It is evident that the prediction of future variance through advanced GARCH type models is essential for an effective energy portfolio risk management. Still it fails to provide a clear view on the specific amount of capital that is at risk on behalf of the investor or any party directly...

The purpose of this paper is to investigate whether a dynamic Value at Risk model and high frequency realized volatility models can improve the accuracy of 1-day ahead VaR forecasting beyond the performance of frequently used models. As such, this paper constructs 60 conditional volatility...

This paper revisits the performance of frequently used risk forecasting methods, such as the Value-at-Risk models. The aim is to analyze its performance, and mitigate its pitfalls by incorporating conditional variance estimates, as generated by a GARCH model. Notably, this paper tests several...

We use the term "ratio problem" to describe the omitted variable and measurement error bias that can arise when a ratio is the dependent variable in an economic model. First, we show how bias can arise from the omission of two classes of variables based on a ratio's denominator. As an example,...

This paper aims to provide a foundation for the notion of economic rate of return and investigate its relations with accounting rates of return. Introducing the notion of depreciation class (the set of depreciation schedules with the same aggregate book value) it is shown that the mean of the...

The classical approach to long term load forecasting is often limited to the use of load and weather information occurring with monthly or annual frequency. This low resolution, infrequent data can sometimes lead to inaccurate forecasts. Load forecasters often have a hard time explaining the...

The objective of this paper is to extend the results on Pseudo Maximum Likelihood(PML) theory derived in Gourieroux, Monfort, and Trognon (GMT)(1984) to a situation where the rst four conditional moments are specied.Such an extension is relevant in light of pervasive evidence that conditional...

We develop a method that identifies the effects of nationwide policy, i.e., policy implemented across all regions at the same time. The core idea is to track outcome paths in terms of stages rather than time, where a stage of a regional outcome at time t is its location on the support of a...

In many manuscripts, researchers use multivariable logistic regression to adjust for potential confounding variables when estimating a direct relationship of a treatment or exposure on a binary outcome. After choosing how variables are entered into that model, researchers can calculate an...

This work employs the Autoregressive Distributed Lag (ARDL) approach to investigate the nexus between macroeconomic variables and inflation in Madagascar. The findings reveal significant impacts of various factors, including imports, GDP, exchange rates, and oil prices, on inflation dynamics....