Share price indices are calculated from the prices of common shares of companies traded on national or foreign stock exchanges. They are usually determined by the stock exchange, using the closing daily values for the monthly data, and normally expressed as simple arithmetic averages of the daily data.

A share price index measures how the value of the stocks in the index is changing, a share return index tells the investor what their “return” is, meaning how much money they would make as a result of investing in that basket of shares.

A price index measures changes in the market capitalisation of the basket of shares in the index whereas a return index adds on to the price index the value of dividend payments, assuming they are re-invested in the same stocks. Occasionally agencies such as central banks will compile share indices.

This is an index based on 2015 = 100.

See definition: https://data.oecd.org/price/share-prices.htm

Also known as: stock market index, equity index, market performance.

Share Prices in Python or via the MCP

Install the Finance Toolkit with:

pip install financetoolkit -U

Then call get_share_prices as shown below.

from financetoolkit import Economics

economics = Economics(start_date="2013-01-01", end_date="2025-12-31")

economics.get_share_prices(countries=['Turkey', 'Belgium', 'Australia'], period='yearly')

Or, after setting up the Finance Toolkit MCP, ask:

How did share prices in Turkey, Belgium and Australia develop each year from 2013 to 2025?

Which returns:

  Turkey Belgium Australia
2013 96.6029 74.3936 92.3054
2014 93.2354 87.8382 98.611
2015 100 100 100
2016 95.6644 95.2324 96.0699
2017 122.746 101.514 105.648
2018 126.263 96.5515 109.205
2019 123.056 92.6847 117.326
2020 140.511 77.8758 111.188
2021 187.146 91.6789 130.475
2022 369.298 93.0484 128.367
2023 785.903 97.9468 131.286
2024 1190.71 106.289 143.996
2025 1272.13 115.355 154.686

Parameters

get_share_prices accepts the following parameters.

ParameterTypeDescriptionExample
countrieslist[str] | str | NoneThe countries to include in the data. Defaults to None.["United States", "Germany"]
periodstr | NoneWhether to return the monthly, quarterly or the annual data. Defaults to None, which is quarterly when the Economics class was initialized with quarterly=True and monthly otherwise."quarterly"
rollingintThe rolling window size to use for smoothing the data (simple moving average). Defaults to None.4
trailingintThe trailing window size to use for summing the data over trailing periods (e.g. a trailing-4-quarter sum). Defaults to None.4
growthboolWhether to return the growth data or the actual data. Defaults to False.True
lagintThe number of periods to lag the data by. Defaults to 1.4
standardizeboolWhether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.True
roundingint | NoneThe number of decimals to round the results to. Defaults to None.2
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