Khan, Asad ul Islam
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Yönetim Bilimleri Fakültesi, İktisat Bölümü
İktisat Bölümü, başta Türkiye ve çevre ülkeler olmak üzere küresel ekonomileri anlayan, var olan sorunları analiz ederken, iktisadi kuramları ve kavramları yetkin ve özgün bir şekilde kullanma becerisine sahip bireyler yetiştirmeyi amaçlamaktadır.
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Khan
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Solunum Sistemi, Genel ve Dahili Tıp, Çevre Bilimleri ve Ekoloji, İş Ekonomisi, Bilim ve Teknoloji
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Yayın Beyond GARCH: Intraday insights into the exchange rate and stock price volatility dynamics in Borsa Istanbul sectors(Shaheed Benazir Bhutto Women University, 2024) Abdul-Rahman, Mutawakil; Khan, Asad ul Islam; Kaplan, Muhittin; Yönetim Bilimleri Fakültesi, İktisat BölümüThis study investigated the impact of exchange rate volatility on sectoral stock volatility by employing the intraday volatility measure directly calculated from the original data, using daily data from 27 Borsa Istanbul sectors between April 29, 2003, and April 25, 2023. In the literature, GARCH models are commonly used to study the volatility spillovers between exchange rates and stock prices, typically using aggregate data. However, the GARCH family models provide inefficient and biased estimates if they are misspecified. Moreover, using aggregate-level data may lead to biased and misleading conclusions. The research used intraday volatility measures to overcome the shortcomings of GARCH models. The ordinary least squares (OLS), GARCH (1,1) methods, and Garman and Klass (1980) volatility estimator are used. The empirical results showed that the estimates from each method vary significantly, and these disparities in the results might be due to misspecification in GARCH (1,1) models. The intraday volatility model estimation results showed that although stock price volatilities in all sectors are positively and significantly affected by exchange rate volatility, their magnitudes vary significantly. Taken together, this implies the presence of vast heterogeneities in the responses of sectoral stock price volatilities to exchange rate volatility. The results encourage policymakers to pay special attention to these heterogeneities to prevent capital flights and underinvestment. Additionally, the findings assist investors in making more effective decisions by helping them adapt their investment strategies to factor in exchange rate fluctuations and mitigate the impact of unexpected events in the exchange rate market.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 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 Subsample stability, change detection and dynamics of oil and metal markets: A recursive approach(Elsevier, 2023) Khan, Asad ul Islam; Shahbaz, Muhammad; Napari, Ayuba; Yönetim Bilimleri Fakültesi, İktisat BölümüThe analysis of historical price data for patterns and using such patterns for predictions and policy recommendations has become ubiquitous in the existing economics literature. These predictions and recommendations are premised on the stability of the statistical properties and inter-variable dynamics for which a single regime or few number of regimes can capture. This, however, is a strong assumption with serious repercussions if violated. In this study, the appropriateness of the stability assumption is questioned using various recursive regressions to test stability, consistency of stationarity and stability in inter-variable dynamics between crude oil, gold, silver, and platinum prices. Using monthly data sourced from the World Bank Commodity Price Data (Pink Sheet) from January 1, 9960 to March 2022, our empirical analysis found level prices of oil, gold, and platinum to be consistently non-stationary with rare exceptions. The level price of silver however is found to be inconsistent with multiple regime switches while the logged series of all variables yielded non-stationarity. The default is stationarity for all the variables when price series are logged differenced and/or differenced for oil, silver, and platinum. Differenced gold prices resulted in inconsistent stationarity with multiple regime changes. Even if rare, the stationarity of all the variables is dependent on time and sample size due to the inconsistence in the stationarity verdict. On the bi-variate relationship in the long run, only level silver prices are found to be cointegrated with oil while logged silver prices are inconsistently cointegrated with logged oil prices. Also, in the short-run, only log of oil prices is found to Granger cause log of silver prices. It is thus recommended that researchers and policy makers be tempered in extrapolating statistical findings in general and the price and interprice dynamics of oil, gold, silver and platinum into the future.Yayın Unravelling crash risk transmission: Cryptocurrency impact on stock markets in G-7 and China(Johar Education Society Pakistan, 2024) Khan, Asad ul Islam; Özcan, Rasim; Ibrahim, Mahat Maalim; Yönetim Bilimleri Fakültesi, İktisat BölümüIn this paper, we use the Empirical Bayes estimation and multiple linear regression approach to examine the impact of the top 5 cryptocurrencies’ crash risks on the G-7 and China equity markets’ crash risks. MATLAB was used to calculate the crash risks, while Stata software was employed for the econometric analysis. Three crash risk measures are used to validate the robustness of the results: (i) the relative frequency of the number of crash days in the market, (ii) the monthly returns’ skewness, and (iii) the down-to-up volatility. Our findings indicate that overall crash risks of the top 5 cryptocurrencies are positively related with G-7 and Chinese stock markets’ crash risk. This suggests that the crash risk transmits from the crypto to the equity markets and the crashes in crypto can serve as a predictor in the stock markets. Furthermore, there is a negative correlation between the historical crash risks of the G-7 stock market and the present crash risks of the same stock market. This suggests that past stock market crashes can serve as a predictive factor for assessing the current risk of a stock market crash.Yayın Public attitudes toward higher