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PurposeThe paper aims to identify the differences between developed and developing country firms with respect to firm-specific and country-level determinants of their capital structure. For this purpose, all constituent firms in one of the oldest Islamic equity indices, Dow Jones Islamic Market World Index (DJIM), are considered and the Muslim-majority status of each firm's domicile country is recognized.Design/methodology/approachThe study employs Hausman–Taylor random effects regression with endogenous covariates to explain the debt ratios of firms in DJIM by separating them into developed and developing country subsamples in an unbalanced panel data setting. Developing country subsample is further split into two based on the Muslim-majority status of each firm's domicile country.FindingsConsistent with the previous literature, this study finds that firm-specific characteristics are the main determinants of their capital structure. Additionally, the paper shows that country-level characteristics have an impact on the debt ratio, however, the types of factors vary across developed and developing countries. Debt ratios in developing country firms are lower than those in developed country firms, largely due to the significantly smaller leverage ratios of firms in Muslim-majority countries. Although the debt ratios of DJIM firms are higher in “non-Muslim” countries, the set of firm-level capital structure determinants are not statistically explained by operating in a “Muslim” country. The study also documents that, before the global financial crisis of 2008, companies in developing countries have gradually become less leveraged worldwide.Originality/valueThis paper provides a new perspective into the differences between developed and developing country firms' capital structures by focusing on a relatively homogeneous data set restricted by leverage screening rules of an Islamic equity index and recognizing the Muslim-majority status of each firm's domicile country.

The authors investigate the impact of social media on S&P index constituents for U.S., European, and emerging markets with the international investor perspective using firm-specific Twitter sentime...

Constant Proportional Portfolio Insurance (CPPI) aims to maximize the performance of the portfolio by protecting a determined base value without using any derivative instruments, and by determining the amounts to be invested in risky and risk-free assets with calculations using the risk multiplier and buffer value. Artificial neural networks (ANNs) are mathematical models that are successfully used in studies such as pattern recognition, function estimation, finding the most appropriate value and classifying data by imitating neural networks in the human brain. This study aims to use the advantages of both the decomposition model (Wavelet Transform) and machine learning model (ANN) to predict the future values of stock indices to decide which risk multiplier to use. The dynamic multiplier CPPI yielded better returns than the classic CPPI in all 5 stock market indices analyzed, and both strategies successfully implemented the previously targeted 95% capital protection. It has been observed that predicting future prices of indices using Artificial Intelligence methods and the performance of the dynamic multiplier CPPI strategy applied based on these predictions is more successful than the conventional CPPI strategy with constant multiplier.

This study documents the labor market outcomes and time-use patterns of women in urban Bangladesh. Using survey data collected in 2018 in low-income neighborhoods of Dhaka, the paper finds that women with children aged 0–5 years have lower likelihood of labor market participation, lower likelihood of working, and lower likelihood of being an earner, compared to women with no children and women with children aged 6 years or older. While this motherhood penalty affects all mothers, those who have young children but have no access to childcare support face the largest penalty. Time-use patterns confirm these findings, indicating that mothers of young children with no access to childcare spend less time on market work, more time on unpaid work, and less time on leisure or other activities. In addition, they are more likely to perform childcare as a secondary activity along with other paid and unpaid work, which may have implications for their productivity and the quality of care provided to children. The paper proposes entry points to ease the double burden of paid and unpaid care work on mothers in urban areas, where the availability and affordability of formal childcare services is low, and community-based or other informal care arrangements are not common.

Amac- Yapay zekada yasanan teknolojik gelismelerin bagimsiz denetime olan etkilerini incelemek calismanin oncelikli amacidir. Calismada, denetimde kullanilan yapay zeka ornekleri ve yapay zekanin denetim sektorune yapacagi katkilar incelenmistir. Yontem- Bagimsiz denetim sektorune etki eden teknolojik gelismelerin yasanmasiyla yapay zekadan alinan verimin arttigi ve yapay zekanin uygulama alaninin cesitlendigi gorulmustur. Bu calismada, bagimsiz denetimde var olan yapay zeka uygulamalari ve gelecekte uygulamaya konulacak yapay zeka projeleri analiz edilmis ve degerlendirilmistir. Bu calismada, teknolojik altyapinin guclenmesiyle ve farkindaligin artmasiyla ortaya cikan yapay zekanin denetimde var olan uygulamalari ve gelecekte uygulamaya konulacak yapay zeka projeleri analiz edilerek degerlendirilmistir. Bulgular- Elde edilen bulgulara gore; Yapay zekanin isletmelere uyarlanabilmesi icin isletmelerin ERP sistemlerini gelistirmesi gerektigi ve bagimsiz denetim yapilacak her firma icin, yapay zekanin tasarlanmasinin olasi zorluklari oldugu ortaya cikmistir. Sonuc- Calismada, yapay zeka ile yapilan denetimin tam zamanli yapilabilecegi ve daha efektif olacagi dusunulmektedir. Fakat yapay zekanin yayginlasmasi ve verimliligin arttirilmasi icin isletme yoneticilerinin Dunya’da yasanan gelismeleri takip edip kendi kurum kulturleri ile birlestirerek uygulamaya koymasi gerektigi dusunulmektedir. Ayrica, isletmeler ERP yazilimlarini gelistirmesi gerektigi, dijitallesme ve entegre program kullanimini arttirmasi gerektigi gorulmustur.

