Exposure-Based Cash-Flow-at-Risk for Value-Creating Risk Management under Macroeconomic Uncertainty

A strategically minded CFO will realize that strategic corporate risk management is about finding the right balance between risk prevention and proactive value generation. Efficient risk and performance management requires adequate assessment of risk and risk exposures on the one hand and performance on the other. Properly designed, a risk measure should provide information on to what extend the firm's performance is at risk, what is causing that risk, the relative importance of non-value-adding and value-adding risk, and the possibilities to use risk management to reduce total risk. In this chapter, we present an approach – exposure-based cash-flow-at-risk – to calculating a firm's downside risk conditional on the firm's exposure to non-value-adding macroeconomic and market risk and to analyzing corporate performance adjusted for the impact of non-value-adding risk.Cash-flow-at risk; Value at risk; Risk management; Value creation; Total risk

THE FAILURE OF MARKETABLE PERMIT SYSTEMS AND UNCERTAINTY OF ENVIRONMENTAL POLICY: A SWITCHING REGIME MODEL APPLIED TO THE DUTCH PHOSPHATE QUOTA PROGRAM

A well-known feature of pollution control with tradable quota rights is that the benefits to ownership will capitalize into prices of the quota. Quota present a unique opportunity to examine the effect of risks introduced by governmental programs because all the return to quota is dependent upon these programs. The uncertainty of future regulatory action results from the probability that the stream of incomes could be reduced (portfolio risk) by policy variation or stopped (default risk) by a substantial switch or shock in policy regime. Eliminating the quota program is the extreme case of default risk, as it would terminate the quota benefits. The paper concentrates on the paradox that environmental regulation can provoke economic and environmental inefficiencies because of policy uncertainty. The theory on investment under uncertainty argues that when future returns are uncertain, an opportunity to wait and see has some (quasi) option value. Under uncertainty, investments and disinvestments will take place at respectively higher and lower levels of returns creating an inaction interval. This interval means that returns to quota can vary over a wide range before trade takes place and offers a new, theoretical explanation for the failure of marketable permit systems. The objectives of this paper are threefold. First, the option value theory is employed to forge a natural connection between political uncertainty and quota price volatility. Second, based on the option value theory, a switching regime model is developed for investing and disinvesting in quota. Third, the empirical evidence for the Dutch Phosphate Quota Program indicates that policy risks led to asset fixity. Consequently, the market of tradable phosphate quota was not effective with major negative implications for both economic and environmental efficiency.switching regime, option theory, policy risk, asset fixity, phosphate quota, pork production., Environmental Economics and Policy, Risk and Uncertainty,

Unemployment with Observable Aggregate Shocks

Consider an economy subject to two kinds of shocks: (a) an observable shock to the relative demand for final goods which causes dispersion in relative prices, and (b) shocks, unobservable by workers, to the technology for transforming intermediate goods into final goods. A worker in a particular intermediate goods industry knows that the unobserved price of his output is determined by (1) the technological shock that determines which final goods industry uses his output intensively and (2) the price of the final good that uses his output intensively. When there is very little relative price dispersion among final goods, then it doesn't matter which final goods industry uses the worker's output. Thus the technological shock is of very little importance in creating uncertainty about the worker's marginal product when there is little dispersion of relative prices. Hence an increase in the dispersion of relative prices amplifies the effect of technological uncertainty on a worker's marginal value product. We consider a model of optimal labor contracts in a situation where the workers have less information than the firm about their marginal value product. A relative price shock of the type described above increases the uncertainty which workers have about their marginal value product. We show that with an optimal asymmetric information employment contract the industries which are adversely affected by the relative price shock will contract more than they would under complete information (i.e., where workers could observe their marginal value product). On the other hand the industry which is favorably affected by the relative price shock will - not expand by more than would be the case under complete information. Hence an observed relative demand shock, which would leave aggregate employment unchanged under complete information, will cause aggregate employment to fall under asymmetric information about the technological shock.

Value Uncertainty and Buyer Contracting:Evidence from Online Labor Markets

Online labor markets become increasingly important in creating jobs for millions of online freelancers around the globe. However, 60% of projects fail to reach to a contract, indicating a waste of time and effort for both buyers and freelancers. Given the fact that a buyer is often uncertain about the price (common value) of a project, this paper empirically examines how this uncertainty on common value—measured as bids price dispersion--affects buyer’s contract decisions. We find bids price dispersion has a negative effect on buyer’s contract decisions. And this effect becomes smaller as a project receives more bids. The paper contributes to online labor market literature by focusing on buyer’s uncertainty over common value and proposing the importance of bids price dispersion in buyers’ contract decisions. Managerial implications for the platform and freelancers’ bidding strategies under common value uncertainty are discussed

