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The development of machine learning-based forecasting approaches in financial markets offers advantages such as rapid and precise decision-making, complexity management, risk mitigation, algorithmic trading, and reduction of emotional biases. These methods can create a competitive edge for financial success through their continuous learning and adaptation capabilities. This article presents a memory-based machine learning approach for predicting the Borsa Istanbul (BIST) 100 index, utilizing popular architectures like Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) for sequential data analysis. The models demonstrated low losses in training and validation phases and successfully followed the general trends of the BIST 100 index. However, they showed deviations from actual values during market volatility, highlighting uncertainties and the limits of their generalization abilities. Predictions were based on patterns in the training dataset but indicated increasing uncertainty over time. This study has the potential to provide significant insights into the application of machine learning algorithms on financial data. [ABSTRACT FROM AUTHOR]

With the high-frequency trading process, which is a subclass of algorithmic trading transactions, intraday information has increasing importance. Traditional statistical methods often fall short in capturing the intricate patterns and volatility inherent in such high-frequency data. In contrast, artificial neural network (ANN) models demonstrate remarkable capability in handling these challenges, and vector autoregressive (VAR) models provide insights into short-term relationships among variables. This study highlights the importance of using both ANN and VAR models for processing these short time intervals. BIST100 index, which is the main index of Borsa Istanbul, is predicted with two different models in different data ranges with ANN models and VAR models. Both generated ANN models successfully complete the training stages, with extremely high precision, and exhibit exceptionally low error values in their predictions. Although both models are effective, the evidence favors the model evaluated using 5-min data for both the training and prediction phases of ANN models. However, the relative importance of 15-min data in explaining the variation of BIST100 is higher. Moreover, the VAR model results indicate that the short-term relationship between variables can be influenced by the range of data and the 15-min interval data of the variables play a more significant role in explaining the BIST100 index over the longer term. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economics & Administrative Sciences / Afyon Kocatepe Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of Afyon Kocatepe University, Faculty of Business Administration and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Çankırı Karatekin University Journal of the Faculty of Economics & Administrative Sciences is the property of Cankiri Karatekin University, Faculty of Economics & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Çalışmanın amacı, Borsa İstanbul'da (BIST) işlem gören enerji şirketlerinin 2022 dönemi finansal performansının hibrit ÇKKV yöntemleri kullanılarak araştırılmasıdır. Bu çalışmada, seçilen şirketlerin finansal performansını incelemek için LOPCOW-CRITIC ve CoCoSo'ya dayalı yeni bir model önerilmektedir. Kriterler bu alanda daha önce yapılan araştırmalara dayanarak belirlenmiştir. Finansal performans değerlendirmesi, on üç kriter ve yirmi iki şirket dikkate alınarak gerçekleştirilmiştir. Kriterlerin ağırlıklarının hesaplanmasında LOPCOW ve CRITIC olmak üzere iki farklı objektif ağırlıklandırma yöntemi kullanılmıştır. Daha sonra kriter ağırlıkları toplu ağırlıklandırma yöntemi (AWM) kullanılarak birleştirilmiştir. AWM yönteminden elde edilen sonuçlara göre stok devir hızı ve ATR sırasıyla en önemli ve en az önemli kriter olarak bulunmuştur. Kriterlerin ağırlıkları belirlendikten sonra alternatifler CoCoSo yöntemi kullanılarak sıralanmıştır. CoCoSo yönteminden elde edilen sonuçlara göre MAGEN ve PAMEL'in sırasıyla en yüksek ve en düşük finansal performansa sahip olduğu tespit edilmiştir. Ayrıca önerilen model duyarlılık analizi kullanılarak test edilmiştir. Önerilen modelin sağlamlığı ve güvenilirliği on farklı senaryo altında izlenmiştir. Genel sonuçlar, 2022 yılında MAGEN, ZEDUR ve KARYE'nin en yüksek finansal performansa sahip olduğunu, en düşük finansal performansı ise sırasıyla ARASE, AKSEN ve PAMEL'in gösterdiğini ortaya koymuştur.

Copyright of Journal of Selçuk University Social Sciences Vocational School is the property of Journal of Selcuk University Social Sciences Vocational School and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Finance Letters / Maliye Finans Yazıları Dergisi is the property of Maliye Finans Yazilari Yayimcilik Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study is to examine the cash flows generated by the companies in the BIST 100 Index as a result of their operating, investing, and financing activities. For this aim, the data of 79 companies from 2005 to 2021 have been used, and the relevant cash flows have been analyzed according to the sectors. Despite the fact that cash flows in the manufacturing sector have increased and decreased over the years, the most obvious break in all cash flows occurred in 2009, with a sharp decrease. Cash flows in the holding and investment sector have not followed a trend over time. Over the years, all cash flows in technology sector' companies have not followed a regular trend. Although similar trends have been discovered in some cases based on the type of cash flows (from operating, investing, and financing activities) in the sectors examined, it has also been determined that there are some cases with opposite cases. Lastly, regardless of the industry in which companies operate, cash flow is critical, and companies will struggle to continue operations without sufficient cash flows. [ABSTRACT FROM AUTHOR]

