Algebraic structure of vector fields in financial diffusion models and its applications

High-order discretization schemes of SDEs using free Lie algebra-valued random variables are introduced by Kusuoka [Adv. Math. Econ., 2004, 5, 69–83], [Adv. Math. Econ., 2013, 17, 71–120], Lyons–Victoir [Proc. R. Soc. Lond. Ser. A Math. Phys. Sci., 2004, 460, 169–198], Ninomiya–Victoir [Appl. Math. Finance, 2008, 15, 107–121] and Ninomiya–Ninomiya [Finance Stochast., 2009, 13, 415–443]. These schemes are called KLNV methods. They involve solving the flows of vector fields associated with SDEs and it is usually done by numerical methods. The authors have found a special Lie algebraic structure on the vector fields in the major financial diffusion models. Using this structure, we can solve the flows associated with vector fields analytically and efficiently. Numerical examples show that our method reduces the computation time drastically.     

Calibration of a nonlinear feedback option pricing model

We consider the option pricing model proposed by Mancino and Ogawa, where the implementation of dynamic hedging strategies has a feedback impact on the price process of the underlying asset. We present numerical results showing that the smile and skewness patterns of implied volatility can actually be reproduced as a consequence of dynamical hedging. The simulations are performed using a suitable semi-implicit finite difference method. Moreover, we perform a calibration of the nonlinear model to market data and we compare it with more popular models, such as the Black–Scholes formula, the Jump-Diffusion model and Heston's model. In judging the alternative models, we consider the following issues: (i) the consistency of the implied structural parameters with the times-series data; (ii) out-of-sample pricing; and (iii) parameter uniformity across different moneyness and maturity classes. Overall, nonlinear feedback due to hedging strategies can, at least in part, contribute to the explanation from a theoretical and quantitative point of view of the strong pricing biases of the Black–Scholes formula, although stochastic volatility effects are more important in this regard.     

Tax liens: a novel application of asset pricing theory

Although relatively obscure, the market for distressed real estate tax liens exists in over 30 U.S. states, with a market size estimated to be around 20 billion dollars. While this niche asset class is relatively unknown to academics, internet advertising hypes tax liens to the populace as providing extraordinary returns. Not yet scientifically studied, this market provides a fertile and untouched arena for the application of asset pricing theory. Using insights from several areas of asset pricing, we formulate and test a pricing model for tax liens. The empirical evidence supports the pricing model, the (increasing) competitiveness of the tax lien market, and an unfair tax auction bidding mechanism for property owners that may provide extraordinary returns to investors, lending some credibility to the industry claims. We suggest avenues for extensions and further research.     

Warrant pricing: a review of empirical research

Recently, several warrant pricing studies have become available for different models as well as for different countries. The most important conclusions that can be drawn from reviewing these studies are: (1) it is not necessary to make a correction on option valuation models for the dilution effect; (2) the only model that systematically outperforms the Black-Scholes (1973) type models is the Square Root model; (3) US and German warrants seem to be priced correctly, while deviations are found for English and Japanese warrants (underpriced by the market) and Swiss and Dutch warrants (overpriced by the market).     

Monotonicity in asset returns: New tests with applications to the term structure,the CAPM,and portfolio sorts

Many theories in finance imply monotonic patterns in expected returns and other financial variables. The liquidity preference hypothesis predicts higher expected returns for bonds with longer times to maturity; the Capital Asset Pricing Model (CAPM) implies higher expected returns for stocks with higher betas; and standard asset pricing models imply that the pricing kernel is declining in market returns. The full set of implications of monotonicity is generally not exploited in empirical work, however. This paper proposes new and simple ways to test for monotonicity in financial variables and compares the proposed tests with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.     

Stochastic integrals driven by fractional Brownian motion and arbitrage: a tale of two integrals

Recent research suggests that fractional Brownian motion can be used to model the long-range dependence structure of the stock market. Fractional Brownian motion is not a semi-martingale and arbitrage opportunities do exist, however. Hu and Øksendal [Infin. Dimens. Anal., Quant. Probab. Relat. Top., 2003, 6, 1–32] and Elliott and van der Hoek [Math. Finan., 2003 Elliott, RJ and van de Hoek, J. 2003. A general fractional white noise theory applications to finance. Math. Finan., 13: 301–330. [Crossref], [Web of Science ®] , [Google Scholar], 13, 301–330] propose the use of the white noise calculus approach to circumvent this difficulty. Under such a setting, they argue that arbitrage does not exist in the fractional market. To unravel this discrepancy, we examine the definition of self-financing strategies used by these authors. By refining their definitions, a new notion of continuously rebalanced self-financing strategies, which is compatible with simple buy and hold strategies, is given. Under this definition, arbitrage opportunities do exist in fractional markets.     

