In this paper, I introduce a theoretically justified framework that incorporates scenario analysis into operational risk modeling. The basis for the framework is the idea that only worst-case scenarios contain valuable information about the tail behavior of operational losses. In addition,...

This paper addresses challenges of estimating operational risk regulatory capital when a loss sample is truncated from below at a data collection threshold. Recent operational risk literature reports that the attempts to estimate loss distributions by the maximum likelihood method are not always...

We enhance the method of integrating scenarios proposed in Ergashev (2012) into risk models. In particular, we provide additional theoretical insights of the method with focus on stress testing Value-at-Risk models. We extend the application of the method, which is originally proposed for...

In finance and economics, there is a great deal of work on the theoretical modeling and statistical estimation of the yield curve (defined as the relation between $-\frac{1}{\tau }\log p_{t}(\tau )$ and $\tau$, where $p_{t}(\tau )$ is the time $t$ price of the zero-coupon bond with payoff 1 at...