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Unexpected bankruptcies of companies cause significant damage to company partners, investors, employees, countries, commercial and financial creditors. In this context, the financial failure risks should be constantly measured and controlled. However, it is important to constantly check the validity of financial models that measure the risk of the financial failure of companies. Because the higher the validity rates of these models, the higher the probability of investors and researchers to make the right decision according to the results obtained from these models. In this context, validity tests widely used in the literature, namely Altman (1968), Springate (1978), Ohlson (1980), Fulmer (1984), Zmijewski (1984), Canada (1987) and Grove (2001) models, were applied in this study. The study sample comprises of 8 energy companies in the US markets, which were officially declared bankrupt between 2018 and 2020. The universe of the study includes all companies and excludes financial institutions, financial companies and insurance companies. The research results have shown that Springate and Altman models best predict the financial failure risk of companies. However, Canadian and Fulmer models are the second group of models with the highest performance. The overall accuracy rate of the Grover model is also slightly above the overall average, while the overall accuracy rate of the Zmijewski and Ohlson models is below the general average., Firmaların beklemedik iflasları, şirket ortaklarına, yatırımcılara, çalışanlara, devlete, ticari ve finansal alacaklılara büyük zarar vermektedir. Bu kapsamda, şirketlerin finansal başarısızlık risklerinin sürekli ölçülerek kontrol edilmesi gerekir. Fakat firmaların finansal başarısızlık riskini ölçen finansal modellerin de geçerliliklerinin sürekli olarak kontrol edilmesi önemlidir. Çünkü bu modellerin geçerlilik oranları ne kadar yüksek olursa, yatırımcı ve araştırmacıların bu modellerden elde edilen sonuçlara göre doğru karar verme ihtimalleri de o kadar yükselmiş olur. Bu bağlamda, bu çalışmada literatürde yaygın olarak kullanılan Altman (1968), Springate (1978), Ohlson (1980), Fulmer (1984), Zmijewski (1984), Kanada (1987) ve Grove (2001) modellerinin geçerlilik testleri yapılmıştır. Çalışmanın örneklemi, ABD piyasalarında yer alan ve 2018 ile 2020 yılları arasında resmi olarak iflası açıklanan 8 adet enerji işletmesinden oluşmaktadır. Çalışmanın evreni, finansal kuruluşlar, mali şirketler ve sigorta şirketleri dışında kalan tüm şirketlerdir. Araştırma sonuçlarına göre, Springate ve Altman modellerinin şirketlerin finansal başarısızlık riskini en iyi tahmin eden modeller olduğu görülmüştür. Bununla birlikte Kanada ve Fulmer modelleri başarı performansı en yüksek ikinci grup modellerdir. Grover modelinin de başarı ortalaması genel ortalamanın biraz üzerindedir. Bununla birlikte, Zmijewski ve Ohlson modellerinin genel başarı oranı genel ortalamanın altında kalmıştır.

Financial inclusion is defined as the access of households and firms to beneficial and reasonably priced financial products and services which are in line with their necessities. These could be financial transactions, transfers, savings, and loans. After narrowing down the definition, it then measures financial inclusion by using indexation technique. A major contribution of this study is the development of a measure of financial inclusion via formation of three indices, namely financial access index, firm-level and household-level financial usage indices. These three indices capture different aspects of financial inclusion, which is comprised of access to financial services by both households and firms in addition to effective use of these services. Based on Global Findex database and the Enterprise Survey database collected by the World Bank, Financial Access database collected by the International Monetary Fund the study introduces measures of household-level and firm-level inclusion, with placing Europe and Central Asia in a historical and cross-country perspective. By using Panel and Ordinary Least Squares regression analysis, it analyzes the impact of financial inclusion on two important macroeconomic variables, namely growth and inequality. Moreover, it focuses particularly on the ECA region and analyzes the dynamics in the region. The study aims at documenting the status of financial inclusion in ECA, while shedding light on the impact of financial inclusion on growth and inequality. It concludes that, in line with the contemporary literature, financial inclusion enhances growth and reduces inequality with better access to resources to finance both consumption and investment. According to the article’s findings, the positive impact of financial inclusion on growth is significant in the ECA region.

The purpose of this research is to contribute to the academic field by demonstrating the relationship between stock related Twitter messages, their frequencies, sentiment analysis; stock return, volume, and volatility of Dow Jones Index and BIST30 & BIST100 Index. In this study, The Multinomial Naive Bayes Text Classifier is used as methodology since it is the most conventional method for text classification based on previous research. Using computational linguistics methods, 138.070 English and 34.632 Turkish tweets have been analyzed on a daily basis for a period of 8 months. The results demonstrated a strong relationship between tweets and their impact on the market. Moreover, according to results, there is a positive correlation between the number of retweets and BIST Volume lag-1 and lag+1. In addition, this article confirms that stock microblogs contain valuable information for investors and it can be an assistance in predicting the future market index.