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Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. The nonlinear machine learning models generate statistically and economically sizable profits in the long-short portfolios of equity options even after accounting for transaction costs. Although option-based characteristics are the most important standalone predictors, stock-based measures offer substantial incremental predictive power when considered alongside option-based characteristics. Finally, we provide compelling evidence that option return predictability is driven by informational frictions and option mispricing. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate risk represents an increasingly vital issue to countries, companies, and institutional investors, making it a reality but not a distant threat to humanity. Considering the effects of climate risks on firms' financial indices and financing options, the study investigates whether climate risk is priced by the capital markets of South Africa. The study used reported carbon emissions as a measure of climate risk of 81 listed companies in the Johannesburg Stock Exchange from 2011 to 2020 to examine whether climate risk is considered and priced by the South Africa capital market. Data was sourced from DataStream database- a global financial and macroeconomic time-series database providing data on equities, stock market indices, currencies, company fundamentals, fixed income securities, and key economic indicators. We used the two-step system Generalized Method of Moments estimation technique that copes with endogeneity concerns to corroborate the effects of climate risk on cost of capital and capital structure. We find that climate risk is priced in both cost of debt capital and cost of equity capital. Specifically, we find that an increase in a firm's exposure to climate risk increases the cost associated with issuing debt and equity capital. We also find that climate risk exposure decreases the debt-equity ratio. Additionally, the study showed that firm size, leverage ratio, capitalization, profitability, and turnover affect both cost of capital and capital structure of listed firms. The study concludes that climate risk is priced in cost of financing in the capital market of South Africa. The study recommends that firms should invest in installing eco-friendly machinery that aligns with changing market expectations in order to reduce their carbon emissions. The study therefore highlights the need for companies to proactively assess and manage climate risks, incorporate climate considerations into their strategic decision-making, and enhance their resilience to climate-related challenges. JEL Classifications: C23; G10, Q50 Keywords: Climate risk, cost of capital, capital structure, capital markets, INTRODUCTION Climate risk represents an increasingly vital issue to countries, companies, and institutional investors (Ginglinger, 2020), making it a reality but not a distant threat to humanity (Hjort, 2016). Since [...]

We investigate the implications of recovering real-world conditional expectation of return functions using options on the S&P 500 index and Treasury bond futures. First, we construct estimates of the probability of disasters, defined as higher than 6%, 5%, or 4% equity market declines over option expiration cycles. This measure of disaster probability forecasts realized disasters. Second, we employ options on the futures of the 10- and 30-year Treasury bonds to construct estimates for the expected return of bond futures. These measures display forecasting ability for subsequent futures returns beyond the level, slope, and curvature variables extracted from the yield curve. [ABSTRACT FROM AUTHOR]

The pricing problem of European option is investigated under the generalized fractional jump-diffusion model. First of all, the generalized fractional jump-diffusion model is proposed, with the assumption that the underlying asset price follows this model, and the explicit solution is derived using the Itô formula. Then, the partial differential equation (PDE) of the European option price is obtained by using the delta-hedging strategy, and the analytical solutions of the European call and put option prices are obtained through the risk-neutral pricing principle. Moreover, the accuracy of closed-form formula for European option pricing is verified by the Monte Carlo simulation. Furthermore, the properties of the pricing formulas are discussed and the impact of main parameters on the option pricing model are analyzed via calculations of Greeks. Finally, the rationality and validity of the established option pricing model are verified by numerical analysis. [ABSTRACT FROM AUTHOR]

We focus on analyzing the risk preferences of suppliers regarding two types of financing: partial credit guarantee (PCG) and trade credit financing (TCF). Using the conditional value-at-risk (CVaR) criterion, we study each supply chain member's equilibrium solution and optimal financing strategy under the assumption of demand distributions with an increasing failure rate. Initially, we present an analytical solution of the risk-averse supplier's wholesale price, and prove that the optimal wholesale price decreases in the risk-averse level and initial capital, and increases in the credit guarantee ratio. Furthermore, we derive optimal financing strategies for both the supplier and the retailer under various circumstances. However, it is important to note that the results reveal a potential trade-off associated with PCG. While risk-averse suppliers may be more inclined to provide PCG compared to risk-neutral suppliers, this financing option can negatively impact the supplier's utility and the expected profits of the retailers. Finally, we illustrate how the optimal financing strategies shift in response to changes in the risk-averse level and credit guarantee ratio, and present the win-win situations for the supplier and the retailer. [ABSTRACT FROM AUTHOR]

