*This paper is the result of work being undertaken as part of a collaborative research program entitled ‘Unemployment: Economic Analysis and Policy Modelling’. The project is generously supported by the Australian Research Council and the following collaborative partners: Commonwealth Department of Family and Community Services, Commonwealth Department of Employment, Workplace Relations and Sma...

The Hinich (1982) bispectrum test for nonlinearity and Gaussianity indicates that the residuals of the Tiao-Box (1981) constrained and unconstrained VAR models for the gas furnace data reject the assumption of Gaussianity and linearity over a grid of bandwidths for estimating the bispectrum. These findings call into question the specification of the linear VAR and VARMA models assumed by Tiao-B...

Value at Risk (VaR) has emerged in recent years as a standard tool to measure and control the risk of trading portfolios. Yet, existing theoretical analyses of the optimal behavior of a trader subject to VaR limits have produced a negative view of VaR as a risk-control tool. In particular, VaR limits have been found to induce increased risk exposure in some states and an increased probability o...

simply stated, a vaR model is a model of the distribution of future profits and losses of a bank’s trading portfolio. vaR models combine information on a bank’s trading positions across various products with statistical estimations of the probability distribution of the underlying market factors and their relation to each other. the final output of a vaR model is a vaR estimate, which is define...

This paper tests the ability of popular New Keynesian models, which are traditionally used to study monetary policy and business cycles, to match the data regarding a key channel for monetary transmission: the dynamic interactions between macroeconomic variables and their corresponding expectations. In the empirical analysis, we exploit direct data on expectations from surveys. To explain the j...

Event risk is the risk that a portfolio’s value can be affected by large jumps in market prices. Event risk is synonymous with “fat tails” or “jump risk”. Event risk is one component of “specific risk,” defined by bank supervisors as the component of market risk not driven by market-wide shocks. Standard Value-at-Risk (VaR) models used by banks to measure market risk do not do a good job of cap...

It is well known that many countries around the world depend on the US as their major trade partner. As a result, if something does happen to US economy it surely will affect the economy of all these countries. In this study, we investigate the relationship between the US and four Asian emerging stock markets namely Hong Kong, India, South Korea and Malaysia using monthly data between 1996 and ...

This paper investigates the information content of the ex post overnight return for one-day-ahead equity Value-at-Risk (VaR) forecasting. To do so, we deploy a univariate VaR modeling approach that constructs the forecast at market open and, accordingly, exploits the available overnight close-to-open price variation. The benchmark is the bivariate VaR modeling approach proposed by Ahoniemi et a...

Multivariate time-series modeling and forecasting is an important problem with numerous applications. Traditional approaches such as VAR (vector auto-regressive) models and more recent approaches such as RNNs (recurrent neural networks) are indispensable tools in modeling time-series data. In many multivariate time series modeling problems, there is usually a significant linear dependency compo...