国际油价冲击与中国的经济增长——基于非对称关系视角的分析

本文基于季度数据，引入非对称协整模型，考察国际油价与中国经济增长的动态关系，并鉴于油价波动对不发达经济体可能的冲击，还测度了油价的不确定性并探析其对经济增长的影响，结果表明：（1）从短期来看，国际油价变化是国内经济增长的单向Granger原因，“中国因素”对全球油价变化的影响尚不明显；（2）从长期来看，国际油价和经济增长具有非对称协整关系，油价上涨对经济的影响明显大于油价下跌所产生的效应；（3）国际石油市场存在正反馈交易行为，导致油价波动在油价上涨时表现更加明显。油价不确定性在短期内对经济增长存在负面影响，长期中则不会显著影响经济增长。以上结果意味着必须高度重视石油安全问题，加强油价波动预警与风险管理系统。     

Oil and Gas Exploration Valuation and the Value of Waiting

The timing flexibility of investments in oil and gas assets can potentially add value. In this article, we examine the value of waiting in exploration projects and propose a real option–based valuation method using least-squares Monte Carlo simulation. We show that the dynamics of the oil and gas prices have a large impact on the value of the option to wait, especially for projects with long lead times and durations. The uncertainty in the forward price curve is modeled using a two-factor stochastic price process. The article also presents the valuation method in the form of MATLAB functions and routines that can be used as an efficient test and analysis platform using the industry-standard input formats.     

Optimal Pricing and Order-Up-To S Inventory Policy with Expected Utility of the Present Value Criterion

The article determines pricing and order-up-to level S inventory decisions over an infinite planning horizon from the point of view of a risk-averse decision maker. The demand is assumed to be stochastic but influenced by the selling price which is a decision variable. Shortages are allowed and backordered partially. We calculate the present value of the cash flow over the entire planning horizon and incorporate the notion of risk aversion into the model using a concave utility function. We numerically demonstrate the model and investigate the impact of different model-parameters on the optimal decisions. It is observed that the optimal selling price for a risk-averse decision maker is not less than the optimal selling price of a risk-neutral decision maker while the optimal order level for the risk-averse decision maker is always less than that of the risk-neutral decision maker.     

The Role of Uncertainty in Investment: An Examination of Competing Investment Models Using Commercial Real Estate Data

Neoclassical investment decision criteria suggest that only the systematic component of total risk affects the rate of investment, as channeled through the built-asset price. Alternatively, option-based investment models suggest a direct role for total uncertainty in investment decisionmaking. To sort out uncertainty's role in investment, we specify and empirically estimate a structural model of asset-market equilibrium. Commercial real estate time-series data with two distinct measures of asset price and uncertainty are used to assess the competing investment models. Empirical results generally favor predictions of the option-based model and hence suggest that irreversibility and delay are important considerations to investors. Our findings also have implications for macroeconomic policy and for forecasts of cyclical investment activity.     

Impact of demand uncertainty on supply chain cooperation of single-period products

Cooperation is an approach of improving competitive advantages of a supply chain. A two-echelon supply chain consisting of a manufacturer and a retailer for a single-period product is studied, and retail-market demand uncertainty is described by coefficient of variation. We develop a cooperation mechanism to address the cooperation and its implementation between the manufacturer and the retailer, two market situations are considered: (i) the wholesale price and the order quantity are decision variables, (ii) the wholesale and the retail prices as well as the order quantity are decision variables. In both market situations, our research shows that: (1) the cooperation mechanism can improve the overall channel profits and the supply chain members’ allocated profits, (2) the described cooperation is conditional on retail-market demand uncertainty: it can be implemented if, and only if, the fluctuation of retail-market demand is relatively small and coefficient of variation of retail-market demand does not exceed an upper bound. Impacts of retail-market demand uncertainty on wholesale price, order quantity and/or retail price have also been investigated through analytical and numerical analyses. Although our research is based on the assumption that the manufacturer dominates the supply chain in the non-cooperative situation, which is not the case for most retailer-driven supply chains, this research is still significant on providing guidelines for practitioners in current China mid-level car market that is similar to situations described in the paper.     

A Robust Optimization Approach to Capital Rationing and Capital Budgeting

We study the pure capital rationing and the horizon capital budgeting problems using a robust optimization framework. The models and the methodology we propose take into account the uncertainty of the input data. The uncertainty of the cash flows is modeled as a range of values that is allowed for each uncertain data. Unlike stochastic models, this approach does not make assumptions on the probability distribution of uncertain data. Moreover, this approach is highly tractable, easy to implement, and provides insights into portfolio selection problems. An attractive point of the model is that the decision maker can set the value of the parameters that control the robustness of the optimal solution, in order to balance the trade-off between protection level and performance. We illustrate our models with examples that show promising results. We also provide new duality and KKT optimality conditions.     

