Department of Management

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  • ItemOpen Access
    Transformational leadership, idiosyncratic deals and employee outcomes
    (Emerald Publishing, 2024-02-26) Karakitapoğlu Aygün, Zahide; Erdogan, Berrin; Caughlin, David E.; Bauer, Talya N.
    Purpose: Transformational leadership (TFL) has been suggested to create positive changes in employees with the goal of developing them into leaders. The authors integrate this well-established leadership style with recent research on idiosyncratic deals (i-deals). The authors suggest TFL as a predictor of task and development-based i-deals, and propose i-deals as a mediating mechanism linking TFL to employee outcomes (job satisfaction, job stress and manager-rated performance). Design/methodology/approach: The authors used a time-lagged research design, and collected four waves of data from 140 employees and 78 leaders. Findings: TFL was found to be an important predictor of i-deals. I-deals predicted job satisfaction and job stress; and it mediated the relationship between TFL and these two employee outcomes. Yet, i-deals were not associated with employee performance and did not mediate the relationship. Originality/value: First, it shows that transformational leaders who consider employees' unique skills and support their professional growth are more likely to grant personalized arrangements. Second, drawing from social exchange theory, it illustrates that i-deals may act as a linkage between TFL and employee outcomes. The paper bridges leadership and i-deals literature to identify key leverage points through which leaders can enhance employee satisfaction, well-being and performance. © 2023, Emerald Publishing Limited.
  • ItemOpen Access
    Statistical arbitrage: factor investing approach
    (Springer Science and Business Media Deutschland GmbH, 2023-09-16) Akyıldırım, E.; Goncu, A.; Hekimoğlu, A.; Nguyen, D. K.; Şensoy, Ahmet
    We introduce a continuous time model for stock prices in a general factor representation with the noise driven by a geometric Brownian motion process. We derive the theoretical hitting probability distribution for the long-until-barrier strategies and the conditions for statistical arbitrage. We optimize our statistical arbitrage strategies with respect to the expected discounted returns and the Sharpe ratio. Bootstrapping results show that the theoretical hitting probability distribution is a realistic representation of the empirical hitting probabilities. We test the empirical performance of the long-until-barrier strategies using US equities and demonstrate that our trading rules can generate statistical arbitrage profits. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
  • ItemOpen Access
    A dynamic multi-level iterative algorithm for clearing European electricity day-ahead markets: an application to the Turkish market
    (Taylor and Francis Ltd., 2023-05-12) Büke, B.; Sayın, M.; Tanrısever, Fehmi
    Designing and clearing day-ahead electricity market auctions have recently received significant attention from academia and practice alike. Given the size and the complexity of day-ahead market auctions, clearing them within the time limits imposed by the market is a major practical concern. In this paper, we model all the practical details of the Turkish day-ahead electricity market and provide a new multi-level iterative heuristic to clear the market. We compare our results with a commercial solver using data provided by Energy Exchange Istanbul. Our heuristic achieves an average optimality gap less than 0.09%, with an average solution time of just 14 s; whereas the commercial solver takes, on average, 18 min (and in some cases up to three hours) to find the optimal solution. We also demonstrate that using our heuristic solution to warm-start the commercial solver further reduces the solution time by 25%, on average. Overall, our heuristic proves to be very efficient in clearing the Turkish day-ahead market. We also test the performance of our algorithm as the problem size grows.
  • ItemOpen Access
    Puritanical moral rules as moral heuristics coping with uncertainties
    (Cambridge University Press, 2023-10) Kurdoğlu, Rasim Serdar
    As the cultural evolution of a puritanical moral norm in Turkey illustrates, puritanical moral norms are not developed by nonrational reasoning concerned with purity and cleanliness. People utilize puritanical moral rules as moral heuristics for making intendedly rational decisions about whether to cooperate or not when the commitment of the counterparty is uncertain.
  • ItemOpen Access
    Forecasting high‐frequency excess stock returns via data analytics and machine learning
    (John Wiley and Sons Inc., 2023-01) Akyildirim, E.; Nguyen, D.K.; Şensoy, Ahmet; Šikić, M.
