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This paper builds on the ARCH approach for modeling distributions with time-varying conditional variance by using the generalized Student t distribution. The distribution offers flexibility in modeling both leptokurtosis and asymmetry (characteristics seen in high-frequency financial time series data), nests the standard normal and Student t distributions, and is related to the Gram Charlier and mixture distributions. An empirical ARCH model based on this distribution is formulated and estimated using hourly exchange rate returns for four currencies. The generalized Student t is found to better model the empirical conditional and unconditional distributions than other distributional specifications.
A selective index of major research papers prepared by IMF staff in 1991-98.
This report, commissioned by the Executive Board, was prepared by a committee of academic economists. The report assesses the appropriateness of current research activities, the quality and added value of the IMF's economic research and its utility in the IMF among its member countries and within the wider economics community. This publication also includes responses to the report by the IMF's staff, Managing Director, and Executive Board.
Research activity in the IMF emphasizes the links between the organization's policy and operational concerns. The main objectives of research is IMF staff understanding of policy and operational issues relevant to the institution, and to improve the analytical quality of the work prepared for management and the Executive Board and the advice provided to member countries. The scope of research in the IMF is defined by the purposes and functions of the institution. In order to foster innovation and ensure quality control, the IMF makes much of its research available outside the institution and encourages staff to interact with academia and other research organizations through conferences, seminars, and occasional joint research projects. The visiting scholar’s program has also enhanced the quality of research done in the IMF. This program brings in leading members of the economics profession from around the world to assist in the preparation of papers for the Executive Board and to conduct research on IMF-related issues.
This paper analyzes contagion and volatility with imperfect credit markets. The paper interprets contagion effects as an increase in the volatility of shocks impinging on the economy. The implications of this approach are analyzed in a model in which domestic banks borrow at a premium on world capital markets, and domestic producers borrow at a premium from domestic banks. Financial spreads depend on a markup that compensates lenders, in particular, for the expected cost of contract enforcement. Higher volatility increases financial spreads and the producers’ cost of capital.
Literature Review from the year 2020 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, language: English, abstract: This paper is a review to the GARCH family's models. Since the seminal paper of Engle from 1982, much advancement has been made in understanding GARCH models and their multivariate extensions. In MGARCH models parsimonious models should be used to overcome the difficulty of estimating the VEC model ensuring MGARCH modeling is to provide a realistic and parsimonious specification of the variance matrix ensuring its positivity. BEKK models are flexible but require too many parameters for multiple time series of more than four elements. BEKK models are much more parsimonious but very restrictive for the cross-dynamics. They are not suitable if volatility transmission is the object of interest, but they usually do a good job in representing the dynamics of variances and covariance. DCC models allow for different persistence between variances and correlations, but impose common persistence in the latter (although this may be relaxed) Student's t distribution assumption is more proper under negative skewness and high kurtosis of return series. Understanding and predicting the temporal dependence in the second-order moments of asset returns is important for many issues in financial econometrics. It is now widely accepted that financial volatilities move together over time across assets and markets. Recognizing this feature through a multivariate modeling framework leads to more relevant empirical models than working with separate univariate models. From a financial point of view, it opens the door to better decision tools in various areas, such as asset pricing, portfolio selection, option pricing, and hedging and risk management. Indeed, unlike at the beginning of the 1990s, several institutions have now developed the necessary skills to use the econometric theory in a financial perspective.
Modeling the unconditional distribution of returns on exchange rate and measuring its tails area are issues in the finance literature that have been studied extensively by parametric and non-parametric estimation procedures. However, a conflict of robustness is derived from them because the time series involved in this process are usually fat tailed and highly peaked around the center. Moreover, it has been an empirical fact that the initial phase of a freely floating exchange rate regime has experienced high volatility across many economies. The purpose of this paper is twofold. First, we try to capture the behavior of the Colombian exchange rate under the flexible system by fitting special types of distributions in order to obtain a new insight of the underlying distribution. Secondly, we measure the tail area through the Hill estimator. This strategy requires the number of extreme observations in he tails to be known. Therefore, the decision rule of choosing an optimal cutting observation based on the idea of spacing statistics is implemented by using a Monte Carlo simulation under different underlying distributions. The decision model is formulated in such a way that the mean squared error is minimized.