Volatility activity: Specification and estimation

The paper examines volatility activity and its asymmetry and undertakes further specification analysis of volatility models based on it. We develop new nonparametric statistics using high-frequency option-based VIX data to test for asymmetry in volatility jumps. We also develop methods for estimating and evaluating, using price data alone, a general encompassing model for volatility dynamics where volatility activity is unrestricted. The nonparametric application to VIX data, along with model estimation for S&P index returns, suggests that volatility moves are best captured by an infinite variation pure-jump martingale with a symmetric jump compensator around zero. The latter provides a parsimonious generalization of the jump-diffusions commonly used for volatility modeling.     

Volatility estimation from observed option prices

It is well established that the standard Black-Scholes model does a very poor job in matching the prices of vanilla European options. The implied volatility varies by both time to maturity and by the moneyness of the option. One approach to this problem is to use the market option prices to back out a local volatility function that reproduces the market prices. Since option price observations are only available for a limited set of maturities and strike prices, most algorithms require a smoothing technique to implement this approach. In this paper we modify the implementation of Andersen and Brotherton-Ratcliffe to provide another way of dealing with this issue. Numerical examples indicate that our approach is reasonably successful in reproducing the input prices.     

Volatility estimation for stock index options: A GARCH approach

The objective of this paper is to compare the mispricing of option valuation models when alternate techniques are applied to the volatility estimation. Akgiray (1989) shows that out-of-sample forecasts of return variances of stock indices based on a GARCH model are superior predictors of the actual ex-post variances in comparison to forecasts generated using standard rolling regression methods. A second objective of this study is to examine if Akgiray's results carry over to option valuation. Although we find that the implied volatility technique results in the least mispricing, within the class of forecasts using only historic returns data, the use of GARCH models will also significantly reduce model mispricing.     

Electricity derivatives pricing with forward-looking information

In order to increase overall transparency on key operational information, power transmission system operators publish an increasing amount of fundamental data, including forecasts of electricity demand and available capacity. We employ a fundamental model for electricity prices which lends itself well to integrating such forecasts, while retaining ease of implementation and tractability to allow for analytic derivatives pricing formulae. In an extensive futures pricing study, the pricing performance of our model is shown to further improve based on the inclusion of electricity demand and capacity forecasts, thus confirming the general importance of forward-looking information for electricity derivatives pricing. However, we also find that the usefulness of integrating forecast data into the pricing approach is primarily limited to those periods during which electricity prices are highly sensitive to demand or available capacity, whereas the impact is less visible when fuel prices are the primary underlying driver to prices instead.     

The pricing of credit risk derivatives

This paper considers the pricing of derivatives that protect holders of corporate bonds from a reduction in their value because of a deterioration in their credit quality. These derivatives are structured as either puts on the bond price or calls on the bond spread (above the risk free rate) in the context of models developed by Merton (1974) and Black and Cox (1976). The pricing properties of these options are derived using both analytical and numerical methods.     

Measure preserving derivatives and the pricing kernel puzzle

Recent empirical studies have found evidence of nonmonotonicity in the pricing kernels for a variety of market indices. This phenomenon is known as the pricing kernel puzzle. The payoff distribution pricing model of Dybvig predicts that the payoff distribution of a direct investment of $1 in a market index may be replicated by investing less than $1 in some derivative written on that market index whenever the associated pricing kernel is nondecreasing. Using the Hardy–Littlewood rearrangement inequality, we obtain an explicit solution for the cheapest replicating derivative, which we refer to as the optimal measure preserving derivative. The optimal measure preserving derivative is the permutation appearing in Ryff’s decomposition of the pricing kernel with respect to the market payoff measure. We compute optimal measure preserving derivatives corresponding to the estimated physical and risk neutral distributions in the paper by Jackwerth (2000) that first brought attention to the pricing kernel puzzle.     

