The use of GARCH models is widely used as an effective method for capturing the volatility clustering inherent in financial returns series. The residuals from such models are however often non-Gaussian, and two methods suggest themselves for dealing with this; outlier removal, or use of...

We introduce a dynamic banking-macro model, which abstains from conventional mean-reversion assumptions and in which—similar to Brunnermeier and Sannikov (2010)—adverse asset-price movements and their impact on risk premia and credit spreads can induce instabilities in the banking sector. To...

This paper studies the issue of local instability of the banking sector and how it may spillover to the macroeconomy. The banking sector is considered here as representing a wealth fund that accumulates capital assets, can heavily borrow and pays bonuses. We presume that the banking system faces...

We investigate consequences of overleveraging and financial-sector stress on real economic activities. When banks become vulnerable, due to high leveraging, and there is a strong feedback between the real and the financial sector, a regime of high financial stress may arise. The vulnerability of...

After the financial market meltdown of the years 2007–2008 the Obama administration responded with large fiscal stimulus package, yet the reaction to this stimulus has been diverse. Some predicted a multiplier effect in the order of 1.5, others argued that the multiplier will be less than 0.5....

This paper introduces a Banking-Macro Model and estimates the linkages through a Multi-Regime VAR (MRVAR). We first introduce a dynamic model which is akin to the Brunnermeier and Sannikov (BS) model (2010). The banking sector borrows from capital markets, issues liabilities, accumulates assets,...

Assumptions about the dynamic and distributional behavior of risk factors are crucial for the construction of optimal portfolios and for risk assessment. Although asset returns are generally characterized by conditionally varying volatilities and fat tails, the normal distribution with constant...

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and,...