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Borsa Istanbul 100 Index, known as BIST100, is the main indicator to measure the performance of the 100 highest stocks publicly traded in Borsa Istanbul concerning market and trading volume. BIST 100 index prediction is a popular research domain for its complex data structure caused by stock price, commodity, interest rate and exchange rate effects. The study proposed hybrid models using both Genetic, Particle Swarm Optimization, Harmony Search and Greedy algorithms from metaheuristic algorithms approach for dimension reduction, and MARS for prediction.

This paper aims to model in the simplest way through metaheuristic algorithms hybridized with the MARS model the effects of stock, commodity, interest and exchange rate variables on BIST 100 during the Covid-19 pandemic period (in the process of closing) between January 2020 and June 2021.

The most suitable hybrid model was chosen as PSO & MARS by calculating the RMSE, MSE, GCV, MAE, MAD, MAPE and R2 measurements of training, test and overall dataset to check every model's efficiency. Empirical results demonstrated that the proposed PSO & MARS hybrid modeling procedure gave results both as good as the MARS model and a simpler and non-complex model structure.

Using metaheuristic algorithms as a supporting tool for variable selection can help to identify important independent variables and contribute to the establishment of more non-complex models.ing, test and overall dataset to check every model's efficiency.

Investors who can transfer their savings to investments in a well-regulated market benefit not only themselves but also economic development. Hence, it is crucial for fund owners to evaluate their stock market investment decisions. The goal of the study is to understand which model determines the asset returns most efficiently. In this regard, the validity of single and multi-index asset pricing models (capital asset pricing model-CAPM and Fama–French models) has been examined in the Turkish Stock Exchange for 2009–2020, with the quantile regression (QR) approach.

On 18 portfolios comprised of quoted stocks in the Istanbul Stock Exchange 100 (ISE-100/BIST-100), we test the CAPM, the Fama and French three factor model (FF3) and the Fama and French five factor model (FF5). Empirical analyses have been carried out via QR approach regressing the portfolios' average weekly excess returns on risk premium/market factor (Rm-Rf), firm size, book value/market value (B/M), profitability and investments factors. QR estimation has been employed since QR is more effective and provides a better definition of the distribution’s tails.

Our empirical findings have revealed that the average excess weekly returns can be explained more strongly via CAPM. Moreover, Fama and French models are expected to give more reliable result with more data, whereas the market premium would give robust results for the Turkish Capital Market.

Individuals investing in financial assets must find the price model that best fits the market. The return can be approximated in the most appropriate manner using the right variables.

The study differs from other research by comparing the asset pricing models via examining the assets' weekly returns with QR in the Istanbul Stock Exchange 100 (ISE-100).

This study investigates the impact of simultaneously replacing both midday single-price call auction and lunch break with multi-price continuous trading on intraday volatility–volume patterns as well as the intraday volatility–volume nexus.

The analysis utilises 150 m tick-by-tick transaction data related to 333 stocks traded on Borsa Istanbul Equity Market covering a period of 2 months prior to and following the change. In addition to graphic comparisons, the study uses difference in mean tests, panel-fixed generalized least squares (GLS), panel-random GLS and random-effects linear models with AR(1) disturbance regression estimations.

The results show that intraday volatility and trading volume form an inverse J-shape and are positively correlated. It is observed that the implementation of the regulation change decreased intraday volatility and increased trading volume. Additionally, the results indicate a negative volatility–liquidity and a positive volume–liquidity relationship, supporting the mixture of distribution hypothesis.

Enhanced market efficiency provides greater opportunity for investment and risk management. Investors can benefit from the findings on the intraday volatility–volume nexus, which is an indicator of informed trading, and regulatory authorities can use volume to oversight volatility.

This very rare regulation change of the simultaneous replacement of the lunch break and midday call auction with continuous trading is investigated in the context of intraday volume and volatility. This study also expands upon some important findings on the volume–volatility nexus for the Turkish Stock Market.

Social media (SM) networks offer a golden opportunity for firms that particularly engage in international activities to set up sustainable customer relationships and improve competitiveness. The purpose of this study is to examine the influence of SM adoption on the export intensity (EI) of firms listed on Borsa Istanbul (BIST) for the years 2010–2020. The authors use social media index (SMI) to measure SM adoption and firm size (FSize) as a moderator on exploring the interaction of SM and EI.