Pure jump models for pricing and hedging VIX derivatives

Recent non-parametric statistical analysis of high-frequency VIX data (Todorov and Tauchen, 2011) reveals that VIX dynamics is a pure jump semimartingale with infinite jump activity and infinite variation. To our best knowledge, existing models in the literature for pricing and hedging VIX derivatives do not have these features. This paper fills this gap by developing a novel class of parsimonious pure jump models with such features for VIX based on the additive time change technique proposed in Li et al., 2016a, Li et al., 2016b. We time change the 3/2 diffusion by a class of additive subordinators with infinite activity, yielding pure jump Markov semimartingales with infinite activity and infinite variation. These processes have time and state dependent jumps that are mean reverting and are able to capture stylized features of VIX. Our models take the initial term structure of VIX futures as input and are analytically tractable for pricing VIX futures and European options via eigenfunction expansions. Through calibration exercises, we show that our model is able to achieve excellent fit for the VIX implied volatility surface which typically exhibits very steep skews. Comparison to two other models in terms of calibration reveals that our model performs better both in-sample and out-of-sample. We explain the ability of our model to fit the volatility surface by evaluating the matching of moments implied from market VIX option prices. To hedge VIX options, we develop a dynamic strategy which minimizes instantaneous jump risk at each rebalancing time while controlling transaction cost. Its effectiveness is demonstrated through a simulation study on hedging Bermudan style VIX options.     

Volatility, Efficiency, and Trading: Further Evidence

Along the lines of Amihud and Mendelson (1987a, 1989,1991), this study investigates the unique trading mechanism of the Korea Stock Exchange (KSE) and its intraday behavior of stock price volatility. The evidence from this study indicates that the introduction of an additional clearing procedure at the afternoon closing makes price discovery process more efficient than before from the viewpoint of stock price volatility. Hence, such trading mechanisms can be applied to emerging stock markets as well as developed stock markets. In addition, based on intraday analysis, stock price volatilities appear to occur mainly during the trading period, not during the lunch break or overnight period. Consequently, the results confirm the previous studies that information arrival and trading activities are the main sources of volatility.     

Differences and derivatives in kernel estimation

Estimators of derivatives of a density function based on differences of the empirical distribution function (Maltz 1974) are identified as derivatives of kernel density estimators using particular kernel functions. Properties of this family of kernels are investigated.     

Joint dynamic modeling and option pricing in incomplete derivative-security market

In this study, we evaluate the option prices on two assets under stochastic interest rates when the stochastic process that underlying asset prices follow is depending on a correlated bivariate Markov-modulated geometric Brownian motion model with jump risks. More specifically, we conduct the joint dynamic modeling by identifying two independent compound Poisson processes with the log-normal jump sizes to describe both individual jumps and systematic cojumps. Facilitating the cojumping behavior this way with the time-inhomogeneity of the volatility, option pricing expressions are readily obtainable since the Gerber–Siu’s approach is employed to determine a pricing kernel. The empirical results and numerical illustrations are provided to show the impact of cojumps and stochastic volatilities on option prices.     

Volatility, growth, and welfare

This paper constructs an endogenous growth model driven by self-fulfilling expectation shocks to explain the stylized fact that the average growth rate of GDP is related negatively to volatility and positively to capacity utilization. The implied welfare gain from further stabilizing the U.S. economy is about a quarter of annual consumption, which is consistent in order of magnitude with estimates based on the empirical studies of Ramey and Ramey (1995) and Alvarez and Jermann (2004). Hence, policies designed to reduce fluctuations can generate large welfare gains because smaller fluctuations are associated with permanently higher rates of growth.     

波动率预测:GARCH模型与隐含波动率

在预测未来波动率时,究竟是基于历史数据的时间序列模型还是基于期权价格的隐含波动率模型效率更高?本文对香港恒生指数期权市场所含信息的研究发现,在预测期限较短(一周)时,GARCH(1,1)模型所含信息较多,预测能力最强,但在预测较长期限(一个月)时,隐含波动率所含信息较多,预测能力较强。同时,期权市场交易越活跃,所反映的信息就越全面,隐含波动率的预测能力也就越强。     

Fat tails and spurious estimation of consumption‐based asset pricing models

The standard generalized method of moments (GMM) estimation of Euler equations in heterogeneous‐agent consumption‐based asset pricing models is inconsistent under fat tails because the GMM criterion is asymptotically random. To illustrate this, we generate asset returns and consumption data from an incomplete‐market dynamic general equilibrium model that is analytically solvable and exhibits power laws in consumption. Monte Carlo experiments suggest that the standard GMM estimation is inconsistent and susceptible to Type II errors (incorrect nonrejection of false models). Estimating an overidentified model by dividing agents into age cohorts appears to mitigate Type I and II errors.     

