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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.)

We document the causal effects of single-name options trading on the absolute level of information content of prices (stock price informativeness) by exploiting the Penny Pilot Program as an exogenous shock to options trading volume. We find that options trading increases underlying stock price informativeness and information acquisition by both option and stock investors, consistent with the framework of Goldstein and Yang (2015). The findings are driven by firms for which options are more important sources of information and firms with more efficiently priced options. Options market introduction in a sample of 25 other economies also leads to higher price informativeness. [ABSTRACT FROM AUTHOR]

Why would some firms persist with continued operations when facing unfavorable economic conditions? Although prior studies have investigated the roles of uncertainty and sunk costs as sources of inertia, an unacknowledged type of sunk cost associated with temporary suspensions of operations is related to the erosion of existing capabilities. Building on the resource-based view and real options theory, we argue that resource idling contributes to capability erosion and that the anticipated capability loss motivates firms to refrain from idling their resources under demand uncertainty in the first place. The negative effects of uncertainty on resource idling are likely to be particularly strong for firms with superior capabilities and for those having a greater reliance on human capital. Using data on oil drilling contractors in Texas, the empirical evidence lends support to our theoretical arguments. Our insights suggest that resource idling shapes the development path of capabilities and risks jeopardizing firms' competitive advantages. The seemingly operational decision of temporarily idling resources can therefore be quite strategic for a firm, and "hysteresis," or inertia in continuing operations, can preserve firms' capabilities. [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.)

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]

In this study, we derived pricing formulas for various forward-start style exotic options based on an uncertain stock models with periodic dividends. Specifically, we present valuations for forward-start, Cliquet/Ratchet, and spread options. In addition, we conducted numerical simulations of these formulas and compared them to pricing formulas for the same options based on a dividendpaying stock model driven by standard Brownian motion. [ABSTRACT FROM AUTHOR]

This article presents a novel tree approach to pricing derivatives linked to new Risk-Free Rate benchmarks. The methodology is versatile and can be applied to both backward–and forward-looking caplets. It draws upon the analogy with the pricing of Asian options, allowing for effective pricing in the context of these new benchmark rates. This article demonstrates the efficacy of this approach by applying it to model the overnight rate using numerical examples. The focus is on established interest rate tree models, which are widely utilized in the financial industry for valuing bonds with options linked to legacy benchmarks like LIBOR. The numerical examples presented in this article validate the reliability and accuracy of the proposed tree-based approach, showcasing its superiority over traditional Monte Carlo simulation methods. [ABSTRACT FROM AUTHOR]

In this article we propose a semi-analytic approach to pricing American options in time-dependent jump-diffusion models with exponential jumps. The idea of the method consists of further generalization of our method developed for pricing barrier (Itkin, Lipton, and Muravey 2021) and American (Carr and Itkin 2021; Itkin and Muravey 2024) options in various time-dependent one factor and even stochastic volatility models. The proposed approach: i) allows arbitrary dependencies of the model parameters on time; ii) reduces solution of the pricing problem for American options to a simpler problem of solving a system of an algebraic nonlinear equation for the exercise boundary and a linear Fredholm-Volterra integral equation for the option Gamma; once done, the American option price is presented in closed form; iii) the options' Greeks solve a similar Fredholm-Volterra linear equation obtained by just differentiating the pricing equation by the required parameter. Also, solving integral equations instead of PIDE usually brings better accuracy under the same speed, or better speed under the same accuracy. [ABSTRACT FROM AUTHOR]

The distribution of financial data usually shows strong skewness and kurtosis. In this article, we propose a probability distribution with parameters explicitly representing skewness and kurtosis. This distribution extends logistic distribution to a wide range of distributions bounded by Gaussian and Laplace. The properties of the new distribution are studied, and parameter estimation methods are proposed. As an application, the new distribution can be used for pricing volatility skew and smile in option quotes and constructing local volatility models for the evaluation of path-dependent financial derivatives. [ABSTRACT FROM AUTHOR]

