Building and Backtesting an RSI Strategy with OctoBot Script
Summary
This guide introduces OctoBot Script, an alpha-stage Python framework for writing automated trading strategies and running backtests. Its example uses the relative strength index (RSI) to identify potential buy entries: it calculates RSI from historical close prices, records the candle times when RSI falls below a configurable threshold, and enters a position when the current time matches one of those entries. The example sets a take profit and stop loss, plots the indicator, and generates a backtest report.
The sample uses BTC/USDT daily data and demonstrates configuration, data retrieval, asynchronous strategy execution, and report generation. It is an implementation example rather than evidence of profitability: the page provides no reported backtest results or comparison against a benchmark. The framework is explicitly identified as alpha, and the sample's RSI threshold and exit settings are illustrative parameters, not established recommendations. The guide also notes a Python version requirement for installation.
Key ideas
- The example enters long positions when RSI falls below a configured threshold.
- It precomputes qualifying candle times from historical closes and checks them during strategy execution.
- The sample attaches a take profit and stop loss to each market entry.
- OctoBot Script supports asynchronous backtesting and plotting, but the framework is described as alpha.
- The page demonstrates implementation and reporting without providing evidence of strategy performance.
Tags
Full text
# OctoBot Script
---
title: "Commencer le scripting"
description: "Exploitez la puissance du framework OctoBot au sein de vos propres stratégies de trading scriptées en Python tout en gardant la simplicité d'un Pine Script TradingView."
sidebar_position: 17
---
# OctoBot Script
:::note
Pour les utilisateurs d'
<a href="https://github.com/Drakkar-Software/OctoBot-script" rel="nofollow">OctoBot Script</a>
.
:::
:::info
La traduction française de cette page est en cours.
:::
## Le framework de trading par script basé sur OctoBot
> OctoBot Script est dans une version alpha
OctoBot Script vous permet d'exploiter la puissance du framework OctoBot tout en gardant la simplicité d'un Pine Script TradingView.
With OctoBot Script, automatisez vos stratégies de trading en utilisant vos scripts hautement optimisés
- Que ce soit à partir de vos idées de stratégies scriptées, comme sur le Pine Script de <a href="https://www.tradingview.com/?aff_id=27595" rel="nofollow">TradingView</a>
- Ou en utilisant une stratégie avancée basée sur l'IA
## Installer OctoBot Script depuis pip
> OctoBot Script nécessite **Python 3.10**
```{.sourceCode .bash}
python3 -m pip install OctoBot wheel appdirs==1.4.4
python3 -m pip install octobot-script
```
## Exemple de script: une strategie RSI
Dans cet exemple, OctoBot script permet de créer rapidement une stratégie de trading basée sur le <a href="https://www.investopedia.com/terms/r/rsi.asp" rel="nofollow">RSI</a> comprenant:
- une prise de profit à 25% de gains
- un stop loss à 15% de perte
```python
async def rsi_test():
async def strategy(ctx):
# Will be called at each candle.
if run_data["entries"] is None:
# Compute entries only once per backtest.
closes = await obs.Close(ctx, max_history=True)
times = await obs.Time(ctx, max_history=True, use_close_time=True)
rsi_v = tulipy.rsi(closes, period=ctx.tentacle.trading_config["period"])
delta = len(closes) - len(rsi_v)
# Populate entries with timestamps of candles where RSI is
# below the "rsi_value_buy_threshold" configuration.
run_data["entries"] = {
times[index + delta]
for index, rsi_val in enumerate(rsi_v)
if rsi_val < ctx.tentacle.trading_config["rsi_value_buy_threshold"]
}
await obs.plot_indicator(ctx, "RSI", times[delta:], rsi_v, run_data["entries"])
if obs.current_live_time(ctx) in run_data["entries"]:
# Uses pre-computed entries times to enter positions when relevant.
# Also, instantly set take profits and stop losses.
# Position exists could also be set separately.
await obs.market(ctx, "buy", amount="10%", stop_loss_offset="-15%", take_profit_offset="25%")
# Configuration that will be passed to each run.
# It will be accessible under "ctx.tentacle.trading_config".
config = {
"period": 10,
"rsi_value_buy_threshold": 28,
}
# Read and cache candle data to make subsequent backtesting runs faster.
data = await obs.get_data("BTC/USDT", "1d", start_timestamp=1505606400)
run_data = {
"entries": None,
}
# Run a backtest using the above data, strategy and configuration.
res = await obs.run(data, strategy, config)
print(res.describe())
# Generate and open report including indicators plots
await res.plot(show=True)
# Stop data to release local databases.
await data.stop()
# Call the execution of the script inside "asyncio.run" as
# OctoBot script runs using the python asyncio framework.
asyncio.run(rsi_test())
```
## Rapport généré
## Rejoignez la communauté
Nous avons récemment créé un canal Telegram dédié au script OctoBot.
<a href="https://t.me/+366CLLZ2NC0xMjFk" rel="nofollow">Telegram News</a>Shown in full with attribution under the source's licence. Licence: GPL-3.0
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.