TR
EN
Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500
Öz
Main purpose of this study is the investigation of the relationships between economic and financial variables. This subject is well documented in the literature for both emerging and developed markets but, the contribution of this study to the literature is that the direction of the relationships is investigated by using a different method. In this study, the time series chain graphical model is utilized to examine the relationship between selected economic and financial variables over time. Time Series Chain Graphical Model enables to explore the conditional dependence among variables that are repeatedly measured at different time points. Our research validates the accuracy of the proposed model by segmenting the data by year. Additionally, graphical models are employed for precision and autocorrelation matrix analysis. We use the USA dataset, which can be found in the study of Gloyal and Welch (2021), there exist 16 variables that exhibit occasional conditional dependence and infrequent temporal dependence. This analysis, which is important in showing policy makers whether there is a relationship between variables, can also be applied to Turkish data at later stages.
Anahtar Kelimeler
Kaynakça
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- Dritsaki, Melinda (2005). Linkage Between Stock Market and Macroeconomic Fundamentals: Case Study of Athens Stock Exchange. Journal of Financial Management & Analysis 18(1), 38-47.
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Ayrıntılar
Birincil Dil
İngilizce
Konular
Ekonomik Modeller ve Öngörü
Bölüm
Araştırma Makalesi
Erken Görünüm Tarihi
25 Eylül 2024
Yayımlanma Tarihi
29 Eylül 2024
Gönderilme Tarihi
11 Ağustos 2024
Kabul Tarihi
20 Eylül 2024
Yayımlandığı Sayı
Yıl 2024 Cilt: 8 Sayı: 3
APA
Farnoudkıa, H., & Ak, A. (2024). Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500. Politik Ekonomik Kuram, 8(3), 893-905. https://doi.org/10.30586/pek.1531696
AMA
1.Farnoudkıa H, Ak A. Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500. PEK. 2024;8(3):893-905. doi:10.30586/pek.1531696
Chicago
Farnoudkıa, Hajar, ve Ayşegül Ak. 2024. “Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500”. Politik Ekonomik Kuram 8 (3): 893-905. https://doi.org/10.30586/pek.1531696.
EndNote
Farnoudkıa H, Ak A (01 Eylül 2024) Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500. Politik Ekonomik Kuram 8 3 893–905.
IEEE
[1]H. Farnoudkıa ve A. Ak, “Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500”, PEK, c. 8, sy 3, ss. 893–905, Eyl. 2024, doi: 10.30586/pek.1531696.
ISNAD
Farnoudkıa, Hajar - Ak, Ayşegül. “Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500”. Politik Ekonomik Kuram 8/3 (01 Eylül 2024): 893-905. https://doi.org/10.30586/pek.1531696.
JAMA
1.Farnoudkıa H, Ak A. Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500. PEK. 2024;8:893–905.
MLA
Farnoudkıa, Hajar, ve Ayşegül Ak. “Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500”. Politik Ekonomik Kuram, c. 8, sy 3, Eylül 2024, ss. 893-05, doi:10.30586/pek.1531696.
Vancouver
1.Hajar Farnoudkıa, Ayşegül Ak. Time Series Chain Graphical Models in the Inference of Economic Data: A Case Study from S&P 500. PEK. 01 Eylül 2024;8(3):893-905. doi:10.30586/pek.1531696