Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.13239 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909940950499328 |
|---|---|
| author | Nguyen, Thanh |
| author_facet | Nguyen, Thanh |
| contents | Cryptocurrency trading has attracted tremendous attention from both retail and institutional investors. However, most traders fail to scale their assets under management due to fragile strategies that collapse during adverse markets. The primary causes are oversized leverage, speculative position sizing, and the absence of robust risk management or hedging mechanisms. This paper introduces Talyxion, an end to end framework for crypto portfolio allocation that shifts the paradigm from speculation to optimization. The proposed pipeline consists of four stages: universe selection, alpha backtesting, volatility aware portfolio optimization, and dynamic drawdown based risk management. By combining operations research techniques with practical risk controls, Talyxion enables scalable crypto portfolios that can withstand market downturns. In live 30 day trading on Binance Futures, the framework achieved a return on investment (ROI) of +16.68%, with the Sharpe ratio reaching 5.72 and the maximum drawdown contained at just 4.56%, demonstrating strong downside risk control. The system executed 227 trades, of which 131 were profitable, resulting in a win rate of 57.71% and a PnL of +1,137.49 USDT. Importantly, these results outperformed the buy and hold baseline (Sharpe 1.79, ROI 4.36%, MDD 4.96%) as well as several top leader copy trading bots on Binance, highlighting both the competitiveness and scalability of Talyxion in real world trading environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_13239 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Talyxion: From Speculation to Optimization in Risk Managed Crypto Portfolio Allocation Nguyen, Thanh Operating Systems Cryptocurrency trading has attracted tremendous attention from both retail and institutional investors. However, most traders fail to scale their assets under management due to fragile strategies that collapse during adverse markets. The primary causes are oversized leverage, speculative position sizing, and the absence of robust risk management or hedging mechanisms. This paper introduces Talyxion, an end to end framework for crypto portfolio allocation that shifts the paradigm from speculation to optimization. The proposed pipeline consists of four stages: universe selection, alpha backtesting, volatility aware portfolio optimization, and dynamic drawdown based risk management. By combining operations research techniques with practical risk controls, Talyxion enables scalable crypto portfolios that can withstand market downturns. In live 30 day trading on Binance Futures, the framework achieved a return on investment (ROI) of +16.68%, with the Sharpe ratio reaching 5.72 and the maximum drawdown contained at just 4.56%, demonstrating strong downside risk control. The system executed 227 trades, of which 131 were profitable, resulting in a win rate of 57.71% and a PnL of +1,137.49 USDT. Importantly, these results outperformed the buy and hold baseline (Sharpe 1.79, ROI 4.36%, MDD 4.96%) as well as several top leader copy trading bots on Binance, highlighting both the competitiveness and scalability of Talyxion in real world trading environments. |
| title | Talyxion: From Speculation to Optimization in Risk Managed Crypto Portfolio Allocation |
| topic | Operating Systems |
| url | https://arxiv.org/abs/2511.13239 |