CEO characteristics: a review of influential publications and a research agenda

This paper provides a systematic review of literature pertaining to CEO characteristics and firm performance. The CEO of a firm provides critical leadership, social capital, and legitimacy, and as such exerts significant influence on firm performance. By using a bibliographic mapping approach, we identify the fifty‐one most influential publications on CEO characteristics. This field has developed from a few Upper Echelon Theory publications into four distinct categories. We review each of these to identify the main contributions to this research area and to outline research gaps and future research trends.     

Pricing a class of exotic commodity options in a multi-factor jump-diffusion model

In a recent paper, Crosby introduced a multi-factor jump-diffusion model which would allow futures (or forward) commodity prices to be modelled in a way which captured empirically observed features of the commodity and commodity options markets. However, the model focused on modelling a single individual underlying commodity. In this paper, we investigate an extension of this model which would allow the prices of multiple commodities to be modelled simultaneously in a simple but realistic fashion. We then price a class of simple exotic options whose payoff depends on the difference (or ratio) between the prices of two different commodities (for example, spread options), or between the prices of two different (i.e. with different tenors) futures contracts on the same underlying commodity, or between the prices of a single futures contract as observed at two different calendar times (for example, forward start or cliquet options). We show that it is possible, using a Fourier transform-based algorithm, to derive a single unifying form for the prices of all these aforementioned exotic options and some of their generalizations. Although we focus on pricing options within the model of Crosby, most of our results would be applicable to other models where the relevant ‘extended’ characteristic function is available in analytical form.     

Efficient analytic approximation of the optimal hedging strategy for a European call option with transaction costs

One of the most successful approaches to option hedging with transaction costs is the utility-based approach, pioneered by Hodges and Neuberger [Rev. Futures Markets, 1989, 8, 222–239]. Judging against the best possible trade-off between the risk and the costs of a hedging strategy, this approach seems to achieve excellent empirical performance. However, this approach has one major drawback that prevents the broad application of this approach in practice: the lack of a closed-form solution. We overcome this drawback by presenting a simple yet efficient analytic approximation of the solution. We provide an empirical testing of our approximation strategy against the asymptotic and some other well-known strategies and find that our strategy outperforms all the others.     

VaR and expected shortfall: a non-normal regime switching framework

We have developed a regime switching framework to compute the Value at Risk and Expected Shortfall measures. Although Value at Risk as a risk measure has been criticized by some researchers for lack of subadditivity, it is still a central tool in banking regulations and internal risk management in the finance industry. In contrast, Expected Shortfall is coherent and convex, so it is a better measure of risk than Value at Risk. Expected Shortfall is widely used in the insurance industry and has the potential to replace Value at Risk as a standard risk measure in the near future. We have proposed regime switching models to measure value at risk and expected shortfall for a single financial asset as well as financial portfolios. Our models capture the volatility clustering phenomenon and variance-independent variation in the higher moments by assuming the returns follow Student-t distributions.     

Sustainable finance and blockchain: A systematic review and research agenda

Sustainable finance and blockchain studies have garnered considerable interest recently. but there has been no systematic analysis of blockchain in sustainable finance to far. To fill this gap, based on the theme structure of blockchain research in the field of renewable finance from November 1, 2008 to January 31, 2022, this paper proposes a multi-level and all-round comprehensive bibliometric method (Co-occurrence Analysis method, Natural Language Processing method, and Exploratory Factor Analysis method) to comprehend the mode, process, and mechanism of the integration of them. The findings indicate that: (1) Blockchain has been widely used in many industries involved in sustainable finance; (2) Blockchain will have a long-term impact on Sustainable Finance in the fields of smart city and sharing economy; (3) Blockchain can be deeply integrated with other technologies to promote the diversified development of sustainable finance. Additionally, we highlight trends and research directions regarding blockchain in sustainable finance research.     

Indigenous sustainable finance as a research field: A systematic literature review on indigenising ESG,sustainability and indigenous community practices

Sustainable finance research has come into its own as an established area in the finance literature. The increased awareness of sustainability and global concerns around environmental, social and governance (ESG) issues, particularly among institutional investors, has catalysed a shift towards greater research and publications in this area. Accompanying this is the emerging body of work being produced on indigenous investments and indigenous community practices. These nascent strands of literature tell a story of the shift that is taking place within the finance field. To chart this shift and create a harmonised view of these bodies of work, this paper conducts a systematic literature review of the significant nexus between sustainable investments and indigenous approaches to sustainability. We present a framework for conceptualising and characterising the various stands of literature and, in so doing, make the case for Indigenous Sustainable Finance (ISF) as a distinct disciplinary field. This paper argues that ISF is distinct from mainstream sustainable finance and other social and management sciences and constitutes a legitimate, well-defined sub-field of research in its own right.     

