Merge branch 'develop' into feat/short
This commit is contained in:
Matthias
@@ -335,7 +335,7 @@ Once the optimized parameters and conditions have been implemented into your str
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To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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Should results don't match, please double-check to make sure you transferred all conditions correctly.
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Should results not match, please double-check to make sure you transferred all conditions correctly.
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Pay special care to the stoploss (and trailing stoploss) parameters, as these are often set in configuration files, which override changes to the strategy.
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You should also carefully review the log of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss` or `trailing_stop`).
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@@ -18,6 +18,7 @@ usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH]
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[-p PAIRS [PAIRS ...]] [--eps] [--dmmp]
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[--enable-protections]
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[--dry-run-wallet DRY_RUN_WALLET]
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[--timeframe-detail TIMEFRAME_DETAIL]
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[--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
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[--export {none,trades}] [--export-filename PATH]
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@@ -55,6 +56,9 @@ optional arguments:
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--dry-run-wallet DRY_RUN_WALLET, --starting-balance DRY_RUN_WALLET
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Starting balance, used for backtesting / hyperopt and
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dry-runs.
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--timeframe-detail TIMEFRAME_DETAIL
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Specify detail timeframe for backtesting (`1m`, `5m`,
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`30m`, `1h`, `1d`).
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--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]
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Provide a space-separated list of strategies to
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backtest. Please note that ticker-interval needs to be
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@@ -62,7 +66,7 @@ optional arguments:
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this together with `--export trades`, the strategy-
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name is injected into the filename (so `backtest-
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data.json` becomes `backtest-data-
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DefaultStrategy.json`
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SampleStrategy.json`
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--export {none,trades}
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Export backtest results (default: trades).
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--export-filename PATH
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@@ -425,7 +429,12 @@ It contains some useful key metrics about performance of your strategy on backte
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- `Drawdown Start` / `Drawdown End`: Start and end datetime for this largest drawdown (can also be visualized via the `plot-dataframe` sub-command).
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- `Market change`: Change of the market during the backtest period. Calculated as average of all pairs changes from the first to the last candle using the "close" column.
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### Assumptions made by backtesting
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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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## Assumptions made by backtesting
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Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions:
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@@ -456,10 +465,30 @@ Also, keep in mind that past results don't guarantee future success.
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In addition to the above assumptions, strategy authors should carefully read the [Common Mistakes](strategy-customization.md#common-mistakes-when-developing-strategies) section, to avoid using data in backtesting which is not available in real market conditions.
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### Further backtest-result analysis
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### Improved backtest accuracy
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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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One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or viceversa?).
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So assuming you run backtesting with a 1h timeframe, there will be 4 prices for that candle (Open, High, Low, Close).
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While backtesting does take some assumptions (read above) about this - this can never be perfect, and will always be biased in one way or the other.
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To mitigate this, freqtrade can use a lower (faster) timeframe to simulate intra-candle movements.
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To utilize this, you can append `--timeframe-detail 5m` to your regular backtesting command.
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``` bash
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freqtrade backtesting --strategy AwesomeStrategy --timeframe 1h --timeframe-detail 5m
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```
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This will load 1h data as well as 5m data for the timeframe. The strategy will be analyzed with the 1h timeframe - and for every "open trade candle" (candles where a trade is open) the 5m data will be used to simulate intra-candle movements.
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All callback functions (`custom_sell()`, `custom_stoploss()`, ... ) will be running for each 5m candle once the trade is opened (so 12 times in the above example of 1h timeframe, and 5m detailed timeframe).
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`--timeframe-detail` must be smaller than the original timeframe, otherwise backtesting will fail to start.
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Obviously this will require more memory (5m data is bigger than 1h data), and will also impact runtime (depending on the amount of trades and trade durations).
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Also, data must be available / downloaded already.
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!!! Tip
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You can use this function as the last part of strategy development, to ensure your strategy is not exploiting one of the [backtesting assumptions](#assumptions-made-by-backtesting). Strategies that perform similarly well with this mode have a good chance to perform well in dry/live modes too (although only forward-testing (dry-mode) can really confirm a strategy).
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## Backtesting multiple strategies
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@@ -7,7 +7,7 @@ This page provides you some basic concepts on how Freqtrade works and operates.
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* **Strategy**: Your trading strategy, telling the bot what to do.
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* **Trade**: Open position.
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* **Open Order**: Order which is currently placed on the exchange, and is not yet complete.
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* **Pair**: Tradable pair, usually in the format of Quote/Base (e.g. XRP/USDT).
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* **Pair**: Tradable pair, usually in the format of Base/Quote (e.g. XRP/USDT).
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* **Timeframe**: Candle length to use (e.g. `"5m"`, `"1h"`, ...).
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* **Indicators**: Technical indicators (SMA, EMA, RSI, ...).
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* **Limit order**: Limit orders which execute at the defined limit price or better.
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@@ -456,7 +456,7 @@ class MyAwesomeStrategy(IStrategy):
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"only_per_pair": False
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})
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return protection
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return prot
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# ...
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@@ -827,8 +827,8 @@ After you run Hyperopt for the desired amount of epochs, you can later list all
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Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
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To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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Should results don't match, please double-check to make sure you transferred all conditions correctly.
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Should results not match, please double-check to make sure you transferred all conditions correctly.
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Pay special care to the stoploss (and trailing stoploss) parameters, as these are often set in configuration files, which override changes to the strategy.
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You should also carefully review the log of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss` or `trailing_stop`).
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@@ -1,4 +1,4 @@
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mkdocs==1.2.2
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mkdocs-material==7.2.4
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mkdocs-material==7.2.5
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mdx_truly_sane_lists==1.2
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pymdown-extensions==8.2
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