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Bachelor 2019/2020

Modeling of the Financial Flows in Logistics on the Basis of the Concept of Utility and Risks

Area of studies: Management
Delivered by: Department of Logistics
When: 4 year, 1, 2 module
Mode of studies: offline
Instructors: Denis Gusev
Language: English
ECTS credits: 4

Course Syllabus

Abstract

The main purpose of the course is to: provide the basic principles and rules of financial mathematics at the level of the theory of quantitative methods in finance, teaching students the practical application of techniques to bring cash flow to the desired point in time based on dif-ferent models (the scheme of simple interest, compound interest scheme, the scheme of contin-uous percent), methods of restructuring cash flows in the format of logistics systems, methods of simultaneous investment and financial planning with the use of modern technology. The course program includes conducting seminars. In these classes students practice skills in the use of methods of financial mathematics, consolidate knowledge of the relevant theoretical material. The program also provides control work for the training of student. Stu-dent self-study also includes: learning theoretical material at a level sufficient for understand-ing the topics and sections of the course, participation in the seminars, which provide number of relevant activities that will help to secure the skills of using methods of financial mathemat-ics.
Learning Objectives

Learning Objectives

  • The main purpose of the course is to: provide the basic principles and rules of financial mathematics at the level of the theory of quantitative methods in finance, teaching students the practical application of techniques to bring cash flow to the desired point in time based on dif-ferent models (the scheme of simple interest, compound interest scheme, the scheme of contin-uous percent), methods of restructuring cash flows in the format of logistics systems, methods of simultaneous investment and financial planning with the use of modern technology.
  • Based on current requirements needed to consider the time value of money in the analysis of logistics op-erations as a result of the discipline, the student must: - have a broad understanding of the basic principles, rules and methods of financial mathematics; - know and use in their future activities of the appropriate methods and models to make optimal decisions on the analysis and restructuring of financial flows in logistics, including - • methods of equivalent transformations of financial flows; • methods of management / debt restructuring; • methods of flow control payments on leasing and insurance contracts in logistics; • methods of investment and financial planning of investments in logistics on the basis of econom-ic and mathematical modeling
Expected Learning Outcomes

Expected Learning Outcomes

  • Ability to present, calculate and transform financial flows in logistics taking into account risks
  • Ability to model financial flows in logistics under conditions of uncertainty
  • Ability to understand Utility concept and attributes of a neoclassical approach to risk management in logistics
  • Ability to use EUC criterion - expected utility in risk management in logistic
  • Ability to model financial flows based on multicriteria optimization methods
  • Ability to use procedures for making multicriteria decisions under risk conditions when modeling financial flows
  • Ability to use mathematical models of simultaneous investment and financial planning in lo-gistics
Course Contents