Fractional Brownian motion has become a standard tool to address long-range dependence in financial time series. However, a constant memory parameter is too restrictive to address different market conditions. Here, we model the price fluctuations using a multifractional Brownian motion assuming that the Hurst exponent is a time-deterministic function. Through the multifractional Itô calculus, both the related transition density function and the analytical European Call option pricing formula are obtained. The empirical performance of the multifractional Black–Scholes model is tested by calibration of option market quotes for the SPX index and offers best fit than its counterparts based on standard and fractional Brownian motions. [ABSTRACT FROM AUTHOR]

In this paper, we apply Markov-modulated models to value continuous-installment options of the European style with a partial differential equation approach. Under regime-switching models and the opportunity for continuing or stopping to pay installments, the valuation problem can be formulated as coupled partial differential equations (CPDE) with free boundary features, which in many ways is similar to the free boundary problem for vanilla American options due to the possibility of early exercise. In this paper, to value the continuous-installment options under the proposed model with a numerical approach, we first express the truncated CPDE as a linear complementarity problem (LCP), and then a finite element method is applied to solve the resulting variational inequality. We studied the existence and uniqueness of the solution and analyzed the stability of the proposed method under some appropriate assumptions, then we illustrated the error estimates on the appropriate spaces. We presented some numerical results to examine the rate of convergence and accuracy of the proposed method for the pricing problem under the regime-switching model. [ABSTRACT FROM AUTHOR]

Since 2016, digital finances have been disrupted by the introduction of open banking policies, which would facilitate data sharing in this particular industry. The UK and the EU have led this approach through the adoption of legal rules that enabled data sharing between financial institutions, particularly payment services providers, under users’ permission; lately, this has been slowly expanded into other financial services and called open finance. In this respect, certain Latin American countries have followed this, particularly led by industry efforts. In contrast to the EU, where the Digital Single Market facilitates the necessary conditions for sharing data, Latin America is fragmented in this respect. As such, this permission might be a weak basis for enabling a cross-border open finance ecosystem. This contribution will explore a selected cohort of Latin American countries and assess whether it would be feasible the development of a regional open finance system. [ABSTRACT FROM AUTHOR]

In this work, we introduce two accurate and efficient finite difference methods based on radial basis functions (RBF–FD) for pricing European and American options under liquidity shocks. The problem is formulated as the semi-linear complementarity and PDE systems for American and European options, respectively. In the context of temporal semi-discretization, we provide two backward difference formulas of order one and two (BDF1 & BDF2). Furthermore, we discuss the stability and convergence properties of the proposed methods. For the American option, to solve the semi-linear system of complementarity problems (LCPs), we combine the RBF-FD approaches with an operator splitting (OS) method. To illustrate the efficiency and accuracy of the suggested methods, we provide numerical examples for both European and American call options and verify them with the existing work in the literature. In numerical discussion, we show the Greeks (Delta & Gamma) plots for the American options. [ABSTRACT FROM AUTHOR]

Currently, the most liquidly traded options on the crypto underlying are the so-called inverse options. An inverse option contract is quoted and traded in the units of the underlying cryptocurrency. The main economic reason for the popularity of inverse contracts in the crypto exchanges (such as Deribit) is that inverse contracts enable traders to operate without maintaining fiat cash accounts. For the theoretical part, we show that inverse options are just regular vanilla options considered under the martingale measure using the forward of the underlying as the numéraire. This measure requires an adjustment to option delta. For the empirical part, we use Deribit options data of past five years to backtest delta-hedged option strategies. We introduce USD and Coin accounting of trading Profit&Loss (P&L) which is important for designing strategies in crypto options. We show empirically that USD and Coin accounting rules are equivalent when performance is measured is Coin and USD units, respectively. We establish that the risk-premia observed in options on Deribit is negative and significant so that strategies selling volatility are expected to generate positive risk-adjusted performance in the long-term. [ABSTRACT FROM AUTHOR]

We formulate a trade-off model that integrates mean reversion in earnings, encompassing dynamic financing decisions that entail both the initial leverage selection and the subsequent decision related to the financing of a growth option. We identify that higher earnings mean reversion speed increases both initial and subsequent leverage ratios for growth option financing and accelerates investment, revealing the volatility-mitigating role of mean reversion speed. Furthermore, our analysis reveals a U-shaped relation between profitability and leverage, influenced by the presence of growth options. In contrast, higher long-term profitability has a positive relationship with leverage, highlighting the differential impact of long-term versus contemporaneous profitability on leverage. The model also yields further implications for corporate policies regarding debt priority structure, investment timing, default thresholds, and credit spreads, contingent on earnings mean reversion dynamics. Our empirical analysis reveals the prevalence of mean reversion in earnings among US firms and provides a comparison of capital structure decisions of firms with mean reverting earnings against firms having non-stationary earnings dynamics. [ABSTRACT FROM AUTHOR]

