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Empirical Analysis Of Long Memory On RMB Exchange Rate Volatility

Posted on:2016-12-30Degree:MasterType:Thesis
Country:ChinaCandidate:C MengFull Text:PDF
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With the rapid development of economic in China and the increasingly frequentinternational trading, China is having an increasingly close contact with the world.Besides with the continued implementation of RMB exchange rate reform, the processof internationalization of the RMB continues to advance, as the connection ofeconomy between domestic and overseas, exchange rate is becoming the focus ofresearch in the field of finance. Since the2008world financial crisis and the2009European sovereign debt crisis broke out, the domestic economy has been influencedby other relevant national macroeconomic situation and regulatory policy via theexchange rate transmission mechanism in the context of economic globalization.Since2012the RMB continued to appreciate under the pressure of external market,exchange rate volatility also expanded. The level and the volatility of exchange rate ofboth have important influence on the internal price, external trade and internationalcapital flows. With the construction and development of One Belt One Road, and thedevelopment and expansion of Asian Infrastructure Investment Bank, the internationalstanding of RMB is further improved. So it will be of great significance to strengthenthe research of RMB exchange rate.This paper mainly study on the volatility characteristics of RMB exchange rate.Based on the fractal market theory, this paper summarizes four characteristics ofRMB exchange rate volatility, the peak apex and thick tail skewed distribution,clustering features, the asymmetric effect and long term memory function. This paperanalyses the characteristics of RMB exchange rate volatility in two aspects fromtheoretical and empirical. And it focuses on the research of the characteristics of theasymmetry and long memory of the RMB exchange rate volatility.The theoretical part elaborates on the fractal market hypothesis, analyzes fourcharacteristics of RMB exchange rate volatility from the aspects of theory, introducesempirical models, and focuses on the test and parameter estimation for longterm memory characteristics. The empirical part uses daily time series data after2005reform of RMB exchange rate. First test the RMB exchange rate volatility peak thick tail distribution and the cluster effect based on statistical analysis and ARCH-LMtest, and then use EGARCH model to parameter estimate non symmetry of theRMB exchange rate volatility, use R/S analysis method to test the long memoryproperty of the volatility of RMB exchange rate, finally use FIGARCH model toparameter estimate long-term memory characteristics of the volatility.The empirical results show that the volatility of RMB exchange ratehas significant peak apex and thick tail, clustering features, the asymmetric effect andlong term memory function. The RMB exchange rate volatility has leptokurtic andleft skewed-t distribution, the model parameters are estimated to Skewed distributionvia the statistical analysis, and it is appropriate to use Skewed-t distribution todescribe the characteristics of peak apex and thick tail and asymmetrical skeweddistribution in the process. The parameters of the EGARCH model estimation resultsshow that RMB exchange rate volatility has a significant asymmetry, and the impactof positive information is greater than the negative information. FIGARCH parameterestimation results are significant. The volatility of RMB exchange rate has obvioushistorical memory function. According to the characteristics of the volatility of RMBexchange rate, in making decisions or predicting the future development trend of theRMB exchange rate volatility, the central bank and investors should fully considerthe characteristics of RMB exchange rate volatility, correctly analyses thenon symmetry effect, consider both the short term and the long term impact of themarket, and take active measures to reasonably predict.
Keywords/Search Tags:Exchange rate volatility, Long memory, FIGARCH model
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