Improve wording in documentation
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@@ -459,7 +459,7 @@ The output will show a table containing the realized absolute Profit (in stake c
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### Further backtest-result analysis
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To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
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You can then load the trades to perform further analysis as shown in our [data analysis](data-analysis.md#backtesting) backtesting section.
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You can then load the trades to perform further analysis as shown in the [data analysis](data-analysis.md#backtesting) backtesting section.
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## Assumptions made by backtesting
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@@ -42,7 +42,7 @@ position for a trade. Be patient!
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### I have made 12 trades already, why is my total profit negative?
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I understand your disappointment but unfortunately 12 trades is just
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not enough to say anything. If you run backtesting, you can see that our
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not enough to say anything. If you run backtesting, you can see that the
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current algorithm does leave you on the plus side, but that is after
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thousands of trades and even there, you will be left with losses on
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specific coins that you have traded tens if not hundreds of times. We
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@@ -80,4 +80,4 @@ For any questions not covered by the documentation or for further information ab
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## Ready to try?
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Begin by reading our installation guide [for docker](docker_quickstart.md) (recommended), or for [installation without docker](installation.md).
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Begin by reading the installation guide [for docker](docker_quickstart.md) (recommended), or for [installation without docker](installation.md).
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@@ -182,7 +182,7 @@ For example, simplified math:
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* the bot buys an asset at a price of 100$
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* the stop loss is defined at -10%
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* the stop loss would get triggered once the asset drops below 90$
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* stoploss will remain at 90$ unless asset increases to or above our configured offset
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* stoploss will remain at 90$ unless asset increases to or above the configured offset
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* assuming the asset now increases to 103$ (where we have the offset configured)
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* the stop loss will now be -2% of 103$ = 100.94$
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* now the asset drops in value to 101\$, the stop loss will still be 100.94$ and would trigger at 100.94$
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@@ -436,7 +436,7 @@ class AwesomeStrategy(IStrategy):
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# ... populate_* methods
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# Set unfilledtimeout to 25 hours, since our maximum timeout from below is 24 hours.
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# Set unfilledtimeout to 25 hours, since the maximum timeout from below is 24 hours.
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unfilledtimeout = {
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'buy': 60 * 25,
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'sell': 60 * 25
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@@ -475,7 +475,7 @@ class AwesomeStrategy(IStrategy):
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# ... populate_* methods
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# Set unfilledtimeout to 25 hours, since our maximum timeout from below is 24 hours.
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# Set unfilledtimeout to 25 hours, since the maximum timeout from below is 24 hours.
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unfilledtimeout = {
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'buy': 60 * 25,
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'sell': 60 * 25
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@@ -511,9 +511,9 @@ The strategy might look something like this:
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*Scan through the top 10 pairs by volume using the `VolumePairList` every 5 minutes and use a 14 day RSI to buy and sell.*
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Due to the limited available data, it's very difficult to resample our `5m` candles into daily candles for use in a 14 day RSI. Most exchanges limit us to just 500 candles which effectively gives us around 1.74 daily candles. We need 14 days at least!
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Due to the limited available data, it's very difficult to resample `5m` candles into daily candles for use in a 14 day RSI. Most exchanges limit us to just 500 candles which effectively gives us around 1.74 daily candles. We need 14 days at least!
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Since we can't resample our data we will have to use an informative pair; and since our whitelist will be dynamic we don't know which pair(s) to use.
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Since we can't resample the data we will have to use an informative pair; and since the whitelist will be dynamic we don't know which pair(s) to use.
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This is where calling `self.dp.current_whitelist()` comes in handy.
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@@ -969,7 +969,7 @@ The following lists some common patterns which should be avoided to prevent frus
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## Further strategy ideas
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To get additional Ideas for strategies, head over to our [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.
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To get additional Ideas for strategies, head over to the [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.
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Feel free to use any of them as inspiration for your own strategies.
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We're happy to accept Pull Requests containing new Strategies to that repo.
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@@ -48,7 +48,7 @@ Sample configuration (tested using IFTTT).
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},
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```
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The url in `webhook.url` should point to the correct url for your webhook. If you're using [IFTTT](https://ifttt.com) (as shown in the sample above) please insert our event and key to the url.
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The url in `webhook.url` should point to the correct url for your webhook. If you're using [IFTTT](https://ifttt.com) (as shown in the sample above) please insert your event and key to the url.
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You can set the POST body format to Form-Encoded (default) or JSON-Encoded. Use `"format": "form"` or `"format": "json"` respectively. Example configuration for Mattermost Cloud integration:
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