    Borsa Istanbul introduced data analytics to present additional information about its market conditions. We examine whether this product can be utilized via var ious machine learning methods to predict intraday excess returns. Accordingly, these analytics provide significant prediction ratios above 50% with ideal profit ratios that can reach up to 33%. Among all the methods considered, XGBoost (logistic regression) performs better in predicting excess returns in the long‐term analysis (short‐term analysis). Results provide evidence for the benefits of both the analytics and the machine learning methods and raise further discussion on the semistrong market efficiency.
  • ItemOpen Access
    Statistical analysis by wavelet leaders reveals differences in multi-fractal characteristics of stock price and return series in Turkish high frequency data
    (World Scientific Publishing Co. Pte. Ltd., 2023-12-08) Lahmiri, Salim; Şensoy, Ahmet; Akyıldırım, Erdinç
    The price and return time series are two distinct features of any financial asset. Hence, exam-ining the evolution of multiscale characteristics of price and returns sequential data in timedomain would be helpful in gaining a better understanding of the dynamical evolution mecha-nism of the financial asset as a complex system. In fact, this is important to understand theirrespective dynamics and to design their appropriate predictive models. The main purpose ofthe current work is to investigate the multiscale fractals of price and return high frequency datain Turkish stock market. In this regard, the wavelet leaders computational method is appliedto each high frequency data to reveal its multi-fractal behavior. In particular, the method isapplied to a large set of Turkish stocks and statistical results are performed to check for (i)presence of multi-fractals in price and returnseries and (ii) differences between prices andreturns in terms of multi-fractals. Our statistical results show strong evidence that high fre-quency price and return data exhibit multi-fractal dynamics. In addition, they show evidenceof distinct fractal characteristics on different scales between price and return series. Further-more, our statistical results show evidence of differences in local fluctuation characteristics ofprice and return time series. Therefore, differences in local characteristics are useful to buildspecific predictive models for each type of data for better modeling and prediction to generateprofits. Besides, we found evidence that both long-range correlations and fat-tail distributionscontribute to the multifractality in Turkish stocks. This finding can be attributed to the majorrole played by international investors in increasing the volatility of Turkish stocks.
  • ItemOpen Access
    Collusion or governance? common ownership and corporate risk-taking
    (Wiley, 2023-09-13) Yao, Shouyu; Guo, Xinyu; Şensoy, Ahmet; Goodell, John W.
    Research Question Disputes over the corporate governance impacts of common ownership continue. Differentiating from existing studies, we focus on the Chinese stock market, exploiting the Top 10 Shareholding File, which includes various investors besides institutional investors, to study the impact of common ownership built through blockholders on corporate risk-taking behavior. Research Findings We find that firms with higher common ownership are less likely to engage in corporate risk-taking, with concomitant decreases in future growth rates. Mechanism analysis shows that blockholders' common ownership exerts its influence through increasing market concentration, with concomitant lessening of market competition. Interestingly, further analyses indicate that, in contrast to blockholders, ownership connectedness built by mutual fund families significantly raises corporate risk-taking along with growth. However, individual investors' common ownership does not show the significant statistical relationship with corporate risk-taking. Theoretical Implications We add to the debate on common ownership on corporate governance. Consistent with the anti-competition stream of literature, the risk-taking-reduction role we identify for blockholder common ownership supports the theory of anti-competition. Our results highlight the need to consider the heterogeneity of common ownership. Policy Implications While blockholder common ownership is evidenced to have a negative effect on corporate risk-taking, with, by extension, a negative impact on economic development, our results also suggest that efficient monitoring mitigates these effects. We also document an interesting heterogeneity in investor types. Mutual fund common ownership, in contrast to blockholder common ownership, is associated with higher risk-taking and more robust firm growth. This suggests the positive role of institutions in corporate governance and the necessity of considering the heterogeneity of common ownership.
  • ItemEmbargo
    A fuzzy cognitive map approach to understand agricultural system and food prices in Türkiye: policy recommendations for national food security
    (John Wiley & Sons Ltd., 2023-11-16) Ekici, Ahmet; Önsel Ekici, Ş.; Yumurtacı Hüseyinoğlu, I. Ö.; Watson, F.
    Once one of the few self-sufficient food countries in the world, Turkey has become dependent on imports to feed its population. Food prices have climbed to among the highest in the world, severely threatening the food security of the country. Most researchers generally attributed the high prices to the increased input costs of agriculture. Although the role of input prices cannot be denied, this paper focuses on a neglected problem that can account for food price inflation: the attitudes and behaviours of farming communities towards agriculture. Through fuzzy cognitive map methodology, known to be very effective in understanding complex networks of problems, we identify and map the relationships among the factors affecting the agriculture system, develop interview and literature-driven scenarios, and test these scenarios to demonstrate their role in explaining the relationship between attitudes and behaviours of farming communities and food prices in Turkey. Our findings provide recommendations to policymakers.
