...Financial Modelling – Session VII Email: jcadete@clsbe.lisboa.ucp.pt Financial Modelling Joaquim Joaquim Cadete Cadete 1 How your work is going to be scored? Svensson Model: IR Swaps: CIR Model: Modeling Formalization (6) Functions Efficiency Gains (3) Functions Efficiency Gains (3) Further Improvements (5) Efficiency Gains (3) User’s Perspective Your Grade Financial Modelling Joaquim Cadete 2 Risk Management: the main concern… Counterparty risk Credit risk Interest rate risk Capital risk and solvency Funding risk Risk Management Reputational risk Foreign exchange risk Off-balance sheet risk Operational risk Financial Modelling Market or trading risk Sovereign risk Regulatory risk Joaquim Cadete 3 Risk and Return Theories Diversification Standard deviation of portfolio return σ Unsystematic or diversifiable risk Systematic or Total risk market-related risk Number of holdings Financial Modelling Joaquim Cadete 4 Interest rate risk: the first layer of volatility… Operational Risk: Betas. Operational risk Systematic risk or nondiversifiable risk Unsystematic or diversifiable risk A Total Risk Shareholders’ risk A E E A E A= E Financial Modelling Joaquim Cadete 5 Interest rate risk: the first layer of volatility… Operational Risk: Betas. If A = E, then RA =...
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...1. Abstract System Dynamic Modelling is an approach to frame and solve complex problems. It is widely used for policy design and analysis. System dynamics analysis is a part of Systems Theory which is used to study the dynamic behaviour of complex systems. The theory is based on acknowledgement of the fact that the inter-relations between the various components of a model, time delays between processes are as important to analyse the behaviour of a model as is the analysis of individual components. SD models solve the problem of simultaneity (mutual causation) by updating all variables in small time increments with positive and negative feedbacks and time delays structuring the interactions and control. In this paper, we have discussed the basic methodology of the technique, and the modelling process. Then, we have discussed the applications of SDM ranging from conventional ones like project management and science and engineering to exploring the concepts of SDM in Brand management and public health issues. 2. Historical background This technique of solving problems was developed in 1950s by Prof Jay Forrester of Massachusetts Institute of Technology, during his involvement with General Electric. He developed his insights about the foundations of engineering which helped him in the creation of system dynamics. He studied the problem of instability in GE employment. In this he did hand simulations (or calculations) of the stock-flow-feedback structure of the GE plants...
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...REPORTING Economic evaluation using decision analytical modelling: design, conduct, analysis, and reporting Evidence relating to healthcare decisions often comes from more than one study. Decision analytical modelling can be used as a basis for economic evaluations in these situations. Stavros Petrou professor of health economics 1, Alastair Gray professor of health economics 2 1 Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK; 2Health Economics Research Centre, Department of Public Health, University of Oxford, Oxford, UK Economic evaluations are increasingly conducted alongside randomised controlled trials, providing researchers with individual patient data to estimate cost effectiveness.1 However, randomised trials do not always provide a sufficient basis for economic evaluations used to inform regulatory and reimbursement decisions. For example, a single trial might not compare all the available options, provide evidence on all relevant inputs, or be conducted over a long enough time to capture differences in economic outcomes (or even measure those outcomes).2 In addition, reliance on a single trial may mean ignoring evidence from other trials, meta-analyses, and observational studies. Under these circumstances, decision analytical modelling provides an alternative framework for economic evaluation. Decision analytical modelling compares the expected costs and consequences of decision options by synthesising information from...
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...Quantitative Methods-II, focuses on ‘Operations Research’ tools which helps in solving problems in different functional domain of business. It also helps to optimize business operations/processes. The Quantitative Method-II tools act as aids to decision makers to take best decision for effective & efficient use of resources which ultimately lead to profit maximization or to achieve multiple goals or objective. | Course must be aligned with a strategic objective of the program Prerequisites/Co-requisites | Quantitative Methods I | Learning Objectives | To learn basic optimization techniques and their managerial applications with a focus on methodologies such as Linear Programming, Transportation models, Assignment Models, Transhipment Models, Games Theory, Queuing Models, Goal Programming, Integer Programming, Non-linear Programming, Simulation and Decision Theory. | Learning objectives must be aligned with learning outcomes of the course Teaching Methods | Modeling, Case study, Software-based solutions | Refer academic policies and procedures handbook For Internal Use Only Session Plan* | SESSION-1: Overview on Operations Research modelling (OR modelling): meaning, definition, steps involved in OR modelling; Session-2: Overview on Linear Programming (LP): LP meaning, various applications,...