Course Contents

  • Section 1. Modeling financial flows in logistics taking into account risks Theme 1.1. Presentation formats of financial flows taking into account risks and their management models in logistics
    Financial flows in logistics. Various formats for representing financial flows: 1) in the form of discrete sequences (for given analyzed time intervals); 2) in the form of continuous functions (taking into account discounting and accrual procedures). Features of modeling fi-nancial flows in logistics in the form of discrete sequences of payments. Transformation and concentration of financial flows, equations of financial equivalence. The relationship of finan-cial rents and index methods for optimizing discrete financial flows. The format for represent-ing financial flows in the form of continuous functions. Baumol's model and its applications to logistics research. Miller-Orr model and its applications in logistics. The concept of risk in the format of financial flows. The concept of production risks. The concept of speculative risks. Features of formalizing the risk factor in the format of discrete payment sequences. Features of the formalization of the risk factor in the format of continuous functions
  • Section 2. Modeling financial flows in logistics in the face of uncertainty Theme 2.1. Formalization of the uncertainty factor in modeling financial flows in logistics
    The concept of uncertainty in modeling financial flows in logistics. Correlation of the analyzed full group of events with the attributes of simulated financial flows for supply chains. Proce-dures for formalizing uncertainty in the format of financial flow models in logistics. Proce-dures for constructing and parameterizing the corresponding event tree. Features of modeling financial flows under uncertainty for inventory management tasks.
  • Section 3. Risk management of financial flows in logistics based on the concept of utility Theme 3.1. Utility concept and attributes of a neoclassical approach to risk management in logistics
    Utility concept and its attributes. Decision making based on the concept of utility. Op-portunities and specifics of taking into account the attitude of a decision maker to risk. Illustra-tions in the format of the famous paradox: St. Petersburg paradox. Utility function: its defini-tion and properties. The concept of risk-free equivalent for proposals in risk when modeling financial flows in logistics based on the concept of utility. Linear conversion over utility func-tion. A theorem on the general form of utility functions. The specifics of the procedures for de-termining the risk-free equivalent. Applications for modeling financial flows in logistics
  • Theme 3.2. EUC criterion - expected utility in risk management in logistic
    Jensen's inequality and its place in risk management theory based on the concept of use-fulness. Properties and interpretations of this inequality, which are due to the convexity or con-cavity of the utility function. Illustrations in financial flow modeling applications in logistics. Classification of decision-makers by their relation to risk based on utility functions (cautious attitude to risk, neutral attitude to risk, risk lovers). The expected utility criterion is EUC. A utility randomization property and its application to the selection of the best utility-based solu-tions. An experimental measurement of utility, taking into account the attitude of decision makers to risk. Comparison of risk-based utility alternatives for modeling financial supply chain flows. Applications and illustrations.
  • Section 4. Methods of multicriteria optimization in modeling financial flows in logistics Theme 4.1. Modeling financial flows based on multicriteria optimization methods
    Peculiarities of risk presentation in modeling financial flows based on the use of deci-sion-making methods according to many criteria. Formalization of risk factors in the form of individual particular criteria. Possibilities of using traditional methods of multicriteria optimi-zation to find the best solutions in the analysis of financial flows. The specifics of implementa-tion in modeling financial flows of the most common selection criteria in logistic studies: min-imax (and / or maximin) criterion, Hurwitz criterion, product criterion (and / or geometric mean), ideal point criterion, generalized selection criteria and etc. Features of procedures for formalizing and clarifying the preferences of decision-makers, which are designed to improve the quality of multi-criteria selection of the best solution based on a synthesis of analytical hi-erarchy processes and traditional methods criterion optimization.
  • Theme 4.2. Procedures for making multi-criteria decisions in risk conditions when modeling financial flows for inventory management and vehicle selection
    Procedures for making multi-criteria decisions in risk conditions when managing stocks using many criteria, among which the requirement to maximize the profitability of working capital is taken into account. The task of the optimal choice of a vehicle under many criteria. Formalization of the risk factor as a separate private criterion. Features of the implementation of the analytical hierarchy method in modeling financial flows. Formalization of various levels of the cautious attitude of the decision-maker to risk. The impact of the transition from one level to another in pairwise comparisons of risk indicators, both on the choice of the best alter-native and on the ranking of alternatives.
  • Section 5. Mathematical models of simultaneous investment and financial planning in lo-gistics
    Features and specific investment optimization models in the analysis of investment de-cisions in the logistics considering the time value of money. Optimization model of simultane-ous investment and financial planning by J. Dean. Optimization model of simultaneous invest-ment and financial planning by G. Albah. and its modification by G. Hughes and G. Vaygartner. Applications of optimization of investment and financial models to analyze and optimize the investment decision-making in logistics.
Assessment Elements

Assessment Elements

  • non-blocking Work on seminars
  • non-blocking Analitical note and other homeworks
  • non-blocking Control work
  • blocking Exam
    The exam consists of a written part (1 academician hour) and an oral part (they are held on the same day). When setting the final grade for an exam, the grades of these two indicated parts / steps are taken into account with equal weights. Moreover, to encourage more active work on the study of the discipline, the following is practiced. The partially oral stage of the exam can be counted even before it begins (as a result of the learning process, which is correlated with answers to special questions, as well as with specially completed tasks or developments, for example, which caused the student to speak at a scientific confer-ence, etc.). The mandatory attributes of such procedures associated with the partial offset of the oral part / stage of the exam include the following conditions. 1) They must be open, i.e. not only a specific student is informed about this, but an announcement is made for the entire group of students or the entire stream. 2) They must be specific, i.e. at the same time, it will certainly be clarified which part related to the oral stage of the exam will be counted; 3) They should be available to every student who wants to use this for-mat of training procedures..
Interim Assessment

Interim Assessment

  • Interim assessment (2 module)
    0.15 * Analitical note and other homeworks + 0.1 * Control work + 0.6 * Exam + 0.15 * Work on seminars
Bibliography

Bibliography

Recommended Core Bibliography

  • Elements of financial risk management, Christoffersen, P. F., 2003
  • Financial institutions management : a risk management approach, Saunders, A., Cornett, M. M., 2018
  • Money, information and uncertainty, Goodhart, C. A. E., 1989

Recommended Additional Bibliography

  • Merna, T., & Al-Thani, F. F. (2008). Corporate Risk Management (Vol. 2nd ed). Chichester, England: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=323307