Using data from January 2004 through November 2019, we examine the relative performance of four options-based investment strategies versus a buy-and-hold strategy in the underlying stock. Specifically, using 10 stocks widely held in 401(k) plans, we examine monthly returns from strategies that include a long stock position as one component. Ignoring early exercises for simplicity, we find that the covered combination and covered call strategies generally outperform the long stock strategy, which in turn generally outperform the collar and protective put strategies, regardless of the performance measure considered. The outperformance of the covered combination was smallest in the 2015–2019 subperiod. These results also hold for equally-weighted and value-weighted portfolios constructed from the 10 individual stocks. Our findings suggest that options-based strategies can improve the risk-return characteristics of a long equity portfolio. [ABSTRACT FROM AUTHOR]

We propose a novel analytical method to evaluate VIX options under the general class of affine and non-affine stochastic volatility models, which extends the current literature in particular to the realm of non-affine stochastic volatility models. The approach is based on a closed-form approximation of the VIX index through the Ito-Taylor expansion and the subsequent continuous-time Markov chain (CTMC) approximation to evaluate VIX options. The formula is in explicit closed-form and does not involve numerical (Fourier) inversions, in contrast to the existing literature. Numerical experiments with several stochastic volatility models demonstrate that it is accurate and efficient by comparing with benchmarks in the literature and Monte Carlo simulations. Empirical experiments demonstrate that in general non-affine stochastic volatility models provide better fit to the VIX options data. [ABSTRACT FROM AUTHOR]

This paper proposes a new index of forward looking absolute deviation extracted from option prices. The new index, named absolute deviation index (ADIX), is model‐free and easy to compute using at‐the‐money call and put option prices. It is shown that the spread between volatility index (VIX) and ADIX captures departures from normality in the risk‐neutral distribution and an empirical analysis using S&P 500 options data for the time period 1996–2021 reveals that the spread carries significant forecasting ability with respect to future equity returns at short to medium horizons. Portfolio strategies that use the spread as a predictor of S&P 500 returns outperform buy‐and‐hold strategies in an out‐of‐sample mean‐variance asset allocation exercise. [ABSTRACT FROM AUTHOR]

This study examines how options trading plays a unique role in curbing firms' earnings management. We find that options trading volume deters managers' earnings manipulations, and the effect can be explained by unique characteristics of the options markets. Our results remain unchanged when using both an instrumental variable approach and difference-in-differences analyses to mitigate endogeneity concerns, and after controlling for investors' short-selling activities. This study adds to the literature by documenting a real impact of options trading on financial reporting. Our results suggest that the options markets promote price efficiency not only by incorporating private information from informed traders, but also by incentivizing managers to disseminate less manipulated information. [ABSTRACT FROM AUTHOR]

We consider a dynamic duopoly game where firms choose both the timing and size of their investments. The existing real options literature predominantly consists of contributions where firms have a single option to invest. This paper relaxes this assumption by giving Firm A multiple options to undertake further investments with the purpose to expand whereas Firm B only holds the option to enter the market. In this asymmetric setting we get the surprising result that, in equilibrium, Firm B invests first. If Firm A invests first, Firm A and Firm B keep on being involved in preemption games for subsequent investments until Firm B enters the market, which leads to inefficiently early investments of Firm A. When Firm B invests first, then only one preemption game is played, which leads to Firm A being free to choose its unrestricted optimal investment moments. [ABSTRACT FROM AUTHOR]

In practice, capital‐constrained third‐party logistics (3PL) firms usually obtain bank financing (BF) to invest in logistics technology to enhance the consumer shopping experience. The emergence of financial innovation has prompted the adoption of alternative financing modes by 3PLs, including e‐commerce platform financing (EPF) and fourth‐party logistics financing (4PF). To clarify the differences among the three financing modes at the operational management level, we develop a Stackelberg game model to capture the strategic interactions between the 3PL and creditors. We examine a platform‐based supply chain where a manufacturer sells products through an e‐commerce platform to consumers, with the logistics services for the supply chain provided by the 3PL and fourth‐party logistics (4PL) firms. The analysis results reveal that the equilibrium interest rates under EPF and 4PF share a similar pattern regarding the logistics service cost coefficient, the commission rate, and the 4PL service fee. The difference is that under EPF (4PF), the logistics service level increases in the commission rate (4PL service fee) but decreases under the other financing strategy. Furthermore, the 3PL is inclined to invest in logistics technology only when the fixed investment cost is low, and these financing modes are complementary rather than alternative. The 3PL and manufacturer can benefit from 4PF (BF) when the logistics service cost coefficient is large and the market size is small (large); otherwise, EPF can enhance their profits. We also find that when the opportunity costs of capital are homogeneous, both the 4PL and the platform are consistently willing to act as financiers themselves. However, when considering heterogeneity in the opportunity costs of capital, they may be reluctant to provide financing. Each financing mode may achieve Pareto improvements under specific conditions. Finally, we also analyze the impact of technology R&D risks and endogenous 4PL service fee, yielding some valuable insights. [ABSTRACT FROM AUTHOR]