Copyright of Turkish Journal of Business Ethics is the property of Economic Enterprise & Business Ethics Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Borçlanma aracı olarak kullanılan sendikasyon kredileri, farklı ülkelerden çok sayıda bankanın katılabileceği özel bir kredi sözleşmesi türüdür. Bu kredileri, yatırımcılar ve diğer ekonomik birimler fon taleplerini karşılamak için kullanmakta ve uluslararası piyasalardan elde edilen bir kaynak olarak görülmektedir. Uluslararası piyasalardan alınan bu krediler Türk bankacılık sisteminde 2004 yılından itibaren önem kazanmaya başlamıştır. Bu çalışmada da Ocak 2013 – Kasım 2022 dönemleri arasında Türkiye’de kullanılan sendikasyon kredileri ile dış ticaret hacmi, reel döviz kuru ve ulusal BIST100 endeks arasındaki ilişkinin belirlenmesi amaçlanmaktadır. Ayrıca çalışmada Türkiye’de Covid-19 salgınının etkisini dikkate almak için vakaların ortaya çıktığı 2020 Mart ayının sonraki dönemlerine kukla değişken eklenmiştir. Değişkenler arasındaki ilişkiyi belirlemek için Johansen eşbütünleşme testi ve hata düzeltme modeline (VECM) bağlı Granger nedensellik testi uygulanmıştır. Ampirik bulgularda, Johansen eşbütünleşme yaklaşımı sonucunda değişkenler arasında uzun dönemde ilişkinin varlığına ulaşılmıştır. Granger nedensellik testi sonuçlarına göre sendikasyon kredileri ile dış ticaret hacmi ve reel döviz kuru arasında çift yönlü nedensellik ilişkisinin olduğuna ulaşılmıştır. BIST100 endeksinden ise sendikasyon kredisine doğru tek yönlü nedensellik ilişkisi olduğu gözlemlenmiştir.

Stratejik yönetim alanının odak noktası sürdürülebilir rekabet avantajı elde ederek rakiplere kıyasla üstün bir performans sergileyebilmektir. Alanda iki kutbu temsil eden Pozisyon Okulu (PO) ve Kaynaklara Dayalı Yaklaşım (KDY) üstün performans için örgütlerin iyi bir stratejiye sahip olmaları gerektiği konusunda hemfikirdir. Ancak iyi bir stratejinin ne olduğu konusunda aralarında pek çok tartışmalı alan mevcuttur. Strateji olgusu için önemli unsurlardan biri olan misyon ifadesinin nasıl olması gerektiği de bu tartışmalı alanlardan birisidir. PO misyonun endüstri pozisyonuna göre oluşturulması gerektiğini söylerken KDY ise misyonun kaynak ve kabiliyetlerden hareketle oluşturulması gerektiğini belirtmektedir. Bu çalışma ise Türkiye’de yer alan firmaların kendilerini tanımlarken endüstriye mi yoksa kaynaklara ve kabiliyetlere mi yoğunlukla odaklandığı sorusunu yanıtlamayı amaçlamaktadır. Ayrıca sektörel farklılıkların rolünü sorgulamak da amaçlanmıştır. Nitel araştırma olarak tasarlanan bu çalışmada BIST100’de yer alan firmaların misyon ifadeleri içerik analizine tabi tutulmuştur. Sonuçlar firmalarının misyon ifadelerini yoğunlukla PO’nun görüşlerine göre şekillendirdiğini ancak misyon ifadeleri oluşturulurken PO ve KDY görüşleri arasında geçişler yapıldığını göstermiştir. Çalışmanın bir diğer bulgusu ise sektörel farklılıkların misyon ifadelerinde vurgulanan temaların yoğunluklarının farklılaşmasında rol aldığıdır.

Market efficiency is of great importance to many investors, policy makers, as well as researchers. It provides them with information regarding the market and acts as a guide in their decision-making process. For this reason, there have been extensive amount of research done through the years. However, the World has witnessed several major events in the last couple of decades, which has been of great importance for financial markets, having both direct and indirect impacts. The Global Financial Crisis of 2008 and the COVID-19 pandemic can be the two most important events the World has experienced. Although past research shows that the impact of both events on the efficiency of the stock markets were looked at in separate studies, there is lack of studies involving both major events and analysing how the efficiency of the stock market is changing between these periods. The aim of this study is to analyse the weak-form efficiency of the Turkish stock market and how it has evolved over time. There are 4 different data sets used to observe the changes in market efficiency, with full sample ranging from February 1988 to September 2022. Monthly closing prices of the BIST100 Index are analysed using both the traditional linear Augmented Dickey-Fuller unit root test and 5 different non-linear unit root tests. Results show that different tests have different strengths in capturing the stationarity and due to the LNV test Turkish Stock Market was found not to be weak form efficient.

