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<h1 id="backtesting">Backtesting<a class="headerlink" href="#backtesting" title="Permanent link">&para;</a></h1>
<p>This page explains how to validate your strategy performance by using Backtesting.</p>
<p>Backtesting requires historic data to be available.
To learn how to get data for the pairs and exchange you're interested in, head over to the <a href="../data-download/">Data Downloading</a> section of the documentation.</p>
<h2 id="test-your-strategy-with-backtesting">Test your strategy with Backtesting<a class="headerlink" href="#test-your-strategy-with-backtesting" title="Permanent link">&para;</a></h2>
<p>Now you have good Buy and Sell strategies and some historic data, you want to test it against
real data. This is what we call
<a href="https://en.wikipedia.org/wiki/Backtesting">backtesting</a>.</p>
<p>Backtesting will use the crypto-currencies (pairs) from your config file and load ticker data from <code>user_data/data/&lt;exchange&gt;</code> by default.
If no data is available for the exchange / pair / ticker interval combination, backtesting will ask you to download them first using <code>freqtrade download-data</code>.
For details on downloading, please refer to the <a href="../data-download/">Data Downloading</a> section in the documentation.</p>
<p>The result of backtesting will confirm if your bot has better odds of making a profit than a loss.</p>
<div class="admonition tip">
<p class="admonition-title">Using dynamic pairlists for backtesting</p>
<p>While using dynamic pairlists during backtesting is not possible, a dynamic pairlist using current data can be generated via the <a href="../utils/#test-pairlist"><code>test-pairlist</code></a> command, and needs to be specified as <code>"pair_whitelist"</code> attribute in the configuration.</p>
</div>
<h3 id="run-a-backtesting-against-the-currencies-listed-in-your-config-file">Run a backtesting against the currencies listed in your config file<a class="headerlink" href="#run-a-backtesting-against-the-currencies-listed-in-your-config-file" title="Permanent link">&para;</a></h3>
<h4 id="with-5-min-tickers-per-default">With 5 min tickers (Per default)<a class="headerlink" href="#with-5-min-tickers-per-default" title="Permanent link">&para;</a></h4>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting
</code></pre></div>
<h4 id="with-1-min-tickers">With 1 min tickers<a class="headerlink" href="#with-1-min-tickers" title="Permanent link">&para;</a></h4>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting<span class="w"> </span>--ticker-interval<span class="w"> </span>1m
</code></pre></div>
<h4 id="using-a-different-on-disk-ticker-data-source">Using a different on-disk ticker-data source<a class="headerlink" href="#using-a-different-on-disk-ticker-data-source" title="Permanent link">&para;</a></h4>
<p>Assume you downloaded the history data from the Bittrex exchange and kept it in the <code>user_data/data/bittrex-20180101</code> directory.
You can then use this data for backtesting as follows:</p>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>--datadir<span class="w"> </span>user_data/data/bittrex-20180101<span class="w"> </span>backtesting
</code></pre></div>
<h4 id="with-a-custom-strategy-file">With a (custom) strategy file<a class="headerlink" href="#with-a-custom-strategy-file" title="Permanent link">&para;</a></h4>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting<span class="w"> </span>-s<span class="w"> </span>SampleStrategy
</code></pre></div>
<p>Where <code>-s SampleStrategy</code> refers to the class name within the strategy file <code>sample_strategy.py</code> found in the <code>freqtrade/user_data/strategies</code> directory.</p>
<h4 id="comparing-multiple-strategies">Comparing multiple Strategies<a class="headerlink" href="#comparing-multiple-strategies" title="Permanent link">&para;</a></h4>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting<span class="w"> </span>--strategy-list<span class="w"> </span>SampleStrategy1<span class="w"> </span>AwesomeStrategy<span class="w"> </span>--ticker-interval<span class="w"> </span>5m
</code></pre></div>
<p>Where <code>SampleStrategy1</code> and <code>AwesomeStrategy</code> refer to class names of strategies.</p>
<h4 id="exporting-trades-to-file">Exporting trades to file<a class="headerlink" href="#exporting-trades-to-file" title="Permanent link">&para;</a></h4>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting<span class="w"> </span>--export<span class="w"> </span>trades
</code></pre></div>
<p>The exported trades can be used for <a href="#further-backtest-result-analysis">further analysis</a>, or can be used by the plotting script <code>plot_dataframe.py</code> in the scripts directory.</p>
<h4 id="exporting-trades-to-file-specifying-a-custom-filename">Exporting trades to file specifying a custom filename<a class="headerlink" href="#exporting-trades-to-file-specifying-a-custom-filename" title="Permanent link">&para;</a></h4>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting<span class="w"> </span>--export<span class="w"> </span>trades<span class="w"> </span>--export-filename<span class="o">=</span>backtest_samplestrategy.json
</code></pre></div>
<p>Please also read about the <a href="../strategy-customization/#strategy-startup-period">strategy startup period</a>.</p>
<h4 id="supplying-custom-fee-value">Supplying custom fee value<a class="headerlink" href="#supplying-custom-fee-value" title="Permanent link">&para;</a></h4>
<p>Sometimes your account has certain fee rebates (fee reductions starting with a certain account size or monthly volume), which are not visible to ccxt.