  • ItemEmbargo
    Connectivity and spillover during crises: highlighting the prominent and growing role of green energy
    (Elsevier, 2023-11-30) Banerjee, A.K.; Şensoy, Ahmet; Goodell, J.W.
    How influential are green energy instruments? We examine how green- and carbon-energy assets differ regarding transmitting and receiving shocks between normal versus crises periods. Crises include the global financial crisis and Euro debt crisis, two waves of COVID-19, and the ongoing Russia-Ukrainian war. Our empirical illustration is based on volatility impulse function (VIRF) for dynamic conditional correlation–generalised autoregressive conditional heteroskedasticity (DCC-GARCH) method using daily data from January 03, 2007–March 31, 2023, of several green and brown energy instruments and market and energy controls, we evidence asymmetric connectedness that increases during crises. For specific green instruments, volatility transmissions can be transmitting or receiving. However, green instruments stand out overall as prominent transmitters, while brown energy instruments are prominent receivers. Results are consistent with green energy vehicles impacted by macroeconomic and market states and reflecting this to investors. Results are also consistent with green and brown interconnectivity. Further network analysis provides robustness to our study results and suggests this role is evolving. The study results are significant for policy intervention during the transition to alternative energy sectors and for risk and portfolio management implications
  • ItemOpen Access
    Food prosumption technologies: A symbiotic lens for a degrowth transition
    (SAGE Publications Ltd, 2023) Vicdan, H.; Ulusoy, E.; Tillotson, J. S.; Hong, S.; Ekici, Ahmet; Mimoun, L.
    Prosumption is gaining momentum among the critical accounts of sustainable consumption that have thus far enriched the marketing discourse. Attention to prosumption is increasing whilst the degrowth movement is emerging to tackle the contradictions inherent in growth-driven, technology-fueled, and capitalist modes of sustainable production and consumption. In response to dominant critical voices that portray technology as counter to degrowth living, we propose an alternative symbiotic lens with which to reconsider the relations between technology, prosumption, and degrowth living, and assess how a degrowth transition in the context of food can be carried out at the intersection of human–nature–technology. We contribute to the critical debates on prosumption in marketing by analyzing the potentials and limits of technology-enabled food prosumption for a degrowth transition through the degrowth principles of conviviality and appropriateness. Finally, we consider the sociopolitical challenges involved in mobilizing such technologies to achieve symbiosis and propose a future research agenda.
  • ItemEmbargo
    M&A activity during the COVID-19 pandemic
    (Taylor&Francis, 2023-05-24) Ançel İlaslan, Z.; Tanyeri-Günsür, Başak
    We investigate whether the COVID-19 pandemic initiated merger waves at the aggregate and industry levels. The COVID-19 pandemic coincides with economic shocks, wide adoption of new technologies, and volatility in stock and energy markets, all potential triggers of restructuring activity. Our sample covers 104,464 acquisition deals of US targets from 2012 to 2022. We identify 37 industry-level merger waves. Twenty-three merger waves start during the COVID-19 pandemic. Eighty percent of the deals during the pandemic were part of an industry merger wave. This concentration of industry waves drove an aggregate merger wave starting on April 2020.
  • ItemEmbargo
    Modeling dynamic VaR and CVaR of cryptocurrency returns with alpha-stable innovations
    (Academic Press, 2023-03-30) Malek, Jiri; Nguyen, Duc Khuong; Şensoy, Ahmet; Tran, Quang Van
    We employ alpha-stable distribution to dynamically compute risk exposure measures for the five most traded cryptocurrencies. Returns are jointly modeled with an ARMA-GARCH approach for their conditional mean and variance processes with alpha-stable innovations. We use the MLE method to estimate the parameters of this distribution, along with those of conditional mean and variance. Our results show that the dynamic approach is superior to the static method. We also find out that these risk measures of five cryptocurrencies do not offer the same pattern of behavior across subperiods (i.e., pre-, during- and post-COVID pandemic).