中国上海燃料油期货定价模型研究

采用协整理论及基于VAR的Grange因果关系检验与冲击反应函数方法对中国上海期货交易所燃料油期货价格作建模分析。单位根检验显示，选取的样本序列均为I（1）。Granger因果关系检验显示：美原油期货价格，新加坡180燃料油现货价格变量为燃料油期价的Granger原因；上海燃料油期货价格是黄埔现货价格的单向的Granger原因，期货价格对现货价格具有发现作用。最终作出的长期协整方程显示：美原油期货价格，新加坡180燃料油现货价格、欧元汇率与上海燃料油现货价构成长期显著的均衡关系。美原油期货价格对沪燃料油期价的弹性为0．85；新加坡180燃料油现货价格对沪燃料油期价的弹性为0．78；欧元汇率对沪燃料油期价的弹性为1．04。从最终建立动态模型来看，模型有较好的拟合及预测精度。因此，该模型对沪燃料油期价风险控制具有较好的参考作用。     

Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach

The conventional wisdom that housing prices are the present value of future rents ignores the fact that unlike dividends on stocks, rent is not discretionary. Housing price uncertainty can affect household property investments, which in turn affect rent. By extending the theory of investment under uncertainty, we model the renter's decision to buy a house and the landlord's decision to sell as the exercising of real options of waiting and examine real options effects on rent. Using data from Hong Kong and mainland China, we find a significant effect of housing price on rent and draw important policy implications.     

Using mean-Gini and stochastic dominance to choose project portfolios with parameter uncertainty

Although a variety of models have been studied for project portfolio selection, many organizations still struggle to choose a potentially diverse range of projects while ensuring the most beneficial results. The use of the mean-Gini framework and stochastic dominance to select portfolios of research and development (R&D) projects has been gaining attention in the literature despite the fact that such approaches do not consider uncertainty regarding the projects’ parameters. This article discusses, with relation to project portfolio selection through a mean-Gini approach and stochastic dominance, the impact of uncertainty on project parameters. In the process, Monte Carlo simulation is considered in evaluating the impact of parametric uncertainty on project selection. The results show that the influence of uncertainty is significant enough to mislead managers. A more robust selection policy using the mean-Gini approach and Monte Carlo simulation is proposed.     

Financial and operational decisions in the electricity sector: Contract portfolio optimization with the conditional value-at-risk criterion

The restructuring of electricity markets around the world have caused increased volatility and uncertainty of the price power. As a result, providers of power now face increased uncertainty and risk in the operational and financial decisions related to procurement. Providers must seek optimal ways to deliver the required volume of power to retailers and end users while managing risk. We consider a mixed-integer programming model for a power providing agent that jointly considers the problem of selecting custom electricity contracts and finding the optimal procurement strategy of meeting contract obligations under spot price uncertainty. A two-stage stochastic integer programming (SIP) model with a conditional value-at-risk (CVaR) constraint to incorporate risk aversion is developed. Computational results are presented that demonstrates the CVaR approach and the results are compared with a corresponding expected cost minimization approach. The SIP model with CVaR will allow acceptance of contracts at lower prices compared to an approach based on a corresponding risk-neutral model as a hedge against uncertainty and mis-specified arbitrage.     

Strategic NPV: Real Options and Strategic Games under Different Information Structures

Research summary : Among the most difficult firm strategic choices is the trade‐off between making a long‐term commitment or holding off on investment in the face of uncertainty. To operationalize strategic management theory under demand, technological and competitive uncertainty, we develop a Strategic Net Present Value (NPV) framework that integrates real options and game theory to quantify value components and interactions at the interface between NPV, real options, and strategic games. Our approach results in new propositions clarifying the way learning‐experience conditions, technological uncertainty, and proprietary information interact to tilt the balance in the interplay between wait‐and‐see flexibility and strategic commitment. As such, Strategic NPV adds to our understanding of the conditions where NPV, real options, or strategic thinking are more relevant. Managerial summary : This study develops and elucidates implementation of a new valuation construct, “Strategic Net Present Value (NPV),” that integrates real options and game theory to more accurately portray strategic decisions underlying management theory. Among the most difficult firm strategic choices in capital intensive industries, such as energy, mining, chip manufacturing, and infrastructure development, is the trade‐off between making a long‐term commitment or holding off on investment in the face of demand, technological, and competitive uncertainties. The study provides new insights on the way various conditions, such as learning‐experience effects, technological uncertainty, and proprietary information, interact to tilt the balance in the interplay between commitment and wait‐and‐see flexibility. As such, Strategic NPV adds to our understanding of when NPV, real options, or strategic thinking matter more critically for decision making. Copyright © 2017 John Wiley & Sons, Ltd.     

Optimal pricing and quality choice of a monopolist under Knightian uncertainty

This paper analyzes a simple vertical product differentiation model with demand uncertainty and derives a risk neutral monopolist's optimal market entry timing, her optimal pricing and optimal quality choice by incorporating Knightian uncertainty, irreversibility, and flexibility in quality-enhancing investment into a continuous-time stochastic model. It is shown that an increase in Knightian uncertainty induces decreases in the optimal price, the optimal quality, and the value of undertaking the quality-enhancing investment by the monopolist. The social optimal entry timing, pricing and quality are also analyzed.     

