APPLICATION OF T-TECHNIQUE FACTOR ANALYSIS TO THE STOCK MARKET.

Area of Science:

• Quantitative Finance
• Econometrics
• Statistical Modeling

Background:

• Analyzing historical stock price data is crucial for understanding market dynamics.
• Previous research often focuses on predicting market fluctuations using various statistical methods.

Purpose of the Study:

• To investigate the underlying factors influencing common stock price movements.
• To assess the validity of identified factors in predicting stock market behavior.
• To differentiate between analytical artifacts and genuine market signals.

Main Methods:

• Collected proportional price changes for 425 individual common stocks over 44 quarter-year periods.
• Normalized stock data and computed cross-products across time periods and stocks.
• Applied factor analysis to the cross-product matrix, yielding seven factors.

Main Results:

• Factor analysis identified seven distinct factors from the stock price data.
• Six factors were determined to be artifacts of the cross-product matrix's simplicial nature.
• A seventh factor was identified, representing general stock market strengths and weaknesses.

Conclusions:

• The majority of factors derived from this analysis are methodological artifacts.
• A single factor captures general market trends, but direct stock market prediction remains limited.
• Findings suggest caution in interpreting factors derived from cross-product matrices in financial time-series analysis.