CLOSED FORM PRICING FORMULAS FOR DISCRETELY SAMPLED GENERALIZED VARIANCE SWAPS

Most of the existing pricing models of variance derivative products assume continuous sampling of the realized variance processes, though actual contractual specifications compute the realized variance based on sampling at discrete times. We present a general analytic approach for pricing discretely sampled generalized variance swaps under the stochastic volatility models with simultaneous jumps in the asset price and variance processes. The resulting pricing formula of the gamma swap is in closed form while those of the corridor variance swaps and conditional variance swaps take the form of one‐dimensional Fourier integrals. We also verify through analytic calculations the convergence of the asymptotic limit of the pricing formulas of the discretely sampled generalized variance swaps under vanishing sampling interval to the analytic pricing formulas of the continuously sampled counterparts. The proposed methodology can be applied to any affine model and other higher moments swaps as well. We examine the exposure to convexity (volatility of variance) and skew (correlation between the equity returns and variance process) of these discretely sampled generalized variance swaps. We explore the impact on the fair strike prices of these exotic variance swaps with respect to different sets of parameter values, like varying sampling frequencies, jump intensity, and width of the monitoring corridor.     

The asymmetric relationship between returns and implied volatility: Evidence from global stock markets

We investigate the asymmetric relationship between returns and implied volatility for 20 developed and emerging international markets. In particular we examine how the sign and size of return innovations affect the expectations of daily changes in volatility. Our empirical findings indicate that the conditional contemporaneous return-volatility relationship varies not only based on the sign of the expected returns but also upon their magnitude, according to recent results from the behavioral finance literature. We find evidence of an asymmetric and reverse return-volatility relationship in many advanced, Asian, Latin-American, European and South African markets. We show that the US market displays the highest reaction to price falls, Asian markets present the lowest sensitivity to volatility expectations, while the Euro area is characterized by a homogeneous response both in terms of direction and impact. These results may be safely attributed to cultural and societal characteristics. An extensive quantile regression analysis demonstrates that the detected asymmetric pattern varies particularly across the extreme distribution tails i.e., in the highest/lowest quantile ranges. Indeed, the classical feedback and leverage hypotheses appear not plausible, whilst behavioral theories emerge as the new paradigm in real-world applications.     

Measuring financial risk and portfolio reversion with time changed tempered stable Lévy processes

Given that underlying assets in financial markets exhibit stylized facts such as leptokurtosis, asymmetry, clustering properties and heteroskedasticity effect, this paper applies the stochastic volatility models driven by tempered stable Lévy processes to construct time changed tempered stable Lévy processes (TSSV) for financial risk measurement and portfolio reversion. The TSSV model framework permits infinite activity jump behaviors of returns dynamics and time varying volatility consistently observed in financial markets by introducing time changing volatility into tempered stable processes which specially refer to normal tempered stable (NTS) distribution as well as classical tempered stable (CTS) distribution, capturing leptokurtosis, fat tailedness and asymmetry features of returns in addition to volatility clustering effect in stochastic volatility. Through employing the analytical characteristic function and fast Fourier transform (FFT) technique, the closed form formulas for probability density function (PDF) of returns, value at risk (VaR) and conditional value at risk (CVaR) can be derived. Finally, in order to forecast extreme events and volatile market, we perform empirical researches on Hangseng index to measure risks and construct portfolio based on risk adjusted reward risk stock selection criteria employing TSSV models, with the stochastic volatility normal tempered stable (NTSSV) model producing superior performances relative to others.     

Modelling the implied volatility surface based on Shanghai 50ETF options

We develop a dynamic factor model to forecast the implied volatility surface (IVS) of Shanghai Stock Exchange 50ETF options. Based on the assumption that dynamic change in IVS is mean-reverting and Markovian, we use a state space model to capture the dynamics of IVS, and set the latent factors to be the Ornstein–Uhlenbeck processes. We obtain the optimal estimations of parameters using the Kalman filter algorithm. Empirical results show that our model performs better than the traditional IVS model in terms of fitting ability and prediction performance.     

The Tunisia Wheat Market in the Context of World Price Volatility: A Stochastic Partial Equilibrium Approach

Food security is a key objective of agricultural and food policy in Tunisia. The 2007–2008 food crisis highlighted the negative impacts of price volatility on international markets both in terms of food insecurity and budget exposure. Tunisian food subsidy expenditures ranged from $180 million to $710 million in 2006–2010, so volatile world prices meant volatile subsidy costs. Moreover, cereal production in Tunisia still has much instability due to climate conditions, which also influences imports and, consequently, subsidy expenditures. This study applies a structural model to conduct stochastic analyses of trade and policy impacts on food security and budget expenditures in the Tunisian wheat market. The methodology disaggregates durum wheat and soft wheat markets and generates projections of import prices of durum wheat and soft wheat, using projections of world prices provided by the Food and Agricultural Policy Research Institute at University of Missouri (FAPRI-MU). The key innovation is the generated stochastic analyses of subsidy costs based on stochastic world price projections and stochastic domestic wheat yields based on historic yield variances. The analysis highlights the sensitivity of subsidy costs to world prices, volumes imported and domestic production, so that alternative policy tools can be considered.     

Evaluating monetary policy under preferences with zero wealth effect: A Bayesian approach

Both real and monetary macro models have parallely exploited the potential for various preferences in accounting for empirical facts. This paper brings the two literatures together by estimating time non-separable preferences with habit formation in consumption that nests several commonly used preferences. In the absence of wealth effects and external habits, these preferences fail to generate observed inflation inertia and output persistence after a monetary policy shock. Furthermore, the data strongly rejects these preferences in favor of preferences with external habits. An alternative solution is to include habit adjusted intermediate wealth effect preferences which are able to simultaneously generate sluggish responses of the variables to a monetary policy shock and fit the data better.     

融资融券对我国股市波动性的影响

本文采集股价指数月收益率和融资融券交易额每月日平均变化率的数据,针对融资融券对我国股市波动性的影响,进行实证检验,并对结果做进一步的解释。     

Redistribution effects of inflation

This note discusses Lee Ohanian׳s paper on “Monetary policy in the midst of big shocks”. In particular, it asks what would happen if assumptions are changed so inflation have redistribution effects. Evidence on nominal positions suggests that such effects can be quantitatively important.     

Forecast combinations under structural break uncertainty

This paper proposes two new weighting schemes that average forecasts based on different estimation windows in order to account for possible structural change. The first scheme weights the forecasts according to the values of reversed ordered CUSUM (ROC) test statistics, while the second weighting method simply assigns heavier weights to forecasts that use more recent information. Simulation results show that, when structural breaks are present, forecasts based on the first weighting scheme outperform those based on a procedure that simply uses ROC tests to choose and forecast from a single post-break estimation window. Combination forecasts based on our second weighting scheme outperform equally weighted combination forecasts. An empirical application based on a NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows that combination forecasts can outperform the random walk forecasting model.     

The design and communication of systematic monetary policy strategies

The efficacy of central bank communications is inextricably linked to the characteristics of the monetary policy framework. Therefore, this paper presents a set of fundamental principles regarding the joint design of monetary policy strategy and communications. The practical implications of these principles are illustrated by considering a number of significant policy challenges faced by central banks in the advanced economies.