Financial statements in power bi, Liau, Jonathan Bastick, Liam

Автор: Ra?l Poler; Josefa Mula; Manuel D?az-Madro?ero
Название: Operations Research Problems
ISBN: 144717190X ISBN-13(EAN): 9781447171904
Издательство: Springer
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Цена: 65290.00 T
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Описание: This book offers a compendium of problems in operations research, in such areas as linear programming, integer programming, non-linear programming, network modeling, inventory theory, queue theory, tree decision, dynamic programming, Markov processes and more.

Автор: Jean-Bernard Lasserre
Название: Linear and Integer Programming vs Linear Integration and Counting
ISBN: 1441918531 ISBN-13(EAN): 9781441918536
Издательство: Springer
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Цена: 102480.00 T
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Описание: This book analyzes and compares four closely related problems, namely linear programming, integer programming, linear integration, and linear summation (or counting). The book provides some new insights on duality concepts for integer programs.

Автор: David W.K. Yeung; Leon A. Petrosjan
Название: Cooperative Stochastic Differential Games
ISBN: 1441920943 ISBN-13(EAN): 9781441920942
Издательство: Springer
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Цена: 130430.00 T
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Описание: Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research.

Автор: Anthony Brabazon; Michael O`Neill
Название: Biologically Inspired Algorithms for Financial Modelling
ISBN: 3642065732 ISBN-13(EAN): 9783642065736
Издательство: Springer
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Цена: 121110.00 T
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Описание:

Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of this book is the application of biologically inspired algorithms (BIAs) to financial modelling.

In a detailed introduction, the authors explain computer trading on financial markets and the difficulties faced in financial market modelling. Then Part I provides a thorough guide to the various bioinspired methodologies neural networks, evolutionary computing (particularly genetic algorithms and grammatical evolution), particle swarm and ant colony optimization, and immune systems. Part II brings the reader through the development of market trading systems. Finally, Part III examines real-world case studies where BIA methodologies are employed to construct trading systems in equity and foreign exchange markets, and for the prediction of corporate bond ratings and corporate failures.

The book was written for those in the finance community who want to apply BIAs in financial modelling, and for computer scientists who want an introduction to this growing application domain."

Название: Heavy-Tail Phenomena: Probabilistic And Statistical Modeling
ISBN: 1441920242 ISBN-13(EAN): 9781441920249
Издательство: Springer
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Цена: 55890.00 T
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Описание: This text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. It is uniquely devoted to heavy-tails and emphasizes both probability modeling and statistical methods for fitting models.

Автор: Georg Ch. Pflug; Alois Pichler
Название: Multistage Stochastic Optimization
ISBN: 3319088424 ISBN-13(EAN): 9783319088426
Издательство: Springer
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Цена: 93160.00 T
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Описание: Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas.

Автор: Michael Bartholomew-Biggs
Название: Nonlinear Optimization with Financial Applications
ISBN: 1489981195 ISBN-13(EAN): 9781489981196
Издательство: Springer
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Цена: 130430.00 T
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Описание: This instructive book introduces the key ideas behind practical nonlinear optimization, accompanied by computational examples and supporting software. It combines computational finance with an important class of numerical techniques.

Автор: Carr
Название: Convex Duality and Financial Mathematics
ISBN: 3319924915 ISBN-13(EAN): 9783319924915
Издательство: Springer
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Цена: 65210.00 T
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Описание:

1. Convex Duality.- 2. Financial Models in One Period.- 3. Finite Period Financial Models.- 4. Continuous Financial Models.- References.

Автор: Ludger R?schendorf
Название: Mathematical Risk Analysis
ISBN: 3642430163 ISBN-13(EAN): 9783642430169
Издательство: Springer
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Цена: 88470.00 T
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Описание: The up-to-date material and logical structure of this volume provides the clarity and orientation needed to gain a solid working knowledge of mathematical risk analysis. It includes a specialized focus on the risk theory deployed in finance and insurance.

Автор: D. Chorafas
Название: Modelling the Survival of Financial and Industrial Enterprises
ISBN: 0333984668 ISBN-13(EAN): 9780333984666
Издательство: Springer
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Цена: 125770.00 T
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Описание: This book analyses the use of modelling in charting the survival of financial and industrial enterprises. The author shows how to use models effectively, and goes on to consider the pitfalls that can occur. The book contains plenty of practical examples, making this a useful `how to` guide.

Автор: Alexey F. Izmailov; Mikhail V. Solodov
Название: Newton-Type Methods for Optimization and Variational Problems
ISBN: 3319353845 ISBN-13(EAN): 9783319353845
Издательство: Springer
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Цена: 102480.00 T
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Описание: This book presents state-of-the-art theoretical analysis of fundamental Newtonian and Newtonian-related approaches to solving optimization and variational problems, and offers a set of tools for the unified treatment of various algorithms.