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...Business Process Modelling CA4 Business Process Modelling 30 Oct 2014 1 Historical View of BP Modelling • • • Work Process Flow (early to mid 1900s) + Frank Gilbreth & his 'Flow Process Charts' (= flowcharts) + First structured method for documenting process flow Work Flow (mid-1970s) + Motivation was disenchantment with the above + Acted as a genesis for BP Modelling Business Process Modelling (2000s) + Trend towards new manuf'ing paradigm – Virtual Enterprise + VE=distributed & parallel BP execution from each VE entity + Need effective process modelling with strict model analysis CA4 Business Process Modelling 30 Oct 2014 2 Business Process Modelling- The “What?” • • • Business process modelling (BPM) is the activity of representing processes of an enterprise, so that the current process may be analyzed and improved. Typically performed by business analysts & managers seeking to improve process efficiency and quality. The process improvements identified by BPM may or may not require IT involvement, although that is a common driver behind modelling a business process. CA4 Business Process Modelling 30 Oct 2014 3 Business Process Modelling- The “Why?” • Business process modelling (BPM) helps companies in the following ways: + To become more process-oriented + To optimise business processes thro Process Change Mgmt: long term planning, execution & control of processes + To document and manage...
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...Competency modelling: A better approach in contemporary HRM practice? Introduction In the contemporary human resource management (HRM) practice, the process of human resource assessment and selection is shifting from the traditional job-based system of HRM to a newly-established competency approach. According to Dubios’ work (1998), more and more medium-sized and larger organizations are adopting the competency approach to replace the traditional job-oriented method to select and assess their employees in the USA and around the globe. This change happens mainly for the reason that the traditional job-based personnel management systems have shown a tendency to break down when jobs are dissolving under more flexible working conditions and simplification of the bureaucratic hierarchies of the contemporary organizations (Lawler, 1999). Based on the works of Nyboe (2004), in principle there are two distinct approaches to align work and competencies: to start with the work and adjust people and their qualifications to work requirements (job or production approach) or, alternatively, to start with the worker and assign tasks to workers according to their skills (competency or training approach). On one hand, in the job approach, tasks are grouped into individual jobs according to what is regarded a rational division of labor, and workers are recruited and trained to meet the requirements of those tasks. On the other hand, a competency approach has a shift of focus from...
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...Business AnAlytics And intelligence Course Starting: 29 June 2014 Application Deadline: Early Decision 28 February 2014 Regular Decision 15 April 2014 (Batch 5) (Classes conducted on-campus as well as off-campus) Certificate Programme on Business Analytics and Intelligence BATCH 5 in god We trust, All Others Must Bring data - W edwards deming he theory of bounded rationality proposed by nobel laureate Herbert Simon is evermore significant today with increasing complexity of the business problems; limited ability of human mind to analyze alternative solutions and the limited time available for decision making. introduction of enterprise resource planning (eRP) systems has ensured availability of data in many organizations; however, traditional eRP systems lacked data analysis capabilities that can assist the management in decision making. Business Analytics is a set of techniques and processes that can be used to analyse data to improve business performance through fact-based decision making. Business Analytics is the subset of Business intelligence, which creates capabilities for companies to compete in the market effectively. Business Analytics is likely to become one of the main functional areas in most companies. Analytics companies develop the ability to support their decisions through analytic reasoning using a variety of statistical and mathematical techniques. thomas devonport in his book titled, “competing on analytics: the new science of winning”, claims...
