Backtesting VaR Models: An Expected Shortfall Approach

Academics and practitioners have extensively studied Value-at-Risk (VaR) to propose a unique risk management technique that generates accurate VaR estimations for long and short trading positions and for all types of financial assets. However, they have not succeeded yet as the testing frameworks of the proposals developed, have not been widely accepted. A two-stage backtesting procedure is proposed to select a model that not only forecasts VaR but also predicts the losses beyond VaR. Numerous conditional volatility models that capture the main characteristics of asset returns (asymmetric and leptokurtic unconditional distribution of returns, power transformation and fractional integration of the conditional variance) under four distributional assumptions (normal, GED, Student-t, and skewed Student-t) have been estimated to find the best model for three financial markets, long and short trading positions, and two confidence levels. By following this procedure, the risk manager can significantly reduce the number of competing models that accurately predict both the VaR and the Expected Shortfall (ES) measures.Value-at-Risk, Expected Shortfall, Volatility Forecasting, Arch Models

Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries

The paper investigates the time-varying correlation between stock market prices and oil prices for oil-importing and oil-exporting countries. A DCC-GARCH-GJR approach is employed to test the above hypothesis based on data from six countries; Oil-exporting: Canada, Mexico, Brazil and Oil-importing: USA, Germany, Netherlands. The contemporaneous correlation results show that i) although time-varying correlation does not differ for oil-importing and oil-exporting economies, ii) the correlation increases positively (negatively) in respond to important aggregate demand-side (precautionary demand) oil price shocks, which are caused due to global business cycle’s fluctuations or world turmoil (i.e. wars). Supply-side oil price shocks do not influence the relationship of the two markets. The lagged correlation results show that oil prices exercise a negative effect in all stock markets, regardless the origin of the oil price shock. The only exception is the 2008 global financial crisis where the lagged oil prices exhibit a positive correlation with stock markets. Finally, we conclude that in periods of significant economic turmoil the oil market is not a safe haven for offering protection against stock market losses

Forecasting economic policy uncertainty

Forecasting the economic policy uncertainty in Europe is of paramount importance given the on-going sovereign debt crisis. This paper evaluates monthly economic policy uncertainty index forecasts and examines whether ultra-high frequency information from asset market volatilities and global economic uncertainty can improve the forecasts relatively to the no-change forecast. The results show that the global economic policy uncertainty provides the highest predictive gains, followed by the European and US stock market realized volatilities. In addition, the European stock market implied volatility index is shown to be an important predictor of the economic policy uncertainty

Forecasting oil prices: High-frequency financial data are indeed useful.

The paper examines the importance of combining high frequency financial information, along with the oil market fundamentals, in order to gain incremental forecasting accuracy for oil prices. Inspired by French et al. (1986) and Bollerslev et al. (1988), who maintain that future asset returns are also influenced by past volatility, we use daily volatilities and returns from financial and commodity markets to generate real out-of-sample forecasts for the monthly oil futures prices. Our results convincingly show that although the oil market fundamentals are useful for long-run forecasting horizons, the combination of the latter with high-frequency financial data significantly improve oil price forecasts, by reducing the RMSE of the no-change forecast by approximately 68%. Results are even more impressive during the oil price collapse period of 2014-15. These findings suggest that we cannot ignore the information extracted from the financial markets when forecasting oil prices. Our results are both statistically and economically significant, as suggested by several robustness tests

Oil price assumptions for macroeconomic policy

Despite the arguments that are put forward by the literature that oil price forecasts are economically useful, such claim has not been tested to date. In this study we evaluate the economic usefulness of oil price forecasts by means of conditional forecasting of three core macroeconomic indicators that policy makers are predicting, using assumptions about the future path of the oil prices. The chosen indicators are the core inflation rate, industrial production and purchasing price index. We further consider two more indicators, namely inflation expectation and monetary policy uncertainty. To do so, we initially forecast oil prices using a MIDAS framework and subsequently we use regression-based models for our conditional forecasts. Overall, there is diminishing importance of oil price forecasts for macroeconomic projections and policy formulation. An array of arguments is presented as to why this might be the case, which relate to the improved energy efficiency, the contemporary monetary policy tools and the financialisation of the oil market. Our findings remain robust to alternative oil price forecasting frameworks