We study the endogenous formation of climate coalitions linked to a preferential free trade arrangement. In a multi-stage, micro founded strategic trade and participation game, coalition and fringe countries dispose of a discriminatory tariff on dirty imports as well as emission permits imposed on domestic producers. Permits are traded on a common permit market inside the coalition and on local markets outside, respectively. We provide an analytical solution for the general equilibrium and the policy game, in the three country case, while the participation game is solved by Monte Carlo simulation. Moreover, conditional probabilities are computed for the transition to coalitions of various sizes induced by free trade. Under various regimes analyzed, we find that preferential free trade can create strong incentives for building effective climate coalitions in terms of depth and breadth. This result even holds if fringe countries are given the option of trade cooperation as a retaliation devise and is driven by a favorable shift in the coalition's terms of trade. As a policy implication, negotiations on international climate treaties and free trade arrangements should be interlinked. [ABSTRACT FROM AUTHOR]

This paper employs a numerical approach to investigate the impact of liquidity shocks on European options in modeling markets. To accurately capture the behavior of European options under liquidity shocks, a coupled system of differential equations is employed, consisting of a degenerate parabolic equation and a diffusion-free equation. The primary focus is on developing and analyzing implicit-explicit methods for numerically simulating European option pricing, specifically considering the presence of liquidity shocks while ensuring the positivity of the solution. The paper also includes convergence analysis and establishes the discrete comparison principle for the developed methods. Numerical experiments are conducted using both uniform and nonuniform meshes to validate the theoretical findings, demonstrating the efficiency and accuracy of the proposed methods. [ABSTRACT FROM AUTHOR]

How to structure the topology of a neural net (the hyperparameters optimization) is a recurring problem of crucial importance for both the quality and rapidity of the learning process, which will be then translated onto the final outputs. In this article, the authors investigate a smart two-step procedure that formalizes the application of deep feed-forward neural nets in the problem of the calibration of the SABR option-pricing model. The analysis is performed without the need of manually preparing the network topology, that is instead optimally chosen by means of a Bayesian algorithm. An extensive numerical experiment shows that their approach possesses superior approximation, calibration and retrieval properties when compared to the Hagan's formula and the ZC map. [ABSTRACT FROM AUTHOR]

In this article, an iterative deterministic policy gradient method for finding optimal strategies in the presence of market impact is introduced. The derivation of the policy gradient sheds light on a proper way of handling the market impact of trades in the context of reinforcement learning. Similar to many machine learning methods, the proposed deterministic policy gradient method is based on mini-batch stochastic gradient descent optimization. The method is demonstrated to consistently perform well for several different objectives and market dynamics when applied to the financial applications of order execution and option hedging. [ABSTRACT FROM AUTHOR]

Recently, there has been considerable interest in machine learning (ML) applications for the valuation of options. The main motivation is the speed of calibration or, for example, the calculation of credit valuation adjustments (CVA). It is usually assumed that there is a relatively liquid market with plain vanilla option quotations that can be used to calibrate (using an ML model) the volatility surface or to estimate the parameters of an advanced stochastic model. In the second stage, the calibrated volatility surface (or the model parameters) is used to value given exotic options, again using a trained neural network (NN) or another ML model. The NNs are typically trained offline by sampling many model and market parameter combinations and calculating the options' market values. In this research, the authors focus on the quite common situation of a nonliquid option market in which one lacks a sufficient number of plain vanilla option quotations to calibrate the volatility surface, but one still needs to value an exotic option, or just a plain vanilla option, subject to a more advanced stochastic model, as is typical for energy and carbon derivatives markets. Their study shows that the historical return moment-based pricing and calibration NNs can be applicable in practice with a performance lower than but still comparable to the option-based calibration. The authors also demonstrate that the performance can be substantially improved when high-frequency historical data, allowing them to apply the concept of realized volatility, are available. [ABSTRACT FROM AUTHOR]