This study utilized financial and non-financial data from 233 companies listed in the Borsa Istanbul BIST SINAI Index from 2010 to 2020. The XGBOOST machine learning algorithm was employed to predict whether these companies would encounter financial distress. The machine was trained using supervised learning, with 80% of the data used for training and 20% for testing purposes. Financial ratios were utilized as independent variables in predicting financial distress. The 25 financial ratios can be categorized into four main headings: Liquidity, Financial Structure, Activity, and Profitability Ratios. Furthermore, the model allowed for individual analysis of each company. In predicting whether companies would experience financial distress, the maximum F1 score (85.1%), recall (84.5%), precision (85.7%), and accuracy (91.6%) were achieved. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the effects of the macroeconomic factors to the movements of the asset returns of the banks in Turkey in terms of systemic risk from 2005 to 2018. In the study, Independent Component Analysis is applied for extracting driving factors of the asset returns of Turkish banks by decomposing the returns into its components. After examining the relationship between the independent components and the macroeconomic variables, the results conclude that one component shows strong similarities with the well-known stock market index of Turkey, namely the BIST100. Besides, the BIST100 is observed as the most important macroeconomic indicator affecting the movements of the asset returns. From systemic risk perspective, the BIST100 and the exchange rate from US dollar to Turkish lira are interpreted as two macro factors that contribute to the systemic risk of Turkish banks. When it is reviewed the regression results of the estimated independent components with the macroeconomic variables, it is found that while the BIST100 affects the asset returns of Turkish banks on its own, three macroeconomic factors (the credit default swap spreads of Turkey, the exchange rate and volatility) jointly affect the banks by creating a chain effect. [ABSTRACT FROM AUTHOR]

Copyright of Bursa Uludağ Journal of Economy & Society / Bursa Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi is the property of Uludag Universitesi Iktisadi ve Idari Bilimler Fakultesi Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bu çalışmada BIST100 hisse senedi endeksinin faiz, döviz kuru ve altın fiyatları açısından duyarlılığının belirlenmesi amaçlanmıştır. Bu amaçla 4 Ocak 2000-28 Haziran 2021 dönemini kapsayan günlük veriler kullanılarak tüm örneklem dönemine ilişkin değişkenler arasındaki uzun ve kısa dönem ilişkilerinin COVID-19 pandemi dönemi ile kıyaslandığında nasıl seyrettiği Johansen-Juselius eşbütünleşme analizi, Granger nedensellik testi, varyans ayrıştırma ve etki-tepki analizleri uygulanarak araştırılmıştır. Elde edilen bulgulara göre, eşbütünleşme analizi için bağımlı değişkenin BIST100 endeksi getirisi olduğu durumda değişkenler arasında bir uzun dönem ilişki bulunmuş olup; altın fiyatlarının BIST100 üzerinde anlamlı bir etkisi bulunamamıştır. Granger nedensellik analizi sonuçları ise ele alınan dönem için BIST 100 endeksi ile hem döviz kuru hem de faiz serisi arasında çift yönlü bir nedensellik ilişkisinin varlığını saptarken, BIST100 endeksinden altın fiyatlarına doğru tek yönlü bir nedensellik ilişkisi ortaya koymuştur. COVID-19 dönemi ele alındığında %5 anlamlılık düzeyinde seriler arasında bir uzun dönem ilişkisi bulunamamış olup, %10 anlamlılık düzeyinde bulunan bir eşbütünleşik ilişki için ise hata düzeltme mekanizması yalnızca bağımlı değişkenin faiz oranları olduğu durumda çalışmıştır. Ayrıca bu dönemde genel dönemdeki kısa dönem ilişkilerinin tersine BIST100 endeksindeki değişimi serinin kendisinden sonra en çok açıklayan değişkenin altın fiyatları olduğu saptanmış olup, altın fiyatlarından BIST100’e doğru ve BIST100’den faiz oranlarına doğru tek yönlü nedensellik ilişkileri elde edilmiştir.

Copyright of International Journal of InformaticsTechnologies is the property of Institute of Informatics, Gazi University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bu makalenin amacı, döviz kurunun hisse senedi getirileri üzerindeki etkisinin incelenmesidir. Bu doğrultuda, döviz kurunun Borsa İstanbul (BIST) 100 Endeksi’nde finans sektörünü temsil eden seçilmiş şirketlerin performansı üzerindeki etkisi COVID-19 pandemi öncesi dönemde (15/09/2019-10/03/2020) ve pandemi sonrası dönemde (11/03/2020-09/10/2020) karşılaştırmalı olarak incelenmiştir. Çalışmada değişkenler arasındaki ilişki üç farklı regresyon modeli (Adler ve Dumas Modeli, Jorion Modeli, Choi ve Prasad Modeli) ile tahmin edilmiştir. Elde edilen bulgulara göre, pandemi öncesi dönemde döviz kurundaki artış, finans sektöründeki hisse senetlerinin ortalama getirisinde azalışa neden olmuştur. Bulgulara göre pandemi öncesi dönemde değişkenler arasındaki ilişki geleneksel yaklaşımla daha uyumludur. Pandemi sonrası dönemde ise değişkenler arasındaki ilişki istatistiksel olarak anlamsızdır. Pandemi sonrası dönemde döviz kurundan hisse senedi getirilerine doğru etkinin anlamsız olması, hisse senedi getirilerinin farklı faktörlerden etkilendiğine işaret etmiştir.