  • ItemEmbargo
    Assessing the US financial sector post three bank collapses: Signals from fintech and financial sector ETFs
    (Elsevier BV, 2023-10-12) Banerjee, A. K.; Pradhan, H. K.; Şensoy, Ahmet; Goodell, J. W.
    We investigate the effects of the collapses of Silicon Valley Bank, Signature Bank, and First Republic Bank on the US financial sector by analysing returns and second moments of traditional financial and fintech ETFs. Using a network model, we examine high-frequency data sampled at one-hour intervals for seventeen ETFs encompassing pre- and crisis periods. We find, using a time-varying parametric vector autoregressive (TVP-VAR) and volatility impulse response analysis, that traditional financial ETFs are net transmitters of returns and volatility spillovers in the network, and that this impact is more pronounced in volatility in the period coinciding with the collapse of the three big banks. We identify effects persisting through the medium term. This study is among the first to comprehensively analyze the recent crisis in the US banking sector, covering a full range of the fall of three big banks.
  • ItemEmbargo
    Does corporate green innovation behaviour impact trade credit? Evidence from China
    (Elsevier Inc., 2023-09) Li, Chen; Şensoy, Ahmet; Song, Ce; Zhang, Mi
    We explore whether and how corporate green innovation influences enterprises’ access to trade credit. Using Chinese corporations listed on the Shanghai and Shenzhen Stock Exchanges between 2014 and 2019 as the sample, we provide evidence that corporate green innovation can significantly enhance enterprises’ trade credit accessibility. This finding remains robust after undertaking various robustness checks. Channel analysis shows that upstream suppliers’ competition intensified by downstream buyers’ green innovation behaviours serves as a crucial linkage between corporate green innovation and trade credit. Heterogeneity analyses indicate that the augmenting impact of green innovation on trade credit accessibility is more pronounced in non-state-owned enterprises, large-size firms, and enterprises with high analyst coverage. Our findings contribute to the literature concerning both corporate green innovation and trade credit, and support enterprises and policymakers to promote green innovation, improve financing conditions, and drive sustainable development.
  • ItemEmbargo
    Impact of media hype and fake news on commodity futures prices: A deep learning approach over the COVID-19 period
    (2023-10-30) Banerjee, Ameet Kumar; Şensoy, Ahmet; Goodell, John W.; Mahapatra, Biplab
    We investigate the reactions of eight commodity futures to media hype and fake news during COVID-19, utilising the Ravenpack news database, along with deep learning algorithms. Results identify a significant impact on commodity prices of media hype and fake news, with this reaction amplified during COVID-19. Compared to alternative deep learning algorithms, bi-directional long-short-term memory is adaptive to forecasting the returns of the commodity futures contracts with lower mean absolute error and root mean square error. Findings, confirmed by Diebold-Mariano testing, as well as alternative data partitioning, show commodity markets are susceptible to fake news and media hype.
  • ItemOpen Access
    On the role of commodity futures in portfolio diversification
    (John Wiley and Sons Inc, 2021-09-20) Lean, H. H.; Nguyen, D. K.; Şensoy, Ahmet; Uddin, G. S.
    The last two decades have witnessed major financial crises that led investors to seek alternative assets and investment strategies to reduce their portfolio risk. In this article, we provide information on the role of commodity futures in designing portfolios and managing risk based on an appealing operational framework. Using more than 20 years of sample data, we first investigate the conditional mean and volatility dynamics of equity and commodity futures markets within a dynamic conditional correlation model setup. We then form alternative equity-commodity futures portfolios by changing the weights of commodity futures and examine if the diversified commodity-equity portfolios perform superior to the all-equity portfolios and four well-known investment strategies that suit most practitioners. Stochastic dominance approach shows that including commodity futures in diversified portfolios does not always improve the risk-return performance, except for gold in some particular portfolio setups. Accordingly, commodity assets have behaved like financial assets (stocks) and tend to be driven by the same pricing factors in general, which reduces the benefits of diversification.