Amac- Denetim raporu kullanicilarinin artan seffaflik ihtiyaci ve talebi dogrultusunda uygulamaya alinan BDS 701 ‘Kilit Denetim Konulari’ standardinin ulkemizde uygulandigi ikinci yilda, denetci raporlarinda standardin uygulamasi, icerik ve detaylar acisindan ele alinmistir. Standardin amaci olan sirkete ait onceli konularin belirlenmesi ve yapilan aciklamalarin kapsamlari analiz edilirken, 2017 ve 2018 yillari raporlari karsilastirilarak, standardin uygulanmasindaki gelisim incelenmistir. Yontem- Bu calisma kapsaminda Halka Acik sirketlerin 2017 ve 2018 denetim raporlari, yer verilen Kilit Denetim Konulari analiz edilerek, kapsam ve aciklamalar acisindan karsilastirilarak yorumlanmistir. Bulgular- BDS 701 kapsaminda ‘Kilit Denetim Konulari’ tespitinde ve raporlarda ele alinma seklinde, sektorel bazda agirlikli olmak uzere, benzer konularin one ciktigi, yer verilen konularin ele alinisi ve aciklamalarinda daha cok genel ifadeleri kullanildigi tespit edilmistir. Sonuc- Standardin uygulamaya yeni alinmis olmasini goz onune alarak, ilerleyen yillarda Kilit Denetim Konulari secimi ve raporlarda ele alinis sekillerinin standardin hedefine ulasacagi beklenmektedir. Boylece standardin amacina bagli olarak sirket faaliyetleri acisindan oncelikli konularin belirlenmesi ve yapilacak aciklamalarda genel ifadeler yerine ilgili sirket icin ozel aciklamalar yapilmasiyla, bilgi kullanicilarinin ihtiyacini karsilama acisindan etkinliginden soz edilebilecektir.

Evaluating service delivery needs in data-poor environments presents a particularly difficult problem for policymakers. The places where the need for social services are most acute are often the very same places where assessing policy interventions is the most challenging. This paper uses Twitter data to gain insights into service delivery needs in a data-poor environment. Specifically, it examines the development priorities of citizens in the north- western region of Pakistan between 2007 and 2020, using natural language processing techniques (NLP) and sentiment analysis of 9.5 million tweets generated by 20,000 unique Twitter users. The analysis reveals that service delivery priorities in this context are centered on access to education, healthcare, food, and clean water. The findings provide baseline data for future on-the-ground research and development initiatives. In addition, the methodology used in this paper demonstrates both current resources and areas in need of future work in the use of NLP techniques in analyzing social media data in other contexts.

This chapter aims to examine calendar anomaly in selected sample countries by using second-order stochastic dominance (SSD) approach. Day-of-the-week and month-of-the-year effects are analysed for a group of 5 developed and 5 developing country indexes to estimate efficient (inefficient) weekdays and months for the period between 1988 and 2016. Then, back-testing procedure is applied for each sample country to compare performance of index returns for 2017-2019 with the strategy arisen by estimation results. Findings suggest that Monday and Friday returns are inefficient and efficient respectively in all developing countries where different results obtained for developed ones. In monthly analysis, December returns found efficient in 8 indexes including S&P 500. However, October is inefficient for all indexes. Positive January effect seems disappeared in most cases. Back-testing results indicate that in a bearish market condition SSD strategy outperforms index returns in general for daily and monthly comparison.

PurposeThis paper aims to examine the stock return behaviour around the bonus issue announcements in eight emerging markets for 2010–2019 by addressing the signalling, cash substitution and liquidity hypotheses.Design/methodology/approachBesides using the standard event study technique to test the presence of an anomaly, country-based regression analyses are performed. Firm-specific factors are used to understand the motive behind the anomaly observed pre- and post-announcement periods. Also, the Amihud illiquidity measure examines the liquidity hypothesis, while standardized profitability and investment ratios compare the long-run operational performance of bonus issuers to test the validity of signalling.FindingsThe findings provide evidence that abnormal returns can be detected ten days before the announcement in some countries, which is a sign of information leakage. The presence of the effect continues only in two countries after the announcement is released. The size of the bonus issue is found strongly significant in most countries, while a weak relation between abnormal return and other factors is detected. Moreover, the signalling hypothesis does not hold in the sense of long-run profitability increase, while liquidity assertion is partially presented.Research limitations/implicationsDue to an inadequate number of announcements in other emerging markets, the number of sample countries is limited by eight.Originality/valueThe research is novel regarding analyzing a wide range of emerging countries with various variables. Also, the paper is distinguished from other studies by applying multiple set of regressions under nine different event windows.