After 1980, the telecom industry rapidly changed. Several new technologies were introduced, and telecom sectors in many countries opened for competition. The new technologies were available to all operators, but not all technologies assumed the same risks. Drawing upon rich archival sources from the Swedish telecom operator Televerket (after 1993, Telia), we examine the investment in and management of one new technology – ISDN. By exploring the choices and rationales for initiating and ending a technology project, we find that they may be pursued for political reasons – what we call 'investment as corporate political activity', and that many years of losses are sometimes not enough to abandon these projects. We also identify a monopolist logic in which projects can be maintained for use as bargaining chips in negotiations over deregulation or options to expand in markets after deregulation. [ABSTRACT FROM AUTHOR]

We address the stock predictability puzzle, a challenge in the stock market often discussed in behavioral finance. Our approach formulates a statistical model within rational finance, avoiding reliance on behavioral finance assumptions, and integrates stock return predictability into the Black–Scholes option pricing framework. Empirical analysis focuses on the predictability of stock prices by option and spot traders, introducing a forward‐looking measure we term "implied excess predictability." Results show that option traders' predictability of stock returns positively correlates with moneyness, whereas for spot traders, this relationship is inverse. These findings suggest a potential asymmetry in stock price predictability between spot and option traders. Additionally, we demonstrate the importance of incorporating stock return predictability into option pricing formulas, particularly for options with strike prices significantly different from the stock price. Conversely, when moneyness is close to unity, predictability is not integrated into option pricing, indicating equal information among spot and option traders. Comparison of volatility measures reveals the difference between implied and realized variances or variance risk premia as potential predictors of stock returns. [ABSTRACT FROM AUTHOR]

Copyright of Die Unternehmensbesteuerung (Ubg) is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We use account-level transaction data to examine trading styles and profitability in a leading derivatives market. Approximately 66% of active retail investors predominantly hold simple, one-sided positions in only one class of options, whereas institutional investors are more likely to use complex strategies. Hypothesizing that the complexity of trading styles reflects investors' skills, we examine the effect of options trading styles on investment performance. We find that retail investors using simple strategies lose to the rest of the market. For both retail and institutional investors, selling volatility is the most successful strategy. We conclude that these style effects are persistent and cannot be fully explained by systematic risk exposure. This paper was accepted by Lukas Schmid, finance. Funding: J. Hu acknowledges financial support from Lee Kong Chian Fellowship. A. Kirilova acknowledges financial support from the Spanish Ministry of Science and Innovation [Grant PID2021-128994NA-I00]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4916. [ABSTRACT FROM AUTHOR]

Entrepreneurship contributes substantially to the modernization and commercial development of an economy. Access to financial resources is key to the successful operation of new ventures which is arrested by COVID-19. Therefore, the present study aims to address the architecture of entrepreneurial finance since the inception of COVID-19. The research adopts a Systematic literature review approach to study the 127 articles chosen for analysis. The findings reveal the usage of novel sources of finance such as crowdfunding, and Initial Coin Offerings during COVID-19. Apart from this, the research also encapsulates the contributions of the articles on venture capital, P2P lending, and angel finance. Also, the study highlights promising avenues for future research focusing on different financing options and drivers of financing choices. [ABSTRACT FROM AUTHOR]

I Design thinking is a human-caused approach to sort out problems and prepare the mindset to deal with the challenges in business. This is a step-by-step method to deal with the entire aspects of production right from product decision to launch of the product. The proper method to know the consumer's need and formulation of suitable action plan to devise solutions is required before product decision. The constructive interaction between design thinking and entrepreneurship development is well-known. Reliable solutions can be derived through design thinking in developing ideas for start-up ventures. The upcoming entrepreneurs can explore many open-ended options and design the options to capture the market share. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to analyse potential models of Islamic crowdfunding as an alternative financing option for micro-entrepreneurs in Malaysia. While crowdfunding has gained traction as an alternative funding source for businesses, it is unclear how far this concept can benefit a group of micro-entrepreneurs in Malaysia. Design/methodology/approach: This study uses a qualitative research approach by using data collected through semi-structured interviews with several experts and practitioners in crowdfunding, Shariah and entrepreneurship. Prior to discussing the facets of the findings, the data were analysed based on a thematic approach. Findings: The findings reveal that while previous works of related literature suggest crowdfunding as a viable alternative financing option for entrepreneurs and their businesses, in reality, its practical implementation presents challenges. Numerous micro-entrepreneurs need more training in the areas of management and marketing. Such concerns raise questions about their ability to attract potential project backers. With the proper selection of Shariah contracts and several approaches to risk management, Islamic crowdfunding can potentially become an alternative funding source for microbusinesses. Research limitations/implications: Given the exploratory nature of this study regarding the applicability of Islamic crowdfunding as an alternative fund for micro-entrepreneurs, its findings may not fully encompass Malaysia's context because of the limited number of participants involved. Practical implications: The findings of this study offer guidelines on how to implement Islamic crowdfunding for micro-entrepreneurs. Consequently, Islamic crowdfunding has the potential to alleviate the government's burden of providing funds for micro-enterprises and enhance their skills and mentality to be more independent, creative and able to promote their products. Social implications: While Islamic crowdfunding can be an alternative opportunity for business enterprises and community-based projects, it promotes the spirit of cooperation and collaboration within society. Originality/value: Although Islamic crowdfunding is a topic that has been discussed previously, empirical investigations in this area remain scarce, mainly through qualitative approaches. Distinguishing from prior literature, this study analyses several potential models of Islamic crowdfunding from the perspectives of experts, practitioners and related agencies for micro-entrepreneurs. Moreover, this study bridges insights from related literature so that they offer practical applications to support micro-entrepreneurs in Malaysia. [ABSTRACT FROM AUTHOR]

