Working With Indicators
Many trading strategies rely on the so-called Trading indicators for example the RSI trading strategy.
To calculate an indicator you can implement your custom calculations for it and use it for your trading strategies or you could use any of the available modules for the task, one of them being the Technical Analysis framework
Start by importing the necessary modules.
Pandas for data handling:
import pandas as pd
The Technical Analysis (TA) framework:
from ta.trend import sma_indicator
ta library, we import a simple moving average indicator from the "trend" submodule.
Important
It is a good practice to assign the simulated MetaTrader5 instance which has similar methods to the native Python API into a separate (easy to remeber) variable. This variable should give us everything we need from the simulated MetaTrader5 instance.
tester = StrategyTester(tester_config=tester_config, mt5_instance=mt5, logging_level=logging.DEBUG)
sim_mt5 = tester.simulated_mt5 # extract the simulated metatrader5 from the StrategyTester object and assign it to a simple variable
logger = tester.logger # obtain the logger
Inside your main function, you want to:
Copy rates from the simulator using a simulated MetaTrader5
def on_tick():
indicator_window = 20
rates = sim_mt5.copy_rates_from_pos(symbol=symbol, timeframe=timeframe, start_pos=0, count=indicator_window)
if rates is None or len(rates) < indicator_window: # if no information was found, or less than expected rates were returned
return # prevent further calculations
Tip
When copying rates errors and zero-length data can be returned sometimes due to several reasons such as:
During the begining of a test, where the simulator is yet to see much data.
For example: Strategy tester's starting date is 01.01.2020, during the simulation (in the first hour and early minutes/seconds) we could request 100 bars in the past (before that time), this would cause all methods that returns past data like "copy_rates" methods to either return None, or less data than anticipated.
To prevent further issues, you should always check if enough data is returned before calculating your indicators.
if rates is None or len(rates) < indicator_window: # if no information was found, or less than expected rates were returned
return # prevent further calculations
If insufficient data is returned, the function should skip indicator calculation until enough data is obtained.
Indicator Calculation
def on_tick():
indicator_window = 20
rates = sim_mt5.copy_rates_from_pos(symbol=symbol, timeframe=timeframe, start_pos=0, count=indicator_window)
if rates is None or len(rates) < indicator_window: # if no information was found, or less than expected rates were returned
return # prevent further calculations
rates_df = pd.DataFrame(data=rates)
sma_indicator_values = sma_indicator(rates_df["close"], window=indicator_window)
logger.info(f"Current sma({indicator_window}) : {sma_indicator_values.iloc[-1]}") # print the last calculated value in the array
Example outputs:
StrategyTester Progress: 0%| | 0/1441 [00:00<?, ?bar/s]2026-01-02 00:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.8057
2026-01-02 01:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.81225
2026-01-02 02:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.8277
2026-01-02 03:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.83785
2026-01-02 04:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.83785
2026-01-05 00:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.833
2026-01-05 01:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.7946
2026-01-05 02:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.754
2026-01-05 03:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.7232
2026-01-05 04:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.69075
StrategyTester Progress: 2%|▏ | 33/1441 [00:00<00:04, 326.34bar/s]2026-01-05 05:00:00 | INFO | Simple Trading Robot | [bot.py:45 - on_tick() ] => Current sma(20) : 156.6599
TL;DR
Below is the full script:
import logging
from strategytester5.tester import StrategyTester
import MetaTrader5 as mt5
import pandas as pd
from ta.trend import sma_indicator
if not mt5.initialize():
raise RuntimeError("Failed to initialize mt5.")
tester_config = {
"bot_name": "Working With Indicators",
"symbols": ["USDJPY"],
"timeframe": "H1",
"start_date": "01.01.2026 00:00",
"end_date": "27.03.2026 00:00",
"modelling" : "Open price only",
"deposit": 1000,
"leverage": "1:100"
}
tester = StrategyTester(tester_config=tester_config, mt5_instance=mt5, logging_level=logging.DEBUG)
sim_mt5 = tester.simulated_mt5 # extract the simulated metatrader5 from the StrategyTester object and assign it to a simple variable
logger = tester.logger
# ---------------------- inputs ----------------------------
symbol = tester_config["symbols"][0] # it should be one among the symbols in symbols list from tester.json (config file/dictionary)
timeframe = sim_mt5.TIMEFRAME_H1 # This should be an integer so you should convert timeframe in string into integer
# ---------------------------------------------------------
def on_tick():
indicator_window = 20
rates = sim_mt5.copy_rates_from_pos(symbol=symbol, timeframe=timeframe, start_pos=0, count=indicator_window)
if rates is None or len(rates) < indicator_window: # if no information was found, or less than expected rates were returned
return # prevent further calculations
rates_df = pd.DataFrame(data=rates)
# print(rates_df.head(-10))
sma_indicator_values = sma_indicator(rates_df["close"], window=indicator_window)
logger.info(f"Current sma({indicator_window}) : {sma_indicator_values.iloc[-1]}") # print the last calculated value in the array
tester.run(on_tick_function=on_tick) # very important!