FORECASTING OIL PRICE VOLATILITY

Objective-based forecast evaluations for crude oil volatility

About the project

Find out about our innovative project aiming to develop objective-based loss functions to evaluate crude oil volatility forecasts.

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Project summary

Oil price volatility forecasting is of major importance due to the financialisation of the oil market and the fact that the oil market participants’ decisions are based on such forecasts (e.g. oil-intensive industries, policy makers, portfolio traders).

Currently, forecasters mainly predict oil price conditional and realized volatility using primarily Generalised Autoregressive Conditional Heteroscedasticity (GARCH) and Heterogeneous Autoregressive (HAR) models and evaluate the forecasts’ performance using statistical loss functions, such as the Mean Absolute Predictive Error (MAPE).

Nevertheless, oil price volatility users are faced with (i) multiple volatility measures apart from conditional and realized (e.g. historical, implied, range-based, bipower, semi-variance, two-scale realized), (ii) multiple forecasting models (HAR, GARCH, ARIMA, Switch-Regimes, Weighted Moving Average (WMA)) and (iii) different applications for which they use oil price volatility forecasts (e.g. policy making, portfolio allocation, risk management).

Hence, the evaluation of the different forecasts using statistical loss functions is not adequate.

Thus, in order to make informed decisions, oil volatility users need to know the most appropriate volatility measure in combination with the most accurate forecasting model.

It is therefore necessary to provide a framework which will consider a range of volatility measures and models and will allow oil volatility users to be able to choose the most appropriate volatility measure combined with the best forecasting model, according to the economic decision for which the forecast will be used.

To achieve this, loss functions that reflect the purpose of the oil price volatility forecast should be employed, i.e. objective-based loss functions rather than stand-alone statistical ones.

Hence, this innovative project aims to lay the foundations for an advanced econometric model framework to be used as a policy and practice suite of tools for the evaluation of the most appropriate oil volatility measures combined with the most accurate forecasting models, based on objective-based loss functions.

This project is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement (No 746025).