Stochastic optimisation-based valuation of smart grid options under firm DG contracts

Under the current EU legislation, Distribution Network Operators (DNOs) are expected to provide firm connections to new DG, whose penetration is set to increase worldwide creating the need for significant investments to enhance network capacity. However, the uncertainty around the magnitude, location and timing of future DG capacity renders planners unable to accurately determine in advance where network violations may occur. Hence, conventional network reinforcements run the risk of asset stranding, leading to increased integration costs. A novel stochastic planning model is proposed that includes generalized formulations for investment in conventional and smart grid assets such as Demand-Side Response (DSR), Coordinated Voltage Control (CVC) and Soft Open Point (SOP) allowing the quantification of their option value. We also show that deterministic planning approaches may underestimate or completely ignore smart technologies

How Do Real Options Concepts Fit in Agile Requirements Engineering?

Agile requirements engineering is driven by creating business value for the client and heavily involves the client in decision-making under uncertainty. Real option thinking seems to be suitable in supporting the client’s decision making process at inter-iteration time. This paper investigates the fit between real option thinking and agile requirements engineering. We first look into previously published experiences in the agile software engineering literature to identify (i) ‘experience clusters’ suggesting the ways in which real option concepts fit into the agile requirements process and (ii) ‘experience gaps’ and under-researched agile requirements decision-making topics which require further empirical studies. Furthermore, we conducted a cross-case study in eight agile development organizations and interviewed 11 practitioners about their decision-making process. The results suggest that options are almost always identified, reasoned about and acted upon. They are not expressed in quantitative terms, however, they are instead explicitly or implicitly taken\ud into account during the decision-making process at interiteration time

On Service Employers’ Hiring Decisions in Online Labor Markets: A Perspective of Price and Quality Discovery

Online labor markets become increasingly important creating jobs for millions of online freelancers around the globe. However, 60% of projects fail to reach to a contract, indicating a waste of time and effort for both buyers and freelancers. Given the fact that a buyer is often uncertain about the price (common value) of a project, this paper empirically examines how this uncertainty on common value—measured as price dispersion--affects buyer’s contract decisions and price sensitivity. We find price dispersion has a negative while quality dispersion has a positive effect on buyer’s contract decisions. Meanwhile, as price dispersion increases, a buyer becomes less sensitive to prices. The paper contributes to online service market literature by focusing on buyer’s uncertainty over common value and proposing the importance of price discovery in buyers’ contract decisions. Managerial implications for the platform and freelancers’ bidding strategies under common value uncertainty are discussed at end

Risk-Driven Design Processes: Balancing Efficiency with Resilience in Product Design

Current design methods and approaches focus on increasing the efficiency of the product design system by, for example, eliminating waste and focusing on value creation. However, continuing failures in the development of complex, large scale products and systems point towards weaknesses in the existing approaches. We argue that product development organizations are hindered by the many uncertainties that are inherent in the process. Common management heuristics ignore uncertainty and thus overly simplify the decision making process. Creating transparency regarding uncertainties and the associated risks (i.e. effect of uncertainties on design objectives) is not seen as an explicit priority. Consequently organizations are unable to balance risk and return in their development choices. Product development processes do not emphasize reduction of risks, particularly those risks that are apparent early in the process. In addition, the resilience of the PD system, i.e. its ability to deliver on-target results under uncertainty, is not deliberately designed to match the level of residual uncertainty. This chapter introduces the notion of Risk-Driven Design and its four principles of 1. Creating transparency regarding design risks; 2. Risk-driven decision making; 3. Minimizing uncertainty; and 4. Creating resilience.Massachusetts Institute of Technology. Lean Advancement InitiativeCenter for Clean Water and Clean Energy at MIT and KFUP

Multiple Imputation Using SAS Software

Multiple imputation provides a useful strategy for dealing with data sets that have missing values. Instead of filling in a single value for each missing value, a multiple imputation procedure replaces each missing value with a set of plausible values that represent the uncertainty about the right value to impute. These multiply imputed data sets are then analyzed by using standard procedures for complete data and combining the results from these analyses. No matter which complete-data analysis is used, the process of combining results of parameter estimates and their associated standard errors from different imputed data sets is essentially the same. This process results in valid statistical inferences that properly reflect the uncertainty due to missing values. This paper reviews methods for analyzing missing data and applications of multiple imputation techniques. This paper presents the SAS/STAT MI and MIANALYZE procedures, which perform inference by multiple imputation under numerous settings. PROC MI implements popular methods for creating imputations under monotone and nonmonotone (arbitrary) patterns of missing data, and PROC MIANALYZE analyzes results from multiply imputed data sets