This paper examines key considerations around central bank digital currency (CBDC) for
use by the general public, based on a comprehensive review of recent research, central
bank experiments, and ongoing discussions among stakeholders. It looks at the reasons
why central banks are exploring retail CBDC issuance, policy and design considerations;
legal, governance and regulatory perspectives; plus cybersecurity and other risk
considerations. This paper makes a contribution to the CBDC literature by suggesting a
structured framework to organize discussions on whether or not to issue CBDC, with an
operational focus and a project management perspective.
The aim of this paper is to discuss the use of the Generalized Hyperbolic Distributions to fit Brazilian assets returns. Selected subclasses are compared regarding goodness of fi t statistics and distances. Empirical results show that these distributions fit data well. Then we show how to use these distributions in value at risk estimation and derivative price computation.
This paper argues that nonfinancial risk management is an essential element of good governance of central banks. It provides a funnelled analysis, on the basis of selected literature, by (i) presenting an outline of central bank governance in general; (ii) zooming in on internal governance and organization issues of central banks; (iii) highlighting the main issues with nonfinancial risk management; and (iv) ending with recommendations for future work. It shows how attention for nonfinancial risk management has been growing, and how this has amplified the call for better governance of central banks. It stresses that in the area of nonfinancial risk management there are no crucial differences between commercial and central banks: both have people, processes, procedures, and structures. It highlights policy areas to be explored.
The aim of this paper is to discuss the use of the Generalized
Hyperbolic Distributions to fit Brazilian assets returns. Selected
subclasses are compared regarding goodness of fit statistics and distances.
Empirical results show that these distributions fit data well. Then we show
how to use these distributions in value at risk estimation and derivative
price computation.
This paper uses the Liu et al. (2007) approach to estimate the optionimplied Risk-Neutral Densities (RND), real-world density (RWD), and relative risk aversion from the Brazilian Real/US Dollar exchange rate distribution. Our empirical application uses a sample of exchange-traded Brazilian Real currency options from 1999 to 2011. Our estimated value of the relative risk aversion is around 2.7, which is in line with other articles for the Brazilian Economy. Our out-of-sample results showed that the RND has some ability to forecast the Brazilian Real exchange rate, but when we incorporate the risk aversion, the out-of-sample performance improves substantially.
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