310 research outputs found

    Indifference Pricing and Hedging in a Multiple-Priors Model with Trading Constraints

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    This paper considers utility indifference valuation of derivatives under model uncertainty and trading constraints, where the utility is formulated as an additive stochastic differential utility of both intertemporal consumption and terminal wealth, and the uncertain prospects are ranked according to a multiple-priors model of Chen and Epstein (2002). The price is determined by two optimal stochastic control problems (mixed with optimal stopping time in the case of American option) of forward-backward stochastic differential equations. By means of backward stochastic differential equation and partial differential equation methods, we show that both bid and ask prices are closely related to the Black-Scholes risk-neutral price with modified dividend rates. The two prices will actually coincide with each other if there is no trading constraint or the model uncertainty disappears. Finally, two applications to European option and American option are discussed.Comment: 28 pages in Science China Mathematics, 201

    Reception of the Goldblatt’s Translation of Red Sorghum from the Perspective of Reception Aesthetics for Overseas Readers

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    Literary translation must meet readers’ aesthetic needs and acceptance psychology for literary works. At the same time, the quality of translation should not only be judged by the source text, but also by the acceptance of readers. Reception aesthetics is a theoretical system that takes readers as the center to study the effect of text acceptance. This paper selects Red Sorghum translated by Howard Goldblatt as the research object, collects readers’ comments on this translation from foreign book review websites (www.goodreads.com), and uses the theory of reception aesthetics to analyze the acceptance of this translation among English readers, aiming to provide more ideas for the translation of Chinese literary works

    Dynkin Game of Convertible Bonds and Their Optimal Strategy

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    This paper studies the valuation and optimal strategy of convertible bonds as a Dynkin game by using the reflected backward stochastic differential equation method and the variational inequality method. We first reduce such a Dynkin game to an optimal stopping time problem with state constraint, and then in a Markovian setting, we investigate the optimal strategy by analyzing the properties of the corresponding free boundary, including its position, asymptotics, monotonicity and regularity. We identify situations when call precedes conversion, and vice versa. Moreover, we show that the irregular payoff results in the possibly non-monotonic conversion boundary. Surprisingly, the price of the convertible bond is not necessarily monotonic in time: it may even increase when time approaches maturity.Comment: 28 pages, 9 figures in Journal of Mathematical Analysis and Application, 201

    Conditions for super-adiabatic droplet growth after entrainment mixing

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    Cloud droplet response to entrainment and mixing between a cloud and its environment is considered, accounting for subsequent droplet growth during adiabatic ascent following a mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction to be predicted from the mixing fraction and from the temperature and humidity for both the cloud and environment. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: at the critical height the cloud droplet radius is the same for both mixed and unmixed parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the super-adiabatic growth region. Analytical results are confirmed with a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixed parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius for polydisperse size distributions. The findings have implications for the origin of large cloud droplets that may contribute to onset of collision-coalescence in warm clouds

    dMAPAR-HMM: Reforming Traffic Model for Improving Performance Bound with Stochastic Network Calculus

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    A popular branch of stochastic network calculus (SNC) utilizes moment-generating functions (MGFs) to characterize arrivals and services, which enables end-to-end performance analysis. However, existing traffic models for SNC cannot effectively represent the complicated nature of real-world network traffic such as dramatic burstiness. To conquer this challenge, we propose an adaptive spatial-temporal traffic model: dMAPAR-HMM. Specifically, we model the temporal on-off switching process as a dual Markovian arrival process (dMAP) and the arrivals during the on phases as an autoregressive hidden Markov model (AR-HMM). The dMAPAR-HMM model fits in with the MGF-SNC analysis framework, unifies various state-of-the-art arrival models, and matches real-world data more closely. We perform extensive experiments with real-world traces under different network topologies and utilization levels. Experimental results show that dMAPAR-HMM significantly outperforms prevailing models in MGF-SNC

    Over-the-air Federated Policy Gradient

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    In recent years, over-the-air aggregation has been widely considered in large-scale distributed learning, optimization, and sensing. In this paper, we propose the over-the-air federated policy gradient algorithm, where all agents simultaneously broadcast an analog signal carrying local information to a common wireless channel, and a central controller uses the received aggregated waveform to update the policy parameters. We investigate the effect of noise and channel distortion on the convergence of the proposed algorithm, and establish the complexities of communication and sampling for finding an ϵ\epsilon-approximate stationary point. Finally, we present some simulation results to show the effectiveness of the algorithm

    Study on Resource Configuration on Cloud Manufacturing

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    The purpose of manufacturing is to realize the requirement of customer. In manufacturing process of cloud system, there exist a lot of resource services which have similar functional characteristics to realize the requirement. It makes the manufacturing process more diverse. To develop the quality and reduce cost, a resource configuration model on cloud-manufacturing platform is put forward in this paper. According to the generalized six-point location principle, a growth design from the requirement of customers to entities with geometric constraints is proposed. By the requirement growing up to product, a configuration process is used to match the entities with the instances which the resources in the database could supply. Different from most existing studies, this paper studies the tolerance design with multiple candidate resource suppliers on cloud manufacturing to make the market play a two-level game considering the benefit of customers and the profit of resources to give an optimal result. A numerical case study is used to illustrate the proposed model and configuration process. The performance and advantage of the proposed method are discussed at the end

    LQG Control Over SWIPT-enabled Wireless Communication Network

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    In this paper, we consider using simultaneous wireless information and power transfer (SWIPT) to recharge the sensor in the LQG control, which provides a new approach to prolonging the network lifetime. We analyze the stability of the proposed system model and show that there exist two critical values for the power splitting ratio {\alpha}. Then, we propose an optimization problem to derive the optimal value of {\alpha}. This problem is non-convex but its numerical solution can be derived by our proposed algorithm efficiently. Moreover, we provide the feasible condition of the proposed optimization problem. Finally, simulation results are presented to verify and illustrate the main theoretical results

    Compact Lattice Gadget and Its Applications to Hash-and-Sign Signatures

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    Lattice gadgets and the associated algorithms are the essential building blocks of lattice-based cryptography. In the past decade, they have been applied to build versatile and powerful cryptosystems. However, the practical optimizations and designs of gadget-based schemes generally lag their theoretical constructions. For example, the gadget-based signatures have elegant design and capability of extending to more advanced primitives, but they are far less efficient than other lattice-based signatures. This work aims to improve the practicality of gadget-based cryptosystems, with a focus on hash-and-sign signatures. To this end, we develop a compact gadget framework in which the used gadget is a square matrix instead of the short and fat one used in previous constructions. To work with this compact gadget, we devise a specialized gadget sampler, called semi-random sampler, to compute the approximate preimage. It first deterministically computes the error and then randomly samples the preimage. We show that for uniformly random targets, the preimage and error distributions are simulatable without knowing the trapdoor. This ensures the security of the signature applications. Compared to the Gaussian-distributed errors in previous algorithms, the deterministic errors have a smaller size, which lead to a substantial gain in security and enables a practically working instantiation. As the applications, we present two practically efficient gadget-based signature schemes based on NTRU and Ring-LWE respectively. The NTRU-based scheme offers comparable efficiency to Falcon and Mitaka and a simple implementation without the need of generating the NTRU trapdoor. The LWE-based scheme also achieves a desirable overall performance. It not only greatly outperforms the state-of-the-art LWE-based hash-and-sign signatures, but also has an even smaller size than the LWE-based Fiat-Shamir signature scheme Dilithium. These results fill the long-term gap in practical gadget-based signatures
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