To account for this in backtesting, you can use the <code>--fee</code> command line option to supply this value to backtesting.
This fee must be a ratio, and will be applied twice (once for trade entry, and once for trade exit).</p>
<p>For example, if the buying and selling commission fee is 0.1% (i.e., 0.001 written as ratio), then you would run backtesting as the following:</p>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting<span class="w"> </span>--fee<span class="w"> </span><span class="m">0</span>.001
</code></pre></div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Only supply this option (or the corresponding configuration parameter) if you want to experiment with different fee values. By default, Backtesting fetches the default fee from the exchange pair/market info.</p>
</div>
<h4 id="running-backtest-with-smaller-testset-by-using-timerange">Running backtest with smaller testset by using timerange<a class="headerlink" href="#running-backtest-with-smaller-testset-by-using-timerange" title="Permanent link">&para;</a></h4>
<p>Use the <code>--timerange</code> argument to change how much of the testset you want to use.</p>
<p>For example, running backtesting with the <code>--timerange=20190501-</code> option will use all available data starting with May 1<sup>st</sup>, 2019 from your inputdata.</p>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting<span class="w"> </span>--timerange<span class="o">=</span><span class="m">20190501</span>-
</code></pre></div>
<p>You can also specify particular dates or a range span indexed by start and stop.</p>
<p>The full timerange specification:</p>
<ul>
<li>Use tickframes till 2018/01/31: <code>--timerange=-20180131</code></li>
<li>Use tickframes since 2018/01/31: <code>--timerange=20180131-</code></li>
<li>Use tickframes since 2018/01/31 till 2018/03/01 : <code>--timerange=20180131-20180301</code></li>
<li>Use tickframes between POSIX timestamps 1527595200 1527618600:
<code>--timerange=1527595200-1527618600</code></li>
</ul>
<h2 id="understand-the-backtesting-result">Understand the backtesting result<a class="headerlink" href="#understand-the-backtesting-result" title="Permanent link">&para;</a></h2>
<p>The most important in the backtesting is to understand the result.</p>
<p>A backtesting result will look like that:</p>
<div class="highlight"><pre><span></span><code>========================================================= BACKTESTING REPORT ========================================================
| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses |
|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|--------:|
| ADA/BTC | 35 | -0.11 | -3.88 | -0.00019428 | -1.94 | 4:35:00 | 14 | 0 | 21 |
| ARK/BTC | 11 | -0.41 | -4.52 | -0.00022647 | -2.26 | 2:03:00 | 3 | 0 | 8 |
| BTS/BTC | 32 | 0.31 | 9.78 | 0.00048938 | 4.89 | 5:05:00 | 18 | 0 | 14 |
| DASH/BTC | 13 | -0.08 | -1.07 | -0.00005343 | -0.53 | 4:39:00 | 6 | 0 | 7 |
| ENG/BTC | 18 | 1.36 | 24.54 | 0.00122807 | 12.27 | 2:50:00 | 8 | 0 | 10 |
| EOS/BTC | 36 | 0.08 | 3.06 | 0.00015304 | 1.53 | 3:34:00 | 16 | 0 | 20 |
| ETC/BTC | 26 | 0.37 | 9.51 | 0.00047576 | 4.75 | 6:14:00 | 11 | 0 | 15 |
| ETH/BTC | 33 | 0.30 | 9.96 | 0.00049856 | 4.98 | 7:31:00 | 16 | 0 | 17 |
| IOTA/BTC | 32 | 0.03 | 1.09 | 0.00005444 | 0.54 | 3:12:00 | 14 | 0 | 18 |
| LSK/BTC | 15 | 1.75 | 26.26 | 0.00131413 | 13.13 | 2:58:00 | 6 | 0 | 9 |
| LTC/BTC | 32 | -0.04 | -1.38 | -0.00006886 | -0.69 | 4:49:00 | 11 | 0 | 21 |
| NANO/BTC | 17 | 1.26 | 21.39 | 0.00107058 | 10.70 | 1:55:00 | 10 | 0 | 7 |
| NEO/BTC | 23 | 0.82 | 18.97 | 0.00094936 | 9.48 | 2:59:00 | 10 | 0 | 13 |
| REQ/BTC | 9 | 1.17 | 10.54 | 0.00052734 | 5.27 | 3:47:00 | 4 | 0 | 5 |
| XLM/BTC | 16 | 1.22 | 19.54 | 0.00097800 | 9.77 | 3:15:00 | 7 | 0 | 9 |
