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rgpv syllabus BTech Grading System 8th Semester Microsoft Word - CSBS_RGPV_8_sem_Syllabus
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB801 IT Project Management
Course Outcome(s):
Students will be able to
Learn activities involved in IT projects management.
Apply agile process to project management.
Plan application development using Scrum.
Develop abilities to use DevOps in projects.
Develop understanding of Containers use in projects.
UNIT – I
Project Overview and Feasibility Studies- Identification, Market and Demand Analysis, Project Cost Estimate, Financial Appraisal.
UNIT – II
Project Scheduling: Project Scheduling, Introduction to PERT and CPM, Critical Path Calculation, Precedence Relationship, Difference between PERT and CPM, Float Calculation and its importance, Cost reduction by Crashing of activity.
Cost Control and Scheduling: Project Cost Control (PERT/Cost), Resource Scheduling & Resource Leveling
Agile Project Management: Introduction, Agile Principles, Agile methodologies, Relationship between Agile Scrum, Lean, DevOps and IT Service Management (ITIL).
UNIT – IV
Scrum: Various terminologies used in Scrum (Sprint, product backlog, sprint backlog, sprint review, retro perspective), various roles (Roles in Scrum), Best practices of Scrum.
UNIT – V
DevOps: Overview and its Components, Containerization Using Docker, Managing Source Code and Automating Builds, Automated Testing and Test Driven Development, Continuous Integration, Configuration Management, Continuous Deployment, Automated Monitoring.
Other Agile Methodologies: Introduction to XP, FDD, DSDM, Crystal
Text Book(s):
Mike Cohn, “Succeeding with Agile: Software Development Using Scrum”, Addison Wesley, 2009
Pearson, Robert C. Martin, Juli, James Shore, “The Art Of Agile Development”, O'Reilly, 2013
John Hunt, “Agile Software Construction”, 1st Edition, Springer,2005
Roman Pichler, “Agile Product Management with Scrum”.
Ken Schwaber, “Agile Project Management with Scrum” (Microsoft Professional)
Andrew Stellman, Jenifer Greene, “Head First Agile”, Oreilly, 2017
Peggy Gregory, Casper Lassenius, Xiaofeng Wang Philippe Kruchten (Eds.), “Agile Processes in Software Engineering and Extreme Programming”, 22nd International Conference on Agile Software Development, XP 2021 Virtual Event, June 14–18, 2021, Proceedings, Springer
Joseph Phillips, IT Project Management: On Track from Start to Finish, 3rd Edition, McGraw-Hill, 2010
Clinton Keith, “Agile Game Development”, Addison Wesley, 2010
Scott M Graffius, “Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions”, CreateSpace, 2016
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB802-(A) Behavioral Economics
Course Outcome(s):
The student will be able to:
Gain an understanding on models in behavioral economics in relation with social sciences.
Understand the basics of choice theories along with cognitive neurosciences.
Demonstrate an understanding on beliefs, heuristics, biases and choices under uncertainty.
Analyse intertemporal choices and the applications.
Evaluate and analyse strategic choice, anomalies and its applications.
UNIT – I
Introduction: The neoclassical/standard model and behavioral economics in contrast; historical background; behavioral economics and other social sciences; theory and evidence in the social sciences and in behavioral economics; applications – gains and losses, money illusion, charitable donation.
UNIT – II
Basics of choice theory: Revisiting the neoclassical model; utility in economics and psychology; models of rationality; connections with evolutionary biology and cognitive neuroscience; policy analysis – consumption and addiction, environmental protection, retail therapy; applications – pricing, valuation, public goods, choice anomalies
UNIT – III
Beliefs, heuristics and biases: Revisiting rationality; causal aspects of irrationality; different kinds of biases and beliefs; self-evaluation and self-projection; inconsistent and biased beliefs; probability estimation; trading applications – trade in counterfeit goods, financial trading behavior, trade in memorabilia
Choice under uncertainty: Background and expected utility theory; prospect theory and other theories; reference points; loss aversion; marginal utility; decision and probability weighting; applications – ownership and trade, income and consumption, performance in sports.
