Optimal Investment Decisions Through Dynamic Programming PDF Download

Author: İrem Demirci
Publisher:
ISBN:
Category : Investments
Languages : en
Pages : 246

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Author: Gerard F. Schreuder
Publisher:
ISBN:
Category : Forests and forestry
Languages : en
Pages : 70

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Author: Werner Jammernegg
Publisher: Springer Science & Business Media
ISBN: 364246646X
Category : Business & Economics
Languages : en
Pages : 167

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Book Description
This book describes some models from the theory of investment which are mainly characterized by three features. Firstly, the decision-maker acts in a dynamic environment. Secondly, the distributions of the random variables are only incompletely known at the beginning of the planning process. This is termed as decision-making under conditions of uncer tainty. Thirdly, in large parts of the work we restrict the analysis to binary decision models. In a binary model, the decision-maker must choose one of two actions. For example, one decision means to undertake the invest ·ment project in a planning period, whereas the other decision prescribes to postpone the project for at least one more period. The analysis of dynamic decision models under conditions of uncertainty is not a very common approach in economics. In this framework the op timal decisions are only obtained by the extensive use of methods from operations research and from statistics. It is the intention to narrow some of the existing gaps in the fields of investment and portfolio analysis in this respect. This is done by combining techniques that have been devel oped in investment theory and portfolio selection, in stochastic dynamic programming, and in Bayesian statistics. The latter field indicates the use of Bayes' theorem for the revision of the probability distributions of the random variables over time.

Author: Pinar Keles
Publisher:
ISBN: 9780549277545
Category :
Languages : en
Pages : 122

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Book Description
Investments, especially those in engineering applications and research and development, are generally made in stages. Thus, a company must often manage a portfolio of projects in various stages of development while also determining which new investments to undertake. We model, solve, and analyze the portfolio management problem for multi-stage investments with stochastic dynamic programming (SDP). As the presented recursion is intractable for large-scale problem instances, we present an approximation scheme which allows for the solution of longer horizon problems in order to ensure good time zero decisions when maximizing the discounted, expected worth of decisions over time. Additionally, the approximation approach provides two estimates of the probability of making the best decision at time zero, providing additional information to the decision maker. Numerous examples illustrate the ability to examine different budget levels, delay options (lengths, penalties, and costs), initial portfolios, project returns, and interaction effects of projects in the pipeline. While previous research focusing on single project analysis has highlighted the importance of the delay option, we illustrate how critical this option is when one considers an interdependent portfolio of projects over time, especially when projects late in the review process may fail and/or budgets are small. We show that our approximate dynamic programming (ADP) approach can be used to solve large scale multi-stage investment problems by decomposing them into subproblems and solving each subproblem individually before combining them under a total budget constraint. This method provides optimal investment levels for different categories of projects while considering the interaction between different categories. We specifically consider pharmaceutical R & D projects. We also analyze the impact of two different budget expenditure policies on periodic investment decisions. These two policies are 'whole costing', where we need to pay the entire stage cost at the time of an accept decision, and 'periodic costing', where we break investment costs based on the duration of the stage and reduce the current cycle budget only by the amount of cost allocated to the current cycle. Through several experiments, it is concluded that the periodic costing better uses budget dollars over long problem horizons, especially when we have the delay option.

Author: Heman Das Lohano
Publisher:
ISBN:
Category :
Languages : en
Pages : 352

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Author: Dimitris Melas
Publisher:
ISBN:
Category : Academic theses
Languages : en
Pages : 0

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Author: Robert K. Dixit
Publisher: Princeton University Press
ISBN: 1400830176
Category : Business & Economics
Languages : en
Pages : 484

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Book Description
How should firms decide whether and when to invest in new capital equipment, additions to their workforce, or the development of new products? Why have traditional economic models of investment failed to explain the behavior of investment spending in the United States and other countries? In this book, Avinash Dixit and Robert Pindyck provide the first detailed exposition of a new theoretical approach to the capital investment decisions of firms, stressing the irreversibility of most investment decisions, and the ongoing uncertainty of the economic environment in which these decisions are made. In so doing, they answer important questions about investment decisions and the behavior of investment spending. This new approach to investment recognizes the option value of waiting for better (but never complete) information. It exploits an analogy with the theory of options in financial markets, which permits a much richer dynamic framework than was possible with the traditional theory of investment. The authors present the new theory in a clear and systematic way, and consolidate, synthesize, and extend the various strands of research that have come out of the theory. Their book shows the importance of the theory for understanding investment behavior of firms; develops the implications of this theory for industry dynamics and for government policy concerning investment; and shows how the theory can be applied to specific industries and to a wide variety of business problems.

