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automatically detect maximum required data based on user fed indicators (to avoid NaNs in dataset for rolling indicators), add new config parameter for backtesting to let users increase their startup_candles to accommodate high timeframe indicators, add docs to explain all. Add new feature for automatic indicator duplication according to user defined intervals (exhibited in example strat and configs now).

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robcaulk
2022-05-31 18:42:27 +02:00
parent 9b3b08a2bb
commit 7523ed825e
7 changed files with 141 additions and 71 deletions
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docs/freqai.md
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@@ -76,6 +76,7 @@ config setup includes:
```json
"freqai": {
"startup_candles": 10000,
"timeframes" : ["5m","15m","4h"],
"train_period" : 30,
"backtest_period" : 7,
@@ -105,6 +106,7 @@ config setup includes:
### Building the feature set
!! slightly out of date, please refer to templates/FreqaiExampleStrategy.py for updated method !!
Features are added by the user inside the `populate_any_indicators()` method of the strategy
by prepending indicators with `%`:
@@ -194,7 +196,19 @@ Freqai will train 8 separate models (because the full range comprises 8 weeks),
and then backtest the subsequent week associated with each of the 8 training
data set timerange months. Users can think of this as a "sliding window" which
emulates Freqai retraining itself once per week in live using the previous
month of data.
month of data._
In live, the required training data is automatically computed and downloaded. However, in backtesting
the user must manually enter the required number of `startup_candles` in the config. This value
is used to increase the available data to FreqAI and should be sufficient to enable all indicators
to be NaN free at the beginning of the first training timerange. This boils down to identifying the
highest timeframe (`4h` in present example) and the longest indicator period (25 in present example)
and adding this to the `train_period`. The units need to be in the base candle time frame:_
`startup_candles` = ( 4 hours * 25 max period * 60 minutes/hour + 30 day train_period * 1440 minutes per day ) / 5 min (base time frame) = 1488.
!!! Note: in dry/live, this is all precomputed and handled automatically. Thus, `startup_candle` has no
influence on dry/live.
## Running Freqai