The future trajectory for environmental finance: planetary boundaries and environmental,social and governance analysis

Urgent issues such as climate change have drawn increasing attention from finance scholars. Most research has situated a corporate response within the context of the environmental, social and governance performance. However, other disciplines express concerns around environmental degradation within broader frameworks, such as the Planetary Boundaries framework. We highlight the different conceptualisations of ESG and planetary boundaries and call for further research that links finance research to the Planetary Boundaries framework. We describe how contributions in the Accounting & Finance Special Issue on Environmental Finance advance research in this area and explore implications for future research that responds to the imperatives of remaining within Planetary Boundaries.     

金融资源论:对金融功能观与金融机构观的综合研究

金融资源论的提出是对金融基础理论研究的一次重大挑战.从金融机构观向金融功能观的演进是金融理论对现实世界变化的一种回应,金融资源论的提出同样是如此.金融资源的三个层次其实可以分为实体部分和功能部分,这两部分的主要内容和研究思路分别与金融机构观和金融功能观相对应.由此可见,在金融资源论与金融机构观和金融功能观之间存在着某种逻辑联系,即金融资源论是对金融机构观与金融功能观的一种综合,具有更为开阔的理论研究视角.这既为金融资源论构建了更为坚实的理论基础,也为金融资源论的进一步完善拓展了空间.     

Sentiment and Financial Health Indicators for Value and Growth Stocks: The European Experience

In this study, we analyse the effect of macroeconomic surprises on inflation compensation data – the sum of inflation expectation, risk and liquidity premia – in the euro area. The empirical analysis is based on a daily data set, which covers a wide spectrum of maturities, stemming from inflation-indexed markets between 2 January 2004 and 31 December 2007. Our results suggest that when gauging short- and medium-term inflation compensations, market operators are sensitive to surprises related to real activity and prices. Notwithstanding, long-term inflation compensations remain generally unresponsive to macroeconomic surprises, attesting the European Central Bank's high credibility on the sample under consideration. The study also cross-checks the results from two different euro area inflation-indexed instruments (bonds and swaps) which differ slightly regarding medium-term horizon but give a similar picture regarding long-term horizons.     

Determinants of Saving-Borrowing Decisions and Financial Inclusion in a High Middle Income Country: The Turkish Case

We use a representative survey of the Turkish household sector and investigate factors impinging on saving-borrowing behavior. We run four probit regressions to elucidate (i) the saving decision, (ii) asset choice or portfolio composition for those who save, (iii) the bank loan decision and lastly (iv) the formal versus informal borrowing decision. We find income, education, marital status and region within country strongly correlate with those decisions. We offer some insights regarding the influence of variables like rural to urban migrant status and religious belief on saving and borrowing decisions. We discuss the long-term implications of our findings on the Turkish household savings performance.     

金融支持文化产业研究:济宁案例

本文从文化产业公益性和商业性共存这一特性入手,结合文化产业发展现状,以济宁市金融支持文化产业实践为例,通过分析,找到金融支持文化产业的合理切入点,提出解决方案,为金融支持文化产业发展作出有益探索。     

Skewed distributions in finance and actuarial science: a review

That the returns on financial assets and insurance claims are not well described by the multivariate normal distribution is generally acknowledged in the literature. This paper presents a review of the use of the skew-normal distribution and its extensions in finance and actuarial science, highlighting known results as well as potential directions for future research. When skewness and kurtosis are present in asset returns, the skew-normal and skew-Student distributions are natural candidates in both theoretical and empirical work. Their parameterization is parsimonious and they are mathematically tractable. In finance, the distributions are interpretable in terms of the efficient markets hypothesis. Furthermore, they lead to theoretical results that are useful for portfolio selection and asset pricing. In actuarial science, the presence of skewness and kurtosis in insurance claims data is the main motivation for using the skew-normal distribution and its extensions. The skew-normal has been used in studies on risk measurement and capital allocation, which are two important research fields in actuarial science. Empirical studies consider the skew-normal distribution because of its flexibility, interpretability, and tractability. This paper comprises four main sections: an overview of skew-normal distributions; a review of skewness in finance, including asset pricing, portfolio selection, time series modeling, and a review of its applications in insurance, in which the use of alternative distribution functions is widespread. The final section summarizes some of the challenges associated with the use of skew-elliptical distributions and points out some directions for future research.     

A general framework for the derivation of asset price bounds: an application to stochastic volatility option models

We present a generalization of Cochrane and Saá-Requejo’s good-deal bounds which allows to include in a flexible way the implications of a given stochastic discount factor model. Furthermore, a useful application to stochastic volatility models of option pricing is provided where closed-form solutions for the bounds are obtained. A calibration exercise demonstrates that our benchmark good-deal pricing results in much tighter bounds. Finally, a discussion of methodological and economic issues is also provided.