UNIT – IV
Intertemporal choice: Geometric discounting; preferences over time; anomalies of inter-temporal decisions; hyperbolic discounting; instantaneous utility; alternative concepts – future projection, mental accounts, heterogeneous selves, procedural choice; policy analysis – mobile calls, credit cards, organization of government; applications – consumption and savings, clubs and membership, consumption planning
UNIT – V
Strategic choice: Review of game theory and Nash equilibrium – strategies, information, equilibrium in pure and mixed strategies, iterated games, bargaining, signalling, learning; applications – competitive sports, bargaining and negotiation, monopoly and market entry. Individual preferences; Choice anomalies and inconsistencies; social preferences; altruism; fairness; reciprocity; trust; learning; communication; intention; demographic and cultural aspects; social norms; compliance and punishment; inequity aversion; policy analysis – norms and markets, labor markets, market clearing, public goods; applications – logic and knowledge, voluntary contribution, compensation design.
Text Book(s):
N. Wilkinson and M. Klaes, An introduction to Behavioral Economics, Bloomsbury Publishing, 3rd edition, 2017.
Paul A. Samuelson, William D. Nordhaus, Sudip Chaudhuri and AnindyaSen, “Economics”, 19th edition, Tata McGraw Hill, 2010.
Robert H. Frank, 2014, “Microeconomics and Behaviour”, McGraw-Hill, 9th Edition, 2014.
Philip Corr, Anke Plagnol, “Behavioral Economics: The Basic”, Routledge, 1st edition, 2018.
Reference Book(s):
Tobias F. R., The Behavioral Economics of Inflation Expectations: Macroeconomics Meets Psychology, Cambridge University Press, 1st, 2020.
William Boyes and Michael Melvin, “Textbook of Economics”, DTECH, 6th Edition, 2004.
N. Gregory Mankiw, “Principles of Economics”, Thomson learning, 3rd Edition, 2003.
Richard Lipsey and Alec Charystal, “Economics”, Oxford, University Press, 12th Edition, 2011
Bazerman, Max and Don Moore. Judgment in Managerial Decision Making, 2012. 8th Edition, John Wiley & Sons.
Kahneman, Daniel.Thinking, Fast and Slow, 2011, New York: Farrar, Straus and Giroux
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB802-(B) Computational Finance & Modeling
Course Outcome(s):
The student will be able to:
Understand existing financial models in a quantitative and mathematical way.
Apply these quantitative tools to solve complex problems in the areas of portfolio management, risk management and financial engineering.
Explain the approaches required to calculate the price of options.
Identify the methods required to analyse information from financial data and trading systems
UNIT – I
Numerical Methods and Models: Numerical methods relevant to integration, differentiation and solving the partial differential equations of mathematical finance: examples of exact solutions including Black Scholes and its relatives, finite difference methods including algorithms and question of stability and convergence, treatment of near and far boundary conditions, the connection with binomial models, interest rate models, early exercise, and the corresponding free boundary problems, and a brief introduction to numerical methods for solving multi-factor models.
UNIT – II
Black-Scholes framework: Black-Scholes PDE: simple European calls and puts; put-call parity. The PDE for pricing commodity and currency options. Discontinuous payoffs - Binary and Digital options. The Greeks: theta, delta, gamma, vega&rho and their role in hedging. The mathematics of early exercise - American options: perpetual calls and puts; optimal exercise strategy and the smooth pasting condition. Volatility considerations - actual, historical, and implied volatility; local vol and volatility surfaces. Simulation including random variable generation, variance reduction methods and statistical analysis of simulation output. Pseudo random numbers, Linear congruential generator, Mersenne twister RNG. The use of Monte Carlo simulation in solving applied problems on derivative pricing discussed in the current finance literature. The technical topics addressed include importance sampling, Monte Carlo integration, Simulation of Random walk and approximations to diffusion processes, martingale control variables, stratification, and the estimation of the “Greeks. ”
UNIT – III
Financial Products and Markets: Introduction to the financial markets and the products which are traded in them: Equities, indices, foreign exchange, and commodities. Options contracts and strategies for speculation and hedging.
UNIT – IV
Application areas: Pricing of American options, pricing interest rate dependent claims, and credit risk. The use of importance sampling for Monte Carlo simulation of VaR for portfolios of options.
