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Yayın A comparative assessment of frequentist forecasting models: Evidence from the S&P 500 pharmaceuticals index(İstanbul University Press, 2023) Muneza, Christian; Khan, Asad ul Islam; Badshah, Waqar; Khan, Asad ul Islam; Yönetim Bilimleri Fakültesi, İktisat BölümüThis paper compares three forecasting methods, the autoregressive integrated moving average (ARIMA), generalized autoregressive conditional heteroscedasticity (GARCH), and neural network autoregression (NNAR) methods, using the S&P 500 Pharmaceuticals Index. The objective is to identify the most accurate model based on the mean average forecasting error (MAFE). The results consistently show the NNAR model to outperform ARIMA and GARCH and to exhibit a significantly lower MAFE. The existing literature presents conflicting findings on forecasting model accuracy for stock indexes. While studies have explored various models, no universally applicable model exists. Therefore, a comparative analysis is crucial. The methodology includes data collection and cleaning, exploratory analysis, and model building. The daily closing prices of pharmaceutical stocks from the S&P 500 serve as the dataset. The exploratory analysis reveals an upward trend and increasing heteroscedasticity in the pharmaceuticals index, with the unit root tests confirming non-stationarity. To address this, the dataset has been transformed into stationary returns using logarithmic and differencing techniques. Model building involves splitting the dataset into training and test sets. The training set determines the best-fit models for each method. The models are then compared using MAFE on the test set, with the model possessing the lowest MAFE being considered the best. The findings provide insights into model accuracy for pharmaceutical industry indexes, aiding investor predictions, with the comparative analysis emphasizing tailored forecasting models for specific indexes and datasets.Yayın A comparative assessment of frequentist forecasting models: Evidence from the S&P 500 pharmaceuticals index(Istanbul University, 2023) Muneza, Christian; Khan, Asad ul Islam; Badshah, Waqar; Khan, Asad ul Islam; Yönetim Bilimleri Fakültesi, İktisat BölümüThis paper compares three forecasting methods, the autoregressive integrated moving average (ARIMA), generalized autoregressive conditional heteroscedasticity (GARCH), and neural network autoregression (NNAR) methods, using the S&P 500 Pharmaceuticals Index. The objective is to identify the most accurate model based on the mean average forecasting error (MAFE). The results consistently show the NNAR model to outperform ARIMA and GARCH and to exhibit a significantly lower MAFE. The existing literature presents conflicting findings on forecasting model accuracy for stock indexes. While studies have explored various models, no universally applicable model exists. Therefore, a comparative analysis is crucial. The methodology includes data collection and cleaning, exploratory analysis, and model building. The daily closing prices of pharmaceutical stocks from the S&P 500 serve as the dataset. The exploratory analysis reveals an upward trend and increasing heteroscedasticity in the pharmaceuticals index, with the unit root tests confirming non-stationarity. To address this, the dataset has been transformed into stationary returns using logarithmic and differencing techniques. Model building involves splitting the dataset into training and test sets. The training set determines the best-fit models for each method. The models are then compared using MAFE on the test set, with the model possessing the lowest MAFE being considered the best. The findings provide insights into model accuracy for pharmaceutical industry indexes, aiding investor predictions, with the comparative analysis emphasizing tailored forecasting models for specific indexes and datasets.Yayın Balancing growth and sustainability: The impact of Greenfield investment on trade adjusted carbon emissions(Elsevier, 2024) Raza, Ali; Azam, Kamran; Khan, Asad ul Islam; Badshah, Waqar; Yönetim Bilimleri Fakültesi, İktisat BölümüIn the last two decades, the surge in carbon emissions has escalated environmental damage and is a major concern globally. Recognized as a significant threat to humanity, unchecked environmental degradation can potentially hinder the achievement of sustainable development. As a result, accurate monitoring of carbon emissions becomes imperative for formulating effective climate policies. Taking into consideration, this study has taken the newly developed consumption-based carbon emissions measure to study the pollution haven hypothesis and examine the link between Greenfield Investment (GFI) inflows to host nations and their environmental impact for 85 developing countries from 1990 to 2020. The results show a positive correlation between Greenfield