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AbstractThis article argues that there are parallels between developments in modern science and in art and culture, including the culture of finance, and that these developments can be tracked by a notion of volatility not just as change, but as how change itself has changed. Describing this paradigm shift requires a language that is precise but indeterminate, a language akin to metaphor, understood as figures of volatility. Three such figures are anamorphosis, anachronism, and catachresis. These figures are major instantiations of volatility, though they do not exhaust all the possibilities. What they indicate is not just that our frames of understanding have shifted, but that we are dealing with problematic, multiple, and overlapping frames: anamorphosis problematizes our experience of space, anachronism of time, and catachresis of language. These figures are not all in play at the same time. In literature, catachresis may be the dominant figure; in dance, anamorphosis; in 'slow cinema', anachronism. The aim is less to arrive at a set of defining characteristics than to follow a series of transformations across different cultural fields. Almost every field in our time is volatile each in its own way, and this has consequences for methodology. If figures are tools to think with, not to regulate thought, a necessary method would be to allow these figures to emerge from the material, not from a checklist. The question of volatility is arguably the key intellectual challenge of our time because it allows us to see deviation from a norm not just as an aberration, but as an indication that established norms are losing their normative value.

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 literature, with a distinct focus on forecasting applications. Volatility is inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then discusses a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management. Sections 3, 4 and 5 present a variety of alternative procedures for univariate volatility modeling and forecasting based on the GARCH, stochastic volatility and realized volatility paradigms, respectively. Section 6 extends the discussion to the multivariate problem of forecasting conditional covariances and correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 concludes briefly. JEL Klassifikation: C10, C53, G1.

Purpose. There are sufficient evidences in the literature that welfare of food producers and consumers is easily compromised due to unfavorable food price volatility dynamics. Therefore, this study investigates the volatility dynamics in food price index returns (FPIRETURNS), imported food price index returns (CIFCPIRETURNS), price of dollars at bureau de change (BDCRETURNS) and inter-bank rate (EXRETURNS). Design/Methodology/Approach. In view of the increasing quest to account for volatility behavior such as non-linear and time-varying risk premium in food price series using an appropriate tool, this paper adopts exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model. This is because it allows error terms to be conditional heteroscedastic, and the dynamics process generating the underlying heteroscedasticity to be asymmetric. That is, the model introduces a parameter that can reveal how conditional variance respond to both positive and negative shocks of equal magnitude (asymmetric effect). Findings and Implications. The study finds leverage effect and high persistence in some of the selected models. Also, exchange rate volatility affects volatility of FPIRETURNS, but it is more pronounced on the volatility of CIFCPIRETURNS. Limitations. Inadequate data especially for CIFCPIRETURNS is a huge limitation in this study. Originality. However, this study has sufficient empirical evidences that instability in forex market flows into the Nigerian food market with pronounced leverage effect and persistence in food price volatility. The recommendation is, government should implement stabilization policy in the forex market as a precursor to ensuring stability in domestic food market.

AbstractThis paper explores the possibility that financial depth may have an asymmetric impact on macroeconomic volatility by affecting its "good" and "bad" components in different ways. While "good" volatility refers to positive shocks to gross domestic product, consumption and investment growth, "bad" volatility denotes negative fluctuations in these macroeconomic indicators. Dynamic panel regressions in a sample of 97 countries over the period 1960–2010 provide evidence of asymmetry on three main grounds. First, financial depth reduces good volatility but does not have much impact on bad volatility except that it reduces some bad volatility of consumption. Second, though financial depth reduces both good and bad volatility of consumption, the reduction in the good component is much greater. Third, the impact of financial depth on macroeconomic volatility varies across sectors. Particularly in low‐income economies, financial depth enables better consumption decisions but poorer investment choices. These results have important policy implications.

PurposeTo investigate whether monetary volatility in the US exerts any asymmetric impact on output volatility over the period 1974‐2002.Design/methodology/approachFor the empirical purposes, the analysis makes use of the multi‐variable GARCH (MVGARCH), which allows not only the presence of volatility clustering but also the presence of asymmetries in that volatility clustering.FindingsThe empirical findings suggest that money supply volatility exerts a significant asymmetric influence on output volatility, i.e. the variance of output changes more due to positive changes than negative changes of money supply volatility.Originality/valueThe paper investigates, for the first time, the presence of any asymmetric impact of the volatility of money on the volatility of output in the case of the US.

AbstractIn this paper I relate the risk premia in the stock and bond markets to the conditional volatility of returns and time‐varying reward‐to‐volatility variables. I find that the relation between the expected returns on the stocks and bonds and the volatility of returns is time varying. I provide an approach for evaluating the relative importance of the time‐varying volatility of returns and reward‐to‐volatility variables to explain the predictability of risk premia for stock and bond returns. I show that changing reward‐to‐volatility variables explain more predictable variation in the risk premia for stocks and bonds than changing volatility of returns.

AbstractWe assess the relationship between regime‐dependent volatility in S&P 500, economic policy uncertainty, the S&P 500 bull and bear sentiment spread (bb_sp), as well as the Chicago Board Options Exchange's VIX over the period 2000–2018. Our findings from two‐covariate GARCH–MIDAS (GM) methodology, regime switching Markov Chain, and quantile regressions suggest that the association of realized volatility and sentiment varies across high‐ and low‐volatility regimes and depends on investors' sensitivity toward incidents of market uncertainties under these regimes. The findings suggest that these indicators may not be useful in volatility forecasting, especially under high‐volatility regimes.