Do Aussie markets smile? Implied volatility functions and determinants

If options are correctly priced, the interpretation of volatility in the Black–Scholes model (as identifying the volatility of the underlying asset) is violated. The empirical relation between the model ‘implied volatility’ and the degree to which the option is in-the-money (moneyness) has been reported as resembling a U-shape (or ‘smile’) for options on currencies (and more of a ‘smirk’ for options on equities). In this article, using multivariate time-series analysis and employing an impulse response function, we investigate the structural relationships and dynamics of the volatility smile in relation to the option liquidity, key features of the underlying asset and market momentum. Our findings confirm evidence of a number of biases in the Black–Scholes model consistent with Chou et al. (2011) in regard to liquidity in both the underlying and the option itself, and with Peña et al. (1999) as to the importance of the option time to maturity. As well as delineating such biases as they co-relate both with each other and with the underlying asset volatility and momentum, we find that the pronounced smile is related to the differential sensitivities of in-the-money and out-of-the-money options, which itself suggests an explanation for the characteristic smile shape.     

Cross-country performance of Lévy regime-switching models for stock markets

This article compares the performance of regime-switching Lévy models across sixteen (16) international stock markets. From a cross-country perspective, the empirical application is dedicated to the study of equity markets in the Americas, Asia and Europe. The results are of interest for a financial audience in order to document the sensitivity of stock indexes to the intensity of jumps, under changing economic regimes (expansion or recession). We pick up singularities in Japan and Malaysia compared to other countries and regions of the world.     

Optimal trading strategies for Lévy-driven Ornstein–Uhlenbeck processes

This study derives an optimal pairs trading strategy based on a Lévy-driven Ornstein–Uhlenbeck process and applies it to high-frequency data of the S&P 500 constituents from 1998 to 2015. Our model provides optimal entry and exit signals by maximizing the expected return expressed in terms of the first-passage time of the spread process. An explicit representation of the strategy’s objective function allows for direct optimization without Monte Carlo methods. Categorizing the data sample into 10 economic sectors, we depict both the performance of each sector and the efficiency of the strategy in general. Results from empirical back-testing show strong support for the profitability of the model with returns after transaction costs ranging from 31.90% p.a. for the sector ‘Consumer Staples’ to 278.61% p.a. for the sector ‘Financials’. We find that the remarkable returns across all economic sectors are strongly driven by model parameters and sector size. Jump intensity decreases over time with strong outliers in times of high market turmoil. The value-add of our Lévy-based model is demonstrated by benchmarking it with quantitative strategies based on Brownian motion-driven processes.     

Calibration of implied volatility for the exchange rate for the Chinese Yuan from its derivatives

Revised implied volatility curves and surfaces for the Chinese Yuan (CNY) exchange rate are obtained from market quotations for CNY non-deliverable options by solving an inverse problem of foreign exchange option pricing, which is calculated using a regularization approach in an optimal control framework. To take account of the market expectation for the CNY exchange rate, a stochastic adjusted factor is applied that follows a Vasicek model with parameters fitted from market quotations for CNY non-deliverable forwards. A well-posed numerical scheme is implemented.     

Investors’ fear and herding in the stock market

ABSTRACT

In this article, we examine herding in three developed stock markets testing for the impact of investors’ ‘fear’ on herding estimations. To this end, we employ daily data of all listed stocks from USA, UK and Germany from January 2004 to July 2014. We examine herd behaviour applying the cross-sectional dispersion approach. Moreover, we investigate the asymmetric herding behaviour under different market states and sub-periods. The stock markets under examination provide comparable implied volatility indices which are used as a proxy for fear. As a result, apart from the standard herding estimations within and across markets, we also augment the benchmark model with the fear indicator. Our empirical results document the statistically significant impact of fear on herding estimations. Moreover, there is evidence of cross market herding as well as evidence of herding in the UK during specific sub-periods.     

Value,sign, and social structure: the ‘game’ metaphor and modern social science

This exploratory paper, part of continued work on the history of game theory, seeks to illustrate certain links between von Neumann's theory of games and contemporaneous ideas in other fields. In particular, we claim that the emergence of the analytical metaphor of the ‘game’ in economics can be viewed as part of a general reconceptualization of theory in a range of disciplines. That methodological reconstitution may be described as the emergence of a Structuralist view, an approach to theorizing which treated its object – be that a text, a kinship arrangement, or an economy – as a self-contained system, with its own internal logic, subject to its own ‘laws’. In particular, individual texts, or observed social and economic arrangements, are now viewed as variations on an underlying logical theme, on a structural invariant. The latter is to be uncovered, in the case of linguistics, through the analysis of phonemes; in kinship analysis, through the rules governing the exchange of women because of the incest taboo; in von Neumann and Morgensterns game theory, through the possibilities for equilibrium coalition formation, based on the stable set. There thus emerged a tendency, across the intellectual spectrum, towards seeing things in combinatorialterms. Theoretical coherence was to be found in examining how objects ‘held together’ rather than analysing where they ‘came from’: nineteenth-century concerns with history, evolution and individual psychology give way to a distinctly modern emphasis on synchronic, formal structure, on analogical reasoning. Atomism gave way to holism, and formal elegance superceded immediate empirical content. Recourse to the metaphor of the ‘game’ was constitutive of this shift, which we examine by referring to Saussures General Course in Linguistics, to Formalism in mathematics and literary analysis, to Lévi-Strauss's analysis of kinship and myth, and to von Neumann and Morgenstern's Theory of Games and Economic Behaviour.     

Equity market information and credit risk signaling: A quantile cointegrating regression approach

Investigating linkages between credit and equity markets, we consider daily aggregate U.S. CDS spreads as well as well-chosen equity market and implied volatility indexes over ten years. We describe such robust (to spurious correlation) relationship with the quantile cointegrating regression approach. Such approach handles extreme quantiles/CDS values and their behavior with respect to the equity market's influence. Heteroskedastic patterns such as time-varying variance, but also autocorrelation, skewness and leptokurtosis are captured. Thus, the sensitivity of aggregate CDS spreads to equity market price and volatility channels is accurately measured across quantiles and spreads. Such quantile-dependent sensitivity exhibits asymmetric responses to equity market shocks. A sub-period analysis investigates potential regime shifts in estimated quantile cointegrating regressions. Quantile cointegrating coefficients vary over time and quantiles, and exhibit different magnitudes across sub-periods and spreads. Therefore, the relationship is unstable over time. We also propose a scenario analysis and risk signaling application for credit risk management prospects. Under specific risk levels, credit risky situations are described conditional on the equity market's information over time, and related expected aggregate CDS spreads are computed. Estimated conditional quantiles/CDS spreads act as credit alert triggers.