Since the S&P 100 Index underlies both American (OEX) and European (XEO) options, the value of the early exercise premium of American options can be directly observed. We find that the mid‐quote of an XEO option can be higher than that of an otherwise identical OEX option, and liquidity can explain this overpricing phenomenon of European options. Our results show that illiquid options are significantly overpriced in the S&P 100 Index options market. This finding indicates that an illiquid option can be overvalued with a higher market offer price, which is the requirement of market makers for compensation for providing liquidity. [ABSTRACT FROM AUTHOR]

In this paper, we develop a discrete‐time affine option‐pricing model that explicitly incorporates the dynamics of conditional skewness. The new proposed model features different dynamics for conditional skewness and variance. To stress the difference in information, we use alternative realized measures constructed from high‐frequency historical returns to update skewness and variance dynamics. By Fourier inversion, we derive closed‐form option valuation formulas. Empirically, the flexibility that the model offers for conditional skewness as well as high‐frequency information from the underlying asset contribute to superior performance upon benchmark models using S&P 500 index options. Overall, the joint modeling of dynamic conditional skewness and realized measures leads to an out‐of‐sample gain of 12.25% in pricing accuracy. The improvements are more pronounced for deep in‐the‐money calls, options with shorter maturities, and during highly volatile periods. [ABSTRACT FROM AUTHOR]

Background: Out-of-pocket (OOP) payment is one of many countries' main financing options for health care. High OOP payments push them into financial catastrophe and the resultant impoverishment. The infrastructure, society, culture, economic condition, political structure, and every element of the physical and social environment influence the intensity of financial catastrophes in health expenditure. Hence, the incidence of Catastrophic Health Expenditure (CHE) must be studied more intensively, specifically from regional aspects. This systematic review aims to make a socio-ecological synthesis of the predictors of CHE. Method: We retrieved data from Scopus and Web of Science. This review followed PRISMA guidelines. The interest outcomes of the included literature were the incidence and the determinants of CHE. This review analyzed the predictors in light of the socio-ecological model. Results: Out of 1436 screened documents, fifty-one met the inclusion criteria. The selected studies were quantitative. The studies analyzed the socioeconomic determinants from the demand side, primarily focused on general health care, while few were disease-specific and focused on utilized care. The included studies analyzed the interpersonal, relational, and institutional predictors more intensively. In contrast, the community and policy-level predictors are scarce. Moreover, neither of the studies analyzed the supply-side predictors. Each CHE incidence has different reasons and different outcomes. We must go with those case-specific studies. Without the supply-side response, it is difficult to find any effective solution to combat CHE. Conclusion: Financial protection against CHE is one of the targets of sustainable development goal 3 and a tool to achieve universal health coverage. Each country has to formulate its policy and enact laws that consider its requirements to preserve health rights. That is why the community and policy-level predictors must be studied more intensively. Proper screening of the cause of CHE, especially from the perspective of the health care provider's perspective is required to identify the individual, organizational, community, and policy-level barriers in healthcare delivery. [ABSTRACT FROM AUTHOR]

