Estimating Risk under Interval Uncertainty: Sequential and Parallel Algorithms
نویسندگان
چکیده
In traditional econometrics, the quality of an individual investment – and of the investment portfolio – is characterized by its expected return and its risk (variance). For an individual investment or portfolio, we can estimate the future expected return and a future risk by tracing the returns x1, . . . , xn of this investment (and/or similar investments) over the past years, and computing the statistical characteristics based on these returns. The return (per unit investment) is defined as the selling of the corresponding financial instrument at the ends of, e.g., a one-year period, divided by the buying price of this instrument at the beginning of this period. It is usually assumed that we know the exact return values x1, . . . , xn. In practice, however, both the selling and the buying prices unpredictably fluctuate from day to day – and even within a single day. These minute-by-minute fluctuations are rarely recorded; what we usually have recorded is the daily range of prices. As a result, we can only find the range [xi, xi] of possible values of the return xi. In this case, different
منابع مشابه
Application of Sequential Gaussian Conditional Simulation to Underground Mine Design Under Grade Uncertainty
In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most widely used method to quantify risk analysis to overcome the drawbacks of the estimation methods...
متن کاملRobustness-based portfolio optimization under epistemic uncertainty
In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...
متن کاملAn Assessment Method for Project Cash Flow under Interval-Valued Fuzzy Environment
Effective project management requires reliable knowledge of cash required in different stages of project life cycle. Getting this knowledge is highly dependent on sophisticated consideration of project environment. Nature of projects and their environments are associated with uncertain conditions. In this paper, a new project cash flow assessment method based on project scheduling is proposed t...
متن کاملA Multi-Criteria Analysis Model under an Interval Type-2 Fuzzy Environment with an Application to Production Project Decision Problems
Using Multi-Criteria Decision-Making (MCDM) to solve complicated decisions often includes uncertainty, which could be tackled by utilizing the fuzzy sets theory. Type-2 fuzzy sets consider more uncertainty than type-1 fuzzy sets. These fuzzy sets provide more degrees of freedom to illustrate the uncertainty and fuzziness in real-world production projects. In this paper, a new multi-criteria ana...
متن کاملThree Hybrid Metaheuristic Algorithms for Stochastic Flexible Flow Shop Scheduling Problem with Preventive Maintenance and Budget Constraint
Stochastic flexible flow shop scheduling problem (SFFSSP) is one the main focus of researchers due to the complexity arises from inherent uncertainties and also the difficulty of solving such NP-hard problems. Conventionally, in such problems each machine’s job process time may encounter uncertainty due to their relevant random behaviour. In order to examine such problems more realistically, fi...
متن کامل