Market efficiency is of great importance to many investors, policy makers, as well as researchers. It provides them with information regarding the market and acts as a guide in their decision-making process. For this reason, there have been extensive amount of research done through the years. However, the World has witnessed several major events in the last couple of decades, which has been of great importance for financial markets, having both direct and indirect impacts. The Global Financial Crisis of 2008 and the COVID-19 pandemic can be the two most important events the World has experienced. Although past research shows that the impact of both events on the efficiency of the stock markets were looked at in separate studies, there is lack of studies involving both major events and analysing how the efficiency of the stock market is changing between these periods. The aim of this study is to analyse the weak-form efficiency of the Turkish stock market and how it has evolved over time. There are 4 different data sets used to observe the changes in market efficiency, with full sample ranging from February 1988 to September 2022. Monthly closing prices of the BIST100 Index are analysed using both the traditional linear Augmented Dickey-Fuller unit root test and 5 different non-linear unit root tests. Results show that different tests have different strengths in capturing the stationarity and due to the LNV test Turkish Stock Market was found not to be weak form efficient. [ABSTRACT FROM AUTHOR]

Recently, interest in digital currencies has been increasing, one of the innovations brought by technology in money markets. Its popularity is increasing day by day due to its ability to perform leveraged transactions, its promise of profit in a short time, and its ease of buying and selling. In this study, it is aimed to determine the relationship between Bitcoin and the BIST100 index, which is one of the financial variables, since it has the highest volume among cryptocurrencies. In this direction, this relationship was analyzed in the Eviews11 package program using daily data between 15.04.2011 and 25.06.2021. For this purpose, in the first stage of the analysis, whether the variables contain a unit root was tested with traditional unit root tests. Then, to test the cointegration relationship between the series, Engel-Granger Cointegration Analysis and as causality tests, the Engel-Granger Causality Test and Toda-Yamamoto Causality Tests were used. In the light of these analyzes, according to the results of the cointegration test, it has been determined that the relationship between the Bitcoin-BIST100 index is cointegrated. While the Engel-Granger Causality test confirmed that there was a two-way causality relationship from BIST100 index to Bitcoin prices, according to the results of the Toda-Yamamoto Causality test, it was significant at the 5% significance level from BIST100 index to Bitcoin prices, and a one-way Toda-Yamamoto causality relationship was observed. Finally, in the conclusion part of the study, all these findings were evaluated together with the recommendations. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the relationship between stock and Turkey in particular macroeconomic variables. In this study, the relationship between GDP, exchange rate (Dollar / TL), interest rate, and inflation and the return of the BIST100 Index were determined empirically for this purpose. The quarterly data set used in the study covers between 2003: Q1 and 2018: Q3. In the analysis, as well as the cointegration test which used in order to determine the existence of the relationship between the variables, the causality test were used to determine the direction of this relationship, and the variance decomposition test was used to determine where the shock caused in the variables originated. As a result of the analysis, a long-term cointegrated relationship between BIST100 and macroeconomic factors has been reached according to the break in trend model. In addition, statistically significant bidirectional causality between BIST 100 and interest rate; unidirectional causalities running from BIST100 to GDP and from BIST 100, GDP, and interest rate to inflation, interest rate to exchange rate are detected as a result of causality tests. According to the latest analysis of variance decomposition, the results obtained in the study are in line with the expectations and the literature. Accordingly, it is seen that the interest rate and exchange rate have the strongest long-term explanatory relations with BIST100. In the light of the findings, it can be said that there are important implications for both investors and policymakers.

1984 yılında oluşturulan üst kademe (upper echelons) kuramı şirketlerin üst yönetim ekiplerinin özelliklerinin şirket performansına etkisini gündeme taşımıştır. Bu konuda birçok araştırma yapılmış olsa da Türkiye’de yapılmış detaylı bir çalışma bulunmamaktadır. Bu çalışmada, Türkiye’deki büyük ölçekli firmaların önemli bir kısmını içeren BİST100 endeksindeki şirketlere ait 2015-2019 yıllarını kapsayan veri seti kullanılarak şirket CEO’larının özelliklerinin şirket performansına etkisi incelenmiştir. Araştırmadan elde edilen sonuçlara CEO yaşı, CEO ikiliği, CEO’nun aynı firmada çalıştığı süre ve CEO’nun aynı firma içinden atanmasının şirket performansına etkisi bulunmamaktadır. CEO’nun mevcut pozisyonda geçirdiği sürenin ve toplam CEO olarak çalışma tecrübesinin istatistiksel olarak anlamlı bir şekilde şirket performansına olumlu yansıdığı görülmüştür. Araştırmada önemli bulgular olarak (1) BİST100’deki şirketlerin %84’ünün CEO pozisyonuna içerden atama yaptıkları, (2) içerden atanan CEO’ların aynı pozisyonda dışarıdan atanan CEO’lara kıyasla üç kat daha fazla kaldığı ve (3) CEO olarak çalışılan süre ile elde edilen performans arasında pozitif ilişki olduğu tespit edilmiştir.