Despite the presence of a huge amount of research on various aspects related to the rationale for selection of optimal technologies, spatial aspects have traditionally remained unattended by scientists. Justification for selection of optimal technologies for the production and transportation of good and justification for selection of optimal location and capacity of the corresponding industries are interrelated tasks of the complex problem of optimizing the spatial and technological development of an economic sector within the relevant space. At first, based on the criterion of the availability of factors of production of the corresponding good, attractive production sites are identified and for each of them selection of place-based optimal production technology is justified. The developed systematic approach involves the stage of identifying locally optimal places and technologies of production and transportation for each sales market option according to the criterion of the minimum total costs of producing a good in the volume of demand of the corresponding sales market option and the costs of transporting this good to potential sales markets that form the evaluated market option sales in the amount of their demand. At the final stage, options for potential systemically optimal places and technologies, which are formed from locally optimal places and technologies, are compared. The option of potential systemically optimal locations and corresponding production and transportation technologies with minimal total costs for production and transportation is the best. [ABSTRACT FROM AUTHOR]

Women's empowerment is now a global development objective. However, the instrumentalization of this approach to gender equality has prompted calls for research into the financing of interventions. With donors now reporting the gender credentials of their spending, this article follows the money for one region—Southeast Asia—to investigate how donors are engaging with women's economic empowerment. Through a systematic review, it identifies and codes women's economic empowerment projects. Data is analyzed according to geographic distribution, thematic distribution, and participant types. The article offers important insights into funding patterns and deficiencies in current reporting practices. It finds, first, while there is a more thematically diverse mix of projects being funded than indicated in previous research, women's economic empowerment continues to be interpreted in Southeast Asia as women's market inclusion, continuing the trend of instrumentalization. Second, and consistent with emergent research highlighting the political uses of aid transparency, it demonstrates that donors are engaging in gender wash by inadequately and incorrectly reporting project characteristics. By upselling their gender credentials, donors are characterizing their activities as advancing gender equality despite often intensifying the challenges faced by women, underscoring the urgent need to reform reporting practices. [ABSTRACT FROM AUTHOR]

The Black–Scholes equation is an important analytical tool for option pricing in finance. This paper discusses the Lie symmetry analysis of the time fractional Black–Scholes equation derived by the fractional Brownian motion. Some exact solutions are obtained, the figures of which are presented to illustrate the characteristics with different values of the parameters. In addition, a new conservation theorem and a generalization of the Noether operators are developed to construct the conservation laws for the time fractional Black–Scholes equation. [ABSTRACT FROM AUTHOR]

Risk-neutral fuzzy probability measures play a crucial role in evaluating American fuzzy put option and fuzzy call option pricing models that depend on the amount of increase or decrease of the equity prices. Volatility and risk-free interest rate are the two significant parameters that are affecting the financial market frequently. In 2008, Muzzioli et al [9] and Xcaojian Yu [17] used non-overlapping triangular/trapezoidal and non-overlapping fuzzy trapezoidal numbers respectively to describe the same to study American put option model. In this study, we recommend fuzzy measures involving non-overlapping fuzzy octagonal numbers using which we demonstrate American Put Fuzzy Option Model (APFOM) by incorporating the uncertain values to real in the volatile series. [ABSTRACT FROM AUTHOR]

It is well known that interest rates and credit spreads are negatively correlated. Any successful model for pricing callable corporate bonds has to take this correlation into account. A new approach for the analysis of corporate bond options is developed by using two correlated geometric Brownian motion (GBM) processes for the spread and interest rate components of corporate bond yields. Analysis of the results and comparison with market prices suggest that the traditional methods of calculating the option premium overestimate the value of the call option. Our analysis can also explain why risk neutral credit spreads are significantly wider than implied by default probability and in fact justify higher spreads. [ABSTRACT FROM AUTHOR]

We examine the relation between excess corporate cash holdings and equity option market liquidity from January 3, 2005 to December 31, 2019. We show that the level of cash reserve in excess of what can be captured by firm characteristics significantly explains stock option liquidity. Trading volume and option open interest increase in companies with a higher magnitude of excess cash, whereas the bid–ask spreads of stock options decline in excess cash. Our findings confirm the theoretical prediction that excess cash improves option market liquidity as it reduces adverse selection problems caused by uncertainty in firm valuations. This relation remains more pronounced with put options, out‐of‐the‐money contracts, and short‐maturity contracts. In addition, excess cash has a stronger impact on option liquidity within firms that have a greater degree of informed trading and during high‐volatility periods in financial markets. Our results show that when uncertainty about firm prospects rises, excess cash becomes more valuable and affects option market liquidity. [ABSTRACT FROM AUTHOR]

