Modeling Financial Processes and Systems (CS 398A)








CS 397N; or equivalent, or instructor’s permission




1.       J. Lawler and H. Howell-Barber, Service Oriented Architecture: SOA Strategy, Methodology, and Technology, Bacon Raton, FL: Auerbach Publications, 2008

2.       K. Kim, Electronic and Algorithmic Trading Technology: A complete Guide, New York, NY: Academic Press/Elsevier 2007

3.       I. Aldridge, High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems, New York, NY: John Wiley & Sons, 2009

4.       B. Franks, Taming the Big data Tidal Wave, Hoboken, NJ: John Wiley & Sons, 2012



1.       Entrepreneur and Inc Magazines

2.       T. Byers, R. Dorg, & Q. Nelson, Technology Ventures: From Ideas to Enterprise, 3rd edition, McGraw Hill, 2011.

3.       J. Edmonds, How to Think about Algorithms, New York: Cambridge University Press, 2008

4.       Research papers

5.       Internet





Fall 2012



Course Description: Modeling of Financial Processes and systems through Technologies is a course that defines a program management methodology for modeling processes and services through service-oriented architecture (SOA) technologies as well as algorithmic and high frequency trading inclusive of the concepts of big data. The course is project-based and will include case studies of business firms applying or not applying entrepreneurship frameworks of the methodology on modeling processes empowered by SOA technologies, tools and utilities; efficacy and utility of electronic and algorithmic trading; and use of big data to better understand business processes and systems. The course concerns business fundamentals in the modeling of processes and systems through SOA technologies, big data analytics, and algorithmic and high frequency trading. Entrepreneurs for team mentors, project selection and scaling, and guest speakers will be used to provide an industry practical orientation to the course to complement the theoretical underpinnings.


Learning Objectives and Outcomes

Each team and students and expected to accomplish the following by the end of the course:


  1. Learn the correlation of business process management, entrepreneurship, enterprise architecture, program management methodology and service-oriented architecture (SOA) technology


  1. Learn the entrepreneurship frameworks of program management methodology as applied or not applied in firms in industry in modeling new products, processes and services of an inherently financial nature in projects of SOA technology


  1. Learn the business fundamentals of SOA technology as they empower an entrepreneurship strategy


  1. Learn the entrepreneurship opportunities that exist with market inefficiency and the profit incentives available at different frequencies as well as with the type of strategies employed in algorithmic trading of different assets


  1. Understand the concept of big data and its entrepreneurial value as it pertains to financial analytic processes and criterion based analysis


  1. Demonstrate the ability to transfer knowledge between theory and practice and vice versa



Tentative Examination Schedule:


Course Section

Project Deliverable Dates

Project Submissions & Presentation

Final Exam Date

CS 398A/CRN: 73239

[9/13], 9/20, 10/4, 10/25,  11/8, 11/29//2012

December 6, 2012

December 13, 2012


Class meeting Schedule


Course Section

Day, Time, and Location of Class Sessions

First and Last Day of Class

CS 398A/CRN: 73239

 Thursday: 6:00pm – 8:45pm;

First class: September 5, 2012

Last class: December 21, 2012


Note 1: This course is interdisciplinary with knowledge content from computing, finance, and entrepreneurship. It involves applying computing and entrepreneurship knowledge and skills to financial problems anchored in big data with the purpose to produce a new or enhanced product, process, or service. To accomplish this task, students will develop generic skills in teamwork, problem-solving, project management, and communication through cooperation, collaboration, and project-based learning.


Note 2: To facilitate and promote learning, you are encouraged to download the lectures from Blackboard and study them along with the material in the textbooks and any other relevant sources including the mentor. All lessons will be posted on Blackboard within a week of the lesson being introduced. Use the textbooks and other suggested sources to complement and perhaps, at times, expand and elucidate ideas presented in the lecture notes. Note that mere reading is not studying.


Note 3: The course is structured around the project-based learning strategy including some combination of such techniques as those highlighting active learning, inquiry-based lecture-discussion and problem based learning, collaborative learning and problem-solving. There will be many opportunities to develop salient practice problem solving skills with currency in industry throughout the course. To get the most out of the course, you are encouraged to follow and keep up with the reading assignments and genuinely determine its merit relative to your project. For those problems you cannot solve, determine the nature of your difficulty and bring it up in class or during office hours. The idea is to come to class prepared and willing to learn as well as ready to ask questions about the course materials and project/problem. You will be tested individually and as teams at the beginning of each major phase of course, which is about five times. The mantra of this course is learning, learning, learning and more learning!


