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The effects of climate change on financial markets

Preprint | 2023 | Yeditepe University Academic and Open Access Information System

There is a critical relationship between climate change and financial markets. In this study, temperature change values are used to examine the impact of climate change on agriculture, banking, investment, and insurance sectors. The study determines the relationship between temperature changes and agriculture, banking, investment, and insurance indices in BIST by regression analysis. The results show that climate change has different impacts on different sectors. While the agricultural sector is more sensitive to temperature changes, its impact on the bankingand investment sectors may be more limited. These results suggest that temp . . .erature changes directly and significantly impact the financial performance of the agricultural sector and provide a broad understanding of the potential impacts of climate change on financial markets and the agricultural sector. In addition, the insurance sector can be affected by climate change, and temperature increases can trigger changes in insurance indices. These results emphasize that climate change is an essential factor in financial sector performance and risk management. In this context, policies and strategies to combat climate change should focus on promoting stability and sustainability in financial markets Daha fazlası Daha az

Estimation of international trade

Preprint | 2023 | Yeditepe University Academic and Open Access Information System

The study analyzed foreign trade volume among Turkey and 37 OECD countries, especially the sway of the logistics performance index on Turkey's foreign trade volume. In light of this, the effects of the logistic performance index in determining Turkey's foreign trade volume were analyzed by using the data of Turkey and OECD countries in the 2007-2020 period. In the study, three different models were established in which the total foreign trade volume, Turkey's exports to OECD countries, and Turkey's imports with OECD countries are dependent variables. The variables used in the models are the GDP of Turkey and OECD countries, R&D inve . . .stments, population, logistics performance index, and distance between countries. Since the models have problems with autocorrelation, heteroskedasticity, and cross-section dependence, the Huber-Eicker-White estimator, which is robust to these problems, was used. When the results obtained were examined, it was concluded that the sign of the relationship between GDP and foreign trade volume of the countries in the model in which the foreign trade volume was the dependent variable was positive. The gravity model has main variables used in the studies. Among these, the variable that expresses the geographical distance between countries is among the most used. In the study, the direction of relationship with trade flows is negative. Turkey's logistics performance index positively and significantly affects foreign trade volume in the first two models. It has been observed that there is a positive relationship between the populations of OECD countries and Turkey's foreign trade volume, in line with expectations. When the study's primary purpose is evaluated, Turkey's logistics performance index has a positive and significant effect on foreign trade volume Daha fazlası Daha az

Forecasting realized volatility of BIST indices with har-type models

Tüysüz, Şükriye

Preprint | 2023 | Yeditepe University Academic and Open Access Information System

In this paper, realized volatility of a selection of BIST Indices are forecasted with Heterogeneous Autoregressive Model (HAR) and its variations. For this purpose, ticks between 2001 and 2021 are used to generate 5-minute returns, which formed the basis for calculations of realized volatility and other realized measures. In the study, rolling windows are utilized for forecasting the volatility of one day ahead. These predictions are then compared to the actual realized volatilities. The study provides a thorough comparison of HAR-type models, and emphasizes the importance of underlying time series’ characteristics in forecasting. M . . .oreover, the findings of this paper also hint at matters of diversification particular to index volatility forecasting. In overall, HAR Models proved to be a successful estimator for Turkish Stock Exchange time series Daha fazlası Daha az

Large-scale forecasting of large fluctuations using wavelet coherence and multifractal behavior and developing wavelet coherence for multiple time series

Erzurumlu, Yaman Ömer | Ünal, Gazanfer

Preprint | 2022 | Yeditepe University Academic and Open Access Information System

Shocks, jumps, booms, and busts are typical large fluctuation markers that appear in crisis. Identifying financial crises and estimating leading indicators with strong relations during crisis periods have an essential role in the literature. This thesis examines the dynamic co-movements of leading indicators' multifractal features to identify financial crises due to large fluctuations. The detected dynamic relationships predict leading indicators with scale-by-scale analysis and make large-scale predictions better than challenger models. As a natural result of these studies, the n-dimensional wavelet coherence method is examined, an . . .d the vectorwavelet package is transferred to the R program. This thesis consists of three independent parts, and the contents of the studies are summarized below. In the first part, stock returns' co-movements with other leading indicators in crisis periods are analyzed with multiple and quadruple wavelet coherence using interest rate, exchange rate, and trade balance differences. The scale-by-scale wavelet transformation was used to predict large-scale relationships, and stock return estimation was performed. In the second part, the multifractal characteristics of sectoral default probabilities of the real sector in Turkey and Turkey sovereign CDS rates were examined by detrended fluctuation analysis. Significant dynamic connections between the Hölder exponents of the default rates and CDS during financial crisis periods have been examined. During the periods of financial crises, among the Hölder exponents, severely correlated large scales show multifractal features. Scale-by-scale wavelet transform has been used to predict large-scale relationships, and hence vector fractionally autoregressive integrated moving average forecasting provides better results than scalar models. The final part of the thesis introduces a new wavelet methodology to handle multivariate time series dynamic co-movements by extending multiple quadruple wavelet coherence methodologies. The primary motivation of our works is to measure wavelet coherence analytically for the specific dimension Daha fazlası Daha az

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