investment and Consumption-based Carbon Dioxide Emissions (CCO 2 ) in sampled nations. Similarly, energy usage and export damage the environment because developing countries rely on conventional and old methods of energy usage. The results were further analyzed for low, lower middle, and upper middle income countries as well. The subsample outcome shows that Greenfield investment has a more damaged environment in low income countries as compared to lower middle and upper middle income countries. These insights underscore the urgency for developing countries to adopt environmentally conscious policies to attract international investors. It also emphasizes the need for stringent regulations aimed at curbing environmental pollution and complying with the Sustainable Development Goals (SDGs). Similarly, low and lower middle income countries to attract Greenfield investment, may also focus more on strict environmental pollution policies. Industries must be shifted from conventional energy methods to renewable energy sources. Sustainable Development Goals; 7, 12, and 13 can be achieved by host countries, alluring investors to invest in terms of Greenfield in renewable energy resources, which would be used in automobile transportation, to shift industries from conventional energy resources to renewable energy resources. The same Greenfield investment would also be used in bringing efficient machinery for more production in industries with minimal environmental pollution.Yayın Exploring effects of macroeconomic variables on financial markets: Evidence from Türkiye(Türk Kooperatifçilik Kurumu, 2023) Ahmadzada, Murad; Kaplan, Fikri; Badshah, Waqar; İnsan ve Toplum Bilimleri Fakültesi, Sosyoloji BölümüThe entire economy of the nation and businesses both are impacted by macroeconomic factors and these factors are the main drivers of financial markets over the world. Türkiye has faced significant economic and political challenges that have affected its financial markets for a long time. After global financial crisis, Türkiye’s financial markets experienced ups and downs that brought risks for investors. This paper aims to examine the relationship between macroeconomic variables and the stock exchange index for the case of Türkiye using monthly data the period between January 2010 and December 2015. Unit root tests (Augmented Dickey-Fuller, Phillips Perron) and OLS model were applied to investigate whether macroeconomic factors such as GDP, Exchange Rate, Inflation Rate, M2, and global factors such as Crude Oil Prices, Gold Prices have an impact on ISE 100 Index, or not. The empirical findings show that Exchange Rate, M2, GDP, Gold prices, and Oil prices significantly affected the ISE 100 Index. As the results indicate, there is no evidence that the inflation rate contributes to the ISE 100 Index.Yayın Is the effect of a health crisis symmetric for physical and digital financial assets? An assessment of gold and bitcoin during the pandemic(Public Library of Science, 2023) Badshah, Waqar; Musah, Mohammed; Khan, Asad ul Islam; Özer, Ercan; Yönetim Bilimleri Fakültesi, İktisat BölümüThe emergence of the covid-19 health crisis, in this advanced technological era where connections between markets, nations, and economies have grown stronger than ever before, the shock of the COVID-19 pandemic quickly had an impact on both physical and digital financial assets. The Chinese financial market experienced the first consequences of the covid-19 pandemic, then spilled over to other financial markets, including those for cryptocurrencies and the precious metals. This study examines the impact of the covid-19 pandemic on the volatilities of the dynamics of bitcoin and gold. Both assets share some characteristics, such as online trading platforms, however, gold is a tangible financial asset unlike bitcoin, which is digitally generated without any physical form. This study argues that the similarities and differences between bitcoin and gold play major roles in how the covid19 crisis affected their respective dynamics. Using daily data ranging from 9/22/2014 to 1/ 31/2023 and employing ARMA as the mean equation for GARCH model, the impact of the health crisis (covid-19) is examined on the volatilities of the prices and volumes of bitcoin and gold. Empirical evidence points out that, the pandemic has a symmetric impact on the volatilities of bitcoin and gold price returns, causing them to be more volatile. The impact of the covid-19 observed on the volume returns of the assets, however, is asymmetrical. The empirical results give evidence to the role that the vital differences existing between these assets played during the covid-19 pandemic.Yayın Parallelisms between individual and organizational career(ECOFORUM, 2021) Isac, Nicoleta; Badshah, Waqar; Yönetim Bilimleri Fakültesi, İktisat BölümüIn the conditions of the competitive economy, a special role has the