From 04b65eae3c3789dbe11a4917725749df64b778c0 Mon Sep 17 00:00:00 2001 From: Matthias Date: Wed, 3 Jul 2024 17:24:48 +0200 Subject: [PATCH] docs: Fix format used for backtesting-predictions --- docs/freqai-running.md | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/docs/freqai-running.md b/docs/freqai-running.md index 553a8b698..1b721b658 100644 --- a/docs/freqai-running.md +++ b/docs/freqai-running.md @@ -73,11 +73,11 @@ Backtesting mode requires [downloading the necessary data](#downloading-data-to- --- -### Saving prediction data +### Saving backtesting prediction data To allow for tweaking your strategy (**not** the features!), FreqAI will automatically save the predictions during backtesting so that they can be reused for future backtests and live runs using the same `identifier` model. This provides a performance enhancement geared towards enabling **high-level hyperopting** of entry/exit criteria. -An additional directory called `backtesting_predictions`, which contains all the predictions stored in `hdf` format, will be created in the `unique-id` folder. +An additional directory called `backtesting_predictions`, which contains all the predictions stored in `feather` format, will be created in the `unique-id` folder. To change your **features**, you **must** set a new `identifier` in the config to signal to FreqAI to train new models. @@ -89,7 +89,6 @@ FreqAI allow you to reuse live historic predictions through the backtest paramet The `--timerange` parameter must not be informed, as it will be automatically calculated through the data in the historic predictions file. - ### Downloading data to cover the full backtest period For live/dry deployments, FreqAI will download the necessary data automatically. However, to use backtesting functionality, you need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). You need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that there is a sufficient amount of training data *before* the start of the backtesting time range. The amount of additional data can be roughly estimated by moving the start date of the time range backwards by `train_period_days` and the `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters) from the beginning of the desired backtesting time range.