Calculating Population Variance in Financial Data using MySQL 8: A Practical Guide

VAR_POP: Population Variance

  1. Measuring Variability:
    • Variance measures the spread of data points within a population.
    • It shows how much individual data points deviate from the population mean.
  2. Risk Assessment:
    • VAR_POP is used in finance to assess investment portfolio risk.
    • Higher VAR_POP indicates higher risk, lower VAR_POP suggests lower risk.
  3. Hypothesis Testing:
    • VAR_POP helps statisticians determine significant differences between populations.
    • It assesses the degree of variation within each population.
  4. Model Building:
    • Data scientists use VAR_POP to build predictive models.
    • Understanding data variance helps in model selection and evaluation.
  5. Quality Control:
    • VAR_POP monitors consistency and quality in manufacturing.
    • Large variances may indicate production issues.
  6. Scientific Research:
    • VAR_POP is used to analyze data variability in various scientific disciplines.
    • For example, it can measure variance in test scores among students.

In MySQL 8:

MySQL 8 introduced the VAR_POP() function to calculate population variance.

Step 1: Create a Table and Insert Financial Data

Assuming you have a table named daily_returns for stock return data:

CREATE TABLE daily_returns (
date DATE,
stock_symbol VARCHAR(10),
daily_return DECIMAL(5, 2)

— Insert sample data
INSERT INTO daily_returns (date, stock_symbol, daily_return)
(‘2023-09-01’, ‘AAPL’, 0.02),
(‘2023-09-02’, ‘AAPL’, -0.5),
(‘2023-09-03’, ‘AAPL’, 0.75),
— Insert more data for AAPL and other stocks
(‘2023-09-01’, ‘GOOGL’, 0.2),
(‘2023-09-02’, ‘GOOGL’, 0.1),
(‘2023-09-03’, ‘GOOGL’, -0.1);
— Insert more data for GOOGL and other stocks

Step 2: Calculate Population Variance

To calculate population variance for a specific stock, use the VAR_POP() function:

VAR_POP(daily_return) AS population_variance
stock_symbol = ‘AAPL’;

This query calculates the population variance of daily returns for the ‘AAPL’ stock symbol.

Step 3: Interpretation

The result of the query provides the population variance for the ‘AAPL’ stock.

A higher population variance indicates higher volatility or risk, while a lower variance suggests lower risk.

Repeat the query for other stock symbols to calculate their population variances.

Note: To calculate sample variance instead of population variance, use the VAR_SAMP() function.

This example demonstrates how to calculate population variance for financial data in MySQL 8 using the VAR_POP() function.

Adapt this approach to analyze risk associated with different stocks or financial instruments.

About Shiv Iyer 452 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.