Copyright of Journal of Abant Social Sciences / Abant Sosyal Bilimler Dergisi is the property of Journal of Abant Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The housing market and the stock market are the most important markets for Turkey. Therefore, these markets have a sensitive place in the economic growth of countries. This sensitivity is due to the fact that both markets always carry risks, and also cause them to have special internal risk bonds. In this study, Markov Switching Model was used to examine this relationship between the House Price Index in Turkey and the BIST100 price index. This model is one of the most popular methods in the literature on nonlinear series in recent years. According to the results of the Markov Switching Model, while the possibility of transition between regimes in series is low, the possibility of staying in the same regime is quite high. In addition, the series are not cointegrated according to the result of the Johansen Cointegration test. [ABSTRACT FROM AUTHOR]

Knowing the direction and degree of impact of the main factors affecting the level of the stock market index is of great importance for investors to create a successful investment strategy. Accordingly, examining the effects of various economic, political, and psychological factors on stock market indices attracts researchers' attention. Portfolio theories, which have been modernized with the definition of risk, include some models that explain stock prices. Some models that determine stock prices under modern portfolio theories include macroeconomic variables considered as systematic risk factors. These models analyze the effect of some macroeconomic variables, which are accepted as systematic risk factors, on stock prices. From this point of view, the study aims to evaluate the asymmetric effects of selected macroeconomic variables on the ISE100 index. To achieve this goal, 111-month data sets between January 2012 and March 2021 are initially analyzed with Hatemi-J (2012) Asymmetric Causality Test and then Hatemi-J (2014) Asymmetric Impulse-Response Functions. As a result of the analysis, a significant causality is determined from only the positive shocks of the dollar rate to the negative shocks of the ISE100 index. [ABSTRACT FROM AUTHOR]

In this study, the effect of macroeconomic variables on stock returns in Borsa Istanbul is examined. XU100, XTUMY, XUMAL, XUHIZ, and XUSIN stock market indices were used as dependent variables; and money supply, interest rates, inflation rates, exchange rate, and confidence indices are used as independent variables. The data set covers the years between 2010 and 2020. In the study in which the least-squares method was used, the relationship between variables was tested in monthly and quarterly periods. According to the findings obtained from the research, it has been determined that (1) there is a positive relationship between money supply and small-cap companies and manufacturing companies, (2) there is a negative relationship between interest rates and large-cap companies and financial companies, (3) there is a positive relationship between composite leading indicator and large companies, small companies and financial companies, and (4) there is a negative relationship between the exchange rate and large-cap companies, financial companies and service companies. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic deeply has affected the economy and financial markets of all countries. The aim of this research is to classify firms in the BIST 100 index through selected financial ratios and to compare their pre-COVID-19 and the COVID-19 period situation. In the research, cluster analysis was carried out with 14 different ratios regarding the liquidity ratios, financial structure ratios, operational ratios and profitability ratios from the financial statements of 81 firms between 2019Q1 and 2020Q3. As a result of the cluster analysis, it was determined that 7 clusters were obtained in both the pre-COVID-19 and the COVID-19 period, but the number of firms and firms forming the clusters differed. In the COVID-19 period, it was revealed that the firms with the highest rate of profitability per share, net profit margin and asset profitability were DEVA, ECILC, ASELS, KERVT, TATGD firms operating in the health, pharmaceutical, communication and food sectors. It is expected that the study will benefit investors both by identifying the firms they can invest in and by examining the clusters obtained in investing through portfolio diversification. [ABSTRACT FROM AUTHOR]

Importance of gold as an alternative investment tool has raised after the global economic crisis. Increasing risks in financial markets caused the gold to be a hedging instrument against instability and fluctuations. Investors behave differently in normal times and crisis times. In cases where the movements of gold and stock exchange markets are diversified, gold can be used in portfolio diversification, as a tool of hedging and as a safe haven. When the returns of stock market are expected to diminish, investors use the gold as an alternative investment tool. In this context, the aim of this study is to determine if using gold in their portfolio as an alternative investment tool provides benefit for the investors or not. For this purpose, the relationship between gold and stock market is tested using monthly time series data of gold prices and Borsa Istanbul 100 from 2006- April to 2018- August. Before building the model, time series properties of the model are investigated and the best VAR model is selected. Causality relationship between the variables is tested using with Toda-Yamamoto causality test. Return series are calculated in order to be used in the model. According to the results of the study, the hypothesis stating “there is no causality relationship from gold return series to BIST 100 series and there is no causality relationship from BIST 100 series to gold return series” is accepted. In conclusion, it is beneficial for investors to use gold as an alternative investment tool in order to diversify the risks.