An efficient numerical method is propoesd for a parabolic linear complementarity problem (LCP) arising in the valuation of American options on zero-coupon bonds under the Cox–Ingersoll–Ross (CIR) model. With variable substitutions, we first transform the original pricing problem into a degenerated linear complementarity problem on a bounded domain, and present a corresponding variational inequality (VI). We then give the full discretization scheme of VI constructed by finite element and finite difference methods in spatial and temporal directions, respectively. Within the framework of VI, the stability and the rate of convergence are obtained. Moreover, for the resulted discretised variational inequality, we present a primal-dual active set (PDAS) method to solve it. Numerical results are carried out to test the usefulness of the proposed method compared with existing methods. [ABSTRACT FROM AUTHOR]

This article adopts an institutionalist perspective in order to address the energy transition process and to consider, in particular, the alternative financing mechanisms that would be able to support a structural transformation that is sustainable in the long term. It argues that such a transformation can be regarded in a holistic and broader way as an eco-transition process that involves the whole society and economy and requires a societal public organization. A relevant holistic approach to eco-transition should focus on the institutional conditions that are required for a new sustainable and structural change framework. In this aim, the article points to the features of the transition process that display the characteristics of a public good. The durable provision of such a good calls for the transformation of the financing schemes in force to support green investments beyond the usual opposition between market-friendly and government-guided economic policies. A relevant avenue is to organize the financing of the eco-transition under the supervision of public institutions even though the contribution of private bodies might be valuable according to the rules of long-term non-speculative financial support of markets. [ABSTRACT FROM AUTHOR]

While asymmetric mixture models improve option pricing over generic pricing models, mispricing remains due to their inability to capture the effect of economic factors on price levels. This paper uses the hidden truncation normal (HTN) distribution introduced by Arnold et al. (1993) and the NGARCH model of Engle and Ng (J Finance, 48:1749–1778, 1993) to price options. Compared to the Black–Scholes model, the HTN -NGARCH option pricing model has extra parameters linked to economic dynamics and with economic interpretations. The model integrates some stylized facts underlying option prices such as a time-varying price of risk, non-normal innovations, asymmetry, and kurtosis. The model can be estimated by maximum likelihood. With an application to market data, we show that the HTN -NGARCH model accurately prices index options and captures adequately the smirk of implied volatility. [ABSTRACT FROM AUTHOR]

This paper demonstrates the benefits, from an expected utility perspective, of including a derivative into the universe of tradeable assets under the affine GARCH model proposed by Heston and Nandi (Rev Financ Stud 13(3):585–625, 2000. https://doi.org/10.1093/rfs/13.3.585). For this purpose, we first introduce a Power Option into the market, derive its value and moment generating function thanks to the affine GARCH structure. We then expand on the results presented by Escobar-Anel et al. (Oper Res Perspect 9:100216, 2022) by solving for the optimal investment allocations into the stock, a cash account and the option. We show that investors who are able to include a derivative indeed outperform those who only invest into the stock and the bank account. In this spirit, investors who fail to include, even a low level of exposure to the derivative, could see up to 7% annual wealth-equivalent losses. This confirms findings in continuous-time models dating to Liu and Pan (J Financ Econ 69(3):401–430, 2003). An empirical analysis on the S &P500 confirms the superiority in terms of Sharpe ratio, and maximum drawdown of portfolios with options, in-sample and out-of-sample. [ABSTRACT FROM AUTHOR]

Understanding how price-volume information determines future price movement is important for market makers who frequently place orders on both buy and sell sides, and for traders to split meta-orders to reduce price impact. Given the complex non-linear nature of the problem, we consider the prediction of the movement direction of the mid-price on an option order book, using machine learning tools. The applicability of such tools on the options market is currently missing. On an intraday tick-level dataset of options on an exchange traded fund from the Chinese market, we apply a variety of machine learning methods, including decision tree, random forest, logistic regression, and long short-term memory neural network. As machine learning models become more complex, they can extract deeper hidden relationship from input features, which classic market microstructure models struggle to deal with. We discover that the price movement is predictable, deep neural networks with time-lagged features perform better than all other simpler models, and this ability is universal and shared across assets. Using an interpretable model-agnostic tool, we find that the first two levels of features are the most important for prediction. The findings of this article encourage researchers as well as practitioners to explore more sophisticated models and use more relevant features. [ABSTRACT FROM AUTHOR]