Public spaces can be an instrument to increase social cohesion, yet they are often underutilized. This paper presents findings from a randomized virtual reality experiment with more than 2,000 participants in Karachi, Pakistan. The paper investigates the relationship between urban design, willingness to use public spaces, and social cohesion. The findings show that exposure to a two-and-a-half-minute-long virtual reality experience featuring various urban design and social diversity elements has a statistically significant impact. In particular, improvements in the design of a public park through the virtual reality experience increased the park's perceived attractiveness and participants'willingness to use it. Exposure to diverse social groups in the virtual reality experience, by itself, had mixed impacts on social cohesion indicators such as trust and perception of and willingness to interact with outgroups. The impacts varied by ethnic affiliation, income, sex, and education level. This may be partly explained by the segregated nature of Karachi and the high prevalence of mistrust of outgroups. The paper illustrates how modern technology can be used as an effective, low-cost tool for diagnosing social phenomena, soliciting feedback about urban interventions for inclusive design, and promoting social contact.

Purpose - This study aims to investigate the effect of business cycle on the relation between working capital management and corporate performance.Methodology - We examine the relation between working capital and profitability under economic down and upturns, on energy firms which are traded on Istanbul Stock Exchange and included in BISTELKT index. Working capital is measured by cash conversion cycle. EBIT to total assets ratio is used to represent profitability and business cycle is modeled by gross domestic products. Data is on quarterly basis from 2012 to 2018.Findings - The analysis shows that there is a negative relation between cash conversion cycle and profitability during economic growth, while a reverse relation exists in economic recession periods.Conclusion- The study shows that the efficient working capital management is important in terms of the firms' profitability, and must be included in financial planning especially in the times of economic upturns.

Purpose - This study aims to examine the effect of capital structure on firm specific variables such as stock performance, growth, profitability. The study also aims to investigate relationship between GDP, inflation and capital structure of firms in a macro view. Methodology - To apply our study, we use eight main companies of Turkey Non-Metal Mineral Products Index which are carrying out its operations in cement industry. To represent firm value, growth and, profitability, we use stock price, sales and EBITDA margin, respectively. We retrieve our data from Rasyonet on a quarterly basis from 2000 to 2018. Findings - Our regression analysis shows that leverage generally does not have any significant relationship with examined variables. Also, we could not find any relationship with debt ratio and inflation for our companies. Conclusion- Investment purpose debt increase is mostly observed in recent years, so it takes time to see result of it.

Amac- Bu calismanin amaci Euro/Turk lirasi kurunun hareketinin istatistik ve yapay sinir aglari yontemleri ile tahmin edilmesidir. Yontem- Calismada iki farkli tahmin yontemi ile Euro/Turk lirasi kuru tahmini yapilmistir. Girdi olarak her iki modelde de son 10 yilin Euro/Turk lirasi gunluk kuru kullanilmis ve son 1 yilin gunluk dolar kuru tahmin edilmistir. Bulgular- Yapay sinir aglari yontemi ile bulunan ortalama mutlak hatalar istatistik yontemi ile bulunanlarin yaklasik %2’si kadar daha azdir. Tahminler 365 gunun her biri icin “rolling window” yontemi kullanilarak yapildigindan, elde edilen sonuclarin “robust” oldugu soylenebilir. Sonuc- Arastirmada kullanilan her iki modelin de belirli bir basari ile Dolar kurunu tahmin tahmin edebildikleri ancak Yapay Sinir Aglari modelinin, istatistik modeline kiyasla daha basarili sonuclar verdigi gozlemlenmistir. Bundan sonraki calismalarda dissal degiskenlerin de modele eklenmesi ile tahmin performansinin arttirilabilmesi mumkun olabilir.

Purpose- The aim of the study is to understand going concern issue, to reveal the importance of going concern disclosures in audit reports for both company managements and investors, and to raise an opinion how going concern needs to be discussed in audit reports.Methodology- International Standards on Auditing (ISA) 570 “Going Concern” was studied, and its effect to audit reports analyzed.Findings- It is revealed going concern was emphasized in the audit reports of the companies studied, but necessary amount of disclosures were not found. Also, in some examples, it was coincided auditors’ opinions were not appropriate with the going concern issue.Conclusion- The effect of ISA 570 “Going Concern” on audit reports was analyzed. It was determined whether the companies can go on with their businesses or not, and it is revealed auditors should take going concern issue into account seriously in their opinions., Amaç- Bu çalışmada genel olarak, işletmelerde süreklilik varsayımının anlaşılması, işletmelerin sürekliliğe dair açıklamalara bağımsız denetim raporlarında yer verilmesinin işletme yönetimi ile yatırımcı açısından önemini ortaya çıkarmak ve bağımsız denetim raporlarında sürekliliğin ne şekilde işlenmesi gerektiğine dair bir kanı oluşturulması hedeflenmiştir.Yöntem- Bağımsız Denetim Standardı 570 İşletmenin Sürekliliği Varsayımı genel olarak incelenerek Bağımsız Denetim Raporlarına etkisi ve önemi analiz edilmiştir.Bulgular- İncelenen işletmelerin Bağımsız Denetim Raporlarında süreklilik varsayımına yer verildiği görülmüş olmakla beraber, bu konuya yeterince açıklama getirilmediği saptanmıştır. Süreklilik kavramına uygun olarak denetçi görüşü verilmediği örneklere de rastlanmıştır.Sonuç- Bu çalışmada, Bağımsız Denetim Standardı 570 İşletmenin Sürekliliği Varsayımı’nın bağımsız denetim sürecine ve finansal tablolara etkisi ve önemi incelenmiştir. İşletmenin faaliyetlerini sürdürüp sürdürmeyeceğinin saptanması ve bu hususun finansal tablolara etkisinin bağımsız denetimde denetçinin dikkate alması gereken önemli bir konu olduğu görülmüştür.

