The effects of trading activity on market volatility

The paper re-examines the question of excessive implied persistence of volatility estimates when GARCH type models are used. Ten actively traded US stocks are considered and as already established in the literature, when volume traded is inserted in the GARCH (1, 1) or (EGARCH 1, 1) models for returns, the estimated persistence is decreased. Since volume is affected also by within-the-day price movements and hence is not weakly exogenous relative to returns, alternative proxies for trading activities are suggested. It is concluded that the difference between the opening price and the closing price of the previous day accounts also for most of the persistence in the autoregressive conditional heteroskedasticity.     

The effects of Federal funds rate surprises on S&P 500 volatility and volatility risk premium

In this paper, we examine the effects of expected and surprise components in Federal funds target rate changes on realized and implied volatility. We find that surprise changes in the target rate significantly increase volatility. Consistent with the efficient market hypothesis, our analysis suggests that the expected component of a target rate change as well as the target rate change itself, do not significantly affect volatility. We also show that larger than expected decreases in the Federal funds target rate tend to lower the volatility risk premium.     

The importance of the volatility risk premium for volatility forecasting

In this paper, we study the role of the volatility risk premium for the forecasting performance of implied volatility. We introduce a non-parametric and parsimonious approach to adjust the model-free implied volatility for the volatility risk premium and implement this methodology using more than 20 years of options and futures data on three major energy markets. Using regression models and statistical loss functions, we find compelling evidence to suggest that the risk premium adjusted implied volatility significantly outperforms other models, including its unadjusted counterpart. Our main finding holds for different choices of volatility estimators and competing time-series models, underlying the robustness of our results.     

Dynamic effects of idiosyncratic volatility and liquidity on corporate bond spreads

We study the dynamic impact of idiosyncratic volatility and bond liquidity on corporate bond spreads over time and empirically disentangle both effects. Using an extensive data set, we find that both idiosyncratic volatility and liquidity are critical mainly for the distress portfolios, i.e., low-rated and short-term bonds; for others only volatility matters. The effects of volatility and liquidity shocks on bond spreads were both exacerbated during the recent financial crisis. Liquidity shocks are quickly absorbed into bonds prices; however, volatility shocks are more persistent and have a long-term effect. Our results overall suggest significant differences between how volatility and liquidity dynamically impact bond spreads.     

On the causes of volatility effects of conglomerate breakups

We describe four channels through which breakups can potentially increase idiosyncratic volatility for parent firms. These are: loss of diversification (portfolio effect), change in growth opportunities, change in operational efficiency, and the flow and assimilation of information (information effect). The relevance of each channel depends on the mode of a breakup. We explain conceptually and show empirically, using a sample of 530 breakups (259 spinoffs and 271 equity carveouts), that the portfolio effect is dominant for spinoff parents, while the information effect gains importance for carveout parents. Our novel insight is that the magnitude of the information effect depends on the pre-announcement information set held by investors; we provide a simple state-space model and empirical evidence to support this intuition. We also find a relation between the change in operational efficiency and the change in idiosyncratic volatility for spinoff parents.     

利率平滑:基于学习机制和美联储实践的分析与启示

本文通过引入学习机制,在不确定性视角下剖析了利率平滑的作用原理。认为具有学习机制的利率平滑有助于公众和央行以较低成本获取充分信息从而形成合理预期;同时,对美联储利率平滑操作实践的分析表明,利率平滑并非绝对最优,也具有一定的政策风险。因此,我国央行可在一定条件下进行利率平滑,且须注重学习才能提高政策操作效果。     

Estimating volatility clustering and variance risk premium effects on bank default indicators

Review of Quantitative Finance and Accounting - Default risk increases substantially during financial stress times due to mainly the two reasons: volatility clustering and investors’ desire...     

The Jacobi stochastic volatility model

We introduce a novel stochastic volatility model where the squared volatility of the asset return follows a Jacobi process. It contains the Heston model as a limit case. We show that the joint density of any finite sequence of log-returns admits a Gram–Charlier A expansion with closed-form coefficients. We derive closed-form series representations for option prices whose discounted payoffs are functions of the asset price trajectory at finitely many time points. This includes European call, put and digital options, forward start options, and can be applied to discretely monitored Asian options. In a numerical study, we show that option prices can be accurately and efficiently approximated by truncating their series representations.     

The impact of delivery terms on stock return volatility

The application of generalized ARCH models to daily stock returns shows changes in delivery and payment terms to be an important factor in determining measured volatility. In contrast, the holding period between trading days when markets are closed is relatively unimportant. This new approach allows fresh insights into stock return volatility and indicates that subsequent research on stock return volatility should incorporate the effects of payment delays.     

The informational content of implied volatility

Implied volatility is widely believed to be informationallysuperior to historical volatility, because it is the 'market's'forecast of future volatility. But for S&P 1 00 index options,the most actively traded contract in the United States, we findimplied volatility to be a poor forecast of subsequent realizedvolatility. In aggregate and across subsamples separated bymaturity and strike price, implied volatility has virtuallyno correlation with future volatility, and it does not incorporatethe information contained in recent observed volatility.     

