Soydas, Safak Sonmez; Cam, Alper Veli

The market value of firms is mainly affected by financial factors. Financial factors such as sales, profitability, changes in equity, debt structure, competitiveness, interest rates, and inflation affect the market value of firms positively or negatively. Additionally, even if the financial data of firms are investable, some nonfinancial factors can significantly affect the market value of firms. Many nonfinancial factors, such as political and social events, natural disasters, technological developments, government policies, investor confidence or distrust (behavioral finance), managerial changes, sectoral developments, and social media, can change the market value of firms by having a greater impact on their stock prices. Determining the level and timing of the impact of these financial or nonfinancial factors will help institutional or individual investors in their investment decisions. The primary objective of this study is to identify the financial and nonfinancial factors affecting the market value of firms operating in the aviation sector. In this context, the factors affecting the market value of the firms were analyzed using the fundamental analysis data of three firms whose stocks are traded in Borsa Istanbul, one of the emerging markets. In the study, abnormal declines in stock prices of these firms were identified, and the importance levels of the factors that caused them were tried to be revealed. In this direction, a fundamental analysis was performed using financial data obtained from the financial statements of airline companies from the years 2014-2023. The events in the world and Turkey during the relevant periods that affected the capital markets were analyzed and compared. The results of the study are important for both domestic and foreign investors who will invest based on the market value of companies operating in the aviation sector.

Cam, Handan; Cam, Alper Veli; Demirel, Ugur; Ahmed, Sana

This paper presents a sentiment analysis combining the lexicon-based and machine learning (ML)-based approaches in Turkish to investigate the public mood for the prediction of stock market behavior in BIST30, Borsa Istanbul. Our main motivation behind this study is to apply sentiment analysis to financial-related tweets in Turkish. We import 17189 tweets posted as "#Borsaistanbul, #Bist, #Bist30, #Bist100″ on Twitter between November 7, 2022, and November 15, 2022, via a MAXQDA 2020, a qualitative data analysis program. For the lexicon-based side, we use a multilingual sentiment offered by the Orange program to label the polarities of the 17189 samples as positive, negative, and neutral labels. Neutral labels are discarded for the machine learning experiments. For the machine learning side, we select 9076 data as positive and negative to implement the classification problem with six different supervised machine learning classifiers conducted in Python 3.6 with the sklearn library. In experiments, 80 % of the selected data is used for the training phase and the rest is used for the testing and validation phase. Results of the experiments show that the Support Vector Machine and Multilayer Perceptron classifier perform better than other classifiers with 0.89 and 0.88 accuracy and AUC values of 0.8729 and 0.8647 respectively. Other classifiers obtain approximately a 78,5 % accuracy rate. It is possible to increase sentiment analysis accuracy with parameter optimization on a larger, cleaner, and more balanced dataset by changing the pre-processing steps. This work can be expanded in the future to develop better sentiment analysis using deep learning approaches.

Cam, Alper Veli; Tosunoglu, Busra; Gurtay, Enes

Financial ratios obtained from past data are used in estimations of the future, which is financially uncertain, in many studies and analyses. In this regard, financial ratios can be used to determine stock values and therefore the value of the company. The objective of this study is to determine the relationship between the financial ratios of companies and stock values. Accordingly, ten year and quarterly data of16 cement factories whose stocks are traded on the Istanbul Stock Market (BIST) between years 2005-2014 are studied. In the study, current ratio, acid test ratio, liability ratio, accounts receivable turnover rate, inventory turnover rate, market value/book value are used as independent variables. Financial leverage and size of assets are used as control variables and stock value is used as the dependent variable. In accordance with the results of panel data analysis, it is seen that there is a meaningful relationship between acid-test ratio, liability ratio, market value/book value and financial leverage and between stock values.