Objective- Decision makers usually use conventional methods in appraising investment projects. However, nowadays, dynamic valuation models about the future of investments also needs to be included in the decision making process. This study aims to show that a property construction investment project, which seems to be unprofitable with conventional methods currently, can be implemented profitably in the future by using a fuzzy real option method with dynamic characteristics. Using fuzzy numbers in addition to the classical fuzzy option theory will expand the model’s scope and enable it to contain more information, thereby making it more appropriate for investment environments with high uncertainty. In addition, both the standard deviation calculated from expected value of the fuzzy numbers and the historical volatility will be used for the fuzzy real option valuation. Thus, it is aimed to compare the two methods. Finally, it is aimed to transfer expert opinions to the model as well. Methodology- The project valuation of a property construction investment planned to be made in Turkey has been performed by using Trinomial Fuzzy Real Option method. First, the volatility variable of this model was determined on the basis of Carlsson and Fuller’s proposal of expected values and standard deviations for fuzzy numbers. Next, the historical volatility of house price index used for the volatility variable of the model. Finally, these two methods were compared. The model also includes expert opinions. These expert opinions have been transferred to the model with the aggregation of fuzzy numbers. Findings- According to the valuation conducted with Trinomial Fuzzy Real Options, the property construction investment project, which seems to be unprofitable currently, can be implemented profitably in the future. Due to the transactional nature of fuzzy numbers, volatility value, which is calculated on the basis of standard deviation of cash flows, will increase per annum. On the other hand, the historical volatility is used as a constant for all investment years. In parallel with this approach, the optimum investment year of the model using the standard deviation of cash flows as volatility has been different the model with historical volatility. Conclusion- The idea of using options in investment projects adds both managerial flexibility and uncertainty concepts to the valuation process. In addition to the term volatility, which is used for the concept of uncertainty in the model, the naturally existent uncertainty of fuzzy numbers is also used in the model. Furthermore, it is shown that the investment project, which seems to be unprofitable currently, can be carried out profitably in the future with the managerial flexibility of a delay option. While the volatility, which is calculated on the basis of the standard deviation of cash flows, postpones the optimum investment timing with its increasing value, the historical volatility model gives earlier optimum investment timing.

Employing a Data Envelopment Analysis (DEA) approach, we investigate the technological progress, efficiency, and productivity of the Turkish securities firms between 2010 and 2015. After measuring the performance of these firms with DEA analysis, we combine the efficiency scores with contingency factors (ownership, size and bank affiliation) in a panel regression analysis in order to determine the effects. Our results indicate that the securities industry in general is less efficient than the existing technology allows. The relative productivity of the Turkish securities industry in general improved. Foreign acquisition has positive significant contribution to the efficiency of securities firms. Smaller firms, due to their inability to respond to technological innovation, experienced especially large decreases in both efficiency and productivity.

This paper studies gender education gaps among indigenous and nonindigenous groups in Bolivia. Using the National Census of Population and Housing 2012 and an estimation method analogous to difference-in-differences, the paper finds that the intersection of gender and indigenous identity confers cumulative disadvantage for indigenous women in literacy, years of schooling, and primary and secondary school completion. Although gender education gaps have become narrower across generations, there remain significant differences among indigenous groups. The Aymara have the largest gender gap in all outcomes, despite having high overall attainment rates and mostly residing in urban centers, with greater physical access to schools. The Quechua have relatively smaller gender gaps, but these are accompanied by lower attainment levels. The paper discusses the possible sources of these differentials and highlights the importance of taking gender dynamics within each indigenous group into greater consideration.