In this study, the effect of corporate governance practice on stock returns is examined. The research was analyzed within the framework of public disclosure and transparency, shareholder, stakeholders and board of directors, which has both corporate subheadings and corporate governance total score. The study was analyzed by using Panel Vector Autoregressive (PVAR) model for 2009-2016 periods. According to the results, corporate governance practice in Turkey is not effective in buying stocks of investors. The corporate governance of the companies is reflected negatively in the long term returns. Investor profile in Turkey is not interested in how the company is generally managed, investors are more care about short-term returns. It is thought that the corporate governance of firms should be introduced more in order to become a long-term preference for the investor.

Bu çalışma BIST 100 borsa endeksinin negatif ve pozitif yönlü hareketlerinin tahmin edilmesini konu edinmektedir. Yapay sinir ağı, destek vektör makinesi ve naive Bayes algoritmasının tahmin performansları karşılaştırılmaktadır. Analizler iki aşamalı olarak yapılmaktadır. Birinci aşamada tahmin modellerinde girdi olarak kullanılacak dokuz adet teknik gösterge, borsa endeksi açılış, kapanış, en yüksek ve en düşük fiyatlar, kullanılarak hesaplanmakta ve sürekli olan bu teknik göstergeler barındırdıkları trende göre kategorize edilerek yeni bir veri seti oluşturulmaktadır. İkinci aşamada ise, trend belirleyici veri seti girdi olarak kullanılmakta ve seçilen üç makine öğrenme algoritması kullanılarak tahminler yapılmaktadır. BIST 100 veri seti 2009-2018 Aralığını kapsayan günlük kapanış fiyatlarını içermektedir. Analizlerle, destek vektör makineleri algoritmasının en iyi sınıflandırıcı olduğu sonucuna ulaşılmıştır. Ayrıca, daha önceki benzer çalışmalarla karşılaştırmalar yapılarak gerek kullanılan veri seti gerekse tahmin modellerinin etkileri tartışılmaktadır.

While the studies in the literature are mostly in the form of comparing Islamic indices with conventional indices, Islamic stocks with their conventional counterparts and sukuks with traditional bonds, in this study different from these, the performance ratios of Islamic bonds (sukuks) have been compared with 2-year government bonds, exchange rates and BIST100 index. The aim of this study is to answer the question; "Can sukuk be a financial asset that is protected against risks arising from interest, exchange rate and stock market and a stabilizing financial asset in the portfolio?". In the study, performance measurements of sukuk, 2-year bond return, USD/TL exchange rate and BIST100 index for the period 2006-2020 were made and analyzed by using Sharpe, Information and Sortino performance ratios. According to the findings, in terms of Sharpe and Sortino performance ratios obtained in four of the 5 periods analyzed, it is seen that the sukuk has a structure that is protected against the risks of stocks, exchange rate and interest rate. This situation is seen more clearly in the second period of (2008-2010) global crisis and the recovery period afterwards. [ABSTRACT FROM AUTHOR]