Media Content,Accounting Quality,and Liquidity Volatility

We examine how the linguistic content of news items affects the volatility of a firm's liquidity, and we consider whether accounting quality moderates the media content-liquidity volatility relation. Regarding the unconditional relation between media content and liquidity volatility, one view is media content could reduce liquidity volatility by providing additional information about fundamental values; another view is it could increase liquidity volatility by increasing investor uncertainty, particularly for negative news. Using data from Thomson Reuters News Analytics, we find evidence supporting the view that media content, positive and negative, has incremental information. Regarding the moderating role of accounting quality, pre-existing accounting information of higher quality could enhance investors' reactions to media content by providing a more precise baseline, or it could reduce investors' reactions to the news if investors anchor on higher quality financial statements. Our findings are consistent with more credible accounting information serving an anchor role, and suggest that investors condition their reaction to media content based on the quality of a firm's pre-existing accounting information.     

企业数字化、业绩波动性与投资效率

本文基于2014～2019年沪深两市上市公司数据,探究企业数字化如何影响投资效率.研究发现,企业数字化提升了投资效率,尤其抑制了过度投资.机制检验发现,业绩波动性在数字化与企业投资效率间起部分中介作用.进一步通过异质性检验发现,相比于国有企业、新兴产业以及经济政策不确定性较小的样本,在非国有企业、非新兴产业以及经济政策...     

Volatility and welfare

This paper explores the relationship between volatility and welfare. Even though households prefer smooth streams of consumption and leisure, welfare can be increasing in the volatility of an exogenous driving force if factor supply is sufficiently elastic. We provide some analytical results for a model without capital, and do some quantitative exercises in a model with capital and a variety of shocks. Welfare is greater in high shock volatility regimes under plausible parameter values. Augmenting the model with features that increase the elasticity of factor supply extends the range of parameters over which higher volatility results in greater welfare.     

A comparative analysis of security pricing using factor, macrovariable and arbitrage pricing models

This study compares and contrasts the single factor, three factor, macrovariable and APT models, using industry portfolios of all available firms on CRSP from 1980 to 1992. Comparatively, the APT is best, macrovariable second best and single factor model worse in pricing securities. Consistently, the market variable is cross sectionally priced in all models, and two of four APT factors capture the majority of variance in industry returns. In the latter case, factor three is ***DIRECT SUPPORT *** A00DH002 00002 consistently related to market returns, and factors two and three are also associated with risk premiums and exchange rates after 1987. Factor four is not related to any macrovariable, and term structure and production are never related to any risk factor.     

Technical change,inflation and pricing decisions

The paper discusses long-term managerial cost pricing, thus taking into account both operating and capital costs of new plant. This approach is relevant to the public industries, oligopoly and can also be the basis for competitive pricing. The model integrates pricing and investment decisions, and incorporates, among other factors, expected future technical change and inflation. The treatment is illustrated in relation to a range of industries with very different rates of technical advance. It also discusses the reasons for the frequent failure for full potential gains from such advances to be realized and hence for sluggish economic growth.     

Bounded rationality,anchoring-and-adjustment sentiment,and asset pricing

This paper presents a framework that incorporates an investor’s limited attention and anchoring and adjustment sentiment and their joint effects on asset pricing, with endogenous cost of neglecting part of the dividends and the asymmetric rationality levels of investors. We find that the combined effect of the two bounded rationality factors is often embodied in the “loss”, and the retail investors are insensitive to market sentiment and forced to pay more cognitive loss. A higher level of investor rationality and bullish market sentiment will jointly increase demand and then prices, while the effects of different bounded rationality factors are asymmetric.     

Threshold estimation of Markov models with jumps and interest rate modeling

We reconstruct the level-dependent diffusion coefficient of a univariate semimartingale with jumps which is observed discretely. The consistency and asymptotic normality of our estimator are provided in the presence of both finite and infinite activity (finite variation) jumps. Our results rely on kernel estimation, using the properties of the local time of the data generating process, and the fact that it is possible to disentangle the discontinuous part of the state variable through those squared increments between observations not exceeding a suitable threshold function. We also reconstruct the drift and the jump intensity coefficients when they are level-dependent and jumps have finite activity, through consistent and asymptotically normal estimators. Simulated experiments show that the newly proposed estimators perform better in finite samples than alternative estimators, and this allows us to reexamine the estimation of a univariate model for the short term interest rate, for which we find fewer jumps and more variance due to the diffusion part than previous studies.