浅谈煤制甲醇项目的煤气化技术选择

石油是一种不可再生资源,必须要寻求新能源的制造方法,其中,甲醇的大规模生产也受到了各个国家有关部门的高度重视。本文主要从原料、产品与投资方面几个方面对多喷嘴对置式水煤浆气化技术、Shell技术、BGL煤熔渣气化工艺进行分析,得出最优的生产技术。     

基于量子三叉树的量子Black-Scholes期权定价

将量子概率引入到期权定价是最近几年一个新的研究趋势,也称为量子金融.为了期权定价更方便,文章建立了量子三叉树模型,同时利用量子概率建立了连续量子Black-Scholes(B-S)模型。实例应用和Matlab期权敏感性分析都验证了量子B-S优于经典B-S,从而为连续期权定价提供量子决策的途径。     

Is it still economic to build a new coal-fired power plant in the U.S.? A real option analysis

In the U.S., virtually no new coal-fired power plants have been built in recent years. Both industry experts and academics seem to believe that no rational firm will build a new coal-fired plant. Will such a trend continue in the future? To provide insights into this question, we investigate the optimal decision of an electricity company with an irreversible and deferrable opportunity to build either a new coal-fired or natural gas-fired power plant as its new base-load resource. According to our real option analysis, the optimal decision depends on the location. In the case of the eastern U.S., it is optimal to choose a natural gas plant if a firm is given a choice among a new natural gas plant, a new coal plant and deferring the investment. However, contrary to the common sentiment in the industry and academia, building a new coal plant in the western U.S. is still more economical than building a new natural gas plant in the absence of emission pricing. Furthermore, introducing carbon pricing to western U.S. states, as California did, can substantially increase the probability that a firm will optimally choose a natural gas plant over a coal plant.     

Test for the real option in consumer behavior

Consumers become indecisive when facing too many choices. Economic analysis suggests that when a decision involves uncertain outcome, can be delayed and is irreversible, there will be a real option in the cost–benefit analysis. For example, the option to keep alive a consumer's purchasing decision has a significant value. It allows the consumer to take advantage of any future advantageous deals while avoiding the bad choices. This renders the consumer more hesitant. When a consumer decides to exercise his buying decision, he demands a compensation for the loss of this option. Hence, the benefits of a purchase must be over and above its costs by a wide margin (the option value). Data from a survey at a Turkish university on hypothetical purchase decisions confirmed the existence of this real option. We conclude with marketing policy recommendations and future research directions. Connection to the Prospect Theory is briefly explored.Note: Although the 3rd person singular pronoun he/his was used throughout to describe the consumer, he was intended to be gender-neutral.     

不完全市场下的期权定价理论综述

由于B-S定价公式是在完全市场条件假设下推导出来的,这与现实存在很大的出路,因此后来的学者就针对市场条件状况,研究了不同市场条件下的期权定价,其中以不完全市场条件下的期权定价为主,这显然与事实更加吻合。不完全市场主要可以分为带交易费用的期权市场、存有违约风险的期权市场以及信息不完全的期权市场。文章在此基础上,分析总结了在这个市场假设条件下的研究现状,并给出了未来值得深入研究的方向:主要是进一步放松B-S定价模型的假设条件,引入更多的现实因素,深入研究不同市场状况下的期权定价问题。     

Superhedging under ratio constraint

We consider superhedging of contingent claims under ratio constraint. It has been widely recognized that the minimum cost of superhedging a contingent claim with certain portfolio constraints is equal to the price of a claim with appropriately modified payoff but without constraints. In terms of the backward stochastic differential equation (BSDE) and the variational inequality equation approach, we revisit this result and provide two counterexamples.     

基于福州市降水量数据研究降水期权定价

为应对干旱、洪涝等降水事件给相关经济主体带来的风险,基于1953年1月至2016年12月福州市月均累积降水量数据,运用威尔克斯法对降水量进行建模,利用蒙特卡罗模法对降水期权进行定价从而得到降水期权价值,并提出发展我国降水期权的政策建议。     

Decision-making in incomplete markets with ambiguity—a case study of a gas field acquisition

We apply utility indifference pricing to solve a contingent claim problem, valuing a connected pair of gas fields where the underlying process is not standard Geometric Brownian Motion and the assumption of complete markets is not fulfilled. First, empirical data are often characterized by time-varying volatility and fat tails; therefore, we use Gaussian generalized autoregressive score (GAS) and GARCH models, extending them to Student’s t-GARCH and t-GAS. Second, an important risk (reservoir size) is not hedgeable. As a result, markets are incomplete which makes preference free pricing impossible and thus standard option pricing methodology inapplicable. Therefore, we parametrize the investor’s risk preference and use utility indifference pricing techniques. We use Least Squares Monte Carlo simulations as a dimension reduction technique in solving the resulting stochastic dynamic programming problems. Moreover, an investor often only has an approximate idea of the true probabilistic model underlying variables, making model ambiguity a relevant problem. We show empirically how model ambiguity affects project values, and importantly, how option values change as model ambiguity gets resolved in later phases of the projects. We show that traditional valuation approaches will consistently underestimate the value of project flexibility and in general lead to overly conservative investment decisions in the presence of time-dependent stochastic structures.     

Too Good to be True? An Analysis of the Options Market's Reactions to Earnings Releases

Using option implied risk neutral return distributions before and after earnings announcements, we study the option market's reaction to extreme events over earnings announcements. While earnings announcements generally reduce short‐term uncertainty about the stock price, very good news does not reduce uncertainty and slightly bad news actually increases uncertainty. We also find that left tail probabilities decrease over earnings releases while right tail probabilities increase. We interpret these findings as evidence of maintained investor expectations that very good news is generally not released during earnings announcements, combined with skepticism in the form of lingering uncertainty at the release of such very good news.     

Reserves and cash flows under stochastic retirement

Uncertain time of retirement and uncertain structure of retirement benefits are risk factors for life insurance companies. Nevertheless, classical life insurance models assume these are deterministic. In this paper, we include the risk from stochastic time of retirement and stochastic benefit structure in a classical finite-state Markov model for a life insurance contract. We include discontinuities in the distribution of the retirement time. First, we derive formulas for appropriate scaling of the benefits according to the time of retirement and discuss the link between the scaling and the guarantees provided. Stochastic retirement creates a need to rethink the construction of disability products for high ages and ways to handle this are discussed. We show how to calculate market reserves and how to use modified transition probabilities to calculate expected cash flows without significantly more complexity than in the traditional model. At last, we demonstrate the impact of stochastic retirement on market reserves and expected cash flow in numerical examples.