Purpose- Natural catastrophes such as earthquakes and tsunamis have been a great concern since the beginning of humanity and even before. Apart from the severe property damage they cause, these unforeseen incidents leave thousands of injured and dead. Events like the Indian Ocean and Japan earthquakes and tsunamis even lead to substantial impacts over the global economies. Through this interest, this study aims to determine the impacts of both incidents, over several stock market indices. Methodology- In order to capture the influence of these events on various stock markets, an investor sentiment methodology is adopted. Trading volume is selected as an investor sentiment proxy and it is regressed against multiple macroeconomic data. The residuals of these analyses are assigned as investor sentiment indices for both cases respectively.Furthermore, an EGARCH model is developed to observe the impacts of investor sentiment associated with both incidents, on the considered stock markets. Findings- The stock returns of Japan and Vietnam are negatively influenced by investor sentiment associated with the Indian Ocean Earthquake and Tsunami while the stock returns of Indonesia, South Korea, China and Singapore are positively influenced. Thus, the conditional volatilities of Sri Lanka, Indonesia, Thailand, Taiwan and Vietnam are negatively affected. Moreover, the stock returns of Indonesia, South Korea and Thailand are impacted negatively by investor sentiment related to the Japan Earthquake and Tsunami. Hence, the conditional volatility of Indonesia is positively influenced while it is negatively affected for Vietnam. Conclusion- In contrast with the previous studies, there is strong evidence that most of the selected stock market indices are influenced by both events while the shocks brought by these events are long-lived through the selected stock markets. Moreover, Indian Ocean Earthquake and Tsunami incident seems to generate higher investor sentiment effects on the stock markets than Japan Earthquake and Tsunami incident does.Consequently, Indonesia and Vietnam are considered to be highly impacted by the investor sentiment related to both events. However, Hong Kong, Malaysia and India do not happen to have any investor sentiment effects regarding both earthquakes and tsunami incidents.

Purpose- This study investigates weak form market efficiency of Istanbul Stock Exchange (ISE) via Random Walk Hypothesis (RWH). Methodology- Two random walk tests, Dickey-Fuller and Runs test are used to search for random walk in stock market. Natural log returns of BIST-30 index firms, BIST-30 index, participation index firms and participation index are analysed by both tests over a five year period from 2013 to 2018. Therefore, BIST30 index returns together with BIST100 and BISTTUM indexes are analysed in a longer period from 2000 to 2018 including 2001 and 2008 financial crises in Turkey. Findings- Weak form market efficiency is justified according to Dickey Fuller test, but not for Runs test. Conclusion- While Dickey Fuller test results reject random walk in ISE, which leads that weak form market efficiency is not justified; Runs test are failed to give certain results on market efficiency for the same data set and time period.

Purpose This paper aims to compare two groups of stocks to analyze the efficiency of an ethical portfolio in comparison with a conventional portfolio. Design/methodology/approach Efficiency test by second-order stochastic dominance (SSD) approach is applied on two groups, which consist of 12 stocks. Ethical portfolio is chosen from the stocks complying with the participation banking rules. Conventional portfolio is selected from Borsa Istanbul (BIST) with choosing the corresponding stocks for each ethical stock according to the sector and market capitalization. All the stocks of both groups are pairwise SSD compared. Findings Both groups of 12 stocks are inefficient portfolios; however, a group of 7 stocks constitute an efficient ethical portfolio with the total weight of 50.82 per cent among the set of 12 ethical stocks. On the other hand, a group of 6 stocks constitute an efficient conventional portfolio, with the total weight of 45.16 per cent among the set of 12 conventional stocks. By pairwise SSD comparison of corresponding stocks from both groups, despite none of the conventional stocks dominate ethical stocks, four ethical stocks dominated the conventional ones. Originality/value Back-testing and comparison with benchmark BIST 100 Index have been done for the selected portfolios. According to back-testing results, groups of SSD efficient stocks outperformed the groups, from which they were selected. Furthermore, both SSD efficient portfolios have higher returns than benchmark index, BIST 100.

Fuzzy logic, originally introduced by Lofti Zadeh in the 1960's, resembles human reasoning in its use of approximate, vague, noisy or imprecise data/information and uncertainty to generate decisions. According to Sriram (2005), fuzzy theory was designed with a specific purpose of mathematically representing vagueness and provides formalized procedures for tackling the impreciseness inherent in many variables in a multitude of problems. Crises, bubbles, fiscal politics etc. makes investing difficult in financial markets. These issues haphazardly raise and cause irregular characteristics which also raise risk. On the other hand, traders and market participants try to reduce risk and increase returns. We try to make dependable suggestion tool which contains a few technical indicators using fuzzy logic modeling. In financial markets technical analysis is commonly used to provide trading decisions. Technical analysis presumes that there are trends and patterns in financial assets’ movements. In this study, BIST-30 and Islamic (Participation) Index data is used between March 2012 and November of 2014 taken from Borsa Istanbul. The aim of the study is to create a new technical analysis indicator using fuzzy logic method which could be an alternative to popular indicators used by traders. BUY and SELL signals given by indicators’ after closing prices are assumed to be applied in the next day opening prices when calculating the indicators’ performance. The performance of the indicator for BIST-30 and Islamic index is measured by modified sharpe ratio and compared to widely used indices like MACD, MA, RSI and OBV. The Sharpe ratio is used to calculate risk adjusted return. It shows the rate of return as opposed to risk. The asset which has the higher Sharpe Ratio is considered to yield better return for the same amount of risk.

