Update docs

docs/advanced-backtesting.md

@@ -1,6 +1,6 @@
 # Advanced Backtesting Analysis
 
-## Analyse the buy/entry and sell/exit tags
+## Analyze the buy/entry and sell/exit tags
 
 It can be helpful to understand how a strategy behaves according to the buy/entry tags used to
 mark up different buy conditions. You might want to see more complex statistics about each buy and
@@ -10,21 +10,14 @@ determine indicator values on the signal candle that resulted in a trade opening
 !!! Note
     The following buy reason analysis is only available for backtesting, *not hyperopt*.
 
-We first need to tell freqtrade to export the signal candles for each opened trade,
-so add the following option to your config file:
+We need to run backtesting with the `--export` option set to `signals` to enable the exporting of
+signals **and** trades:
 
-```
-'backtest_signal_candle_export_enable': true,
+``` bash
+freqtrade backtesting -c <config.json> --timeframe <tf> --strategy <strategy_name> --timerange=<timerange> --export=signals
 ```
 
-We then need to run backtesting and include the `--export` option to enable the exporting of
-trades:
-
-```bash
-freqtrade backtesting -c <config.json> --timeframe <tf> --strategy <strategy_name> --timerange=<timerange> --export=trades
-```
-
-To analyse the buy tags, we need to use the `buy_reasons.py` script from
+To analyze the buy tags, we need to use the `buy_reasons.py` script from
 [froggleston's repo](https://github.com/froggleston/freqtrade-buyreasons). Follow the instructions
 in their README to copy the script into your `freqtrade/scripts/` folder.
 
@@ -39,9 +32,9 @@ backtesting with the `--cache none` option to make sure no cached results are us
 If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` file in the
 `user_data/backtest_results` folder.
 
-Now run the buy_reasons.py script, supplying a few options:
+Now run the `buy_reasons.py` script, supplying a few options:
 
-```bash
+``` bash
 python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange> -g0,1,2,3,4
 ```
 
@@ -76,5 +69,5 @@ python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange
 ```
 
 The indicators have to be present in your strategy's main DataFrame (either for your main
-timeframe or for informatives) otherwise they will simply be ignored in the script
+timeframe or for informative timeframes) otherwise they will simply be ignored in the script
 output.

mkdocs.yml

@@ -29,6 +29,7 @@ nav:
     - Data Analysis:
         - Jupyter Notebooks: data-analysis.md
         - Strategy analysis: strategy_analysis_example.md
+        - Backtest analysis: advanced-backtesting.md
     - Advanced Topics:
         - Advanced Post-installation Tasks: advanced-setup.md
         - Edge Positioning: edge.md