The Experts below are selected from a list of 6240 Experts worldwide ranked by ideXlab platform
David Johnstone - One of the best experts on this subject based on the ideXlab platform.
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sensitivity of the discount rate to the Expected Payoff in project valuation
Decision Analysis, 2017Co-Authors: David JohnstoneAbstract:A routine method in business is to value risky capital investment projects by discounting their Expected cash Payoffs at “risk-adjusted” discount rates. Discount rates are purportedly allied to projects in “the same risk-class,” but there is little clarity about what makes a risk class. The capital asset pricing model (CAPM) gives two mathematically equivalent definitions. One is that assets in the same risk class have the same “beta,” and the other is that they have the same ratio of Payoff mean to Payoff covariance (with “the market”). The second depiction, albeit widely unknown, is more interesting in terms of cash flow fundamentals. Its implication is that the “denominator” (risk-adjusted discount rate) depends on its own “numerator” (Expected Payoff). In practical circumstances, the CAPM price-implied discount rate can be highly sensitive to changes in the Expected Payoff, contradicting the convention of discounting an Expected cash flow at some fixed “risk-adjusted” rate regardless of its dollar amount.
Stewart W. Wilson - One of the best experts on this subject based on the ideXlab platform.
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Classifier Fitness Based on Accuracy
Evolutionary Computation, 1995Co-Authors: Stewart W. WilsonAbstract:In many classifier systems, the classifier strength parameter serves as a predictor of future Payoff and as the classifier's fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of Expected Payoff, but the classifier's fitness is given by a measure of the prediction's accuracy. The system executes the genetic algorithm in niches defined by the match sets, instead of panmictically. These aspects of XCS result in its population tending to form a complete and accurate mapping X A P from inputs and actions to Payoff predictions. Further, XCS tends to evolve classifiers that are maximally general, subject to an accuracy criterion. Besides introducing a new direction for classifier system research, these properties of XCS make it suitable for a wide range of reinforcement learning situations where generalization over states is desirable.
R.r. Yager - One of the best experts on this subject based on the ideXlab platform.
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Decision making with fuzzy probability assessments
IEEE Transactions on Fuzzy Systems, 1999Co-Authors: R.r. YagerAbstract:We discuss the idea of a fuzzy probability assessment, the association a collection of fuzzy probabilities with the outcomes of a random experiment. Fuzzy probability assessments often result from the linguistic specification of probabilities as provided by human experts. The question of consistency of the fuzzy probability assessment is considered. Finally, the problem of decision-making, selecting a best alternative action, in the face of a fuzzy probability assessment is investigated. Here we focus on the issue of obtaining the Expected Payoff of alternatives in the face of a fuzzy probability assessment. In the course of solving this problem we develop a representation of an effective probability distribution in the face of a fuzzy probability assessment.
Rahul Jain - One of the best experts on this subject based on the ideXlab platform.
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A Two Stage Stochastic Mechanism for Selling Random Power
2019 American Control Conference (ACC), 2019Co-Authors: Nathan Dahlin, Rahul JainAbstract:We present a two stage auction mechanism that renewable generators (or aggregators) could use to allocate renewable energy among load serving entities (LSEs). The auction is conducted day-ahead. LSEs submit bids specifying their valuation per unit, as well as their real-time fulfillment costs in case of shortfall in generation. We present an allocation rule and a de-allocation rule that maximizes Expected social welfare. Since the LSEs are strategic and may not report their private valuations and costs truthfully, we design a two-part payment, one made in Stage 1, before renewable energy generation level W is realized, and another determined later to be paid as compensation to those LSEs that have to be “de-allocated” in case of a shortfall. We propose a two-stage Stochastic VCG mechanism which we prove is incentive compatible in expectation (Expected Payoff maximizing bidders will bid truthfully), individually rational in expectation (Expected Payoff of all participants is non-negative) and is also efficient. To the best of our knowledge, this is the first such two-stage mechanism for selling random goods.
Stephen Jewson - One of the best experts on this subject based on the ideXlab platform.
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closed form expressions for the pricing of weather derivatives the Expected Payoff for t distributed indices
2008Co-Authors: Stephen JewsonAbstract:We derive closed-form expressions for the Expected Payoff of weather derivatives contracts for a t distributed weather index. There are three common situations in which t distributions might serve as a reasonable model for weather indices: first, some weather variables may be t distributed; second the t distribution can be used as a fatter-tailed alternative to the normal distribution as a stress test or model alternative;and third, objective Bayesian predictions of normally distributed data are t distributed.
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closed form expressions for the pricing of weather derivatives the Expected Payoff for gamma distributed indices
2004Co-Authors: Stephen JewsonAbstract:We derive closed-form expressions for the Expected Payoff of a number of types of weather derivative contract under the assumption of a gamma distributed settlement index.
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Closed-form Expressions for the Pricing of Weather Derivatives Part 4 - The Kernel Density
SSRN Electronic Journal, 2004Co-Authors: Stephen JewsonAbstract:We derive closed-form expressions for the Expected Payoff, the delta, the gamma and the Payoff variance for weather options that depend on an underlying index with a distribution modelled by the kernel density.
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Comparing the Potential Accuracy of Burn and Index Modelling for Weather Option Valuation
SSRN Electronic Journal, 2004Co-Authors: Stephen JewsonAbstract:We use simulations to compare the potential accuracy of burn and index modelling applied to the calculation of the Expected Payoff and other diagnostics for weather options.
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The Use of Weather Forecasts in the Pricing of Weather Derivatives
Meteorological Applications, 2003Co-Authors: Stephen Jewson, Rodrigo CaballeroAbstract:We discuss how weather forecasts can be used in the pricing of weather derivatives and derive results for the most important types of weather index and contract. We show that calculating the Expected Payoff of linear contracts on linear indices requires only forecasts of the mean temperature over the contract period. Calculating the Expected Payoff of linear contracts on non-linear indices requires forecasts of both the mean and the distribution of temperatures, but not of the dependence between temperature distributions on different days. Calculating the Expected Payoff of non-linear contracts requires forecasts of the full multivariate distribution of temperature over the whole contract. For contracts that extend beyond the end of the available forecasts, correlations between the forecast and the post-forecast periods must be taken into account when estimating this distribution. We present two methods by which this can be achieved, both of which combine information from climatological models of daily temperature with information from probabilistic forecasts.