The effects of oil price shocks on stock market volatility: Evidence from European data

The paper investigates the effects of oil price shocks on stock market volatility in Europe by focusing on three measures of volatility, i.e. the conditional, the realized and the implied volatility. The findings suggest that supply-side shocks and oil specific demand shocks do not affect volatility, whereas, oil price changes due to aggregate demand shocks lead to a reduction in stock market volatility. More specifically, the aggregate demand oil price shocks have a significant explanatory power on both current-and forward-looking volatilities. The results are qualitatively similar for the aggregate stock market volatility and the industrial sectors' volatilities. Finally, a robustness exercise using short-and long-run volatility models supports the findings

Forecasting the Oil Volatility Index Using Factors of Uncertainty

The oil volatility index (OVX) has attracted the attention of investors, as oil prices have been subject to high degrees of variation in the last few decades, and investors would therefore benefit from obtaining accurate forecasts of OVX. In this paper, we aim to develop models that can accurately generate OVX forecasts. The contribution of our study to the literature lies in the incorporation of different factors that reflect uncertainty as potential drivers of OVX. For example, implied volatility (IV) indices, such as the VIX and GVZ are examined. Apart from the inclusion of IV indices, we investigate whether other uncertainty indicators play a significant role in generating OVX forecasts. Our results show that the predictive ability of the models is not enhanced by the inclusion of most of the aforementioned factors of uncertainty, with the single exception of the U.S. economic policy uncertainty index, which seems to improve the forecasting ability of a simple model that focuses on the OVX as a target variable

Business cycle synchronisation in EU: a time-varying approach

The paper investigates the time -varying correlation between the EU12 -wide business cycle and the initial EU12 member -countries based on scalar -BEKK and multivariate Riskmetrics model frameworks for the period 1980-2009. The paper provides evidence that changes in the business cycle synchronisation correspond to institutional changes that have taken place at a European level.Business cycle synchronisation has moved in a direction positive for the operation of a single currency suggesting that the common monetary policy is less costly in terms of lost flexibility at the national level. Thus,any questions regarding the optimality and sustainability of the common currency area in Europe should not be attributed to the lack of cyclical synchronisation

Investments and uncertainty revisited: The case of the US economy.

This paper examines the relationship between investments and uncertainty for the US economy, as the latter is approximated by consumer sentiment, purchasing managers’ prospects and economic policy uncertainty. Contrary to the existing literature, we provide evidence that this relationship is time-varying. The time variation is attributed to the observed temporal replacement effect between private and public investments. Furthermore, we show that there are two distinct correlation regimes in this relationship and unless we concentrate on them, we cannot fully unravel the real link between uncertainty and investments. Finally, we examine whether the use of the two correlation regimes provides better forecasts for investments compared to the use of the uncertainty indices alone. The forecasting exercise reveals that the use of correlation regimes provides statistically superior out of-sample forecasts

Oil and currency volatilities: Co-movements and hedging opportunities

The current literature concentrates its attention to the interactions between oil and exchange rates, focusing only on the first moments. Extending this line of research, we investigate the time-varying correlation between the volatilities of two oil benchmarks (Brent and WTI) and six currencies of the major oil-importers and oil-exporters, for the period from February 1, 1999 to May 30, 2016, using a Diag-BEKK model. The optimal portfolio weights and hedge ratios for portfolios comprised of the aforementioned volatilities, are also examined. The analysis reveals that oil and currency volatilities exhibit positive correlations during major global or region-specific economic events (such as the Global Financial Crisis of 2007–2009 and the EU debt crisis period). By contrast, country-specific events yield heterogeneous time-varying correlations between oil and the different currencies in our sample. Both the optimal portfolio weights and optimal hedge ratios estimations demonstrate a time-varying behaviour, suggesting that continuous portfolio rebalancing is necessary for diversification purposes. The findings also show that risk reduction based on the optimal portfolio weight strategy is primarily beneficial for oil volatility investors, whereas currency volatility investors achieve better hedging using the optimal hedge ratio strategy