Using a sample of 150 firms listed on the BIST Industrials Index, this study explores how the adoption of SM affects EI by using panel data analysis over the period of 2010–2020.

The results indicate that the SMI has a positive and significant effect on the EI. FSize positively moderates the interaction of SMI and EI, indicating that large firms benefit more from the SM in increasing export performance. The findings reflect high potential of EI improvement through adopting right SM policies in emerging markets.

The sample covers only public companies listed on the BIST Industrials Index. Future studies may extend the coverage and include multiple emerging markets to draw generalized results for the export-oriented firms. This research also analyzes solely four SM networks, i.e. Facebook, Instagram, Twitter and YouTube. However, there are many other SM networks that firms use in online marketing in foreign markets. Finally, this research did not discuss the potential factors that could influence the use of SM in emerging market firms.

This study denotes the significant role of SM adoption on the EI of firms in an emerging market setting from the perspective of resource-based view. It presents an insightful approach in understanding the mission played by SM networks in enhancing the EI of Turkish firms. Policymakers may use the findings to develop public support programs to promote the adoption and implementation of the SM among exporting firms in emerging markets.

The study provides evidence on the effects of SM adoption on the EI from the perspective of emerging countries. It also helps to gain a deeper understanding of how different SM platforms contribute to the internationalization of firms.

The aim of this research is to examine the effect of corporate sustainability performance on financial performance and the role of agency costs and business risk in determining this effect.

This study uses the data of 83 non-financial Turkish firms listed on Istanbul Stock Exchange during the period 2014–2021. Two-step system GMM models are applied to examine the study’s hypotheses.

The results indicate a positive effect of corporate sustainability performance on financial performance, and that this effect is significant only for firms that are more likely to suffer agency costs of equity, firms with R&D expenditures and firms with lower business risk.

The results of this study confirm the importance of regulations introduced by regulators to support the sustainability initiatives for firms that have less ability to access funds required for their investments. In addition, the findings provide important insight into the role of the persistence of corporate sustainability performance in enhancing financial performance through mitigating managers' opportunistic behavior.

To the author’s knowledge, this research is one of few that examine the effect of agency costs and business risk on the corporate sustainability–financial performance relationship in emerging markets.

There has been an increase in research examining whether and how companies disclose climate change impacts and how these disclosures influence capital structure strategies in recent years. However, prior literature has generally focused on developed countries. This paper proposes to examine the impact of voluntary climate change disclosures on corporate financing decisions in an emerging economy.

The dataset includes 335 firm-year observations listed in the Borsa Istanbul (BIST) 100 manufacturing industry firms that participated in the Carbon Disclosure Project (CDP) questionnaire from 2016 to 2020, characterized by high public awareness of greenhouse gas emissions in Turkey. To accomplish this aim, two models have been constructed that link capital structure strategies with voluntary corporate climate change disclosures while controlling for firm-level attributes in terms of size, profitability, market value and free float ratio (FFR).

The significant and negative relationship between the voluntary disclosure of climate-related activities and long-term borrowing is consistent with the arguments that companies with high commitments are unlikely to reduce default risk in emerging markets. This paper also provides empirical evidence that the high size and the level of low profitability magnify this relationship between CDP and financial leverage.

The Paris Agreement seems to be a significant point where corporate lenders have become aware of the commitment of policymakers to fight climate change. The results have significant implications for both managerial strategies and environmental regulatory policy-making issues. In addition, the findings shed light on the strategic behavior of managers in the consideration of climate change risks and related transparency.

This study empirically documents the effect of ambiguity on stock returns in a major emerging market along with the ambiguity attitudes under various market conditions.

Ambiguity is measured as the volatility of return probability distributions extracted from high frequency intraday data via a method developed by Brenner and Izhakian (2018). The impact of ambiguity is then tested on stock market returns.

The results show that ambiguity is a priced factor in Turkish stock market with a positive premium that is distinct from risk premium. In contrast with the findings in the US market, the investors in Turkey show an increasing level of ambiguity aversion as expected probability of favorable returns deviate from the mean value. The investors are effectively ambiguity neutral in lateral markets. The results are robust to testing with higher moments, sentiment measures and under recession conditions.