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...Workshop Balbir Barn 12th February 2007 Agenda • • • • • Why we construct Business Process Models A historical context Approaches to business process modelling Business Process Modelling Notation Tools and standards summary 2 What is a Business Process? • Davenport & Short (1990) define business process as – "a set of logically related tasks performed to achieve a defined business outcome." A process is "a structured, measured set of activities designed to produce a specified output for a particular customer or market. • Business processes as transformations of inputs to outputs input output • Other models available: – Language-Action-Perspective (LAP) (Winograd and Flores 1986) • Production, coordination tasks using language for communication 3 Purposes of Business Process Modeling: Organization Design • • • • • • Process Documentation Process Reorganization Process Monitoring and Controlling Continuous Improvement Quality Management: ISO 9000 Benchmarking: Compare with best practice • Knowledge Management: 4 Purposes of Business Process Modeling: Information Systems Design • • • • • Selection of ERP software Model based Customizing Software Development Workflow Management Simulation 5 What to model of a business process • Tasks • Coordination between tasks – synchronization – decisions – parallel work – repetition –… • • • • Organizational responsibilities Required resources and constraints Information input and output … 6 ...
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...limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) given the resources available to search among possible combinations in the target population of environments (E). Crop improvement can be viewed as a search strategy on a complex G×M×E adaptation or fitness landscape. Here we consider design of an integrated systems approach to crop improvement that incorporates advanced technologies in molecular markers, statistics, bio-informatics, and crop physiology and modelling. We suggest that such an approach can enhance the efficiency of crop improvement relative to conventional phenotypic selection by changing the focus from the paradigm of identifying superior varieties to a focus on identifying superior combinations of genetic regions and management systems. A comprehensive information system to support decisions on identifying target combinations is the critical core of the approach. We discuss the role of ecophysiology and modelling in this integrated systems approach by reviewing (i) applications in environmental characterization to underpin weighted selection; (ii) complex-trait physiology and genetics to enhance the stability of QTL models by linking the vector of coefficients defining the dynamic model to the genetic regions generating variability; and (iii) phenotypic prediction in the target population of environments to assess the value of putative combinations of traits and management...
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...Objective: Operations Research is the science of decision making and the art of decision modelling. It is a set of quantitative tools used by the managers to take decisions and formulate their business strategies. The basic objective of this course is to provide an understanding of the important techniques used in decision making. A certain level of mathematical hands-on expertise will be required to ensure understanding of the tools in operations research. At the end of the course you are expected to • Formulate real world decision making situations as mathematical optimisation problems • Solve linear programming problems • Be able to understand what the solution means • Understand basic concepts of transportation, assignment and integer programming problems. Reference [1] F.S.Hillier and M.S.Hillier, Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets, Tata McGraw-Hill, New Delhi,. [2] H.A.Taha, Operations Research An Introduction, Prentice Hall of India Private Limited, New Delhi. [3] Hiller and Lieberman, Introduction to Operations Research, Tata McGraw Hill, New York,. [4] N. Balakrishnan, B. Render and R.M.Stair, Managerial Decision Modeling With Spreadsheets, Pearson Education. Objective: Operations Research is the science of decision making and the art of decision modelling. It is a set of quantitative tools used by the managers to take decisions and formulate their business strategies. The basic...
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...Vol. 2(2), 3-8, February (2013) Res. J. Management Sci. Interpretive Structural Modelling (ISM) approach: An Overview Rajesh Attri1, Nikhil Dev1 and Vivek Sharma2 2 Department of Mechanical Engineering, YMCA University of Science and Technology, Faridabad, INDIA Department of Mechanical Engineering, Advanced Institute of Technology and Management, Palwal, INDIA 1 Available online at: www.isca.in Received 27th November 2012, revised 27th January 2013, accepted 1st February 2013 Abstract Interpretive structural modelling (ISM) is a well-established methodology for identifying relationships among specific items, which define a problem or an issue. This approach has been increasingly used by various researchers to represent the interrelationships among various elements related to the issue. ISM approach starts with an identification of variables, which are relevant to the problem or issue. Then a contextually relevant subordinate relation is chosen. Having decided the contextual relation, a structural self-interaction matrix (SSIM) is developed based on pairwise comparison of variables. After this, SSIM is converted into a reachability matrix (RM) and its transitivity is checked. Once transitivity embedding is complete, a matrix model is obtained. Then, the partitioning of the elements and an extraction of the structural model called ISM is derived. In this paper, key concept of ISM approach is discussed in detail. Keywords: ISM, SSIM, RM, variable, modelling. ...
