Add Backtesting and Hyperopt documentation

2025-12-03 10:33:08 +00:00 · 2018-01-02 22:43:00 -08:00
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+# Backtesting
+This page explains how to validate your strategy performance by using 
+Backtesting.
+
+## Table of Contents
+- [Test your strategy with Backtesting](#test-your-strategy-with-backtesting)
+- [Understand the backtesting result](#understand-the-backtesting-result)
+
+## Test your strategy with Backtesting
+Now you have good Buy and Sell strategies, you want to test it against
+real data. This is what we call 
+[backtesting](https://en.wikipedia.org/wiki/Backtesting).
+
+
+Backtesting will use the crypto-currencies (pair) from your config file
+and load static tickers located in 
+[/freqtrade/tests/testdata](https://github.com/gcarq/freqtrade/tree/develop/freqtrade/tests/testdata).
+If the 5 min and 1 min ticker for the crypto-currencies to test is not 
+already in the `testdata` folder, backtesting will download them 
+automatically. Testdata files will not be updated until you specify it.
+
+The result of backtesting will confirm you if your bot as more chance to
+make a profit than a loss.
+
+
+The backtesting is very easy with freqtrade.
+
+### Run a backtesting against the currencies listed in your config file
+**With 5 min tickers (Per default)**
+```bash
+python3 ./freqtrade/main.py backtesting --realistic-simulation
+```
+
+**With 1 min tickers**
+```bash
+python3 ./freqtrade/main.py backtesting --realistic-simulation --ticker-interval 1
+```
+
+**Reload your testdata files**
+```bash
+python3 ./freqtrade/main.py backtesting --realistic-simulation --refresh-pairs-cached
+```
+
+**With live data (do not alter your testdata files)**
+```bash
+python3 ./freqtrade/main.py backtesting --realistic-simulation --live
+```
+
+For help about backtesting usage, please refer to 
+[Backtesting commands](#backtesting-commands).
+
+## Understand the backtesting result
+The most important in the backtesting is to understand the result.
+
+A backtesting result will look like that:
+```
+====================== BACKTESTING REPORT ================================
+pair        buy count    avg profit %    total profit BTC    avg duration
+--------  -----------  --------------  ------------------  --------------
+BTC_ETH            56           -0.67         -0.00075455            62.3
+BTC_LTC            38           -0.48         -0.00036315            57.9
+BTC_ETC            42           -1.15         -0.00096469            67.0
+BTC_DASH           72           -0.62         -0.00089368            39.9
+BTC_ZEC            45           -0.46         -0.00041387            63.2
+BTC_XLM            24           -0.88         -0.00041846            47.7
+BTC_NXT            24            0.68          0.00031833            40.2
+BTC_POWR           35            0.98          0.00064887            45.3
+BTC_ADA            43           -0.39         -0.00032292            55.0
+BTC_XMR            40           -0.40         -0.00032181            47.4
+TOTAL             419           -0.41         -0.00348593            52.9
+```
+
+The last line will give you the overall performance of your strategy,
+here:
+```
+TOTAL             419           -0.41         -0.00348593            52.9
+```
+
+We understand the bot has made `419` trades for an average duration of
+`52.9` min, with a performance of `-0.41%` (loss), that means it has 
+lost a total of `-0.00348593 BTC`.
+ 
+As you will see your strategy performance will be influenced by your buy 
+strategy, your sell strategy, and also by the `minimal_roi` and 
+`stop_loss` you have set. 
+
+As for an example if your minimal_roi is only `"0":  0.01`. You cannot
+expect the bot to make more profit than 1% (because it will sell every 
+time a trade will reach 1%).
+```json
+"minimal_roi": {
+    "0":  0.01
+},
+```
+
+On the other hand, if you set a too high `minimal_roi` like `"0":  0.55`
+(55%), there is a lot of chance that the bot will never reach this 
+profit. Hence, keep in mind that your performance is a mix of your 
+strategies, your configuration, and the crypto-currency you have set up.
+
+## Next step
+Great, your strategy is profitable. What if the bot can give your the
+optimal parameters to use for your strategy?  
+Your next step is to learn [how to find optimal parameters with Hyperopt](https://github.com/gcarq/freqtrade/blob/develop/docs/hyperopt.md)