UNIT –V
Statistical Analysis of Financial Returns: Fat-tailed and skewed distributions, outliers, stylized facts of volatility, implied volatility surface, and volatility estimation using high frequency data. Copulas, Hedging in incomplete markets, American Options, Exotic options, Electronic trading, Jump Diffusion Processes, High-dimensional covariance matrices, Extreme value theory, Statistical Arbitrage.
References:
R. Seydel: Tools for Computational Finance, 2nd edition, Springer-Verlag, New York, 2004.
P. Glasserman: Monte Carlo Methods in Financial Engineering, Springer-Verlag, New York,2004.
Pelsser: Efficient Methods for Valuing Interest Rate Derivatives, Springer-Verlag, New York,2000.
M. Capinski and T. Zastawniak, Mathematics of Finance: An Introduction to Financial Engineering, Springer, 2010
S. M. Ross, An Elementary Introduction to Mathematical Finance, Cambridge University Press, 2011.
D. Ruppert, Statistics and Data Analysis for Financial Engineering
R. Carmona: Statistical Analysis of Financial Data in S-Plus
N. H. Chan, Time Series: Applications to Finance
R. S. Tsay, Analysis of Financial Time Series
J. Franke, W. K. Härdle and C. M. Hafner, Statistics of Financial Markets: An Introduction
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB802-(C) Industrial Psychology
Course Outcome(s):
Students will be able to
Become conversant about the major content areas of Industrial Psychology (i.e., job analysis, recruitment, selection, employment law, training, performance management, and health/well- being issues in the workplace).
Gain further comfort with statistical concepts in the context of making personnel decisions to reinforce content learned in introductory statistics course.
Gain practical experience by completing a series of hands-on projects involving job analysis, selection decisions, training programs, and employee well-being.
Deepen their understanding of tests and measurements so that you can collect accurate information and make sound data-based decisions.
Prepare for other focused seminar courses in Industrial/Organizational Psychology or Human Resource Management.
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB803-(A) Enterprise Systems
Course Outcome(s):
Students will be able to
Understand basic elements of Enterprise systems.
Understand implementation stages and processes of an ERP system.
Understand the process of integrating legacy systems and other current IT systems with an ERP system
Develop skills in understanding architecture and non-functional requirements in developing Enterprise system development and their deployment
Understand future trends in Enterprise architectures.
UNIT – I
Introduction to Modern Enterprise Systems: Introduction to enterprise systems. Elements of enterprise systems – Business Information system, Decision support systems, Knowledge management systems, Financial and human resource systems. Kinds of Enterprise systems- B2C and B2B models.
Components of Enterprise systems: Channels (Mobile, web, desktop, partner integration), Data management, workflow, Controlling and Auditing, Accounting etc.
Sample Enterprise systems: ERP, SCM, CRM, Product Life cycle management (PLM), HR Systems (HRM), GL systems.
Enterprise System architectures: Batch processing, Monolithic, client server, ecommerce, service oriented, microservice, and cloud architectures.
Introduction to Enterprise Application architectures: Layer Architecture, Event driven Architecture, Service oriented Architecture, Microservice architecture, Plug-in architecture.
UNIT – III
Application architecture Patterns: Layering, Organizing domain logic, Mapping to database, Web Presentation, Concurrency.
Enterprise Application Integration: Introduction to Enterprise Integration, different integration styles. Elements of messaging-based Integration.
Enterprise Integration patterns: Modern service integration techniques. Introduction to WSDL, SOAP. Introduction RESTFul webservices integration. Differences between SOAP and REST.
UNIT – IV
Deployment of Enterprise applications: Key requirements in deployment - Stability, capacity, Security, availability, Network, Availability, and Transparency (Basic Introduction only).
Concepts of Cloud computing, cloud platforms and their role in Enterprise systems: Core Concepts – Types of Cloud: Private, public, and Hybrid clouds. Advantage of cloud computing – Scaling, Availability, and cost. Disadvantages – Technology overload, Security, Monitoring and troubleshooting, Testing, Latency etc. Cloud service models: - Infrastructure, platform, Software as a Service in Cloud Computing. Major public clouds: Google cloud, AWS, Azure.
UNIT – V
Application development and deployment in cloud – Dockers, micro services, Kubernetes, Serverless. Continuous Integration/Continuous Delivery
Introduction to Enterprise Architecture: Importance of Enterprise Architecture. Enterprise architecture models. Zachman Framework, TOGAF Framework
Enterprise Architecture Case study: To be identified
Text Book(s):
Ralph Stair, George Reynold, “Principle of Information Systems”, 10 ed.