The January effect across volatility regimes

Using a Markov regime switching model, this article presents evidence of the well-known January effect on stock returns. The specification allows a distinction to be drawn between two regimes: one with high volatility and another with low volatility. We obtain a time-varying January effect that is, in general, positive and significant in both volatility regimes. However, this effect is larger in the high-volatility regime. In sharp contrast with most of the previous literature, we find two major results: (1) the January effect exists for all sizes of portfolio; (2) the negative correlation between the magnitude of the January effect and portfolio size fails across volatility regimes. Moreover, our evidence supports a slight decline in the January effect for all sizes of portfolio except the smallest, for which it is even larger.     

The effect of mergers on implied volatility of equity options

This paper uses a sample of 25 large mergers from 1996 to 2004 to study the effect of mergers on the implied volatilities of equity options. The results indicate a statistically significant increase in volatility beyond the amount predicted if the transaction were effectively nothing more than a portfolio combination of the target and acquirer. The disparity suggests that, at least for the first 18 months after the transaction becomes effective, market participants expect mergers to increase risk. Integration risk and uncertainty about the extent to which efficiency gains and greater market power are realized are possible explanations for the discrepancy.     

Dynamic correlations and volatility effects in the Balkan equity markets

This paper investigates the presence of time-varying comovements, volatility implications and dynamic correlations in major Balkan and leading mature equity markets, in order to provide quantified responses to international asset allocation decisions. Since asset returns and correlation dynamics are critical inputs in asset pricing, portfolio management and risk hedging, emphasis is placed on the respective (constant and dynamic) equity market correlations produced by alternative multivariate GARCH forms, the Constant Conditional Correlation and the Asymmetric Dynamic Conditional Correlation models. The Balkan stock markets are seen to exhibit time-varying correlations as a peer group, although correlations with the mature markets remain relatively modest. In conjunction with sensitivity analysis on the asymmetric variance–covariance matrix, active portfolio diversification to the Balkan equity markets indicates to potentially improve investors’ risk-return trade-off.     

Price limits in futures markets: effects on the price discovery process and volatility

Price limits are actively employed by many futures exchanges as a regulatory mechanism directed at reducing volatility and improving price discovery process. The aim of this paper is to investigate whether price limits achieve these goals without affecting market liquidity for a number of agricultural futures contracts. We employ models of changing volatility in order to show that price limits do not appear to significantly reduce market volatility. In addition, we find evidence confirming the hypothesis that price limits delay price discovery instead of facilitating it. Our results also suggest that the impact of price limits on volatility and price reversals, found in previous studies, are mainly due to the properties inherent to the futures returns, such as volatility clustering. Finally, although trading decreases significantly due to the price limits, traders do not seem to switch from the contracts affected by price limits to other maturities in order to minimize the impact of circuit breakers.     

The anticipated and concurring effects of the EMU: exchange rate volatility, institutions and growth

Reduced exchange rate volatility and higher and less heterogeneous quality of institutional rules and macroeconomic policies are two of the main (anticipated and concurring) effects expected from a currency union.In this paper, we measure the magnitude of these two effects for the Eurozone countries looking at real effective exchange rates (REER) and at different indicators of quality of institutional rules and macroeconomic policies (QIRMP). We find that the first effect is much stronger than the second when we compare relative changes for Eurozone countries and the rest of the world in the relevant period.We further evaluate the impact of both effects on economic growth on a larger sample of countries. Our findings show that both have significant impact on levels (more robust) and on rates of growth (weaker) of per capita GDP.     

Macroeconomic determinants of stock volatility and volatility premiums

How does stock market volatility relate to the business cycle? We develop, and estimate, a no-arbitrage model, and find that (i) the level and fluctuations of stock volatility are largely explained by business cycle factors and (ii) some unobserved factor contributes to nearly 20% to the overall variation in volatility, although not to its ups and downs. Instead, this “volatility of volatility” relates to the business cycle. Finally, volatility risk-premiums are strongly countercyclical, even more than stock volatility, and partially explain the large swings of the VIX index during the 2007–2009 subprime crisis, which our model captures in out-of-sample experiments.     

Local volatility of volatility for the VIX market

Following a trend of sustained and accelerated growth, the VIX futures and options market has become a closely followed, active and liquid market. The standard stochastic volatility models—which focus on the modeling of instantaneous variance—are unable to fit the entire term structure of VIX futures as well as the entire VIX options surface. In contrast, we propose to model directly the VIX index, in a mean-reverting local volatility-of-volatility model, which will provide a global fit to the VIX market. We then show how to construct the local volatility-of-volatility surface by adapting the ideas in Carr (Local variance gamma. Bloomberg Quant Research, New York, 2008) and Andreasen and Huge (Risk Mag 76–79, 2011) to a mean-reverting process.     

The short-run volatility of money stock targeting

The altered allocations of money market volatility obtained by alternative monetary policy procedures are illustrated by stochastic simulations of a staff monthly model. The results indicate the nature of the tradeoff between short-run volatility in the money stock and in the funds rate that is available to money stock targeting procedures.     

The empirical similarity approach for volatility prediction

In this paper we adapt the empirical similarity (ES) concept for the purpose of combining volatility forecasts originating from different models. Our ES approach is suitable for situations where a decision maker refrains from evaluating success probabilities of forecasting models but prefers to think by analogy. It allows to determine weights of the forecasting combination by quantifying distances between model predictions and corresponding realizations of the process of interest as they are perceived by decision makers. The proposed ES approach is applied for combining models in order to forecast daily volatility of the major stock market indices.