AbstractMost of the existing methods for pricing Asian options are less efficient in the limit of small maturities and small volatilities. In this article, we use the large deviations theory for the analysis of short-maturity Asian options. We present a constant volatility model for the underlying market that incorporates a jump term in addition to the drift and diffusion terms. We estimate the asymptotics for the out-of-the-money, in-the-money, and at-the-money short-maturity Asian call and put options. Under appropriate assumptions, we show that the asymptotics for out-of-the-money Asian call and put options are governed by rare events. For the at-the-money Asian options, the result is more involved and in that case, we find the upper and lower bounds of the asymptotics of the Asian option price. [ABSTRACT FROM AUTHOR]

This study examines the effect of the 2012 introduction of the "Green Credit Guidelines" on the Environmental, Social, and Governance (ESG) performance of polluting enterprises listed on the Chinese A-share market from 2009 to 2019. Using a quasi-natural experiment framework, we employ a difference-in-differences model to evaluate the effectiveness of this green credit policy. Our analysis suggests that the green credit policy significantly hinders the ESG performance of polluting enterprises due to the "crowding out effect." Further investigation reveals that a notable decrease in green innovation, especially in its quality, impedes ESG improvements for these enterprises. Notably, the negative effects are more pronounced for non-state-owned enterprises. Our study provides valuable insights into the dual effects of the green credit policy, highlighting its potential to restrict financing options for polluting enterprises but crowd out resources allocated for environmental projects. To address these challenges, we propose practical strategies aimed at transforming the dual effects into dual benefits, optimizing both economic and environmental effects, and enhancing the overall effectiveness of the policy. [ABSTRACT FROM AUTHOR]

Modeling implied volatility (IV) is important for option pricing, hedging, and risk management. Previous studies of deterministic implied volatility functions (DIVFs) propose two parameters, moneyness and time to maturity, to estimate implied volatility. Recent DIVF models have included factors such as a moving average ratio and relative bid-ask spread but fail to enhance modeling accuracy. The current study offers a generalized DIVF model by including a momentum indicator for the underlying asset using a relative strength index (RSI) covering multiple time resolutions as a factor, as momentum is often used by investors and speculators in their trading decisions, and in contrast to volatility, RSI can distinguish between bull and bear markets. To the best of our knowledge, prior studies have not included RSI as a predictive factor in modeling IV. Instead of using a simple linear regression as in previous studies, we use a machine learning regression algorithm, namely random forest, to model a nonlinear IV. Previous studies apply DVIF modeling to options on traditional financial assets, such as stock and foreign exchange markets. Here, we study options on the largest cryptocurrency, Bitcoin, which poses greater modeling challenges due to its extreme volatility and the fact that it is not as well studied as traditional financial assets. Recent Bitcoin option chain data were collected from a leading cryptocurrency option exchange over a four-month period for model development and validation. Our dataset includes short-maturity options with expiry in less than six days, as well as a full range of moneyness, both of which are often excluded in existing studies as prices for options with these characteristics are often highly volatile and pose challenges to model building. Our in-sample and out-sample results indicate that including our proposed momentum indicator significantly enhances the model's accuracy in pricing options. The nonlinear machine learning random forest algorithm also performed better than a simple linear regression. Compared to prevailing option pricing models that employ stochastic variables, our DIVF model does not include stochastic factors but exhibits reasonably good performance. It is also easy to compute due to the availability of real-time RSIs. Our findings indicate our enhanced DIVF model offers significant improvements and may be an excellent alternative to existing option pricing models that are primarily stochastic in nature. [ABSTRACT FROM AUTHOR]

