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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]

Cloud providers offer various purchasing options to enable users to tailor their costs according to their specific requirements, including on-demand, reserved instances, and spot instances. On-demand and spot instances satisfy short-term workloads, whereas reserved instances fulfill long-term instances. However, there are workloads that fall outside of either long-term or short-term categories. Consequently, there is a notable absence of services specifically tailored for medium-term workloads. On-demand services, while offering flexibility, often come with high costs. Spot instances, though cost-effective, carry the risk of termination. Reserved instances, while stable and less expensive, may have a remaining period that extends beyond the duration of users' tasks. This gap underscores the need for solutions that address the unique requirements and challenges associated with medium-term workloads in the cloud computing landscape. This paper introduces a new cloud broker that introduces IaaS services for medium-term workloads. On one hand, this broker strategically reserves resources from providers, and on the other hand, it interacts with users. Its interaction with users is twofold. It collects users' preferences regarding commitment term for medium-term workloads and then transforms the leased resources based on commitment term, aligning with the requirements of most users. To ensure profitability, the broker sells these services utilizing an auction algorithm. Hence, in this paper, an auction algorithm is introduced and developed, which treats cloud services as virtual assets and integrates the depreciation over time. The findings affirm the lack of services that fulfill medium workloads while ensuring the financial viabilty and profitability of the broker, given that the estimated return on investment (ROI) is acceptable. [ABSTRACT FROM AUTHOR]

Cloud providers offer various purchasing options to enable users to tailor their costs according to their specific requirements, including on-demand, reserved instances, and spot instances. On-demand and spot instances satisfy short-term workloads, whereas reserved instances fulfill long-term instances. However, there are workloads that fall outside of either long-term or short-term categories. Consequently, there is a notable absence of services specifically tailored for medium-term workloads. On-demand services, while offering flexibility, often come with high costs. Spot instances, though cost-effective, carry the risk of termination. Reserved instances, while stable and less expensive, may have a remaining period that extends beyond the duration of users’ tasks. This gap underscores the need for solutions that address the unique requirements and challenges associated with medium-term workloads in the cloud computing landscape. This paper introduces a new cloud broker that introduces IaaS services for medium-term workloads. On one hand, this broker strategically reserves resources from providers, and on the other hand, it interacts with users. Its interaction with users is twofold. It collects users’ preferences regarding commitment term for medium-term workloads and then transforms the leased resources based on commitment term, aligning with the requirements of most users. To ensure profitability, the broker sells these services utilizing an auction algorithm. Hence, in this paper, an auction algorithm is introduced and developed, which treats cloud services as virtual assets and integrates the depreciation over time. The findings affirm the lack of services that fulfill medium workloads while ensuring the financial viabilty and profitability of the broker, given that the estimated return on investment (ROI) is acceptable.

The Heston–Hull–White three-dimensional time-dependent partial differential equation (PDE) is one of the important models in mathematical finance, at which not only the volatility is modeled based on a stochastic process but also the rate of interest is assumed to follow a stochastic dynamic. Hence, an efficient method is derived in this paper based on the methodology of the localized radial basis function generated finite difference (RBF-FD) scheme. The proposed solver uses the RBF-FD approximations on graded meshes along all three spatial variables and a high order time-stepping scheme. Stability is also studied in detail to show under what conditions the proposed method is stable. Computational simulations are given to support the theoretical discussions. [ABSTRACT FROM AUTHOR]

Regional cross-border electricity trading is popular in price and cooperation. It is a reliable path to alleviate the shortage of power supply during rapid economic growth. As an important export commodity, the pricing options for hydropower directly relate to the cooperation intention of business parties. This study demonstrates the price formation methods and internal relationships of cascade hydropower stations in CBET. To simulate the decision-making of a bilateral forward contract, a bi-level optimization model was constructed, and the objectives of each layer represent the interests of both parties. The BOM was linearized with Karush-Kuhn-Tucker conditions and strong duality, and finally solved using mixed-integer linear programming. The prices of CHSs in southwestern China were calculated under different pricing options and the results were absorbed in an actual transaction case. Consequently, the complementarity between different exporting countries was verified. The most suitable pricing option for CBET was determined, that is the unified electricity price based on the marginal cost, to be $481~\textrm {CNY/MW}\cdot \textrm {h}$ , which is 20% to 60% higher than the thermal and photovoltaic from other countries. Furthermore, national policy support and economic subsidies are key guarantees for the sustainable development of CBET, which can reduce the discount electricity price to below that of thermal generation by 30%.

