Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning...

Factor based forecasting has been at the forefront of developments in the macroeconometric forecasting literature in the recent past. Despite the flurry of activity in the area, a number of specification issues such as the choice of the number of factors in the forecasting regression, the...

Economies, societies, and many natural systems evolve and change, sometimes dramatically, so good models and accurate forecasts are vital for policymakers to prepare for and navigate these changes successfully. Yet history is littered with forecasts that went badly wrong, sharply illustrated...

Several procedures to estimate daily risk measures in cryptocurrency markets have been recently proposed in the literature. Among them, procedures taking into account the presence of extreme observations, as well as procedures that include more than a single regime, have performed substantially...

Beyond their importance from the regulatory policy point of view, Value-at-Risk (VaR) and Expected Shortfall (ES) play an important role in risk management, portfolio allocation, capital level requirements, trading systems, and hedging strategies. Unfortunately, due to the curse of...

Sensitivity analysis is important for its own sake and also in combination with diagnostic testing. We consider the question how to use sensitivity statistics in practice, in particular how to judge whether sensitivity is large or small. For this purpose we distinguish between absolute and...

Expectations form the basis of economic decisions of market participants in an uncertain world. Sentiment indicators reflect those expectations and thus have a proven track record for predicting economic variables. However, respondents of surveys perceive the world to a large extent with the...

This collection of papers analyzes the versatility and predictive power of survey expectations data in asset pricing and macroeconomic forecasting. The first paper, Using Sentiment Surveys to Predict GDP Growth and Stock Returns sheds new light on the question of whether or not sentiment...

Despite the vast academic literature on modelling stochastic volatility, many finance practitioners still use the simple "RiskMetrics" approach of J. P. Morgan (1997), based on the exponentially weighted moving average (EWMA) volatility combined with the $\sqrt{h}$-rule for scaling volatility...

Volatility forecasts play a central role among equity risk measures. Besides traditional statistical models, modern forecasting techniques, based on machine learning, can readily be employed when treating volatility as a univariate, daily time-series. However, econometric studies have shown that...