| XMR/BTC | 23 | -0.18 | -4.13 | -0.00020696 | -2.07 | 5:30:00 | 12 | 0 | 11 |
| XRP/BTC | 35 | 0.66 | 22.96 | 0.00114897 | 11.48 | 3:49:00 | 12 | 0 | 23 |
| ZEC/BTC | 22 | -0.46 | -10.18 | -0.00050971 | -5.09 | 2:22:00 | 7 | 0 | 15 |
| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 0 | 243 |
========================================================= SELL REASON STATS =========================================================
| Sell Reason | Sells | Wins | Draws | Losses |
|:-------------------|--------:|------:|-------:|--------:|
| trailing_stop_loss | 205 | 150 | 0 | 55 |
| stop_loss | 166 | 0 | 0 | 166 |
| sell_signal | 56 | 36 | 0 | 20 |
| force_sell | 2 | 0 | 0 | 2 |
====================================================== LEFT OPEN TRADES REPORT ======================================================
| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses |
|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|--------:|
| ADA/BTC | 1 | 0.89 | 0.89 | 0.00004434 | 0.44 | 6:00:00 | 1 | 0 | 0 |
| LTC/BTC | 1 | 0.68 | 0.68 | 0.00003421 | 0.34 | 2:00:00 | 1 | 0 | 0 |
| TOTAL | 2 | 0.78 | 1.57 | 0.00007855 | 0.78 | 4:00:00 | 2 | 0 | 0 |
</code></pre></div>
<p>The 1<sup>st</sup> table contains all trades the bot made, including "left open trades".</p>
<p>The 2<sup>nd</sup> table contains a recap of sell reasons.
This table can tell you which area needs some additional work (i.e. all <code>sell_signal</code> trades are losses, so we should disable the sell-signal or work on improving that).</p>
<p>The 3<sup>rd</sup> table contains all trades the bot had to <code>forcesell</code> at the end of the backtest period to present a full picture.
This is necessary to simulate realistic behaviour, since the backtest period has to end at some point, while realistically, you could leave the bot running forever.
These trades are also included in the first table, but are extracted separately for clarity.</p>
<p>The last line will give you the overall performance of your strategy,
here:</p>
<div class="highlight"><pre><span></span><code>| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 243 |
</code></pre></div>
<p>The bot has made <code>429</code> trades for an average duration of <code>4:12:00</code>, with a performance of <code>76.20%</code> (profit), that means it has
earned a total of <code>0.00762792 BTC</code> starting with a capital of 0.01 BTC.</p>
<p>The column <code>avg profit %</code> shows the average profit for all trades made while the column <code>cum profit %</code> sums up all the profits/losses.
The column <code>tot profit %</code> shows instead the total profit % in relation to allocated capital (<code>max_open_trades * stake_amount</code>).
In the above results we have <code>max_open_trades=2</code> and <code>stake_amount=0.005</code> in config so <code>tot_profit %</code> will be <code>(76.20/100) * (0.005 * 2) =~ 0.00762792 BTC</code>.</p>
<p>Your strategy performance is influenced by your buy strategy, your sell strategy, and also by the <code>minimal_roi</code> and <code>stop_loss</code> you have set.</p>
<p>For example, if your <code>minimal_roi</code> is only <code>"0": 0.01</code> you cannot expect the bot to make more profit than 1% (because it will sell every time a trade reaches 1%).</p>
<div class="highlight"><pre><span></span><code><span class="nt">&quot;minimal_roi&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="nt">&quot;0&quot;</span><span class="p">:</span><span class="w"> </span><span class="mf">0.01</span>
<span class="p">},</span>
</code></pre></div>
<p>On the other hand, if you set a too high <code>minimal_roi</code> like <code>"0": 0.55</code>
(55%), there is almost no chance that the bot will ever reach this profit.
