The role of jumps and leverage in forecasting volatility in international equity markets

We analyze the importance of jumps and the leverage effect on forecasts of realized volatility in a large cross-section of 18 international equity markets, using daily realized measures data from the Oxford-Man Realized Library, and two widely employed empirical models for realized volatility that allow for jumps and leverage. Our out-of-sample forecast evaluation results show that the separation of realized volatility into a continuous and a discontinuous (jump) component is important for the S&P 500, but of rather limited value for the remaining 17 international equity markets that we analyze. Only for 6 equity markets are significant and sizable forecast improvements realized at the one-step-ahead horizon, which, nevertheless, deteriorate quickly and abruptly as the prediction horizon increases. The inclusion of the leverage effect, on the other hand, has a much larger impact on all 18 international equity markets. Forecast gains are not only highly significant, but also sizeable, with gains remaining significant for forecast horizons of up to one month ahead.     

STOCHASTIC LOCAL INTENSITY LOSS MODELS WITH INTERACTING PARTICLE SYSTEMS

It is well known from the work of Schönbucher that the marginal laws of a loss process can be matched by a unit increasing time inhomogeneous Markov process, whose deterministic jump intensity is called local intensity. The stochastic local intensity (SLI) models such as the one proposed by Arnsdorf and Halperin allow to get a stochastic jump intensity while keeping the same marginal laws. These models involve a nonlinear stochastic differential equation (SDE) with jumps. The first contribution of this paper is to prove the existence and uniqueness of such processes. This is made by means of an interacting particle system, whose convergence rate toward the nonlinear SDE is analyzed. Second, this approach provides a powerful way to compute pathwise expectations with the SLI model: we show that the computational cost is roughly the same as a crude Monte Carlo algorithm for standard SDEs.     

Excess volatility and the cross-section of stock returns

We document a reliable positive relation between excess volatility and the cross-section of stock returns over the sample period of 1963 to 2010. Significantly positive differentials have been found between the two decile portfolios with the largest and the least excess volatility, under all the situations we have examined. Size, value, and momentum effects cannot explain our empirical results. Likewise they cannot be explained by liquidity, bid-ask bounce, and risk-aversion-related inventory effects.     

低碳背景下考虑折叠式集装箱的海运空箱调运随机优化研究

考虑碳排放与折叠式集装箱,以海运空箱调运总成本最低为目标函数,建立基于随机机会约束规划的海运空箱调运优化模型,并用Lingo11.0软件建模求解.最后结合算例对模型进行应用分析,并分析碳税、使用折叠式集装箱以及空箱供应量与需求量的随机性对空箱调运总成本的影响.结果表明:碳税增加会使空箱调运总成本增加,但增加幅度不明显;使用折叠式集装箱可以充分发挥其节省舱位空间的优势,不仅能有效解决船舶船型较小的问题,而且能降低船舶运营成本从而降低空箱调运总成本;空箱供应量与需求量的随机性会导致空箱调运总成本大幅增加.     

The rise of market power and Ramsey‐optimal policy implications

De Loecker, Eeckhout, and Unger document that since 1980 aggregate markups in the U.S. economy have significantly increased from 21% above cost to 61% now. In light of this evidence, this paper revisits optimal fiscal and monetary policy recommendations of standard New Keynesian models and shows that under empirically relevant calibrations of market power they radically change: the optimal inflation rate becomes significantly positive and its optimal volatility sharply rises. Moreover, inflation behaves like a random walk in response to unexpected fiscal shocks. Thus, price stability ceases to be the optimal policy outcome.     

FROM SMILE ASYMPTOTICS TO MARKET RISK MEASURES

The left tail of the implied volatility skew, coming from quotes on out‐of‐the‐money put options, can be thought to reflect the market's assessment of the risk of a huge drop in stock prices. We analyze how this market information can be integrated into the theoretical framework of convex monetary measures of risk. In particular, we make use of indifference pricing by dynamic convex risk measures, which are given as solutions of backward stochastic differential equations, to establish a link between these two approaches to risk measurement. We derive a characterization of the implied volatility in terms of the solution of a nonlinear partial differential equation and provide a small time‐to‐maturity expansion and numerical solutions. This procedure allows to choose convex risk measures in a conveniently parameterized class, distorted entropic dynamic risk measures, which we introduce here, such that the asymptotic volatility skew under indifference pricing can be matched with the market skew. We demonstrate this in a calibration exercise to market implied volatility data.     

Tax reforms and stock return volatility: The case of Japan

Although global financial turmoil in recent years has resulted in renewed interest in taxing financial markets, the existing evidence is inconclusive regarding the effect of stock transaction taxes (STT) on stock return volatility. In this respect, Japan provides an excellent opportunity to address the issue, as the country enacted major tax reforms during the long recession beginning in the early 1990s, not only abolishing STT in 1999, but also reducing the capital gains and dividend taxes in 2003. The present paper exploits these tax reform episodes and examines whether and how they affected stock return volatility. In so doing, it employs GARCH-type models using standard daily stock data, as well as HAR models based on realized volatility constructed from high-frequency, intraday data. The estimation results are consistent with the views that, in line with some earlier findings, the STT abolition in 1999 reduced volatility, and that the tax reforms in 2003 also reduced volatility through a cut in the dividend tax, but not in the capital gains tax.     

中国金融业技术效率的区域差异研究

中国金融业技术效率存在较为显著的东、中、西部差异,并成为区域金融业发展水平差异性的影响因素。区域经济发展水平或市场发展水平以及区域教育发展水平的差异性是形成中国区域金融业技术效率差异性的基本原因,区域金融业技术效率水平将经历由特定区域引领到逐步趋于均衡的过程。加快区域金融业技术效率的提高应从区域经济发展或市场发展以及教育水平提高等方面进行。     

Analysing money demand relation for OECD countries using common factors

This article investigates the existence of a long-run money demand relation for a panel data consisting of 13 OECD countries. The analysis is based on the most recent data. The existence of a long-run money demand relation is tested with two new meta-analytic panel cointegrating rank tests which are robust to cross-sectional dependence. Cross-sectional dependency in the data generating process is modelled by unobserved common factors. The observed data are decomposed into idiosyncratic and common components, and these two components are analysed separately to find out the driving forces of the long-run stationary relationship. The evidence shows that the long-run money demand relation is driven by the cross-unit cointegration. Finally, the long-run relation is estimated by taking the common factors into account.