education using sentiment analysis and topic modeling(Springer Nature, 2024) Göçen, Ahmet; Ibrahim, Mahat Maalim; Khan, Asad ul Islam; Yönetim Bilimleri Fakültesi, İktisat BölümüThis study examines higher education through data-mining methodologies, aiming to uncover key themes and sentiments in global discourse. Utilizing sentiment analysis and topic modeling, the research analyzes 157,943 tweets from 84,423 unique users over a five-month period (January to May 2023). This period was selected, coinciding with the rise of artificial intelligence (AI) tools, particularly ChatGPT. The study investigates the discussions, emotional tones, and dominant topics shaping the global narrative of higher education within X (Twitter) data. Key findings include the geographical distribution of tweets and the most frequent positive and negative perceptions. It also addresses critical issues such as affordability, accessibility, and funding in higher education. Furthermore, the data shows public reactions to AI in higher education are initially negative, while higher education tweets are primarily characterized by positivity and optimism. The higher education tweets are mainly posted on the weekend, with decreased activity during weekdays. This research provides insights into the evolving higher education landscape amid rapid technological advancements.Yayın Constant time calculation of the metric dimension of the join of path graphs(MDPI, 2023) Khan, Asad ul Islam; Khan, Asad ul Islam; Zhang, Chuanjun; Haidar, Ghulam; Khan, Murad ul Islam; Yousafzai, Faisal; Hila, Kostaq; Khan, Asad ul Islam; Yönetim Bilimleri Fakültesi, İktisat Bölümü; Yönetim Bilimleri Fakültesi, İktisat BölümüThe distance between two vertices of a simple connected graph G, denoted as (Formula presented.), is the length of the shortest path from u to v and is always symmetrical. An ordered subset (Formula presented.) of (Formula presented.) is a resolving set for G, if for ? (Formula presented.), there exists (Formula presented.) ? (Formula presented.). A resolving set with minimal cardinality is called the metric basis. The metric dimension of G is the cardinality of metric basis of G and is denoted as (Formula presented.). For the graph (Formula presented.) and (Formula presented.), their join is denoted by (Formula presented.). The vertex set of (Formula presented.) is (Formula presented.) and the edge set is (Formula presented.). In this article, we show that the metric dimension of the join of two path graphs is unbounded because of its dependence on the size of the paths. We also provide a general formula to determine this metric dimension. We also develop algorithms to obtain metric dimensions and a metric basis for the join of path graphs, with respect to its symmetries.Yayın Most stringent test of null of cointegration: A Monte Carlo comparison(Taylor & Francis, 2022) Khan, Asad ul Islam; Khan, Asad ul Islam; Khan, Asad ul Islam; Khan, Waqar Muhammad; Hussan, Mehmood; Yönetim Bilimleri Fakültesi, İktisat Bölümü; Yönetim Bilimleri Fakültesi, İktisat BölümüTo test for the existence of long run relationship, a variety of null of cointegration tests have been developed in literature. This study is aimed at comparing these tests on basis of size and power using stringency criterion: a robust technique for comparison of tests as it provides with a single number representing the maximum difference between a test’s power and maximum possible power in the entire parameter space. It is found that in general, asymptotic critical values tends to produce size distortion and size of test is controlled when simulated critical values are used. The simple LM test based on KPSS statistic is the most stringent test at all sample sizes for all three specifications of deterministic component, as it has the maximum difference approaching to zero and lesser than 20% for the entire parameter space.Yayın Roling-window bounds testing approach to analyze the relationship between oil prices and metal prices(Elsevier, 2023) Khan, Asad ul Islam; Khan, Asad ul Islam; Shahbaz, Muhammad; Khan, Asad ul Islam; Mubarak, Muhammad Shujaat; Yönetim Bilimleri Fakültesi, İktisat Bölümü; Yönetim Bilimleri Fakültesi, İktisat BölümüThis paper is to find how the existence of a long-run relationship between oil prices and metals prices evolved for the time from January 1979 to December 2017. The rolling-window autoregressive lag mod- eling (RARDL) testing approach of cointegration has been introduced and applied to assess the long-run relationship considering four rolling windows of 5, 10, 15, and 20 years. The empirical evidence concludes that for a small rolling window of 5 years, there is no evidence of the long-run relationship between oil prices and metals prices, i.e. gold, platinum, and silver. However, there is a long-run relationship between oil prices and steel prices from December 2003 to December 2014. At larger rolling windows of 10, 15 and 20 years, oil prices and gold prices are not cointegrated; however, steel, silver, and platinum have a long-run relationship with oil prices in different periods.Yayın Metric dimensions of bicyclic graphs(MDPI, 2023) Khan, Asad ul Islam; Khan, Asad ul Islam; Khan, Asad ul Islam; Haidar, Ghulam; Abbas, Naeem; Khan, Murad ul Islam; Niazi, Azmat Ullah Khan; Yönetim Bilimleri Fakültesi, İktisat Bölümü; Yönetim Bilimleri Fakültesi, İktisat BölümüThe distance d(va, vb) between two vertices of a simple connected graph G is the length of the shortest path between va and vb. Vertices va, vb of G are considered to be resolved by a vertex v if d(va, v) 6= d(vb, v). An ordered set W = fv1, v2, v3, . . . , vsg V(G) is said to be a resolving set for G, if for any va, vb 2 V(G), 9 vi 2 W 3 d(va, vi) 6= d(vb, vi). The representation of vertex v with respect to W is denoted by r(vjW) and is an s-vector(s-tuple) (d(v, v1), d(v, v2), d(v, v3), . . . , d(v, vs)). Using representation r(vjW), we can say that W is a resolving set if, for any two vertices va, vb 2 V(G), we have r(vajW) 6= r(vbjW). A minimal resolving set is termed a metric basis for G. The cardinality of the metric basis set is called the metric dimension of G, represented by dim(G). In this article, we study the metric dimension of two types of bicyclic graphs. The obtained results prove that they have constant metric dimension.
