Significance of different financial ratios in predicting stock returns: NYSE - cross-industry analysis

• Název práce v češtině: Významnost různých poměrových ukazatelů pro předpovídání akciových výnosů: NYSE - analýza napříč odvětvími
• Název v anglickém jazyce: Significance of different financial ratios in predicting stock returns: NYSE - cross-industry analysis
• Klíčová slova: poměrový ukazatel, předpovídaný akciový výnos, statistická významnost, regresní model, ceteris paribus (c.p.)
• Klíčová slova anglicky: financial ratio, predicted stock return, statistical significance, regression model, ceteris paribus (c.p.)
• Akademický rok vypsání: 2018/2019
• Typ práce: bakalářská práce
• Jazyk práce: angličtina
• Ústav: Institut ekonomických studií (23-IES)
• Vedoucí / školitel: prof. Ing. Michal Mejstřík, CSc.
• Řešitel: skrytý - zadáno vedoucím/školitelem
• Datum přihlášení: 28.05.2019
• Datum zadání: 29.05.2019
• Datum a čas obhajoby: 10.06.2020 09:00
• Datum odevzdání elektronické podoby: 04.05.2020
• Datum proběhlé obhajoby: 10.06.2020
• Oponenti: Mgr. Josef Kurka

Seznam odborné literatury

Hodrick, R. (1992). “Dividend yields and expected stock returns: alternative procedures for inference and measurement.” Review of Financial Studies 5(3): pp. 357 - 386.

Ang, A. & Bekaert, G. (2006). “Stock return predictability: Is it there?” Review of Financial Studies 20(3): pp. 651 - 707.

Holthausen, R. W. & Larcker, D. F. (1992). “The prediction of stock returns using financial statement information.” Journal of Accounting and Economics 15(2): pp. 373 - 411.

Kheradyar, S.; Ibrahim, I. & Nor, F. M. (2011). “ Stock return predictability with financial ratios.” International Journal of Trade, Economics and Finance 2(5): page 391.

Penman, S. H.; Richardson, S. A. & Tuna, I. (2007). “The Book-to-Price Effect in Stock Returns: Accounting for Leverage.” Journal of Accounting Research 45(2): pp. 427 - 467.

Pontiff, J. & Schall, L. (1998). “Book-to-market ratios as predictors of market returns.” Journal of Financial Economics 49(2): pp. 141 - 160.

Basu, S. (1977). “Investment performance of common stocks in relation to their price-earnings ratios: a test of the efficient market hypothesis.” Journal of Finance 32(3): pp. 663 - 682.

Lewellen, J. (2004). “Predicting returns with financial ratios.” Journal of Financial Economics 74(2): pp. 209 - 235.

Altman, E. (1968). “Financial Ratios Discriminant Analysis and the Prediction of Corporate Bankruptcy.” The Journal of Finance 23(4): pp. 589 - 609.

Předběžná náplň práce v anglickém jazyce

Research question and motivation
The research question I am going to study is the significance of certain financial ratios in predicting stock returns on the New York Stock Exchange (NYSE) across selected industries. I will perform an analysis covering three time horizons: 3 months, one year, 3 years.

Comparing stock prices from markedly different sectors might not be appropriate. Thus, when investors decide on which stock to buy, they need to make sure they compare stocks of companies operating in similar industry. Sectors differ in many ways and so do the strategies and behavior of companies. Therefore, some of the income statement and the balance sheet items may have different importance across the industries. It implies that for each sector, certain financial ratios are more relevant when making investment decisions.

Efficient Market Hypothesis (Fama and Samuelson, 1960s) suggests that securities traded on the markets are fairly priced provided that all investors possess equal information. As an implication, no arbitrage opportunity exists and thus there are neither undervalued nor overvalued stocks available. Moreover, the hypothesis states that it is impossible to beat the market by technical or fundamental analysis.

By contrast, according to the Arbitrage Pricing Theory (Ross 1976), an arbitrage opportunity might exist in the financial markets, meaning that an undervalued stock can be purchased. In addition, Pontiff & Schall (1998) showed that stock returns can be predicted using financial ratios. It is due to the inefficiencies in the stock market.

In my thesis, I would like to examine what financial ratios are most relevant for forecasting stock returns in the following industries: airlines, computers/software, financial services, food & beverage, energy. Presumably, P/E ratio, Dividend Yield (DY) and Book-to-Market ratio (B/M) have some power in predicting stock returns because their calculations include the stock price. However, some other important ratios such as inventory turnover, current ratio or debt ratio may indicate the future moves of a stock price with respect to the industry in which the particular company operates.

Another fact influencing the earnings of an entity, and thus the stock price, is the capital structure of a firm. It deals with the division of the company´s capital into debt and equity. Debt-Equity ratio, defined as total debt over total equity, shows the firm´s leverage. Since the interest expenses decrease the corporate taxes, companies are inspired to increase the debt. The goal of the financial managers is to determine such capital structure which minimizes the weighted average cost of capital (WACC). Therefore, the Debt-Equity ratio should be also taken into account when forecasting stock returns.


Contribution
Undoubtedly, each industry has different requirements on the companies, various strength of the competition and other aspects making it impossible to compare stocks from different sectors. Therefore, I decided to analyze stock returns in five entirely distinct industries.

The main goal of my thesis is to determine for each of the selected industries the significance of different financial ratios in predicting the stock returns on the New York Stock Exchange. Based on the results of the regression models, investors will be able to calculate predicted stock returns in selected industries given the values of financial ratios used in the models.

In addition, I will state various strategies for investing in stocks for examined sectors. As the analysis covers three time horizons, the suggested investment strategies will supposedly differ for both industry type and the length of the time period.

To sum it up, my thesis should help investors make decisions when buying stocks from investigated sectors. Thanks to the results of my analysis, it will be easier for traders to assess whether a purchase of a specific share would be a reasonable investment or not.


Methodology
For each of the selected industries, I will download historical balance sheets, income statements and statements of cash flows for a sample of at least ten companies listed on the NYSE. This data is publicly available at financial websites of Yahoo Finance or CNBC.

Then I will build a model with the stock return as the dependent variable and certain financial ratios as independent variables. I intend to run a panel data regression for each industry, based on which I will test the significance of independent variables with respect to a specific time horizon.



Outline:

Abstract

Introduction
• background of the topic
• contribution of my thesis
• NYSE
• structure of the thesis

Related literature
• Efficient Market Hypothesis
• Arbitrage Pricing Theory
• Predicting stock returns using financial ratios

Presentation of various financial ratios
• P/E, B/M, DY
• Debt-Equity ratio
• Other ratios

Regression models
• airlines
• computers/software
• financial services
• food & beverage
• energy


Results interpretation
• significance of different financial ratios for a specific industry
• suggesting investment strategies

Conclusion
• summary of my thesis
• use of the results in practice
• suggestions for further research