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#livedeployment

livedeployment

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Wolfbotio
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⚠️ Remember: 'Same settings' does not guarantee 'same results' when moving from backtesting to live trading. Real-world variables like spreads, order-book depth, and latency are often omitted in simulations. Here is the methodical path for transitioning your proven logic from paper to production using WolfBot: 1. Start by running the strategy on the smallest possible live size, keeping all settings the same. 2. Only after establishing stability, proceed by changing *one* variable at a time (e.g., widening slippage or altering the entry order type). 3. To compare results honestly, don't compare PnL directly. Instead, compare the *behavior*: check if live entry prices are within your expected slippage budget, if exit levels fire as expected, and if the cycle count is similar. 4. Expect specific differences: fills may degrade due to slippage, timing won't be instantaneous (due to API processing), and all transaction fees will become immediately visible. 5. If the live behavior is structurally different from the simulation in an unexplained way (beyond just fees/slippage), pause and return to simulation. This is the most cost-effective debugging step. 6. For a detailed review of this process, consult this guide: https://community.wolfbot.io/docs/paper-to-live-same-settings #AutomatedTrading #TradingStrategy #LiveDeployment #CryptoAutomation #RiskManagement
⚠️ Remember: 'Same settings' does not guarantee 'same results' when moving from backtesting to live trading. Real-world variables like spreads, order-book depth, and latency are often omitted in simulations.

Here is the methodical path for transitioning your proven logic from paper to production using WolfBot:

1. Start by running the strategy on the smallest possible live size, keeping all settings the same.
2. Only after establishing stability, proceed by changing *one* variable at a time (e.g., widening slippage or altering the entry order type).
3. To compare results honestly, don't compare PnL directly. Instead, compare the *behavior*: check if live entry prices are within your expected slippage budget, if exit levels fire as expected, and if the cycle count is similar.
4. Expect specific differences: fills may degrade due to slippage, timing won't be instantaneous (due to API processing), and all transaction fees will become immediately visible.
5. If the live behavior is structurally different from the simulation in an unexplained way (beyond just fees/slippage), pause and return to simulation. This is the most cost-effective debugging step.
6. For a detailed review of this process, consult this guide: https://community.wolfbot.io/docs/paper-to-live-same-settings

#AutomatedTrading #TradingStrategy #LiveDeployment #CryptoAutomation #RiskManagement
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