Автор: John A. Muckstadt; Amar Sapra
Название: Principles of Inventory Management
ISBN: 1493938630 ISBN-13(EAN): 9781493938636
Издательство: Springer
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Цена: 55890.00 T
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Описание: 1 Inventories Are Everywhere.- 1.1 The Roles of Inventory.- 1.2 Fundamental Questions.- 1.3 Factors Affecting Inventory Policy Decisions.- 1.3.1 System Structure.- 1.3.2 The Items.- 1.3.3 Market Characteristics.- 1.3.4 Lead Times.- 1.3.5 Costs.- 1.4 Measuring Performance.- 2 EOQ Model.- 2.1 Model Development: Economic Order Quantity (EOQ) Model.- 2.1.1 Robustness of the EOQ Model.- 2.1.2 Reorder Point and Reorder Interval.- 2.2 EOQ Model with Backordering Allowed.- 2.2.1 The Optimal Cost.- 2.3 Quantity Discount Model.- 2.3.1 All Units Discount.- 2.3.2 An Algorithm to Determine the Optimal Order Quantity for the All Units Discount Case.- 2.3.3 Incremental Quantity Discounts.- 2.3.4 An Algorithm to Determine the Optimal Order Quantity for the Incremental Quantity Discount Case.- 2.4 Lot Sizing When Constraints Exist.- 2.5 Exercises.- 3 Power-of-Two Policies.- 3.1 Basic Framework.- 3.1.1 Power-of-Two Policies.- 3.1.2 PO2 Policy for a Single-Stage System.- 3.1.2.1 Cost for the Optimal PO2 Policy.- 3.2 Serial Systems.- 3.2.1 Assumptions and Nomenclature.- 3.2.2 A Mathematical Model for Serial Systems.- 3.2.3 Algorithm to Obtain an Optimal Solution to (RP).- 3.3 Multi-Echelon Distribution Systems.- 3.3.1 A Mathematical Model for Distribution Systems.- 3.3.1.1 Relaxed Problem.- 3.3.2 Powers-of-Two Solution.- 3.4 Joint Replenishment Problem (JRP).- 3.4.1 A Mathematical Model for Joint Replenishment Systems.- 3.4.2 Rounding the Solution to the Relaxed Problem.- 3.5 Exercises.- Dynamic Lot Sizing with Deterministic Demand.- 4.1 The Wagner-Whitin (WW) Algorithm.- 4.1.1 Solution Approach.- 4.1.2 Algorithm.- 4.1.3 Shortest-Path Representation of the Dynamic Lot Sizing Problem.- 4.1.4 Technical Appendix for the Wagner-Whitin Algorithm.- 4.2 Wagelmans-Hoesel-Kolen (WHK) Algorithm.- 4.2.1 Model Formulation.- 4.2.2 An Order T logT Algorithm for Solving Problem (4.5).- 4.2.3 Algorithm.- 4.3 Heuristic Methods.- 4.3.1 Silver-Meal Heuristic.- 4.3.2 Least UnitCost Heuristic.- 4.4 A Comment on the Planning Horizon.- 4.5 Exercises.- 5 Single-Period Models.- 5.1 Making Decisions in the Presence of Uncertainty.- 5.2 An Example.- 5.2.1 The Data.- 5.2.2 The Decision Model.- 5.3 Another Example.- 5.4 Multiple Items.- 5.4.1 A General Model.- 5.4.2 Multiple Constraints.- 5.5 Exercises.- 6 Inventory Planning over Multiple Time Periods: Linear-Cost Case.- 6.1 Optimal Policies.- 6.1.1 The Single-Unit, Single-Customer Approach: Single-Location Case.- 6.1.1.1 Notation and Definitions.- 6.1.1.2 Optimality of Base-Stock Policies.- 6.1.1.3 Stochastic Lead Times.- 6.1.1.4 The Serial Systems Case.- 6.1.1.5 Generalized of Demand Model.- 6.1.1.6 Capacity Limitations.- 6.2 Finding Optimal Stock Levels.- 6.2.1 Finite Planning Horizon Analysis.- 6.2.2 Constant, Positive Lead Time Case.- 6.2.3 End-of-Horizon Effects.- 6.2.4 Infinite-Horizon Analysis.- 6.2.5 Lost Sales.- 6.3 Capacity Limited Systems.- 6.3.1 The Shortfall Distribution.- 6.3.1.1 General Properties.- 6.3.2 Discrete Demand Case.- 6.3.3 An Example.- 6.4 A Serial System.- 6.4.1 An Echelon-Based Approach for Managing Inventories in Serial Systems.- 6.4.1.1 A Decision Model.- 6.4.1.2 A Dynamic Programming Formulation of the Decision Problem.- 6.4.1.3 An Algorithm for Computing Optimal Echelon Stock Levels.- 6.4.1.4 Solving the Oil Rig Problem: The Stationary Demand Case.- 6.5 Exercises.- 7 Background Concepts: An Introduction to the (s-1, s) Policy under Poisson Demand.- 7.1 Steady State.- 7.1.1 Backorder Case.- 7.1.2 Lost Sales Case.- 7.2 Performance Measures.- 7.3 Properties of the Performance Measures.- 7.4 Finding Stock Levels in (s-1, s) Policy Managed Systems: Optimization Problem Formulations and Solution Algorithms.- 7.4.1 First Example: Minimize Expected Backorders Subject to an Inventory Investment Constraint.- 7.4.2 Second Example: Maximize Expected System Average Fill Rate Subject to an Inventory Investment Constraint.- 7.5 Exercises.- 8 A Tactical Planning Model f