A new model for probabilistic multi-period multi-objective project selection problem

The project selection problem is considered as one of the most imperative decisions for investor organizations. Due to non-deterministic nature of some criteria in the real world projects in this paper, a new model for project selection problem is proposed in which some parameters are assumed probabilistic. This model is formulated as a non-linear, multi-objective, multi-period, zero-one programming model. Then the epsilon constraint method and an algorithm are applied to check the Pareto front and to find optimal solutions. A case study is conducted to illustrate the applicability and effectiveness of the approach, with the results presented and analysed. Since the proposed model is more compatible with real world problems, the results are more tangible and trustable compared with deterministic cases. Implications of the proposed approach are discussed and suggestions for further work are outlined

Improved innovative product strategy assessment model in market research context

In the innovation economy, companies more often face the need quickly and efficiently evaluate not only their existing product and service portfolios in the context of the industry’s potential, but also evaluate theoretical concepts of innovations. There are various systems for evaluating innovation concepts and already existing products and/or services for companies that are planning to expand their business in a new industry. The innovation economy is characterized by the convergence of innovations and the most demanded products on the market with continuous market upgrades. A company which wants to grow in a new industry faces an assessment challenge between already existing, demanded products and the choice of innovative concepts in the context of the company's most perspective growth. As market examples show, a successful company’s entry into a new industry can be related to both an innovative concept and an innovative business model of existing, demanded market products. The aim of the study is to analyse the appropriateness of the existing assessment systems of innovations concepts and market bestselling products from the perspective of an enterprise, considering an expansion into new industry. The theoretical benefit of the study is to highlight a new, complementary model in the assessment of the company's growth strategy in the context of developing new industries and markets. The practical contribution of the study is an improved combined industry and company assessment model. Proposed model is company growth perspective assessment tool in the context of new products, either it is completely new to market or new to company, but already known in the market

Model Uncertainty and its Impact on Derivative Pricing

Financial derivatives written on an underlying can normally be priced and hedged accurately only after a suitable mathematical model for the underlying has been determined. This chapter explains the difficulties in finding a (unique) realistic model \u2014 model uncertainty. If the wrong model is chosen for pricing and hedging, unexpected and unwelcome financial consequences may occur. By wrong model we mean either the wrong model type (specification\ud uncertainty) or the wrong model parameter (parameter uncertainty). In both cases, the impact of model uncertainty on pricing and hedging is significant. A variety of measures are introduced to value the model uncertainty of derivatives and a numerical example again confirms that these values are a significant proportion of the derivative price

Radical innovation: making the right bets

Report published by Advanced Institute of Management ResearchOur research reveals that organisations, here in the UK and elsewhere, must face up to the complex challenges associated with exploring and developing radical ideas and innovations if they are to continue to be successful in the long term. ■ Discontinuous innovation – ‘doing something different’ innovation – is often the driver of sustained competitive advantage and shareholder value creation. As such the ability to support radical innovation is an essential organisational competence. ■ The decision-making process in which resources are allocated to innovation projects is extremely challenging, as the degree of uncertainty involved means that using conventional systems and processes often leads to radical ideas being rejected. ■ The research identifies twelve excuses that organisations use to justify their decision not to pursue radical innovation. Organisations must learn to recognise when they are making these excuses and find other ways of evaluating how to behave when faced with radical innovation. ■ The innovation selection environment that operates in organisations can be described in terms of four zones. In two of those zones, new strategies are required for innovation selection decision-making. ■ There are a number of promising strategies that can help organisations to back an innovation winner. These include: building alternative visions; bridge-building to/from outside the box; probe and learn method; using alternative evaluation and measurement criteria; mobilising sponsorship and championship; using alternative decision-making pathways; deploying alternative funding structures; using alternative – dedicated/devolved/decentralised – implementation structures; mobilising entrepreneurship inside and outside the firm. ■ Through a thorough understanding of the innovation selection process, organisations can avoid the pitfalls that lead to abandoning potentially marketwinning radical ideas. At the same time they can learn how to implement strategies that nurture and develop that all-important discontinuous innovation.Engineering and Physical Sciences Research Council (EPSRC)and Economic and Social Research Council (ESRC

A Fuzzy Logic Stock Trading System Based On Technical Analysis

Technical analysis of financial markets involves analyzing past price movements in order to identify favorable trading opportunities. The objective of this research was to demonstrate that a fuzzy logic stock trading system based on technical analysis can assist average traders in becoming successful by optimizing the use of technical indicators and trading rules that experts use to identify when to buy and sell stock. Research of relevant literature explored the current state of knowledge in methodologies for developing and validating trading systems using technical indicators and fuzzy logic trading systems, providing guidelines for the development and evaluation of the system. Evaluation of the system confirmed that fuzzy logic can have a positive contribution to a successful trading system, and that once a successful trading system has been developed and verified an average trader can be successful by simply following the trading system\u27s buy and sell signals. The trader need not be an expert at interpreting the underlying technical indicators or react to price movements emotionally. The trading decisions are made by the trading system, so the only decision that the average trader need make is whether there is enough confidence in the system to commit real money in live trading. Suggestions for future research include improvements in accuracy and flexibility, and investigation of additional trading models and filters

Recent experience with commercial bank debt reduction

The authors review the case for market-based debt reduction and concerted debt reduction. They explain the new menu-based approach to debt reduction and discuss why it may be preferred to market-based and concerted debt reduction. In a review of the five recent debt-reduction agreements, they find that the menu approach indeed achieved debt reduction at substantially lower costs than a comparable market-based operation. By one measure, the five countries may have saved more than $8 billion. Even a menu-based approach to debt reduction, however, is unlikely to directly benefit the debtor financially. They find that the debtors suffered financial losses equal to a few percent of their GDPs. Indirect benefits, or efficiency gains associated with debt reduction, are necessary to make the operation benefit the debtor.Strategic Debt Management,Economic Theory&Research,Financial Intermediation,Environmental Economics&Policies,Banks&Banking Reform

Economic and regulatory uncertainty in renewable energy system design: a review

Renewable energy is increasingly mobilizing more investment around the globe. However, there has been little attention to evaluating economic and regulatory (E&R) uncertainties, despite their enormous impact on the project cashflows. Consequently, this review analyzes, classifies, and discusses 130 articles dealing with the design of renewable energy projects under E&R uncertainties. After performing a survey and identifying the selected manuscripts, and the few previous reviews on the matter, the following innovative categorization is designed: sources of uncertainty, uncertainty characterization methods, problem formulations, solution methods, and regulatory frameworks. The classification reveals that electricity price is the most considered source of uncertainty, often alone, despite the existence of six other equally influential groups of E&R uncertainties. In addition, real options and optimization arise as the two main approaches researchers use to solve problems in energy system design. Subsequently, the following aspects of interest are discussed in depth: how modeling can be improved, which are the most influential variables, and potential lines of research. Conclusions show the necessity of modeling E&R uncertainties with currently underrepresented methods, suggest several policy recommendations, and encourage the integration of prevailing approaches.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.2 - Per a 2030, augmentar substancialment el percentatge d’energia renovable en el con­junt de fonts d’energiaObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantPostprint (published version