  • ItemEmbargo
    Pricing the net benefits of a public loan guarantee scheme in a developing market
    (Elsevier, 2023-09-17) Bozkurt, A.T.; Günsür, Başak-Tanyeri
    Turkish credit markets experienced a liquidity crunch following the Brexit referendum in June, the attempted coup in July, and the US election in November of 2016. The government announced a 12.5- fold increase in the Treasury support for the Credit Guarantee Fund to alleviate the credit squeeze. We investigate whether investor reactions to the announcement of the increase in Treasury support in KGF are in line with the stated aim of policymakers. Firms listed on Borsa İstanbul averaged 5.72 percent cumulative abnormal returns (CARs) in the 9-day window around the announcement. Investors anticipated the benefits from public guarantees would outweigh the costs. The positive and significant CARs suggest that the information released in the announcement, in line with the program aims, positively affected investor expectations.
  • ItemEmbargo
    Economic policy uncertainty and green innovation: evidence from China
    (Elsevier, 2022-11-11) Cui, X.; Wang, C.; Şensoy, Ahmet; Liao, J.; Xie, X.
    Frequent economic policy adjustments lead to significant increases in economic policy uncertainty (EPU). Few studies have investigated whether EPU influences corporate green innovation. Using a sample of Chinese A-share listed firms from 2005 to 2019, we find strong evidence that EPU is significantly and negatively associated with corporate green innovation. Our moderating effect analysis shows that financial constraints exacerbate the negative impact of EPU on green innovation, while government environmental subsidies can significantly mitigate the negative EPU effect. Moreover, the negative relationship between EPU and green innovation is salient in privately owned enterprises, firms with less industry competition, and firms in regions with weak intellectual property protection. This study has important implications for policymakers regarding increasing government expenditure on environmental protection and strengthening intellectual property protection to promote corporate green innovation.
  • ItemOpen Access
    Sequential versus concurrent final phase product development: approval uncertainty, time-sensitive consumers, asymmetric competition, and government subsidy
    (Sage Publications, Inc., 2023-11-01) Limon, Yasemin; Tang, C. S.; Tanrısever, Fehmi
    Should a firm begin its production even before its new product is approved? In a competitive market with time-sensitive consumers, a firm may choose to adopt the “concurrent process” by conducting the approval process and the production process in parallel so that the product will become available for sale once approved. However, to avoid incurring upfront (production related) investments that are nonrecoverable should the product fail to receive approval, a firm may opt for the “sequential process” so that the production process will only begin after approval. But such a sequential process can delay product launch, making the firm less competitive. These trade-offs between the concurrent and sequential development processes and the recent Covid-19 vaccine development motivate us to examine the process choice in the presence of three salient factors: (a) uncertain product approval, (b) time-sensitive consumers, and (c) asymmetric firm competition—firms have different ex ante approval probabilities. Our equilibrium analysis reveals that it is possible for the laggard firm (the firm with lower ex ante approval probability) to aggressively adopt the concurrent process whereas the leading firm (the firm with higher ex ante approval probability) adopts the sequential process. First, as the approval requirement tightens, both firms have a lower chance of receiving approval, and the laggard firm is more likely to adopt the sequential process than the leading firm. Second, as consumers become more time sensitive, the leading firm is more eager to adopt the concurrent process than the laggard firm. Finally, when the firm asymmetry is large, competition does not always soften and both firms may compete directly by adopting the sequential process. We also examine the case when consumers are “forward-looking” instead of “myopic.” We find that forward-looking behavior increases competition and motivates both firms to adopt the concurrent process. Finally, we consider the case when the government offers subsidies to defray the nonrecoverable investments to increase the chance of having an approved product available sooner. Interestingly, we find such a subsidy can backfire resulting in lower consumer welfare and lower profit for the firms especially when consumers are time insensitive.
  • ItemOpen Access
    Extending the merton model with applications to credit value adjustment
    (Springer Link, 2023-07) Akyildirim, E.; Hekimoglu, A. A.; Şensoy, Ahmet; Fabozzi, F. J.
    Following the global financial crisis, the measurement of counterparty credit risk has become an essential part of the Basel III accord with credit value adjustment being one of the most prominent components of this concept. In this study, we extend the Merton structural credit risk model for counterparty credit risk calculation in the context of calculating the credit value adjustment mainly by estimating the probability of default. We improve the Merton model in a variance-convoluted-gamma environment to include default dependence between counterparties through a linear factor decomposition framework. This allows one to tackle dependence through a systematic common component. Our set-up allows for easier, faster and more accurate fitting for the credit spread. Results confirm that use of the variance-gamma-convolution clearly solves the vanishing credit spread problem for short time-to-maturity or low leverage cases compared to a Brownian motion environment and its modifications.