Purpose - Considering the globalized business word requires to use of standard financial report, it is critical to evaluate financial results with different methods. In this study, it was examined that the impact of cash flow statements analysis on the financial performance, in terms of net profit and stock prices. Methodology - In this study, the relationship of Cash Flow values and the financial performance have been analyzed, using regression analysis. The analysis had been performed on officially announced quarterly data of the firms in Energy Sector in Turkey. Findings - According to result of research analysis, it was observed that periodic connections have emerged, between financial performance and cash flow statements. Conclusion- It was concluded that, despite the temporary connection was observed, the findings not permanent and precise. The role of cash flow statements evaluation need to be tested with other methods considering direct importance on the financial performance rating.

Purpose- This paper aims to forecast the Turkish intraday electricity prices accurately. It will be the first intraday electricity price forecasting work, which uses Long-Short Term Memory (LSTM) application. Methodology- LSTM method is based on a special kind of neural network, which is capable of learning long-term dependencies. This paper aims to achieve the best forecasts, in terms of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), by applying the LSTM model with multistep-ahead prediction approach. Findings- LSTM model created in this study performed better with lagged values, electricity consumption and electricity production values. Especially using the lagged values of the prices and the reserve margin gave successful results. Conclusion- The proposed method has improvement in the accuracy of forecasting. Turkish Intraday Electricity Market needs further research with time series methods as well as other neural network models

Purpose- The purpose of this study is to emphasize the importance of analytical review techniques under ISA 520 in the Independent Auditing process.Methodology- Independent Auditing Standards will be referred to detailly. The impact of the Analytical Review Techniques on the Independent Audit Process will be determined.Findings- It has been determined that Analytical Review Techniques have been used during the completion of Independent Audit's implementation of planning, material accuracy tests and auditsConclusion- Analytical Investigation Techniques are techniques that are widely used in Independent Audit and are an effective audit technique., Amaç- Bu çalışmanın amacı, Uluslararası Bağımsız Denetim Standartları’ndan olan BDS 520 Analitik İnceleme Tekniklerinin bağımsız denetim sürecindeki önemini vurgulamaktır.Yöntem- Bağımsız Denetim Standartları ayrıntılı olarak incelenecektir. Analitik İnceleme Tekniklerinin Bağımsız Denetim sürecine etkisi tespit edilecektir.Bulgular- Analitik İnceleme Tekniklerinin, Bağımsız Denetimin planlama, maddi doğruluk testleri uygulama ve denetimin tamamlanması aşamasında kullanıldığı tespit edilmiştir.Sonuç- Analitik İnceleme Teknikleri, Bağımsız Denetimde yaygın olarak kullanılan tekniklerden olup, etkin bir denetim tekniğidir.

Conventional methods used in project evaluation have a static nature, which cause decision makers to examine investment projects within a narrow scope. As an alternative, real-options theory allows decision makers to use the concepts of uncertainty and managerial flexibility, which classical methods do not deal with, in valuing investment projects. Carlsson and Fuller’s fuzzy real-options theory has been a solution for situations where cash flow and cost variables used in the model cannot be expressed by using classical numbers but by using fuzzy numbers. The idea of using intuitionistic fuzzy numbers in real options theory can expand the narrow scope more effectively than the idea of ​​using classical real-options theory, thereby providing an opportunity to evaluate investment projects from a wider perspective. In this study, intuitionistic fuzzy real-option valuation model has been developed and applied to the evaluation of solar energy investment projects. Studies have shown that solar energy investments that do not seem profitable today in Turkey can perform profitably in the future. Moreover, the historical volatility model differs from the expected valuable models, whereas the optimum investment year between the models formed by the uncertainty inductions from the expected values ​​exhibit minimal difference.DOI: http://dx.doi.org/10.5755/j01.ee.29.2.19206

Accurate electricity price forecasting has become a substantial requirement since the liberalization of the electricity markets. Due to the challenging nature of electricity prices, which includes high volatility, sharp price spikes and seasonality, various types of electricity price forecasting models still compete and cannot outperform each other consistently. Neural Networks have been successfully used in machine learning problems and Recurrent Neural Networks (RNNs) have been proposed to address time-dependent learning problems. In particular, Long Short Term Memory (LSTM) and Gated Recurrent Units (GRU) are tailor-made for time series price estimation. In this paper, we propose to use multi-layer Gated Recurrent Units as a new technique for electricity price forecasting. We have trained a variety of algorithms with three-year rolling window and compared the results with the RNNs. In our experiments, three-layered GRUs outperformed all other neural network structures and state-of-the-art statistical techniques in a statistically significant manner in the Turkish day-ahead market.

