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<li class="md-nav__item">
<a href="edge/" class="md-nav__link">
<span class="md-ellipsis">
Edge Positioning
</span>
</a>
</li>
</ul>
</nav>
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<li>Optimize: Find the best parameters for your strategy using hyperoptimization which employs machine learning methods. You can optimize buy, sell, take profit (ROI), stop-loss and trailing stop-loss parameters for your strategy.</li>
<li>Select markets: Create your static list or use an automatic one based on top traded volumes and/or prices (not available during backtesting). You can also explicitly blacklist markets you don't want to trade.</li>
<li>Run: Test your strategy with simulated money (Dry-Run mode) or deploy it with real money (Live-Trade mode).</li>
<li>Run using Edge (optional module): The concept is to find the best historical <a href="edge/#expectancy">trade expectancy</a> by markets based on variation of the stop-loss and then allow/reject markets to trade. The sizing of the trade is based on a risk of a percentage of your capital.</li>
<li>Control/Monitor: Use Telegram or a WebUI (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).</li>
<li>Analyze: Further analysis can be performed on either Backtesting data or Freqtrade trading history (SQL database), including automated standard plots, and methods to load the data into <a href="data-analysis/">interactive environments</a>.</li>
</ul>