This work introduces a new stochastic volatility model with delay parameters in the volatility process, extending the Barndorff–Nielsen and Shephard model. It establishes an analytical expression for the log price characteristic function, which can be applied to price European options. Empirical analysis on S&P500 European call options shows that adding delay parameters reduces mean squared error. This is the first instance of providing an analytical formula for the log price characteristic function in a stochastic volatility model with multiple delay parameters. We also provide a Monte Carlo scheme that can be used to simulate the model. [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]

Since the early 21st century, within fuzzy mathematics, there has been a stream of research in the field of option pricing that introduces vagueness in the parameters governing the movement of the underlying asset price through fuzzy numbers (FNs). This approach is commonly known as fuzzy random option pricing (FROP). In discrete time, most contributions use the binomial groundwork with up-and-down moves proposed by Cox, Ross, and Rubinstein (CRR), which introduces epistemic uncertainty associated with volatility through FNs. Thus, the present work falls within this stream of literature and contributes to the literature in three ways. First, analytical developments allow for the introduction of uncertainty with intuitionistic fuzzy numbers (IFNs), which are a generalization of FNs. Therefore, we can introduce bipolar uncertainty in parameter modelling. Second, a methodology is proposed that allows for adjusting the volatility with which the option is valued through an IFN. This approach is based on the existing developments in the literature on adjusting statistical parameters with possibility distributions via historical data. Third, we introduce into the debate on fuzzy random binomial option pricing the analytical framework that should be used in modelling upwards and downwards moves. In this sense, binomial modelling is usually employed to value path-dependent options that cannot be directly evaluated with the Black–Scholes–Merton (BSM) model. Thus, one way to assess the suitability of binomial moves for valuing a particular option is to approximate the results of the BSM in a European option with the same characteristics as the option of interest. In this study, we compared the moves proposed by Renddleman and Bartter (RB) with CRR. We have observed that, depending on the moneyness degree of the option and, without a doubt, on options traded at the money, RB modelling offers greater convergence to BSM prices than does CRR modelling. [ABSTRACT FROM AUTHOR]

Since the early 1970s, the study of Black–Scholes (BS) partial differential equations (PDEs) under the Efficient Market Hypothesis (EMH) has been a subject of active research in financial engineering. It has now become obvious, even to casual observers, that the classical BS models derived under the EMH framework fail to account for a number of realistic price evolutions in real-time market data. An alternative approach to the EMH framework is the Fractal Market Hypothesis (FMH), which proposes better and clearer explanations of market behaviours during unfavourable market conditions. The FMH involves non-local derivatives and integral operators, as well as fractional stochastic processes, which provide better tools for explaining the dynamics of evolving market anomalies, something that classical BS models may fail to explain. In this work, using the FMH, we derive a time-fractional Black–Scholes partial differential equation (tfBS-PDE) and then transform it into a heat equation, which allows for ease of implementing a high-order numerical scheme for solving it. Furthermore, the stability and convergence properties of the numerical scheme are discussed, and overall techniques are applied to pricing European put option problems. [ABSTRACT FROM AUTHOR]

This paper studies equity basket options – i.e. multi-dimensional derivatives whose payoffs depend on the value of a weighted sum of the underlying stocks – and develops a new and innovative approach to ensure consistency between options on individual stocks and the index comprising them. Specifically, we show how to resolve a well-known problem that when individual constituent distributions of an equity index are inferred from the single-stock option markets and combined in a multi-dimensional local/stochastic volatility model, the resulting basket option prices will not generate a skew matching that of the options on the equity index corresponding to the basket. [ABSTRACT FROM AUTHOR]

In this paper, option pricing through introducing a novel hybrid method for solving time-fractional Black–Scholes equation is considered. The presented method is based on time and space discretization. Time discretization is according to a second order finite difference formula. Space discretization is done by a spectral method based on fractional order shifted Hahn functions (FOSHFs) and an operational process by defining fractional order Hahn operational matrices. Convergence and error analysis for FOSHFs approximation and also for the proposed method are discussed. For validating obtained theoretical results and demonstrating the accuracy, convergency and efficiency of the method, two numerical examples with the known exact solutions are considerd and compared to other methods. Furthermore, the presented method is used to price three different European options governed by a time-fractional Black–Scholes model: European call option, European put option and European double barrier knock-out call option. [ABSTRACT FROM AUTHOR]