Martin Fowler et al, “Pattern of Enterprise Application Architecture”, Addison-Wesley, 2012
Gregor Hohpe, Bobby Woolf, Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions,
Mark Richards, Software Architecture patterns, 2015, O’Reilly.
Sam Newman, “Building Microservices”, 2015, O’Reilly.
David Farley, Jez Humble, “Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation”, Jan 2016
Software architecture in Practice 3rd Edition- 2014
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB803-(B) Advance Finance
Course Outcome(s):
Students will be able to
To provide understanding of essential terms, concepts and principles of strategic financial management
To build the required skills and ability to apply principles of strategic financial management for corporate decision making
To develop skills in students to use the techniques of planning and analysis
UNIT – I
Sources of Funds (including regulatory framework): Types of securities - Issuing the capital in market - Pricing of issue - Valuation of Stocks and bonds.
Evaluation of Lease Contracts: Leasing – Importance, Types, Tax Considerations, and Accounting Considerations – Evaluation of Lease from the point of view of Lessor and Lessee – Lease versus Buy Decision.
UNIT – II
Dividend Decisions: Traditional Approach, Dividend Relevance Model, Miller and Modigliani Model, Stability of Dividends, Forms of Dividends, Issue of bonus shares, Stock Split
UNIT – III
Restructuring
Corporate Restructuring: Mergers and Acquisitions- Types of Mergers, Evaluation of Merger Proposal, Take-overs, Amalgamation, Leverage buy-out, management buy-out, Corporate Failure and Liquidation.
Financial Restructuring: Share Split –Consolidation -Cancellation of Paid-up Capital -Other Mechanisms
UNIT – IV
Working Capital Management: Working Capital Management: Working Capital Planning - Monitoring and Control of Working Capital -Working Capital Financing ¬Managing the Components of Working Capital-Cash Management -Receivable Management -Inventory Management.
UNIT – VII
Introduction to derivatives: Basics of Futures, Forwards, Options, Swaps -Interest rate Payoff Diagrams, Pricing of Futures, Put Call Parity, Option Pricing using Binomial Model and Black Scholes Model -Use of Derivatives for Risk-Return Management- Credit Default Swaps.
Text Book(s):
Brealey, Myers and Allen, Principles of Corporate Finance
Reference Book(s):
Jonathan Berk, Peter DeMarzo, and Ashok Thampi, Financial Management, Pearson Education in South Asia,
Damodaran, Corporate Finance Theory and Practice, John Wiley & Sons
Rajiv Srivastava and Anil Misra, Financial Management, Oxford University Press
James C Van Horne, and John M. Wachowicz, Fundamentals of Financial Management, PHI
Kevin K. Boeh and Paul W. Beamish, Mergers and Acquisitions: Text and Cases, Sage Publications
John C Hull, Fundamentals of Futures and Options Markets, Cambridge University Press
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB803-(C) Image Processing and Pattern Recognition
Course Outcome(s):
Understand theoretical foundation and concepts of Digital Image Processing.
Apply the knowledge of different image enhancement, and image registration techniques.
Provide mathematical foundations for digital manipulation of images.
Describe the fundamental concepts of various feature extraction techniques and recognize the image scene from image feature.
Acquire the concepts of color image processing.
UNIT-I
Introduction: Image processing systems and its applications. Basic image file formats
Image formation: Geometric and photometric models; Digitization - sampling, quantization; Image definition and its representation, neighbourhood metrics.
UNIT-II
Intensity transformations and spatial filtering: Enhancement, contrast stretching, histogram specification, local contrast enhancement; Smoothing, linear and order statistic filtering, sharpening, spatial convolution, Gaussian smoothing, DoG, LoG.
Rafael C Gonzalez and Richard E Woods, "Digital Image Processing", 3rd Edition, Pearson Education
Maria Petrou and Panagiota Bosdogianni, "Image Processing: The Fundamentals", John Wiley & Sons, Ltd.
K. R. Castleman, "Digital Image Processing", Prentice Hall, Englewood Cliffs.
Blake and A. Zisserman, "Visual Reconstruction", MIT Press, Cambridge.
