| Keywords [eng] |
Share returns, financial results, financial ratios, Vilnius Stock Exchange, determinants, predictors, random-effects model, autoregressive models, explanatory power, forecasting accuracy, combination forecasts |
| Abstract [eng] |
68 pages, 4 figures (without 8 in Annexes), 6 tables, 53 references. Using a sample of ten companies listed on the Vilnius Stock Exchange from January 2009 to December 2021, this academic paper investigates the association between their financial results and share returns. In this research, eight main financial ratios are chosen and evaluated as determinants and predictors of stock returns. The thesis starts with a review of previous studies, followed by a description of the methodology used, data collected, and analysis of the results. The literature on share return determinants and predictors is discussed in the examination of past studies, based on which metrics representing company’s financial results are chosen, six principal hypotheses are formulated, techniques for empirical analysis are chosen, and expected results are formed. Random-effects model was found to be superior to alternative panel data regression models, and it revealed that EPS, P/E, and operating cash flow ratios have a significant relationship with share returns. Studied financial results indicators were found to account for approximately 2% of the variation in share prices, which can be explained by the importance of a company's financial results expectations for stock prices prior to the announcement of actual financial results, as well as other potential indicators (macroeconomic, financial, company-specific) having additional explanatory power. The forecasting accuracy of financial ratios was assessed by including variables under discussion as regressors into a basic ARDL model and comparing results to benchmark AR model predictions based on MSFE-measured forecast errors. Afterwards, combinations of individual forecasts were generated. None of the individual predictors reduced the forecast error of the benchmark model, while it was achieved using combination forecast approach, indicating that combination forecasts should be utilized in practice when forecasting stock returns on the Vilnius Stock Exchange. |
