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 uses 2015 as the base year (= 100)

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

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

No programming experience? With the Finance Toolkit MCP server, AI assistants such as Claude and ChatGPT can calculate the Share Prices for you. Just ask in plain English.

Calculate the Share Prices in Python

The Share Prices is available in the Economics module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_share_prices as shown below.

from financetoolkit import Economics

economics = Economics(start_date="2013-01-01")

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

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

Parameters

get_share_prices accepts the following parameters:

  • countries (list[str] | str | None, optional): The countries to include in the data. Defaults to None.
  • period (str | None, optional): Whether to return the monthly, quarterly or the annual data.
  • rolling (int, optional): The rolling window size to use for smoothing the data (simple moving average). Defaults to None.
  • trailing (int, optional): The trailing window size to use for summing the data over trailing periods (e.g. a trailing-4-quarter sum). Defaults to None.
  • growth (bool, optional): Whether to return the growth data or the actual data.
  • lag (int, optional): The number of periods to lag the data by.
  • standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.
  • rounding (int | None, optional): The number of decimals to round the results to. Defaults to None.
Inflation Rate Consumer Confidence Index Business Confidence Index Composite Leading Indicator House Prices Rent Prices Exchange Rates Producer Price Index Real Effective Exchange Rate Household Savings Rate Household Debt to Income Ratio Misery Index

The Economics module page introduces the module, and the sidebar lists all of its functions.

Share