N. Netravali and B. G. Haskell, "Digital Pictures", Plenum Press.
Watson, "Digital Images and Human Vision", MIT Press, Cambridge.
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rgpv syllabus BTech Grading System 8th Semester Microsoft Word - CSBS_RGPV_8_sem_Syllabus
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB801 IT Project Management
Course Outcome(s):
Students will be able to
Learn activities involved in IT projects management.
Apply agile process to project management.
Plan application development using Scrum.
Develop abilities to use DevOps in projects.
Develop understanding of Containers use in projects.
UNIT – I
Project Overview and Feasibility Studies- Identification, Market and Demand Analysis, Project Cost Estimate, Financial Appraisal.
UNIT – II
Project Scheduling: Project Scheduling, Introduction to PERT and CPM, Critical Path Calculation, Precedence Relationship, Difference between PERT and CPM, Float Calculation and its importance, Cost reduction by Crashing of activity.
Cost Control and Scheduling: Project Cost Control (PERT/Cost), Resource Scheduling & Resource Leveling
Agile Project Management: Introduction, Agile Principles, Agile methodologies, Relationship between Agile Scrum, Lean, DevOps and IT Service Management (ITIL).
UNIT – IV
Scrum: Various terminologies used in Scrum (Sprint, product backlog, sprint backlog, sprint review, retro perspective), various roles (Roles in Scrum), Best practices of Scrum.
UNIT – V
DevOps: Overview and its Components, Containerization Using Docker, Managing Source Code and Automating Builds, Automated Testing and Test Driven Development, Continuous Integration, Configuration Management, Continuous Deployment, Automated Monitoring.
Other Agile Methodologies: Introduction to XP, FDD, DSDM, Crystal
Text Book(s):
Mike Cohn, “Succeeding with Agile: Software Development Using Scrum”, Addison Wesley, 2009
Pearson, Robert C. Martin, Juli, James Shore, “The Art Of Agile Development”, O'Reilly, 2013
John Hunt, “Agile Software Construction”, 1st Edition, Springer,2005
Roman Pichler, “Agile Product Management with Scrum”.
Ken Schwaber, “Agile Project Management with Scrum” (Microsoft Professional)
Andrew Stellman, Jenifer Greene, “Head First Agile”, Oreilly, 2017
Peggy Gregory, Casper Lassenius, Xiaofeng Wang Philippe Kruchten (Eds.), “Agile Processes in Software Engineering and Extreme Programming”, 22nd International Conference on Agile Software Development, XP 2021 Virtual Event, June 14–18, 2021, Proceedings, Springer
Joseph Phillips, IT Project Management: On Track from Start to Finish, 3rd Edition, McGraw-Hill, 2010
Clinton Keith, “Agile Game Development”, Addison Wesley, 2010
Scott M Graffius, “Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions”, CreateSpace, 2016
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB802-(A) Behavioral Economics
Course Outcome(s):
The student will be able to:
Gain an understanding on models in behavioral economics in relation with social sciences.
Understand the basics of choice theories along with cognitive neurosciences.
Demonstrate an understanding on beliefs, heuristics, biases and choices under uncertainty.
Analyse intertemporal choices and the applications.
Evaluate and analyse strategic choice, anomalies and its applications.
UNIT – I
Introduction: The neoclassical/standard model and behavioral economics in contrast; historical background; behavioral economics and other social sciences; theory and evidence in the social sciences and in behavioral economics; applications – gains and losses, money illusion, charitable donation.
UNIT – II
Basics of choice theory: Revisiting the neoclassical model; utility in economics and psychology; models of rationality; connections with evolutionary biology and cognitive neuroscience; policy analysis – consumption and addiction, environmental protection, retail therapy; applications – pricing, valuation, public goods, choice anomalies
UNIT – III
Beliefs, heuristics and biases: Revisiting rationality; causal aspects of irrationality; different kinds of biases and beliefs; self-evaluation and self-projection; inconsistent and biased beliefs; probability estimation; trading applications – trade in counterfeit goods, financial trading behavior, trade in memorabilia
Choice under uncertainty: Background and expected utility theory; prospect theory and other theories; reference points; loss aversion; marginal utility; decision and probability weighting; applications – ownership and trade, income and consumption, performance in sports.