In accordance with the theme of the Yuri Ijiri lectures, I focus on something foundational to accounting: the communication of uncertainty through accounting numbers. I do so in the context of providing information to investors about "the amount, timing, and uncertainty of future cash flows", an objective of accounting standard setters (with emphasis added). I outline accounting principles that convey uncertainty and discuss the implications for a financial statement analysis that extracts information about uncertainty. I also show how accounting-based valuation is modified to incorporate that information. Asset pricing in finance deals with risk and uses accounting numbers to do so. I explain how that endeavor might be improved by recognizing the accounting for uncertainty. That puts accounting and finance on the same platform. Finally, I address normative issues of accounting policy for conveying information about the uncertainty of future cash flows. [ABSTRACT FROM AUTHOR]

When trading in the call and put contracts of option chains, the portfolios of strikes must be selected. The trader must also decide whether to take long or short positions at the selected strikes. Dynamic strategies for making these decisions are discussed in this paper. On any day, the strategies estimate the drift and volatility parameters of the future probability distribution of the price of the underlying asset. From this distribution, the trader can further estimate the future expected profit and expected loss that may be experienced for any portfolio of strikes of the call and put contracts. Expected profit and expected loss are the reward and risk metrics of such portfolios. An optimal portfolio can then be selected by making the reward as high as possible under the risk tolerance set by the trader. Extensive back-testing applications to historical data of SPY option chains illustrate the effectiveness of these strategies, particularly when dealing with short-term expiry options and when acting as a seller of put and call options. [ABSTRACT FROM AUTHOR]

This study contributes to the discussion about a fair and balanced pension system with a collectively funded pension scheme or social security and a defined contribution pillar. With an invigorated risk approach using financial option positions, it considers the variance of socioeconomic interests of different society-earning cohorts. By that, it enables the assumption of un-uniformity in interests about the fair and sustainable pension design. Specifically, we claim that the alternative cost of hedging the ideal position to the counterparty position studies the implied risks and returns that participants are willing to absorb and hence may lead to a fair compromise when there are different interests. The novelty of the introduced method is mainly based on the variety of participants' risks and not on the utility function. Accordingly, we spare the discussion about the right shape of the utility function and the proper calibrations. [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]

This paper deals on the valuation of European call option price in a stochastic environment by employing three factors which are the stochastic model of the asset value, the stochastic interest rate and the transaction cost. We specify that our underlying asset and the stochastic interest rate, particularly Hull-White model, follows a fractional Brownian Motion governed by Hurst parameter H. We used the hedging and replicating technique to established the zero-coupon bond on the European option. Finally, we give a closed-form formula of the European call option price. [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]

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]

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]

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]

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]

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]

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]

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]

New product demand continuously fluctuates throughout the life of the product. As a result, markets typically experience high volatility. Most companies operate in highly competitive industries where the product volume supplied by the competitors significantly affects production plans. These conditions necessitate companies to be flexible and rapidly adapt to such volatility. In this study, we investigate the product introduction strategies under two microeconomic theories: real‐option valuation and game theory. Specifically, we develop a real‐option valuation framework with a flexible capacity based on two game‐theoretic models, namely, Stackelberg and Cournot, in a duopoly market where competitors have either perfect or imperfect information. Furthermore, we construct a lattice to discretize the demand evolution and adopt a regime‐switching approach to characterize the stochastic product lifetime. We conduct an extensive numerical study and compare net present values (NPVs) and optimal capacities obtained from the game‐theoretic models. Our results show that under perfect information, the Stackelberg competition generates more supply with lower prices and less total NPV than the Cournot competition. Moreover, we find that, compared to the fixed‐capacity system, the flexible capacity system increases the NPV in the Stackelberg game (by 5.5%) more than in the Cournot game (by 3.3%). We provide further results on the performance of the companies based on detailed sensitivity analysis for various model parameters. In particular, we observe that fixed and variable production and installation costs majorly impact capacity allocation decisions and profits. [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]

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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.)

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]