The Heston–Hull–White three-dimensional time-dependent partial differential equation (PDE) is one of the important models in mathematical finance, at which not only the volatility is modeled based on a stochastic process but also the rate of interest is assumed to follow a stochastic dynamic. Hence, an efficient method is derived in this paper based on the methodology of the localized radial basis function generated finite difference (RBF-FD) scheme. The proposed solver uses the RBF-FD approximations on graded meshes along all three spatial variables and a high order time-stepping scheme. Stability is also studied in detail to show under what conditions the proposed method is stable. Computational simulations are given to support the theoretical discussions.

The tariff landscape within Switzerland's public transport network is characterized by limited options: the flat rate (Generalabonnement), designed to accommodate frequent customers, and the pay-per-use model (Halbtax), tailored for those who use the network infrequently. However, there is a gap in provision for medium-frequency customers, who lack an intermediary tariff option. Our study employs a combination of conjoint analysis and market simulations to assess the potential appeal of a hypothetical novel three-part tariff structure, referred to as the bonus tariff. The paper first examines customers tariff selection, probing whether choices are influenced by biases favoring either the pay-per-use or flat-rate options. Further, we calculate the significance of various tariff attributes and identify sociodemographic variables predictive of tariff preference. Attributes such as the pre-pay credit and bonus levels exhibit the highest part-worth utilities. The analysis shows that the bonus tariff would capture a significant market share. A market simulation underscores the sensitivity of the business case to factors including bonus levels and the proportion of customers transitioning from flat-rate subscriptions. The overarching outcome suggests a positive impact on revenue with the introduction of the bonus tariff. The conclusion delves into the reasons for these findings and outlines implications for tariff management strategies. [ABSTRACT FROM AUTHOR]

The options pricing on financial assets represents a subject of great interest to academics and practitioners in the financial markets; it is also a phenomenon that has preoccupied specialists in financial and mathematics domains. The Black-Sholes model (1973) is the benchmark model of many models; this model provides us with a basic tool for the pricing option contracts traded in markets. Moreover, it was based on many assumptions that are the stability of volatility, the risk free rate, and the normal distribution. The main objective of the present study is the exhibition and the interpretation methods that are related to the assessment and pricing of options on financial stocks market through the comparison between the theoretical options prices under Black-Scholes model, Monte Carlo Simulation method, and the current option prices on market; in addition to the validity test of both models in order to predict the market prices by an empirical study for the period from 26 December 2013 to 08 May 2014, with daily data using R software and its packages. Finally, It was found that the Black-Sholes model does not perform when the volatility is higher in both periods 6 and 9 months, but for one year the B-S model proved its ability to predict the current prices with a positive relationship. Other findings highlighted the outperformance of the Monte Carlo Simulation Method to predict the current price only when the volatility is lower for both periods 6 and 9 months. [ABSTRACT FROM AUTHOR]

In this study, we consider some pricing currency options models, which are using the Brownian motion, the fractional Broanian motion and the mixed fractional Brownian motion. The partial differential equations for values of European currency options and some Greeks are obtained for all these models. In addition, in the fractional environment, that parameter H has huge effect on pricing options, the impact of the Hurst parameter H is presented. Besides, comparing the Greeks for three currency options models are illustrated by some figures. [ABSTRACT FROM AUTHOR]

This article covers the basics of the mathematical theory of pricing of options in financial markets; where we show that, it is possible to build a multi-period multinomial discrete model any time step Δt and any duration. The model describes the stochastic differential equations which includes the movements of parameters and the volatility; which in general, is also a very random processes folded nature. [ABSTRACT FROM AUTHOR]

Abstract: In this work, an analytic pricing formula for floating strike lookback options under Heston’s stochastic volatility model is derived by means of the homotopy analysis method. The fixed strike lookback options can then be priced on the basis of the results of floating strike and the put–call parity relation for lookback options. [Copyright &y& Elsevier]

Abstract: Average pricing is one of the main ingredients in determining the payoff associated with an Asian option. Since its beginnings in 1980 much has been written on the European-style Asian, especially with a fixed strike. In this article, we extend the work of Zhu to this exotic option. We present an analytic formula pricing an American-style Asian option of floating type. We also extend a symmetry result established by Henderson and Wojakowski. [Copyright &y& Elsevier]

High technology product markets seem to exhibit unique characteristics that impact both the marketer and the customer. The products seem to pose unique marketing challenges and in there has been considerable academic work suggesting different approaches in marketing elements such as segmentation, targeting, positioning, the four Ps, customer relationship management, branding and other strategies. Faster product introductions, strategic alliances, bundle pricing and integrated marketing communications are some of the strategies deemed suitable for high tech products. In addition, a different approach altogether towards strategy making has also been suggested. [ABSTRACT FROM AUTHOR]

The article analyzes three models of stochastic volatility. Investigation of influence of stochastic volatility for pricing options traded in the Vilnius bank is done.