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copulas;portfolio management;financial time series;fuzzy data
|Issue Date:||2017-12-08 15:01:14 (UTC+8)|
This research proposal aims at investigating structure dependence for financial/economic time series with emphasis on imprecise data such as fuzzy data. The current practice in, say, forecasting economic phenomena from observed time series data, is based upon the methods of copulas and their optimization techniques such as maximum entropy. This can be achieved when data are precise. However, observed time series data in econometrics/finance are often coarse, i.e. of low quality, due to errors in measurements, missing data, sample selection, imprecision in observations. We propose to investigate the use of copula techniques for coarse data on this research project. And compare off even the structure and the advantages and disadvantages of the fuzzy correlation coefficient, the asset allocation of the correlation coefficient is more properly described, such as portfolio management, risk management and financial derivatives pricing strategies, as well as to enhance the reliability of financial analysis. Application domains: Risk management in financial econometrics, actuarial sciences, credit management decision.
|Appears in Collections:||[應用數學系] 國科會研究計畫|
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