Copyright of Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi is the property of Itobiad: Journal of the Human & Social Science Researches and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, as a result of the financial liberalization policies implemented it is observed that the relationship between stock prices and exchange rates has increased. With these developments, the importance of studies examining the relationship between stock market and exchange rate has increased. In this study, using historical data for daily basis from 2009: 01-2020: 06 period was to investigate the relationship between the exchange rate and the stock market in Turkey help of the Asymmetric Causality Analysis and Markov Regime Switching Model. In the study, in which the BIST100 Index and the USD/TRY exchange rate were used as variables, there were examined the validity of the "Good Market" and "Portfolio Balance" theories. Markov Regime Switching Model findings showed that a significant relationship between exchange rate and stock prices in both periods of expansion and contraction in Turkey's economy. Hatemi-J (2012) asymmetric causality test findings, there is a causality from positive and negative shock in the BIST100 to positive and negative shock in the exchange rate, and there was a found that the Portfolio Balance theory validity in Turkey. In addition, the existence of causality from from positive shocks in the exchange rate to positive shocks in the BIST100 index demonstrates the validity of the Goods Market theory, and there is no causality relationship between negative shocks. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Social Sciences Institute / Sosyal Bilimler Enstitüsü Dergisi is the property of Bingol University / Rectorate and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: The aim of this study is to examine the volatility spillover effects of German, French and American stock market indices on BIST 100 Turkish stock market index. Dataset consists of daily closing price observations starting from January 2, 2004, until February 6, 2017, for indices DAX 30, CAC 40, S&P 500 and BIST 100. E-GARCH(1,1) method has been used to model the conditional variance. Volatility is in a relatively narrow band under a non-crisis economic conjuncture. On the other hand, it is expected that the global risk will be higher during crisis periods. Therefore, the differentiation in the volatility spillover behavior among the markets while under different economic conditions is a rational expectation. In this regard, the Threshold VAR (TVAR) model was used in the study. In the result of the study, it has been observed that the volatility spillover effect on the BIST 100 index is relatively low in the regimes where the global risk is low, whereas the effect is relatively higher in the regime where the global risk is high. Furthermore, results of analysis also indicate that S&P is the most influential index to affect BIST 100 both in high and low-risk regimes. Öz: Bu çalışmanın amacı Almanya, Fransa ve Amerika hisse senedi piyasalarının Türkiye hisse senedi piyasası üzerindeki oynaklık yayılımı etkisini incelemektir. 02.01.2004 - 06.02.2017 dönemi için günlük frekansda DAX 30, CAC 40, S&P 500 ve BİST 100 endekslerine ilişkin kapanış verileri kullanılmıştır. Koşullu varyans değerlerini elde etmek amacıyla E-GARCH(1,1) modelinden yaralanılmıştır. Volatilitenin normal bir ekonomik konjonktürde nispeten daha dar bir bant içinde olması olağandır. Buna karşın küresel riskin yüksek olduğu kriz dönemlerinde ise daha büyük bir aralıkta seyretmesi beklenen bir durumdur. Dolayısıyla risk açısından farklılık gösteren ekonomik koşullarda, piyasalar arası oynaklık yayılımı davranışlarının da farklılaşması rasyonel bir beklentidir. Bu açıdan araştırmada söz konusu durumu dikkate alan Threshold VAR (TVAR) modellemesi kullanılmıştır. Çalışma sonucunda küresel riskin düşük olduğu rejimde BİST 100 endeksi üzerindeki yayılım etkisinin göreli olarak düşük olduğu, buna karşın küresel riskin yüksek olduğu rejimde ise söz konusu etkinin nispeten yüksek olduğu gözlemlenmiştir. Buna ek olarak BİST 100 endeksinin bu gelişmiş ülkelere ait 3 endeks içerisinden en yoğun olarak S&P endeksinden etkilendiği bulgulanmıştır.

Lehman Brothers slump was taken as base point and changes in pricing mechanisms of BIST100, MSCI EM and Dow Jones were tried to be understood before and after crisis. While daily closed data was used, VAR, Impulse Response, Variance Decomposition and Granger Causality tests were used. According to results, Turkish markets are weaker than other developing countries and react more quickly to negative developments and Dow Jones returns have more explanatory power over BIST100 returns with respect to MSCI EM in precrisis period. In post-crisis period, volatility of Turkish markets decreased much more than other developing countries due to inherent growth dynamics. In addition, the influence of MSCI EM in pre-crisis period over Dow Jones is not effective, but in post-crisis period has become more effective. This can be regarded as a sign of an increase in dominance of developing countries in global economies in post-crisis period.

The effects of top management teams’ characteristics on company performance has become very popular with the upper echelon’s theory, created in 1984. This has led to various academic studies on that topic however there is no detailed study conducted in Turkey. In the study, the effects of CEO characteristics on company performance is analyzed by using data of large-scale Turkish firms which are members of the BIST100 index over 2015 and 2019. According to the results obtained from the research, the age of the CEO, the CEO duality, and the CEO’s experience in the current company have no statistically significant effect on the stock performance. CEO’s experience in the current position and past experience working as a CEO have positive impact on the performance of the company. As the important findings in the research, (1) 84% of the companies in BIST100 are appointed insiders to the CEO position, (2) the insider CEOs stay three times more than the outsiders, and (3) there is a positive relation between CEO’s experience working as a CEO and company performance. [ABSTRACT FROM AUTHOR]

Copyright of Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi is the property of Itobiad: Journal of the Human & Social Science Researches and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Companies are exposed to many risks in their life. Derivatives are one of the tools that companies commonly use in order to mitigate these risks. The fluctuations in the markets in recent years have increased companies' need to use derivatives. For this reason, the importance of derivatives is increasing every day. The purpose of this study is to ascertain the financial risks which arise from the activities of non-financial companies in BIST 100 index operating in Turkey and the derivatives used in the management of these risks. In addition, this study aims to determine the differences between companies using derivatives and those not using derivative products. Therefore, the year-end financial reports of 58 companies, which were continuously in the BIST100 index between 2013 and 2018 were analyzed. The study results showed that the risks that the companies were exposed to included credit risk, liquidity risk, interest risk, currency risk and other risks and only half of the companies, on average, used derivatives in the management of these risks. In addition, it was observed that companies rather hedged themselves against currency risks through futures contracts and used more derivatives in the transportation and energy sectors. Besides, it is seen that the companies using derivative products are big and low liquid companies.