UNIT – IV
Intertemporal choice: Geometric discounting; preferences over time; anomalies of inter-temporal decisions; hyperbolic discounting; instantaneous utility; alternative concepts – future projection, mental accounts, heterogeneous selves, procedural choice; policy analysis – mobile calls, credit cards, organization of government; applications – consumption and savings, clubs and membership, consumption planning
UNIT – V
Strategic choice: Review of game theory and Nash equilibrium – strategies, information, equilibrium in pure and mixed strategies, iterated games, bargaining, signalling, learning; applications – competitive sports, bargaining and negotiation, monopoly and market entry. Individual preferences; Choice anomalies and inconsistencies; social preferences; altruism; fairness; reciprocity; trust; learning; communication; intention; demographic and cultural aspects; social norms; compliance and punishment; inequity aversion; policy analysis – norms and markets, labor markets, market clearing, public goods; applications – logic and knowledge, voluntary contribution, compensation design.
Text Book(s):
N. Wilkinson and M. Klaes, An introduction to Behavioral Economics, Bloomsbury Publishing, 3rd edition, 2017.
Paul A. Samuelson, William D. Nordhaus, Sudip Chaudhuri and AnindyaSen, “Economics”, 19th edition, Tata McGraw Hill, 2010.
Robert H. Frank, 2014, “Microeconomics and Behaviour”, McGraw-Hill, 9th Edition, 2014.
Philip Corr, Anke Plagnol, “Behavioral Economics: The Basic”, Routledge, 1st edition, 2018.
Reference Book(s):
Tobias F. R., The Behavioral Economics of Inflation Expectations: Macroeconomics Meets Psychology, Cambridge University Press, 1st, 2020.
William Boyes and Michael Melvin, “Textbook of Economics”, DTECH, 6th Edition, 2004.
N. Gregory Mankiw, “Principles of Economics”, Thomson learning, 3rd Edition, 2003.
Richard Lipsey and Alec Charystal, “Economics”, Oxford, University Press, 12th Edition, 2011
Bazerman, Max and Don Moore. Judgment in Managerial Decision Making, 2012. 8th Edition, John Wiley & Sons.
Kahneman, Daniel.Thinking, Fast and Slow, 2011, New York: Farrar, Straus and Giroux
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB802-(B) Computational Finance & Modeling
Course Outcome(s):
The student will be able to:
Understand existing financial models in a quantitative and mathematical way.
Apply these quantitative tools to solve complex problems in the areas of portfolio management, risk management and financial engineering.
Explain the approaches required to calculate the price of options.
Identify the methods required to analyse information from financial data and trading systems
UNIT – I
Numerical Methods and Models: Numerical methods relevant to integration, differentiation and solving the partial differential equations of mathematical finance: examples of exact solutions including Black Scholes and its relatives, finite difference methods including algorithms and question of stability and convergence, treatment of near and far boundary conditions, the connection with binomial models, interest rate models, early exercise, and the corresponding free boundary problems, and a brief introduction to numerical methods for solving multi-factor models.
UNIT – II
Black-Scholes framework: Black-Scholes PDE: simple European calls and puts; put-call parity. The PDE for pricing commodity and currency options. Discontinuous payoffs - Binary and Digital options. The Greeks: theta, delta, gamma, vega&rho and their role in hedging. The mathematics of early exercise - American options: perpetual calls and puts; optimal exercise strategy and the smooth pasting condition. Volatility considerations - actual, historical, and implied volatility; local vol and volatility surfaces. Simulation including random variable generation, variance reduction methods and statistical analysis of simulation output. Pseudo random numbers, Linear congruential generator, Mersenne twister RNG. The use of Monte Carlo simulation in solving applied problems on derivative pricing discussed in the current finance literature. The technical topics addressed include importance sampling, Monte Carlo integration, Simulation of Random walk and approximations to diffusion processes, martingale control variables, stratification, and the estimation of the “Greeks. ”
UNIT – III
Financial Products and Markets: Introduction to the financial markets and the products which are traded in them: Equities, indices, foreign exchange, and commodities. Options contracts and strategies for speculation and hedging.
UNIT – IV
Application areas: Pricing of American options, pricing interest rate dependent claims, and credit risk. The use of importance sampling for Monte Carlo simulation of VaR for portfolios of options.
