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Measuring financial systemic stress for Turkey: A search for the best composite indicator

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  • Chadwick, Meltem Gulenay
  • Ozturk, Huseyin

Abstract

In this study, we aim to construct a single financial stress indicator (FSI) for Turkey adopting weekly data from between April 2005 and December 2016. To do so, we compose 15 different FSIs using 14 variables that will represent five different markets, i.e. the money market, the bond market, the foreign exchange market, the equity market and the banking sector. We aggregate these five different markets using a variety of techniques, including principal component analysis (PCA), basic portfolio theory, variance equal weights and the Bayesian dynamic factor model. We compare 15 different FSIs on the basis of their relation to, and the forecasting power of, different variables such as the growth rate of industrial production, the OECD business condition index and the OECD composite leading indicator for Turkey. Our results suggest that there is no simple best indicator for Turkey to measure financial systemic stress. Some indicators offer good forecasting power for economic growth while others have a stronger correlation with systemic risk. Therefore, we offer a final FSI for Turkey conducting a model averaging method via a rolling correlation based weighting scheme to benefit from the information content of all the FSIs and observe that the final FSI successfully indicates the tension periods.

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  • Chadwick, Meltem Gulenay & Ozturk, Huseyin, 2019. "Measuring financial systemic stress for Turkey: A search for the best composite indicator," Economic Systems, Elsevier, vol. 43(1), pages 151-172.
    • Handle: RePEc:eee:ecosys:v:43:y:2019:i:1:p:151-172
    DOI: 10.1016/j.ecosys.2018.09.004
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    2. Ozcelebi, Oguzhan, 2020. "Assessing the impacts of financial stress index of developed countries on the exchange market pressure index of emerging countries," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 288-302.
    3. Xuan Lv & Menggang Li & Yingjie Zhang, 2022. "Financial Stability and Economic Activity in China: Based on Mixed-Frequency Spillover Method," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    4. Kaelo Ntwaepelo & Grivas Chiyaba, 2022. "Financial Stability Surveillance Tools: Evaluating the Performance of Stress Indices," Economics Discussion Papers em-dp2022-06, Department of Economics, University of Reading.

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    More about this item

    Keywords

    Financial stress indicators; Composite indicator of systemic stress; Principal component analysis; Bayesian dynamic factor model; Portfolio theory; Aggregation methods;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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