Smarttbot Crypto Strategy Replication
Budget: $30 – $250 USD
I need help turning the public leaderboard insights on Smarttbot into fully functioning, trend-following crypto robots. My account only lets me see limited performance metrics—not the full parameter sets—so the first step will be to mine the rankings of roughly fifty top performers, infer what drives their edge, and document the recurring patterns you spot.
From there, I want you to recreate that underlying logic, adjust it for current market conditions, and deliver a set of optimized configurations that I can deploy directly on Smarttbot. Robust back-testing, walk-forward validation, and stress tests on major cryptocurrencies are essential to make sure the new bots hold up beyond the sample data.
Please provide:
• A concise report explaining the patterns you uncovered and why they matter.
• The final Smarttbot robot files (or importable JSON/CSV parameter sets) ready to run.
• A short user guide so I can tweak key parameters myself in the future.
If you normally work in Python with libraries like pandas, NumPy, TA-Lib, or leverage the Smarttbot API for bulk metrics extraction and simulation, that would be ideal. Aim to preserve the winning logic you discover while improving risk-adjusted returns and drawdown control. Let’s transform those leaderboard clues into a repeatable, crypto-focused, trend-following suite of bots.
From there, I want you to recreate that underlying logic, adjust it for current market conditions, and deliver a set of optimized configurations that I can deploy directly on Smarttbot. Robust back-testing, walk-forward validation, and stress tests on major cryptocurrencies are essential to make sure the new bots hold up beyond the sample data.
Please provide:
• A concise report explaining the patterns you uncovered and why they matter.
• The final Smarttbot robot files (or importable JSON/CSV parameter sets) ready to run.
• A short user guide so I can tweak key parameters myself in the future.
If you normally work in Python with libraries like pandas, NumPy, TA-Lib, or leverage the Smarttbot API for bulk metrics extraction and simulation, that would be ideal. Aim to preserve the winning logic you discover while improving risk-adjusted returns and drawdown control. Let’s transform those leaderboard clues into a repeatable, crypto-focused, trend-following suite of bots.