UNIT –V
Statistical Analysis of Financial Returns: Fat-tailed and skewed distributions, outliers, stylized facts of volatility, implied volatility surface, and volatility estimation using high frequency data. Copulas, Hedging in incomplete markets, American Options, Exotic options, Electronic trading, Jump Diffusion Processes, High-dimensional covariance matrices, Extreme value theory, Statistical Arbitrage.
References:
R. Seydel: Tools for Computational Finance, 2nd edition, Springer-Verlag, New York, 2004.
P. Glasserman: Monte Carlo Methods in Financial Engineering, Springer-Verlag, New York,2004.
Pelsser: Efficient Methods for Valuing Interest Rate Derivatives, Springer-Verlag, New York,2000.
M. Capinski and T. Zastawniak, Mathematics of Finance: An Introduction to Financial Engineering, Springer, 2010
S. M. Ross, An Elementary Introduction to Mathematical Finance, Cambridge University Press, 2011.
D. Ruppert, Statistics and Data Analysis for Financial Engineering
R. Carmona: Statistical Analysis of Financial Data in S-Plus
N. H. Chan, Time Series: Applications to Finance
R. S. Tsay, Analysis of Financial Time Series
J. Franke, W. K. Härdle and C. M. Hafner, Statistics of Financial Markets: An Introduction
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB802-(C) Industrial Psychology
Course Outcome(s):
Students will be able to
Become conversant about the major content areas of Industrial Psychology (i.e., job analysis, recruitment, selection, employment law, training, performance management, and health/well- being issues in the workplace).
Gain further comfort with statistical concepts in the context of making personnel decisions to reinforce content learned in introductory statistics course.
Gain practical experience by completing a series of hands-on projects involving job analysis, selection decisions, training programs, and employee well-being.
Deepen their understanding of tests and measurements so that you can collect accurate information and make sound data-based decisions.
Prepare for other focused seminar courses in Industrial/Organizational Psychology or Human Resource Management.
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB803-(A) Enterprise Systems
Course Outcome(s):
Students will be able to
Understand basic elements of Enterprise systems.
Understand implementation stages and processes of an ERP system.
Understand the process of integrating legacy systems and other current IT systems with an ERP system
Develop skills in understanding architecture and non-functional requirements in developing Enterprise system development and their deployment
Understand future trends in Enterprise architectures.
UNIT – I
Introduction to Modern Enterprise Systems: Introduction to enterprise systems. Elements of enterprise systems – Business Information system, Decision support systems, Knowledge management systems, Financial and human resource systems. Kinds of Enterprise systems- B2C and B2B models.
Components of Enterprise systems: Channels (Mobile, web, desktop, partner integration), Data management, workflow, Controlling and Auditing, Accounting etc.
Sample Enterprise systems: ERP, SCM, CRM, Product Life cycle management (PLM), HR Systems (HRM), GL systems.
Enterprise System architectures: Batch processing, Monolithic, client server, ecommerce, service oriented, microservice, and cloud architectures.
Introduction to Enterprise Application architectures: Layer Architecture, Event driven Architecture, Service oriented Architecture, Microservice architecture, Plug-in architecture.
UNIT – III
Application architecture Patterns: Layering, Organizing domain logic, Mapping to database, Web Presentation, Concurrency.
Enterprise Application Integration: Introduction to Enterprise Integration, different integration styles. Elements of messaging-based Integration.
Enterprise Integration patterns: Modern service integration techniques. Introduction to WSDL, SOAP. Introduction RESTFul webservices integration. Differences between SOAP and REST.
UNIT – IV
Deployment of Enterprise applications: Key requirements in deployment - Stability, capacity, Security, availability, Network, Availability, and Transparency (Basic Introduction only).
Concepts of Cloud computing, cloud platforms and their role in Enterprise systems: Core Concepts – Types of Cloud: Private, public, and Hybrid clouds. Advantage of cloud computing – Scaling, Availability, and cost. Disadvantages – Technology overload, Security, Monitoring and troubleshooting, Testing, Latency etc. Cloud service models: - Infrastructure, platform, Software as a Service in Cloud Computing. Major public clouds: Google cloud, AWS, Azure.