Author: Jonas Ekblom
Publisher: Linköping University Electronic Press
ISBN: 9176852024
Category :
Languages : en
Pages : 36

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Book Description
This thesis addresses the topic of decision making under uncertainty, with particular focus on financial markets. The aim of this research is to support improved decisions in practice, and related to this, to advance our understanding of financial markets. Stochastic optimization provides the tools to determine optimal decisions in uncertain environments, and the optimality conditions of these models produce insights into how financial markets work. To be more concrete, a great deal of financial theory is based on optimality conditions derived from stochastic optimization models. Therefore, an important part of the development of financial theory is to study stochastic optimization models that step-by-step better capture the essence of reality. This is the motivation behind the focus of this thesis, which is to study methods that in relation to prevailing models that underlie financial theory allow additional real-world complexities to be properly modeled. The overall purpose of this thesis is to develop and evaluate stochastic optimization models that support improved decisions under uncertainty on financial markets. The research into stochastic optimization in financial literature has traditionally focused on problem formulations that allow closed-form or `exact' numerical solutions; typically through the application of dynamic programming or optimal control. The focus in this thesis is on two other optimization methods, namely stochastic programming and approximate dynamic programming, which open up opportunities to study new classes of financial problems. More specifically, these optimization methods allow additional and important aspects of many real-world problems to be captured. This thesis contributes with several insights that are relevant for both financial and stochastic optimization literature. First, we show that the modeling of several real-world aspects traditionally not considered in the literature are important components in a model which supports corporate hedging decisions. Specifically, we document the importance of modeling term premia, a rich asset universe and transaction costs. Secondly, we provide two methodological contributions to the stochastic programming literature by: (i) highlighting the challenges of realizing improved decisions through more stages in stochastic programming models; and (ii) developing an importance sampling method that can be used to produce high solution quality with few scenarios. Finally, we design an approximate dynamic programming model that gives close to optimal solutions to the classic, and thus far unsolved, portfolio choice problem with constant relative risk aversion preferences and transaction costs, given many risky assets and a large number of time periods.

Author: Peter M. Kort
Publisher: Springer Science & Business Media
ISBN: 3642489044
Category : Business & Economics
Languages : en
Pages : 196

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Book Description
1.1. Scope of the Book This book is a contribution to the area of "dynamic models of the firm". The motivation for this kind of research is the following: Empirical studies (e.g. Albach (1976)) have shown that the development of the firm over time can be divided into different stages. such as growth. stationarity and contraction. In order to understand and evaluate these stages in a proper way. it is important to develop a suitable theoretical framework. To that end. economists have applied dynamic mathematical techniques. such as optimal control theory. calculus of variations and dynamic programming to design and analyse dynamic models of the firm. In this way. the economic theory of the firm is extended to a dynamic context. Within the field of the dynamics of the firm this book - develops a general investment decision rule. based on the concept "net present value of marginal investment". which is applicable in deterministic dynamic models of the firm; - studies the influence of adjustment costs of investment on optimal dynamic firm behavior; - extends the stochastic dynamic theory of the firm by connecting it with a dynamic version of the Capital Asset Pricing Model. Before elaborating on "the dynamics of the firm". we first review the subject of net present value in the classical analysis.

Author: Giorgio Consigli
Publisher: Springer
ISBN: 3319416138
Category : Business & Economics
Languages : en
Pages : 310

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Book Description
The scope of this volume is primarily to analyze from different methodological perspectives similar valuation and optimization problems arising in financial applications, aimed at facilitating a theoretical and computational integration between methods largely regarded as alternatives. Increasingly in recent years, financial management problems such as strategic asset allocation, asset-liability management, as well as asset pricing problems, have been presented in the literature adopting formulation and solution approaches rooted in stochastic programming, robust optimization, stochastic dynamic programming (including approximate SDP) methods, as well as policy rule optimization, heuristic approaches and others. The aim of the volume is to facilitate the comprehension of the modeling and methodological potentials of those methods, thus their common assumptions and peculiarities, relying on similar financial problems. The volume will address different valuation problems common in finance related to: asset pricing, optimal portfolio management, risk measurement, risk control and asset-liability management. The volume features chapters of theoretical and practical relevance clarifying recent advances in the associated applied field from different standpoints, relying on similar valuation problems and, as mentioned, facilitating a mutual and beneficial methodological and theoretical knowledge transfer. The distinctive aspects of the volume can be summarized as follows: Strong benchmarking philosophy, with contributors explicitly asked to underline current limits and desirable developments in their areas. Theoretical contributions, aimed at advancing the state-of-the-art in the given domain with a clear potential for applications The inclusion of an algorithmic-computational discussion of issues arising on similar valuation problems across different methods. Variety of applications: rarely is it possible within a single volume to consider and analyze different, and possibly competing, alternative optimization techniques applied to well-identified financial valuation problems. Clear definition of the current state-of-the-art in each methodological and applied area to facilitate future research directions.