Copyright of Journal of Financial Researches & Studies / Finansal Araştirmalar ve Çalişmalar Dergisi is the property of Marmara University, School of Banking & Insurance and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Importance of gold as an alternative investment tool has raised after the global economic crisis. Increasing risks in financial markets caused the gold to be a hedging instrument against instability and fluctuations. Investors behave differently in normal times and crisis times. In cases where the movements of gold and stock exchange markets are diversified, gold can be used in portfolio diversification, as a tool of hedging and as a safe haven. When the returns of stock market are expected to diminish, investors use the gold as an alternative investment tool. In this context, the aim of this study is to determine if using gold in their portfolio as an alternative investment tool provides benefit for the investors or not. For this purpose, the relationship between gold and stock market is tested using monthly time series data of gold prices and Borsa Istanbul 100 from 2006-April to 2018- August. Before building the model, time series properties of the model are investigated and the best VAR model is selected. Causality relationship between the variables is tested using with Toda-Yamamoto causality test. Return series are calculated in order to be used in the model. According to the results of the study, the hypothesis stating "there is no causality relationship from gold return series to BIST 100 series and there is no causality relationship from BIST 100 series to gold return series" is accepted. In conclusion, it is beneficial for investors to use gold as an alternative investment tool in order to diversify the risks. [ABSTRACT FROM AUTHOR]

One of the points of neoclassical economics is the rationality of the individual which is borrowed from classical economics. With this principle, it has been assumed that people are rational in their suffering, pleasure, perceived benefit and planning of future needs. However, market anomalies in the stock market have led to the questioning of this principle which advocates human rationality. The reasons that affect individual investor behavior and the resulting market anomalies have been tried to be explained by researchers in different ways. These studies have included the concept of behavioral finance in the literature. In order to understand the factors that lead to the deterioration of market efficiency, it is necessary to examine the factors affecting human behavior. One of the most common of these factors is the weather conditions. In this study, trading volume and trading size and weather conditions in BIST100 index between February 2011 and September 2015 were considered. For the analysis of the work, weather conditions will be classified as sunny, cloudy, rainy, and snowy. Afterwards, SPSS 22.0 program will be used to determine whether there is a meaningful difference between the average of transaction volume and transaction amounts. [ABSTRACT FROM AUTHOR]

The analysis of linkages between financial markets has been a promising subject of study after globalization. Main consequence of these linkages is on transmission of the crisis from one country to another. Therefore, identifying and modeling of those linkages are important issues in the analysis of financial markets. According to studies the cross-correlations present nonlinear behavior and in general the well-known methods fail to predict such correlations. In this paper, we aim to show the existence of nonlinear cross-correlations between Turkish Stock Exchange and major developed country indices. For this purpose, we use the Multifractal Detrending Moving-Average Cross-correlation Analysis (MF-X-DMA) which is designed for detecting long-range power-law correlations. In the analysis we use the daily financial return and volatility series of Turkish stock market index BIST100 and developed market indexes which are S&P500, DAX30, FTSE100 for a period of 11 years between 01/01/2007-01/01/2018. The results show the existence of multifractality and long-range power-law cross-correlations. • MF-X- DMA is implemented. • Cross-correlations between Turkish Market and Developed Markets are investigated. • Cross-correlations show multifractal nature. • Cross-correlations between volatilities exhibit power-law, long-range dependence. [ABSTRACT FROM AUTHOR]

In addition to the uncertainty and chaotic movements of the financial time series, the nonlinear dynamic structure makes the forecasts very difficult. The fact that the stock market index are affected by the political changes, the general outlook of the economy, the investors' expectations and investment preferences, and the movements of other indexes, make the index estimates quite difficult but attractive. It is known that the machine learning algorithms are successful in estimating stock index movements and their future values. In this study, the problem of forecasting the direction of BIST 100 index movements is discussed. Three different machine learning algorithms, artificial neural networks, support vector machines and naïve Bayes classifier were used and their performances were compared. Ten technical indicators were used as inputs for the models. The data set consists of ten-year daily closing price values covering the 2009-2018 period. Analysis results show that the models can be used to capture stock market index movements, whereas artificial neural network algorithm is a better classifier. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine the volatility spillover effects of German, French and American stock market indices on BIST 100 Turkish stock market index. Dataset consists of daily closing price observations starting from January 2, 2004, until February 6, 2017, for indices DAX 30, CAC 40, S&P 500 and BIST 100. E-GARCH(1,1) method has been used to model the conditional variance. Volatility is in a relatively narrow band under a non-crisis economic conjuncture. On the other hand, it is expected that the global risk will be higher during crisis periods. Therefore, the differentiation in the volatility spillover behavior among the markets while under different economic conditions is a rational expectation. In this regard, the Threshold VAR (TVAR) model was used in the study. In the result of the study, it has been observed that the volatility spillover effect on the BIST 100 index is relatively low in the regimes where the global risk is low, whereas the effect is relatively higher in the regime where the global risk is high. Furthermore, results of analysis also indicate that S&P is the most influential index to affect BIST 100 both in high and low-risk regimes. [ABSTRACT FROM AUTHOR]