UNIT – V
Application development and deployment in cloud – Dockers, micro services, Kubernetes, Serverless. Continuous Integration/Continuous Delivery
Introduction to Enterprise Architecture: Importance of Enterprise Architecture. Enterprise architecture models. Zachman Framework, TOGAF Framework
Enterprise Architecture Case study: To be identified
Text Book(s):
Ralph Stair, George Reynold, “Principle of Information Systems”, 10 ed.
Martin Fowler et al, “Pattern of Enterprise Application Architecture”, Addison-Wesley, 2012
Gregor Hohpe, Bobby Woolf, Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions,
Mark Richards, Software Architecture patterns, 2015, O’Reilly.
Sam Newman, “Building Microservices”, 2015, O’Reilly.
David Farley, Jez Humble, “Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation”, Jan 2016
Software architecture in Practice 3rd Edition- 2014
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB803-(B) Advance Finance
Course Outcome(s):
Students will be able to
To provide understanding of essential terms, concepts and principles of strategic financial management
To build the required skills and ability to apply principles of strategic financial management for corporate decision making
To develop skills in students to use the techniques of planning and analysis
UNIT – I
Sources of Funds (including regulatory framework): Types of securities - Issuing the capital in market - Pricing of issue - Valuation of Stocks and bonds.
Evaluation of Lease Contracts: Leasing – Importance, Types, Tax Considerations, and Accounting Considerations – Evaluation of Lease from the point of view of Lessor and Lessee – Lease versus Buy Decision.
UNIT – II
Dividend Decisions: Traditional Approach, Dividend Relevance Model, Miller and Modigliani Model, Stability of Dividends, Forms of Dividends, Issue of bonus shares, Stock Split
UNIT – III
Restructuring
Corporate Restructuring: Mergers and Acquisitions- Types of Mergers, Evaluation of Merger Proposal, Take-overs, Amalgamation, Leverage buy-out, management buy-out, Corporate Failure and Liquidation.
Financial Restructuring: Share Split –Consolidation -Cancellation of Paid-up Capital -Other Mechanisms
UNIT – IV
Working Capital Management: Working Capital Management: Working Capital Planning - Monitoring and Control of Working Capital -Working Capital Financing ¬Managing the Components of Working Capital-Cash Management -Receivable Management -Inventory Management.
UNIT – VII
Introduction to derivatives: Basics of Futures, Forwards, Options, Swaps -Interest rate Payoff Diagrams, Pricing of Futures, Put Call Parity, Option Pricing using Binomial Model and Black Scholes Model -Use of Derivatives for Risk-Return Management- Credit Default Swaps.
Text Book(s):
Brealey, Myers and Allen, Principles of Corporate Finance
Reference Book(s):
Jonathan Berk, Peter DeMarzo, and Ashok Thampi, Financial Management, Pearson Education in South Asia,
Damodaran, Corporate Finance Theory and Practice, John Wiley & Sons
Rajiv Srivastava and Anil Misra, Financial Management, Oxford University Press
James C Van Horne, and John M. Wachowicz, Fundamentals of Financial Management, PHI
Kevin K. Boeh and Paul W. Beamish, Mergers and Acquisitions: Text and Cases, Sage Publications
John C Hull, Fundamentals of Futures and Options Markets, Cambridge University Press
RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL
New Scheme Based On AICTE Flexible Curricula
VIII Semester
Bachelor of Technology (B. Tech.) - Computer Science and Business Systems (CSBS)
CB803-(C) Image Processing and Pattern Recognition
Course Outcome(s):
Understand theoretical foundation and concepts of Digital Image Processing.
Apply the knowledge of different image enhancement, and image registration techniques.
Provide mathematical foundations for digital manipulation of images.
Describe the fundamental concepts of various feature extraction techniques and recognize the image scene from image feature.
Acquire the concepts of color image processing.
UNIT-I
Introduction: Image processing systems and its applications. Basic image file formats
Image formation: Geometric and photometric models; Digitization - sampling, quantization; Image definition and its representation, neighbourhood metrics.
UNIT-II
Intensity transformations and spatial filtering: Enhancement, contrast stretching, histogram specification, local contrast enhancement; Smoothing, linear and order statistic filtering, sharpening, spatial convolution, Gaussian smoothing, DoG, LoG.