A Gaussian approximation scheme for computation of option prices in stochastic volatility models

We consider European options on a price process that follows the log-linear stochastic volatility model. Two stochastic integrals in the option pricing formula are costly to compute. We derive a central limit theorem to approximate them. At parameter settings appropriate to foreign exchange data our formulas improve computation speed by a factor of 1000 over brute force Monte Carlo making MCMC statistical methods practicable. We provide estimates of model parameters from daily data on the Swiss Franc to Euro and Japanese Yen to Euro over the period 1999–2002.     

Press freedom and jumps in stock prices

Press freedom varies substantially across countries. In a free environment, any news immediately becomes public knowledge through mediums including various electronic media and published materials. However, in an unfree environment, (economic) agents would have more discretionary powers to disclose good news immediately, while hiding bad news or releasing bad news slowly. We argue that this discretion affects stock prices and that stock markets in countries with a free press should be better processors of economic information. Using an equilibrium asset-pricing model in an economy under jump diffusion, we decompose the moments of the returns of international stock markets into a diffusive risk and a jump risk part. Using stock market data for a balanced panel of 50 countries, our results suggest that in countries with a free press, the better processing of bad news leads to more frequent negative jumps in stock prices. As a result, stock markets in those countries are characterized by higher volatility, driven by higher jump risk and more negative return asymmetry. The results are robust to the inclusion of various controls for governance and other country- or market-specific characteristics. We interpret these as good stock market characteristics because a free press improves welfare and increases economic growth.     

Estimation of stable distributions by indirect inference

This article deals with the estimation of the parameters of an α-stable distribution with indirect inference, using the skewed-t distribution as an auxiliary model. The latter distribution appears as a good candidate since it has the same number of parameters as the α-stable distribution, with each parameter playing a similar role. To improve the properties of the estimator in finite sample, we use constrained indirect inference. In a Monte Carlo study we show that this method delivers estimators with good properties in finite sample. We provide an empirical application to the distribution of jumps in the S&P 500 index returns.     

Estimation for multivariate stable distributions with generalized empirical likelihood

This paper considers the generalized empirical likelihood (GEL) method for estimating the parameters of the multivariate stable distribution. The GEL method is considered to be an extension of the generalized method of moments (GMM). The multivariate stable distributions are widely applicable as they can accommodate both skewness and heavy tails. We treat the spectral measure, which summarizes scale and asymmetry, by discretization. In order to estimate all the model parameters simultaneously, we apply the estimating function constructed by equating empirical and theoretical characteristic functions. The efficacy of the proposed GEL method is demonstrated in Monte Carlo studies. An illustrative example involving daily returns of market indexes is also included.     

Contestability of the urban land market: an event study of Hong Kong land auctions

The traditional theory of urban land markets assumes perfect contestability—the absolute freedom of market entry—that compels developers to bid up the land rent to equal the economic profit from land use. This assumption, however, is empirically untested due to the difficulties in measuring the ex ante economic profit of land acquisition. We overcome these difficulties by applying the event-study methodology to Hong Kong government land auctions. When a developer acquires a site at a price below its fair market value, the rationality of the stock market entails a positive abnormal return on the developer’s stock. Our analysis shows evidence of positive expected abnormal returns, indicating an imperfectly contestable land market. We further show that the expected abnormal return increases with the site value and the government land disposal level but decreases with the property market liquidity.     

Does ethics improve stock market resilience in times of instability?

This paper compares the resilience of ethical (Islamic and socially responsible) indexes among five developed (US, UK, Japan, Canada, Australia) and three emerging markets (Brazil, India, South Africa) during the period following the 2008 subprime crisis. It relies on a multivariate CAPM-EGARCH model that accounts for sudden changes in volatility through the application of an iterated cumulative sums of squares (ICSS) algorithm on daily data over the sample period 2008–2014 to model time-varying volatility and ensure reliable estimates. The study confirms the lower systemic risk associated with Islamic indexes during the bearish period and reports that SRI, despite being more subject to systemic risk, offered higher alphas in highly integrated markets, while Islamic indexes performed better in less integrated ones. The evidence also reveals a very limited increase in the models’ predictability power from the integration of sudden changes in volatility into the EGARCH models during the full sample period. This limit is more marked during the bearish sub-period. Our findings have important implications for international investment and portfolio diversification perspectives in times of financial downturn.     

Geopolitical risks and stock market dynamics of the BRICS

This paper examines the effect of geopolitical uncertainty on return and volatility dynamics in the BRICS stock markets via nonparametric causality-in-quantiles tests. The effect of geopolitical risks (GPRs) is found to be heterogeneous across the BRICS stock markets, suggesting that news regarding geopolitical tensions do not affect return dynamics in these markets in a uniform way. GPRs are generally found to impact stock market volatility measures rather than returns, and often at return quantiles below the median, indicating the role of GPRs as a driver of bad volatility in these markets. While Russia bears the greatest risk exposure to GPRs in terms of both return and volatility, India is found to be the most resilient BRICS nation in the group. Noting that geopolitical shocks and in particular terrorist incidents are largely unanticipated, our findings underscore the importance of a strong financial sector that can help return the market to stability and an open economy that allows local investors to diversify country-specific risks in their portfolios.     

Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan

This paper provides closed-form likelihood approximations for multivariate jump-diffusion processes widely used in finance. For a fixed order of approximation, the maximum-likelihood estimator (MLE) computed from this approximate likelihood achieves the asymptotic efficiency of the true yet uncomputable MLE as the sampling interval shrinks. This method is used to uncover the realignment probability of the Chinese Yuan. Since February 2002, the market-implied realignment intensity has increased fivefold. The term structure of the forward realignment rate, which completely characterizes future realignment probabilities, is hump-shaped and peaks at mid-2004. The realignment probability responds quickly to economic news releases and government interventions.     

Intraday effect of news on emerging European forex markets: An event study analysis

We analyze the impact of euro zone/German and U.S. macroeconomic news announcements and the communication of the monetary policy settings of the ECB and the Fed on the forex markets of new EU members. We employ an event study methodology to analyze intraday data from 2011–2015. Our comprehensive analysis of the wide variety of macroeconomic information during the post-GFC period shows that: (i) macroeconomic announcements affect the value of the new EU country exchange rates, (ii) the origin of the announcement matters, (iii) the type of announcement matters, (iv) different types of news (good, bad or neutral) result in different reactions, (v) markets react not only after the news release but also before, (vi) when the U.S. dollar is the base currency the impact of the news is larger than in the case of the euro, (vii) announcements on ECB monetary policy result in stronger effects than those of the Fed, (viii) temporary inefficiencies are present in new EU country forex markets, (ix) new EU country exchange rates react differently to positive US news during the EU debt crisis compared to the rest of the period.     

Econometric estimation in long-range dependent volatility models: Theory and practice

It is commonly accepted that some financial data may exhibit long-range dependence, while other financial data exhibit intermediate-range dependence or short-range dependence. These behaviours may be fitted to a continuous-time fractional stochastic model. The estimation procedure proposed in this paper is based on a continuous-time version of the Gauss–Whittle objective function to find the parameter estimates that minimize the discrepancy between the spectral density and the data periodogram. As a special case, the proposed estimation procedure is applied to a class of fractional stochastic volatility models to estimate the drift, standard deviation and memory parameters of the volatility process under consideration. As an application, the volatility of the Dow Jones, S&P 500, CAC 40, DAX 30, FTSE 100 and NIKKEI 225 is estimated.