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...Term Paper System Modeling Theory– CIS 331 Richard Guirguis Due on 12/8/2010 System Modeling Systems modeling or systems modelling is the approach to the study of the use of models to imagine and construct systems in business and IT development. In business and IT development the term "systems modeling" has multiple meaning. System Modeling can refer to analysis and design efforts, simulation and or system dynamics, and a study of the many uses of these models. There are different approaches to modeling: Agent based data and mathematical modeling. Quality management adopts a number of management principles that can be used by top management to guide their organizations towards improved performance. Principles such as: customer focus, leadership, people’s involvement, the process, system approach to management, continual improvement, facts, and a mutual benefit. . Decision making is a reasoning or emotional process which can be rational or irrational. The cognitive perspective is that the decision making process must be regarded as a continuous process integrated in the interaction with the environment. From a normative perspective, the analysis of individual decisions is concerned with the logic of decision making and rationality and the invariant choice it leads to it can be based on explicit assumptions or tacit assumptions. In decision making, objectives must be established and placed in the order of importance. It is a benefit to also have an alternative course...
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...define and understand the problem. You will then need to convert the business problem into an analytics problem. I other words you need to understand exactly what you are going to predict with the model you build. There is no point in building a fabulous model, only to realise later that what it is predicting is not exactly what the business needs. 2. Data Exploration - Once you have the problem defined, the next step is to explore the data and become more familiar with it. This is especially important when dealing with a completely new data set. 3. Data Preparation – Now that you have a good understanding of the data, you will need to prepare it for modelling. You will identify and treat missing values, detect outliers, transform variables, create binary variables if required and so on. This stage is very influenced by the modelling technique you will use at the next stage. For example, regression involves a fair amount of data preparation, but decision trees may need less prep whereas clustering requires a whole different kind of prep as compared to other techniques. 4. Modelling – Once the data is prepared, you can begin modelling. This is usually an iterative process where you run a model, evaluate the results, tweak your approach, run another model, evaluate the results,...
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...Name: Donato M. Galleon III Discussion Questions #5 IT 193 - Systems Analysis & Design Chapter 5: Data and Process Modeling 1. Describe data and process modeling, and name the main data and process modeling techniques. Data and process modelling uses a variety of techniques to represent an information system and processes and data flow contained within the information system. Methods of data and process modelling can include DFD's (Data Flow Diagrams), object modelling and entity-relationship diagrams. (https://ict108businessinformatics.wikispaces.com/Questions+Week+5) 2. Describe the Gane and Sarson symbols used for processes, data flows, data stores, and entities. Give four examples of typical names for processes, data flows, data stores, and entities. http://www.softtester.org/portfolio/cis244/assignment8.html 3. What is the relationship between a Context Diagram and Diagram 0, and which symbol is not used in a context diagram? A context diagram is a top-level view of an information system that shows the boundaries and scope of the system, whereas a diagram 0 is a DFD that depicts the first level of detail below the initial context diagram and shows major processes, data flows and data stores as well as repeating the external entities and data flows that appear in the context diagram. Data stores are not shown in the context diagram because they are contained within the system and remain hidden until more...
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...CHAPTER 1 What Is Financial Modelling? here are all sorts of complicated definitions of financial modelling, and in my experience there is quite a bit of confusion around what a financial model is exactly. A few years ago, we put together a Plum Solutions survey about the attitudes, trends, and uses of financial modelling, asked respondents “What do you think a financial model is?” Participants were asked to put down the first thing that came to mind, without any research or too much thinking about it. I found the responses interesting, amusing, and sometimes rather disturbing. Some answers were overly complicated and highly technical: n T n n n n “Representation of behaviour/real-world observations through mathematical approach designed to anticipate range of outcomes.” “A set of structured calculations, written in a spreadsheet, used to analyse the operational and financial characteristics of a business and/or its activities.” “Tool(s) used to set and manage a suite of variable assumptions in order to predict the financial outcomes of an opportunity.” “A construct that encodes business rules, assumptions, and calculations enabling information, analysis, and insight to be drawn out and supported by quantitative facts.” “A system of spreadsheets and formulas to achieve the level of record keeping and reporting required to be informed, up-to-date, and able to track finances accurately and plan for the future.” Some philosophical: n “A numerical...
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