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# Backtesting
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This page explains how to validate your strategy performance by using
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This page explains how to validate your strategy performance by using
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Backtesting.
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## Table of Contents
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- [Test your strategy with Backtesting](#test-your-strategy-with-backtesting)
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- [Understand the backtesting result](#understand-the-backtesting-result)
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## Test your strategy with Backtesting
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Now you have good Buy and Sell strategies, you want to test it against
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real data. This is what we call
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real data. This is what we call
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[backtesting](https://en.wikipedia.org/wiki/Backtesting).
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Backtesting will use the crypto-currencies (pair) from your config file
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and load static tickers located in
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[/freqtrade/tests/testdata](https://github.com/freqtrade/freqtrade/tree/develop/freqtrade/tests/testdata).
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If the 5 min and 1 min ticker for the crypto-currencies to test is not
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already in the `testdata` folder, backtesting will download them
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and load static tickers located in
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[/freqtrade/tests/testdata](https://github.com/freqtrade/freqtrade/tree/develop/freqtrade/tests/testdata).
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If the 5 min and 1 min ticker for the crypto-currencies to test is not
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already in the `testdata` folder, backtesting will download them
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automatically. Testdata files will not be updated until you specify it.
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The result of backtesting will confirm you if your bot has better odds of making a profit than a loss.
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@ -216,15 +211,15 @@ TOTAL 419 -0.41 -0.00348593 52.9
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```
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We understand the bot has made `419` trades for an average duration of
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`52.9` min, with a performance of `-0.41%` (loss), that means it has
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`52.9` min, with a performance of `-0.41%` (loss), that means it has
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lost a total of `-0.00348593 BTC`.
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As you will see your strategy performance will be influenced by your buy
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strategy, your sell strategy, and also by the `minimal_roi` and
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`stop_loss` you have set.
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As you will see your strategy performance will be influenced by your buy
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strategy, your sell strategy, and also by the `minimal_roi` and
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`stop_loss` you have set.
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As for an example if your minimal_roi is only `"0": 0.01`. You cannot
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expect the bot to make more profit than 1% (because it will sell every
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expect the bot to make more profit than 1% (because it will sell every
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time a trade will reach 1%).
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```json
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@ -234,21 +229,21 @@ time a trade will reach 1%).
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```
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On the other hand, if you set a too high `minimal_roi` like `"0": 0.55`
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(55%), there is a lot of chance that the bot will never reach this
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profit. Hence, keep in mind that your performance is a mix of your
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(55%), there is a lot of chance that the bot will never reach this
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profit. Hence, keep in mind that your performance is a mix of your
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strategies, your configuration, and the crypto-currency you have set up.
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## Backtesting multiple strategies
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To backtest multiple strategies, a list of Strategies can be provided.
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This is limited to 1 ticker-interval per run, however, data is only loaded once from disk so if you have multiple
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This is limited to 1 ticker-interval per run, however, data is only loaded once from disk so if you have multiple
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strategies you'd like to compare, this should give a nice runtime boost.
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All listed Strategies need to be in the same folder.
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``` bash
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freqtrade backtesting --timerange 20180401-20180410 --ticker-interval 5m --strategy-list Strategy001 Strategy002 --export trades
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freqtrade backtesting --timerange 20180401-20180410 --ticker-interval 5m --strategy-list Strategy001 Strategy002 --export trades
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```
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This will save the results to `user_data/backtest_data/backtest-result-<strategy>.json`, injecting the strategy-name into the target filename.
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@ -266,5 +261,5 @@ Detailed output for all strategies one after the other will be available, so mak
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## Next step
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Great, your strategy is profitable. What if the bot can give your the
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optimal parameters to use for your strategy?
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optimal parameters to use for your strategy?
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Your next step is to learn [how to find optimal parameters with Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md)
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