Güran, Aysun (Dogus Author) The second order stochastic dominance (SSD) has become exceedingly popular in recent years, due to its ability to determine the dominance of one asset over another for all risk-averse investors without a strict requirement in asset distribution. In this study, 33 OECD country indexes and their enriched set of assets, which consists of some combinations of these indexes, are investigated and compared between 2007 and 2015 by utilizing pairwise SSD comparisons, with different data frequencies, such as daily, weekly, monthly and quarterly. This paper contributes to the literature in three points: Firstly, a serious portion of the best performing OECD countries has the lowest GDP (PPP) per capita level. Secondly, the SSD efficient set depends on data frequency. Thirdly, when the data frequency is lowered, the difference between two SSD pairwise efficiency tests decreases.

In this article, hourly prices of the Turkish Day Ahead Electricity Market are forecasted by using various univariate electricity price models, then the out-of-sample forecasts are compared with each other and the benchmarks. This article has two main contributions to the literature: Firstly, it provides a factorial Analysis of Variance (ANOVA) as a pre-whitening method of the price series and allows one to work with the stationary residuals series. Secondly, it is the first work, which compares the performances of all important statistical univariate forecast models in the Turkish electricity market. Results indicate the importance of the factorial ANOVA application and the SARIMA model's success under the given conditions.

Electricity price forecasting has a paramount effect on generation companies (GenCos) due to the scheduling of the electricity generation scheme according to electricity price forecasts. Inaccurate electricity price forecasts could cause important loss of profits to the suppliers. In this paper, the financial effect of inaccurate electricity price forecasts on a hydro-based GenCo is examined. Electricity price forecasts of five individual and four hybrid forecast models and the ex-post actual prices are used to schedule the hydro-based GenCo using Mixed Integer Linear Programming (MILP). The financial effect measures of profit loss, Economic Loss Index (ELI) and Price Forecast Disadvantage Index (PFDI), as well as Mean Absolute Error (MAE) of the models are used for comparison of the data from 24 weeks of the year. According to the results, a hybrid model, 50% Artificial Neural Network (ANN)&ndash, 50% Long Short Term Memory (LSTM), has the best performance in terms of financial effect. Furthermore, the forecast performance evaluation methods, such as Mean Absolute Error (MAE), are not necessarily coherent with inaccurate electricity price forecasts&rsquo, financial effect measures.

Purpose- The aim of this paper is to observe whether generating a portfolio having return more than index by investigating the return performance of index’s stocks and capital structure of firms in index in a certain period. The second aim of this paper is to provide portfolio diversification by using the method of this study. In this paper, firms and stocks on BIST-100 index are referenced for empirical study. Method- Stocks are chosen from BIST-100 index with regard to certain capital structure of firms in stocks, and second orderly stochastic dominance test is implemented on these stocks. Dominant stocks are defined to generate a portfolio after stochastic test and this portfolio’s return performance is compared to the index’-s return. Findings- The portfolio, whose stocks are filtered by a certain capital structure and then chosen by second orderly stochastic dominance test, has return performance better than index’s return. Conclusion- This paper is indicating that second orderly stochastic dominance method and capital structure is an important investigation to generate a portfolio having higher returns more than index’s.

Pupose- Real estate appraisal activity is thedetermination of the likely value of the real estate together with its rightsand benefits on a certain date. The correct appraisal of real estate value whichhelps to determine the asset value of an individual or company is an importanttask. The related legal rights are arranged by SPK and BDDK (BankacılıkDenetleme ve Düzenleme Kurumu) in their published regulations and documentariesand notifications. Methodology- Real estate appraisal reports preparedin Turkey has to be prepared according to International Appraisal Standards andbe in conformity with both Turkish Financial Report Standards and InternationalEvaluation Standards. Real estate appraisal report has to be organized by realestate appraisal experts who are licenced by SPK (Sermaye Piyasası Kurumu) inTurkey. Findings- In terms of the Turkish FinancialReport Standards; it is suggested that the real estate appraisal reports has tobe in conformity with the International Appraisal Standards. In this study, thestructure and evaluation methods of real estate appraisal reports prepared inTurkey has been investigated in the light of Turkish Financial Report Standardsand International Evaluation Standards.Coclusion- Also, taking into account the factthat accounting principles and financial tables should reflect the reality; wecriticize them and suggested some solutions.

Leveraged transactions, widely known as forex trading in Turkey is regulated by the Capital Markets Authority since August 2011 and only brokerage firms are allowed to trade in this industry. Employing the regression analysis, we investigate the effect of foreign exchange volatility on brokerage firms between 2012 and 2016. Our results indicate that, the volatility in foreign exchange rate have a significant positive effect on the revenue of forex trading of brokerage firms. The movements in the direction of foreign exchange rates have a bigger effect on the profit of brokerage firms.

The aim of this study is to construct a model for evaluating the effects of investor sentiment on the conditional volatility by measuring the effects of noise trader demand shocks on returns and volatility where EGARCH model is used to determine whether investor sentiment has more influence on the conditional volatility of various sector indexes. After controlling for macroeconomic shocks, weekly trading volume of Istanbul Stock Exchange 100 is used as investor sentiment proxy. Significant evidence is found that a change in investor sentiment has more influence on conditional volatility of industry, banking, and food and beverages sector indexes when compared with other sectors such as retail or telecommunication.