This study develops new evidence on risk versus mispricing explanations of the well‐known profitability premium. First, we examine whether exposure to expected downside risk is a plausible explanation. We find that high profitability is associated with both lower ex ante and ex post probabilities of future price crashes. Thus, less profitable firms exhibit greater downside risk than highly profitable firms, making a downside risk explanation implausible. Although this fact is overlooked by the market in general, it is anticipated by options traders; we find that put options of low profitability firms are relatively more expensive. Simultaneously, these firms do not exhibit greater probability of jumps, indicating that volatility(risk)‐based explanations for the profitability premium are unlikely to be descriptive. Second, we find that the sticky‐expectations model of Bouchaud et al. (2019, The Journal of Finance, 74, 639–674) only partially explains the profitability premium. While on average, analysts' forecast revisions correct in the same direction as recent profitability, the profitability premium still exhibits a strong relationship to the non‐sticky component of analysts' forecast revisions. Third, institutional investors trade profitability‐based signals but do so with a delay, likely contributing to the premium. Overall, our evidence favours the explanation that the profitability premium is related to investor mispricing of potential downside risk and provides greater clarity on recent findings in the literature. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to comprehensively review the literature on the value and impact of the US Department of Agriculture (USDA) reports and discuss theoretical issues and empirical evidence. Only a handful of studies provide direct estimates of the welfare benefits of USDA information using a rational expectations framework in storable commodity markets. Most studies examine partial evidence of welfare benefits associated with market response to USDA information. These studies include examinations of the impacts of USDA report releases on cash and futures price volatility and other market dynamics, impacts of report releases on options implied volatility, impacts of unanticipated information in USDA reports, as well as informational value, returns, and survey‐based studies. We discuss the methodological and empirical contributions of these studies as well as their shortcomings and potential opportunities for future work. [ABSTRACT FROM AUTHOR]

Amidst rising trading volumes, there's evident demand for volatility trading. This study assists Chinese stakeholders in understanding the iVIX's functionality, offering insights for investments and policy-making. Building on the VIX option pricing model, the research introduces a novel approach: the mean-reverting logarithmic stochastic volatility Hawkes jump model (MLSVHJ). Using VIX call option data from March 9, 2020, to March 18, 2021, the MLSVHJ model outperformed four others during 2020's three US market crashes. Additionally, this model's parameters aligned well with theoretical expectations. However, the positive correlation observed between the iVIX and the Shanghai Composite Index prompts a reevaluation of applying global VIX standards directly to China. [ABSTRACT FROM AUTHOR]

We examine options trading in leveraged Exchange‐Traded Funds (ETFs) and their impact on the performance of the underlying funds. Using implied volatility innovations in call and put options, we demonstrate that option signals from leveraged ETFs are robust predictors of the underlying ETFs' performance. While both levered and unlevered option signals forecast ETF returns, the levered signal is more pronounced in both magnitude and relevance. This predictivity power primarily stems from inverse leveraged ETFs and during economic downturns. Furthermore, we use the leveraged ETF option signals to develop a trading strategy that produces an average abnormal performance of 1.13% per month. [ABSTRACT FROM AUTHOR]

Traditional options pricing relies on underlying asset volatility and contract properties. However, asset volatility is affected by the "lead–lag effects," known as the "momentum spillover effect." To address this, we propose a proxy measuring correlated options' influence based on maturity date. Findings indicate that 1‐day‐lagged proxy indicators positively impact option returns. Furthermore, to capture the dynamic effects of correlated options, we introduce a deep graph neural network‐based model (GNN‐MS). Empirical results on Shanghai Stock Exchange 50 exchange‐traded fund options reveal GNN‐MS significantly outperforms classics, enhancing root‐mean‐square error by at least 8.81%. This study provides novel insights into option pricing considering momentum spillover effects. [ABSTRACT FROM AUTHOR]

This study explores the value of the tax deferral option. By examining ex-day stock-price-change ratios for taxable stock dividends in Taiwan, we find that the tax deferral option is valuable to investors. For a $1 taxable stock dividend, the tax deferral option produces 33.9 ¢ in tax savings, which suggests a tax deferral parameter of 11.3%. We also find that stocks with the tax deferral option have higher trading volumes around ex-days than those without this option, and that higher investor-level tax rates lead to higher value of the tax deferral option. We contribute to the literature by cleanly determining the value of the tax deferral option; our result is not confounded by the restart option. [ABSTRACT FROM AUTHOR]

We estimate a model-free term structure of the ex ante dividend risk premium by combining two data sets with different information about future dividends. We aggregate survey forecasts about future dividends for single companies over multiple horizons to construct a term structure of expected S&P 500 dividend growth rates. We use European call and put option prices on the S&P 500 to estimate the term structures of options-implied dividend growth rates and risk-free rates. Applying the method to 2004–2021 data offers a new, ex ante perspective on the conditional time variation of the term structure of the dividend risk premium. [ABSTRACT FROM AUTHOR]