Optimal exploration investments under price and geological‐technical uncertainty: a real options model

This article develops a real options model for valuing natural resource exploration investments (e.g. oil or copper) when there is joint price and geological‐technical uncertainty. After a successful several‐stage exploration phase, there is a development investment and an extraction phase. All phases are optimized contingent on price and geological‐technical uncertainty.
Several real options are considered. There are flexible investment schedules for all exploration stages and a timing option for the development investment. Once the mine is developed, there are closure, opening and abandonment options for the extraction phase. Our model maintains a relatively simple valuation structure by collapsing price and geological‐technical uncertainty into a one‐factor model.
We apply the model to a copper exploration prospect and find that a significant fraction of total project value is due to the operational, development and exploration options available to project managers.     

Incorporating uncertainty into a supplier selection problem

Supplier selection is an important strategic supply chain design decision. Incorporating uncertainty of demand and supplier capacity into the optimization model results in a robust selection of suppliers. A two-stage stochastic programming (SP) model and a chance-constrained programming (CCP) model are developed to determine a minimal set of suppliers and optimal order quantities with consideration of business volume discounts. Both models include several objectives and strive to balance a small number of suppliers with the risk of not being able to meet demand. The SP model is scenario-based and uses penalty coefficients whereas the CCP model assumes a probability distribution and constrains the probability of not meeting demand. Both formulations improve on a deterministic mixed integer linear program and give the decision maker a more complete picture of tradeoffs between cost, system reliability and other factors. We present Pareto-optimal solutions for a sample problem to demonstrate the benefits of the SP and CCP models. In order to describe the tradeoffs between costs and risks in an analytical form, we use multi-parametric programming techniques to more completely analyze the alternative Pareto-optimal supplier selection solutions in the CCP model. This analysis gives insights into the robustness of the solutions with respect to number of suppliers, costs and probability of not meeting demand.     

THE IMPACT OF POLITICAL RISK ON THE FOREIGN DIRECT INVESTMENT DECISION: A CAPITAL BUDGETING ANALYSIS

Using a capital budgeting framework, we examine the impact of political risk on the foreign direct investment decision. Political risk may alter operating cash flows via discriminatory regulations as well as the investment via expropriation. We model the impact of political operating costs and expropriation costs on the NPV of a project under the assumption that the parameters that affect the NPV are constant over the life of the project. Next, we provide an illustration for the case in which the relevant parameters are variable over the life of the project. The paper concludes with an example of political risk in the 1990s, the case of Black Sea Energy Ltd.'s investment in Russia.     

开放条件下中国货币政策对国际石油价格的影响——基于SVAR模型的实证研究

本文先引入IS-LM-BP模型和AD-AS模型说明中国货币政策因素通过影响石油市场的供需,从而影响石油价格。再采用SVAR模型、脉冲响应函数和方差分解,选择国际石油价格、中国工业增加值、狭义货币供应量、广义货币供应量和利率的月度指标对2005年7月～2015年5月国际油价波动的中国货币政策因素进行实证分析。研究发现：五变量间存在均衡关系,同时中国经济发展对油价的影响程度和时效性最大,其次是货币供应量,M1在短期内对油价的影响比M2显著,利率的影响贡献相对较小。在此结论的基础上,结合中国开放度、石油供需市场、供给侧改革等,提出相关政策建议。     

回收数量受价格和随机因素影响的定价模型

假设在再制造闭环供应链中,集中决策者、第三方和制造商分别从最终客户那里回收废旧品,其回收数量受回收价格和随机因素影响,制造商对获得的旧部件进行再制造,如果旧部件不能满足生产需求,制造商将从新部件供应商那里以高价格采购新部件来补充短缺。本文按照废旧品回收的供应链成员不同,建立了3个定价决策模型,证明了每个模型最优解的存在性和唯一性,然后在特殊情形下进一步求得各模型最优解的解析式,最后用具体算例对模型进行了验证。     

A Multivariate Commodity Analysis with Time-Dependent Volatility—Evidence from the German Energy Market

In recent years commodity markets (in particular electricity, coal, and emissions) encountered extreme price movements and phases of high price volatility. Utility companies are naturally exposed to these kinds of market movements and thus have to set-up an appropriate risk management system. We show that the nonstationary behavior of recent energy prices can be captured by time-dependent (and possibly stochastic) volatility models. We compare their statistical performance and their impact on risk management applications by calculating risk metrics such as value-at-risk. Based on a comprehensive backtesting study we conclude that our suggested models outperform stationary models in most cases and therefore should be considered superior for risk management applications.     

Bewertung und Steuerung von Gasspeichern bzw. Gasspeicherscheiben

In this paper you find a brief introduction to the German gas market as well as a draft of the resulting storage requirements in Germany. In the following different storage usages are looked into from an economical perspective. Additionally the presented evaluating methods in this paper are specified. This paper then introduces stochastic optimization methods which give the possibility to assess the storage against the spot price as well as against to the whole forward curve. For this models to evaluate the market price are illustrated and calibrated on the basis of empirical data.After this a sample storage slice is rated with the Least-Square-Monte-Carlo method based on a stochastic multi factor spot price model. Then the hedging evaluation against the whole forward curve is presented. Concluding you find a comparison of the two methods.