Summary This paper studies the impact of gender and ethnicity on educational outcomes in Bolivia, Mexico, Peru, Senegal, and Sierra Leone, using the Integrated Public Use Microdata Series-International (IPUMS-I) database. Using an estimation method analogous to difference-in-differences, the paper finds that gender-based differences in literacy, primary school completion, and secondary school completion are larger for minority ethnic groups compared to others, or ethnicity-based differences are larger for women compared to men. The findings suggest that the intersection of gender and ethnicity confers cumulative disadvantage for minority groups, especially in Latin American countries, with implications on the design of development programs.

One of the main arguments of behavioral finance is that some properties of asset prices are most probably regarded as deviations from fundamental value and they are generated by the participation of traders who are not fully rational, thus called noise traders. Noise trader theory postulates that sentiment traders have greater impact during high-sentiment periods than during low-sentiment periods, and sentiment traders miscalculate the variance of returns undermining the mean-variance relation. The main objective of this research is to construct a model to evaluate the returns and conditional volatility of various stock market indexes considering the changes in the investor sentiment by measuring the effects of noise trader demand shocks on returns and volatility. EGARCH model is used to determine whether earning shocks have more influence on the conditional volatility in high sentiment periods weakening the mean–variance relation. This paper takes an international approach using weekly market index returns of U.S., Japan, Hong Kong, U.K., France, Germany, and Turkey. Weekly trading volumes of these indexes are regressed against a group of macroeconomic variables and the residuals are used as proxies for investor sentiment and significant evidence is found that there is asymmetric volatility in these market indexes and earning shocks have more influence on conditional volatility when the sentiment is high.

In 2007, as the US subprime mortgage market began to fall down, which reached its peak with the catastrophic collapse of the Lehman Brothers, no one was aware of that this was going to be the worst financial crisis since the Great Depression. Evaluating the advantages and disadvantages connected with financial globalization demands a pure understanding of the influence of financial volatility. Up to the present few researches focused on analyzing macroeconomic volatility of national economies. Therefore, the aim of the paper is to compare the forecast performance of stock market and macroeconomic volatility of US economy between 2007 and 2010. Accordingly, two different types of financial time series were generated, namely weekly stock returns and quarterly return on investment. Firstly, the appropriate model was determined via time series analysis. Secondly, the relevant ARCH-type model was implemented. Finally, conditional variance forecast performance of models was presented with respect to confidence interval. Furthermore, coefficient of correlation between squared residuals and coefficient of conditional variance was given.

Bu calismada islem hacmi degisimlerinin ilgili hisse senedinin fiyatina etkileri ve hisse senedinin getirisini tahmin etmedeki etkinligi incelenmektedir. Yatirimci duyarliligi belirli bir finansal varliga rasyonel olmayan yatirimcilar tarafindan gosterilen ilginin rasyonel yatirimcilar tarafindan rasyonel yatirimci tarafindan gosterilen ilgiliye oranidir. Baker ve Stein’in da calismalarinda belirttigi gibi bir hisse senedi uzerinde yatirimci duyarliliginin etkinligini gosteren, birim zamandaki islem hacmi degisimini gosteren ve islem hacmi trendi olarak tanimlanan bu degiskendeki artislar ayni zamanda yatirimci duyarliliginin artisini temsil etmektedir.Bu calismada IMKB’deki tum hisse senetlerinin islem hacmi trendi karakteristiklerinin gozlemlenmesi hedeflenmektedir. Sonucta islem hacmi trendine iliskin neredeyse tum beta katsayilari pozitif bulunmustur. Bu islem hacmi trendi ile hisse senedi getirilerindeki dogrusal iliskiyi yansitmaktadir.

The main purpose of this study is to investigate stock market cointegration from the market efficiency perspective. Therefore, eleven emerging stock market indices are tested by using weekly data for the period of January 1998-December 2008 and for the sub period of January 2002-December 2008. Comovement among the emerging market countries was analyzed through Johansen cointegration test. The existence of two cointegrating vectors has been found at 5% significance level. However, the firm evidence against the market efficiency could not be established because of the low explanatory power of the results generated from the vector error correction model., Bu çalışmanın amacı hisse senedi piyasaları eşbütünleşimini etkin pazar pespektifinden araştırmaktır. Bu bağlamda 11 gelişmekte olan piyasanın Ocak 1998-Aralık 2008 ve Ocak 2002-Aralık 2008 dönemli haftalık verileri test edilmiştir. Gelişmekte olan ülke piyasalarının birlikte hareketi Johansen eşbütünleşim testi ile incelenmiş ve %5 anlamlılık düzeyinde iki eşbütünleşim vektörü bulunmuştur. Buna rağmen vektör hata düzeltme modelinin açıklama gücünün düşük olmasından dolayı piyasa ekinliğine karşı kesin bir bulgu ortaya konulamamıştır