Abstract. Borrowers default risk is one of the most relevant types of risk in commercial banking and its assessment is important to secure business profitability and avoid huge losses during economic turbulences. This leads to necessity to investigate topics related to assessment of borrowers' default probability and applicability of factors, which would enable to capture the newest trends of borrowers' markets. Leading economic indicators (in addition to financial and other economic indicators) are often suggested as forward-looking in scientific literature. However, there is still a discussion going on applicability of financial ratios and economic indicators. As the problem is relevant in theoretical view as well as for practitioners, this article aims to identify applicability of leading economic indicators for the estimation of default probability. Further, the qualitative criteria for factor selection were identified and used when using detailing, grouping and SWOT analysis methods. Based on current scientific literature analysis, this paper concludes that although leading economic indicators are able to capture forward-looking signals, they should be used with careful analysis of its drawbacks and in combination with financial factors in order to avoid overshooting effects. The limitation of the article is the analysis of factors based on rather theoretical analysis than estimation of quantitative criteria. This suggests that every time using leading economic indicators requires using empirical study of particular indicators' set.

Purpose of the article: Profitability is one of the most important ratios for performance measurement in any competitive commercial bank and key source to fund future working capital and investments needs. This leads to necessity to investigate topics related to profitability and applicability of factors, which would enable to capture latest trends in economy. In scientific literature, leading economic indicators (in addition to financial and lagging/coinciding economic indicators) are suggested as able to capture trends of economic development. However, there is still a discussion going on applicability of these indicators as well as on financial ratios and economic indicators. The problem is relevant from theoretical and practical point of view. Methodology/methods: Quantitative factors for forecasting commercial banks' profitability were identified and tested employing methods of detailing, grouping and quantitative analysis (GMM estimator) in empirical research Scientific aim: To identify applicability of leading economic indicators for bank's profitability forecasting. Findings: Regression analysis of models using blend of bank, industry, economic ratios improves explanatory power in both dimensions -time (higher scores received for all forecasting horizons) and alternatives (different models that use different blends of determinants). Such improvement was found for all forecasting horizons (one, two and three-quarters) resulting improved explanatory power for one, two and three quarters in comparison to models without leading economic indicators. Conclusions: Leading economic indicators can help to better capture forwardd-looking signals, however, to avoid volatility in forecasts they should be employed with careful analysis of their methodologies and in combination with bank and industry specific, lagging and coinciding economic factors.

The research examines an approach to forecast return on equity using leading economic indicators for short periods in banks. ROE is one of the most important ratios for performance measurement. Its adequacy is necessary for competitiveness, attract funding in financial markets, accumulate reserve for future turbulences, secure compliance with supervisory requirements and maintain positive signals for the market. There is still a debate in the literature on factors of commercial banks’ profitability forecasting, techniques, and most appropriate models to improve the correctness of predicting and acquiring more accurate signals for communication on targets. The problems are still relevant from both a theoretical perspective and practical implementation. This research aims to prove the necessity to include leading economic indicators for short term ROE forecasting. It conducts investigations for the relevant studies, using regression analysis, necessary tests, ascertains opportunities and limitations of using these indicators and develops a conceptual model and its assessment major Baltic banks. The results show verification of approach to forecast ROE using leading economic indicators for short periods. Such study complements signalling theory with a new approach, how to predict and acquire signal not only using economic indicators as a general group but sub-group them into coinciding, lagging and leading.