </ul> <p>All trades are verifiable on-chain.</p> <p>Stats: <a href="https://deepalpha.duckdns.org" rel="noopener noreferrer">https://deepalpha.duckdns.org</a><br> Telegram: <a href="https://t.me/DeepAlphaVault" rel="noopener noreferrer">https://t.me/DeepAlphaVault</a></p> <p><em>Not financial advice. Trading involves risk.</em></p> crypto trading ai machinelearning Stefano viana Wed, 08 Apr 2026 08:40:32 +0000 https://dev.to/stefano_viana_dda882cfae5/deepalpha-v60-ai-trading-report-2026-04-08-4ml1 https://dev.to/stefano_viana_dda882cfae5/deepalpha-v60-ai-trading-report-2026-04-08-4ml1 <h1> DeepAlpha v6.0 — AI Trading Report (2026-04-08) </h1> <h2> Market </h2> <ul> <li> <strong>BTC</strong>: $71,650 (-0.4%)</li> <li> <strong>ETH</strong>: $2,253 (+0.6%)</li> <li> <strong>SOL</strong>: $84 (-1.2%)</li> </ul> <h2> Performance </h2> <ul> <li>Return since launch: <strong>-0.0%</strong> </li> <li>Open positions: 3</li> <li>AI model accuracy: 0.0% (walk-forward validated)</li> </ul> <h2> How it works </h2> <p>DeepAlpha is an AI-powered trading system running on Hyperliquid L1 perpetuals. It uses:</p> <ul> <li>LightGBM + XGBoost ensemble trained on 7M+ samples (5 years of data)</li> <li>38 features including RSI, ATR, OBI proxy, CVD, BTC correlation</li> <li>Walk-forward validation (no overfitting)</li> <li>BTC SMA20 regime filter</li> <li>Conservative risk: 5x leverage, 3% equity per trade, ATR-based trailing stops</li> </ul> <p>All trades are verifiable on-chain.</p> <p>Stats: <a href="https://deepalpha.duckdns.org" rel="noopener noreferrer">https://deepalpha.duckdns.org</a><br> Telegram: <a href="https://t.me/DeepAlphaVault" rel="noopener noreferrer">https://t.me/DeepAlphaVault</a></p> <p><em>Not financial advice. Trading involves risk.</em></p> crypto trading ai machinelearning Stefano viana Wed, 08 Apr 2026 08:30:13 +0000 https://dev.to/stefano_viana_dda882cfae5/deepalpha-v60-ai-trading-report-2026-04-08-57o https://dev.to/stefano_viana_dda882cfae5/deepalpha-v60-ai-trading-report-2026-04-08-57o <h1> DeepAlpha v6.0 — AI Trading Report (2026-04-08) </h1> <h2> Market </h2> <ul> <li> <strong>BTC</strong>: $71,650 (-0.4%)</li> <li> <strong>ETH</strong>: $2,253 (+0.6%)</li> <li> <strong>SOL</strong>: $84 (-1.2%)</li> </ul> <h2> Performance </h2> <ul> <li>Return since launch: <strong>-0.0%</strong> </li> <li>Open positions: 3</li> <li>AI model accuracy: 0.0% (walk-forward validated)</li> </ul> <h2> How it works </h2> <p>DeepAlpha is an AI-powered trading system running on Hyperliquid L1 perpetuals. It uses:</p> <ul> <li>LightGBM + XGBoost ensemble trained on 7M+ samples (5 years of data)</li> <li>38 features including RSI, ATR, OBI proxy, CVD, BTC correlation</li> <li>Walk-forward validation (no overfitting)</li> <li>BTC SMA20 regime filter</li> <li>Conservative risk: 5x leverage, 3% equity per trade, ATR-based trailing stops</li> </ul> <p>All trades are verifiable on-chain.</p> <p>Stats: <a href="https://deepalpha.duckdns.org" rel="noopener noreferrer">https://deepalpha.duckdns.org</a><br> Telegram: <a href="https://t.me/DeepAlphaVault" rel="noopener noreferrer">https://t.me/DeepAlphaVault</a></p> <p><em>Not financial advice. Trading involves risk.</em></p> crypto trading ai machinelearning Stefano viana Wed, 08 Apr 2026 06:02:36 +0000 https://dev.to/stefano_viana_dda882cfae5/deepalpha-v60-ai-powered-crypto-trading-system-2026-04-08-50mc https://dev.to/stefano_viana_dda882cfae5/deepalpha-v60-ai-powered-crypto-trading-system-2026-04-08-50mc <h1> DeepAlpha v6.0 — AI Trading Report (2026-04-08) </h1> <h2> Market </h2> <ul> <li> <strong>BTC</strong>: $71,690 (-0.3%)</li> <li> <strong>ETH</strong>: $2,239 (-0.0%)</li> <li> <strong>SOL</strong>: $85 (-1.1%)</li> </ul> <h2> Performance </h2> <ul> <li>Return since launch: <strong>+0.0%</strong> </li> <li>Open positions: 0</li> <li>AI model accuracy: 0.0% (walk-forward validated)</li> </ul> <h2> How it works </h2> <p>DeepAlpha is an AI-powered trading system running on Hyperliquid L1 perpetuals. It uses:</p> <ul> <li>LightGBM + XGBoost ensemble trained on 7M+ samples (5 years of data)</li> <li>38 features including RSI, ATR, OBI proxy, CVD, BTC correlation</li> <li>Walk-forward validation (no overfitting)</li> <li>BTC SMA20 regime filter</li> <li>Conservative risk: 5x leverage, 3% equity per trade, ATR-based trailing stops</li> </ul> <p>All trades are verifiable on-chain.</p> <p>Stats: <a href="https://deepalpha.duckdns.org" rel="noopener noreferrer">https://deepalpha.duckdns.org</a><br> Telegram: <a href="https://t.me/DeepAlphaVault" rel="noopener noreferrer">https://t.me/DeepAlphaVault</a></p> <p><em>Not financial advice. Trading involves risk.</em></p> crypto trading ai machinelearning