This study contributes to empirically documenting ambiguity and ambiguity aversion in a major emerging market along with the opportunity to observe international differences in ambiguity attitudes.

This paper aims to conduct a detailed analysis of the industrial practices currently being used in the geothermal energy industry and to determine whether they are contributing to any limitations. A HAZOP-based upgradation model for improvement in existing industrial practices is proposed to ensure the removal of inefficient conventional practices. The HAZOP-based upgradation model examines the setbacks, identifies its causes and consequences and suggests improvement methods comprising of modern-day technology.

This paper proposed a HAZOP-based upgradation model for improvement in existing industrial practices. The proposed HAZOP model identifies the drawbacks brought on by conventional practices and suggests improvements.

The study reviewed the challenges geothermal power plants currently face due to conventional practices and suggested a total of 22 upgradation recommendations. From those, a total of 11 upgradation modules comprising modern digital technology and Industry 4.0 elements were proposed to improve the existing practices in the geothermal energy industry. Autonomous robots, augmented reality, machine learning and Internet of Things were identified as useful methods for the upgradation of the existing geothermal energy system.

If proposed recommendations are incorporated, the efficiency of geothermal energy generation will increase as cumulating setbacks will no longer degrade the work output.

The proposed recommendation by the study will make way for Industry 4.0 integration with the geothermal energy sector.

The paper uses a proposed HAZOP-based upgradation model to review issues in existing industrial practices of the geothermal energy sector and recommends solutions to overcome operability issues using Industry 4.0 technologies.

The purpose of this paper is to analyze the correlation between the Twitter activity of two airline companies and their stock performance at the Istanbul Stock Exchange (BIST).

Overall, 113,018 tweets were divided into 34,152 semantic and 78,866 share tweets. Semantic tweets are tweets mentioning company’s products or services and were labeled manually and with deep learning models. Share tweets were divided into 13,618 relevant and 65,248 irrelevant tweets.

A positive correlation was found between share tweets and stock performance. Semantic tweets did not display a correlation with stock performance. Relevant share tweets displayed as a strong correlation as all share tweets for one company. Also, the manual labeling of 8,000 tweets led to the discovery of many insights related to service provision in the airway industry, management of digital support channels, management of reputation on social media and using Twitter as a customer support platform.

Relevant share tweets comprise only 20% of all share tweets for one company and show the same level of correlation with stock performance. This means that the efficiency of business intelligence solutions created to monitor Twitter activity can be improved five times by saving computational power, network bandwidth and data storage.

Previous research has analyzed all Twitter activity taken together. By dividing tweets into semantic and share tweets, this paper illustrates that it is, in fact, share tweets that are correlated with stock performance and not semantic tweets.

This article analyzes the moderating role of investment opportunities, business risk and agency costs in shaping the nexus between excess cash and corporate performance.

This research uses dynamic regression models (two-step system generalized method of moments) to analyze the data related to 200 Turkish companies listed on Borsa Istanbul (BIST) for the years between 2009 and 2020.

The findings indicate that when excess cash increases, the financial performance deteriorates only for firms with lower investments compared to firms with more investments. In addition, investment contributes to better financial performance for firms that hold cash surplus, whereas the influence of investment is insignificant for firms that have insufficient cash. Agency costs of equity exacerbate the adverse impact of excess cash on financial performance while agency costs of debt mitigate this effect. Excess cash reduces the financial performance of highly leveraged firms. However, this impact becomes insignificant when debt ratio decreases. The findings also show that investment has more significant role than business risk in building the precautionary motive to hold cash.

The findings of this article are limited to the Turkish market. Future research is still needed in other emerging markets to compare the results and reveal more about the effect of excess cash on firm performance, and how other factors can change this effect.

The findings verify the increased significance of excess cash in the presence of investment opportunities and difficulties in accessing external funds. Nevertheless, the role of the equity related agency problem in reducing the benefits of cash surplus confirms the necessity of policies that support corporate governance, especially in emerging markets.

This article, according to the knowledge of author, is the first to examine the role of agency costs associated with debt and equity, and the compound effect of investment opportunities and business risk on the nexus between excess internal funds and corporate financial performance in emerging markets.