Hence, keep in mind that your performance is an integral mix of all different elements of the strategy, your configuration, and the crypto-currency pairs you have set up.</p>
<h3 id="assumptions-made-by-backtesting">Assumptions made by backtesting<a class="headerlink" href="#assumptions-made-by-backtesting" title="Permanent link">&para;</a></h3>
<p>Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions:</p>
<ul>
<li>Buys happen at open-price</li>
<li>Sell signal sells happen at open-price of the following candle</li>
<li>Low happens before high for stoploss, protecting capital first.</li>
<li>ROI<ul>
<li>sells are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the sell will be at 2%)</li>
<li>sells are never "below the candle", so a ROI of 2% may result in a sell at 2.4% if low was at 2.4% profit</li>
<li>Forcesells caused by <code>&lt;N&gt;=-1</code> ROI entries use low as sell value, unless N falls on the candle open (e.g. <code>120: -1</code> for 1h candles)</li>
</ul>
</li>
<li>Stoploss sells happen exactly at stoploss price, even if low was lower</li>
<li>Trailing stoploss<ul>
<li>High happens first - adjusting stoploss</li>
<li>Low uses the adjusted stoploss (so sells with large high-low difference are backtested correctly)</li>
</ul>
</li>
<li>Sell-reason does not explain if a trade was positive or negative, just what triggered the sell (this can look odd if negative ROI values are used)</li>
</ul>
<p>Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will <strong>never</strong> replace running a strategy in dry-run mode.
Also, keep in mind that past results don't guarantee future success.</p>
<p>In addition to the above assumptions, strategy authors should carefully read the <a href="../strategy-customization/#common-mistakes-when-developing-strategies">Common Mistakes</a> section, to avoid using data in backtesting which is not available in real market conditions.</p>
<h3 id="further-backtest-result-analysis">Further backtest-result analysis<a class="headerlink" href="#further-backtest-result-analysis" title="Permanent link">&para;</a></h3>
<p>To further analyze your backtest results, you can <a href="#exporting-trades-to-file">export the trades</a>.
You can then load the trades to perform further analysis as shown in our <a href="../data-analysis/#backtesting">data analysis</a> backtesting section.</p>
<h2 id="backtesting-multiple-strategies">Backtesting multiple strategies<a class="headerlink" href="#backtesting-multiple-strategies" title="Permanent link">&para;</a></h2>
<p>To compare multiple strategies, a list of Strategies can be provided to backtesting.</p>
<p>This is limited to 1 ticker-interval per run, however, data is only loaded once from disk so if you have multiple
strategies you'd like to compare, this will give a nice runtime boost.</p>
<p>All listed Strategies need to be in the same directory.</p>
<div class="highlight"><pre><span></span><code>freqtrade<span class="w"> </span>backtesting<span class="w"> </span>--timerange<span class="w"> </span><span class="m">20180401</span>-20180410<span class="w"> </span>--ticker-interval<span class="w"> </span>5m<span class="w"> </span>--strategy-list<span class="w"> </span>Strategy001<span class="w"> </span>Strategy002<span class="w"> </span>--export<span class="w"> </span>trades
</code></pre></div>
<p>This will save the results to <code>user_data/backtest_results/backtest-result-&lt;strategy&gt;.json</code>, injecting the strategy-name into the target filename.
There will be an additional table comparing win/losses of the different strategies (identical to the "Total" row in the first table).
Detailed output for all strategies one after the other will be available, so make sure to scroll up to see the details per strategy.</p>
<div class="highlight"><pre><span></span><code>=========================================================== STRATEGY SUMMARY ===========================================================
| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses |
|:------------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:|
| Strategy1 | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 0 | 243 |
| Strategy2 | 1487 | -0.13 | -197.58 | -0.00988917 | -98.79 | 4:43:00 | 662 | 0 | 825 |
</code></pre></div>
<h2 id="next-step">Next step<a class="headerlink" href="#next-step" title="Permanent link">&para;</a></h2>
<p>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 <a href="../hyperopt/">how to find optimal parameters with Hyperopt</a></p>
</article>
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