capitalization of the human and the managerial potential. Career management aims at planning and modeling the progress of employees within the organization in relation to the needs assessments of the organization, but also in relation to the performance of the potential and individual preferences of employees. Career involves the interaction between organizational and individual factors and this paper presents the parallelism between organizational career management (OCM) and individual career management (ICM). The purpose of this paper is to study the theoretical and applied aspects of the career. In order to highlight these aspects, a research was undertaken within an organization, which allowed the study of the career process and the major influencing factors.Yayın Symmetric and asymmetric impacts of commercial energy distribution from key sources on economic progress in Pakistan(MDPI, 2021) Özcan, Rasim; Özcan, Rasim; Rehman, Abdul; Özcan, Rasim; Badshah, Waqar; Radulescu, Magdalena; Öztürk, İlhan; Yönetim Bilimleri Fakültesi, İktisat Bölümü; Yönetim Bilimleri Fakültesi, İktisat BölümüThis paper aims to determine the interaction of commercial energy distribution, including the installed capacity of hydroelectric energy, hydroelectric energy generation, the installed capacity of thermal energy, thermal energy generation, the installed capacity of nuclear energy, and nuclear energy generation, with economic progress in Pakistan over the 1970–2019 period. Both linear and non-linear autoregressive distributed lag models were used to ascertain the symmetric and asymmetric short- and long-run effects. The findings from the linear autoregressive distributed lag model analysis revealed evidence that increases in the installed capacity of nuclear energy, alongside higher levels of hydroelectric energy generation and thermal energy generation, have positively affected economic growth in the short run, while a greater installed capacity of nuclear energy has positively affected economic growth in the long run. The findings from the non-linear autoregressive distributed lag model analysis showed that negative shocks to installed capacities related to hydroelectric, thermal, and nuclear energy reduced economic growth, while positive shocks to hydroelectric energy generation and the installed capacity of nuclear energy boosted economic growth in the short run. Furthermore, in the long run, negative shocks to the installed capacities of hydroelectric and thermal energy reduced economic growth, negative shocks to the installed capacity of nuclear energy enhanced economic growth, and positive shocks to hydroelectric energy generation and the installed capacity of nuclear energy have stimulated economic growth in Pakistan.Yayın The impact of US sanctions on the Consumer Price Index (CPI) of Turkey(Academy of Economic Studies, 2021) Khan, Asad ul Islam; Özcan, Rasim; Badshah, Waqar; Abdul-Malik, Amaama; Yönetim Bilimleri Fakültesi, İktisat BölümüThis paper addresses the assessment of effect of the sanctions imposed on Turkey by the United States of America in the year 2018 on the Consumer Price Index (CPI) of Turkey. The study used a cross sectional data from the 81 provinces in Turkey for the periods of 2016 to 2018 from Turkish Statistical Institute (TUIK). Dummy variable with Ordinary Least Squares (OLS) estimation method is used to determine that how the sanctions affected the CPI over that period by looking at the years before 2018, the year the sanctions were imposed.Yayın Volatility spillovers from US to Emerging seven stock markets: Pre & post analysis of gfc(Int Journal Contemporary Economics & Administrative Sciences, 2021) Irshad, Shoaib; Khurshid, Muzammil; Badshah, Waqar; Bulut, Mehmet; Yönetim Bilimleri Fakültesi, İktisat Bölümü; Yönetim Bilimleri Fakültesi, İktisat BölümüThis study is conducted to check volatility spillovers from the US to Emerging seven stock markets before and after the Global Financial Crisis through the VAR-GARCH model. The pre The Global Financial Crisis (GFC) sub-sample data ranges from January 8, 2002 to June 29, 2007 and Post GFC data starts from July 4, 2009 to December 28, 2014. The outcomes of the VAR-GARCH model show that there are significant volatility spillovers from US stock market to emerging seven stock markets in most cases. The correlations reveal that the US stock market is strongly correlated with the Brazilian stock exchange, Mexican stock exchange and Russian stock exchange. These findings suggest that investors may consider geographical proximity into consideration. The empirical results also mention that the Chinese stock market, the Indonesian stock market and Indian stock market have less effect by the volatility spillovers from the US stock market. The findings also demonstrate that the Brazilian, Mexican and Russian stock markets observed a rapid increase in the CCC with the US market.