Note 4: In the interest of learning, it is very important that you foster an inquisitive mind – do all the required assignments. Failing to do so may diminish your ability to get the most out of each class and the course. Studying is NOT mere reading of the textbook, class notes, and PowerPoint slides, it’s an intimate interaction between you and the information provided to you in the class notes, PowerPoint slides, and the textbook; it requires mindfulness on your part of the information provided to you.




Note 5: Learning is the central objective of this course; teaching and training will be done to facilitate your learning.


Note 6: Learning can be described as a rich, purposeful, complex, developmental, transformational, active and interactive, personal and social, reflective, natural and life-long, implicit, contextual, multilevel, measurable, and somewhat unpredictable process that is deeply impacted by the cultural, structural, and leadership factors of the organization. When someone reflects on their learning and put it into a context with what was previously learnt, he/she is able to gain new knowledge.


Note 7: It is very important you read and familiarize yourself with SCSIS Statement of Student Responsibilities (see Blackboard).


Note 8: You should devote at least 8 hours per week to prepare for this course – more may be needed depending on your rate of learning to sufficiently understand the course content and apply its principles as well as being successful achieving a meaningful grade.


Note 9: You are strongly encouraged to spend an appropriate length of time to research, develop, and implement the project and submit its deliverables in a timely manner; during the problem definition, scoping, design, development, and implementation process seek my help as well as the help of your mentor as needed to resolve any issue you may encounter. Your project should reflect thoughts and input of each person on the team; make sure that you thoroughly understand the project assignment; and you should build the service and product of the project based on sound theory and practical knowhow.


Note 10: Entrepreneurial Product Development Model[1]: The development of a new product is a nonlinear iterative process involving constant fine-tuning because of the many feedback loops. The fine-tuning is done to the technology, product, application, service, or process to the point of commercial readiness.  Roadblocks and speed-bumps include (1) fear of the unknown -- Is there something novel or patentable? (2) What is the level of demand and the adoption pattern? (3) No market knowledge – Is there a customer and a compelling need? (4) Launch strategy – License? Start a company? Be acquired? (5) Find the right application --Is there a potential source of funding for prototyping? (6) Difficulty of moving from laboratory to company.


New technology product development process

1.       Invention or discovery

2.       Initial concept

3.       Feasibility analysis and the business case

4.       Pre-development financial analysis

5.       Design and development of platform prototype

6.       Testing and validation

7.       Design and development of commercial application

8.       In-house product test and limited market test

9.       Pre-launch business plan






Dr. A. Joseph



163 Williams St., 2nd floor, room 231



212 346 1492


Office Hours:


Wednesday: 9:00am – 2:00pm





Grading Policy


Project (including prototype and Business Plan):



New Business Pitch:



Teamwork/class participation:

Journal (Due weeks: 3, 6, 9, & 12):

Collaboration and meetings with Mentors:



10% [9/20, 10/18, 11/8, & 12/6/2012]




[None other than the project]

In-class examinations:


5 project deliverables [9 points each – 9/20, 10/4, 10/25, 11/8, & 11/29/2012]

Final examination:



Team’s Average Performance [Bonus]:

Above 86%:

76% -- 86%:

65% -- 75%:

Below 65%:


0 -- 10%










Final Grade Determination


Above 92

90% -- 92%



87% -- 89%



83% -- 86%



80% -- 82%



77% -- 79%



70% -- 76%



65% -- 69%



60% -- 64%



Below 60%






Note: Grade is computed to the nearest whole number.



Note: SCSIS Student Responsibilities statement is attached to this syllabus.





Week #1-3

A.      Big Data: Meaning; relative difference; risks; structure; exploration, filtering, and integration with other data; an example of what web data reveals about customers (e.g., shopping behaviors, purchasing patterns and preferences,  and feedback behaviors); producing great analysis (analysis versus reporting, making analysis great, core versus advanced analytics, framing the problem correctly, statistical significance and inferences versus business importance).


B.      Project: Orientation to and discussion of project assignment; collaborative learning, project-based learning, and team dynamics; collection of student information for team formation; overview of the creative and innovative processes and ways to improve them; and protecting one’s ideas through patents, trademarks, and copyrights.


C.      Assignment 1a: Individual student project idea and brief class presentation of it (in week 2)

Assignment 1b: Introduction to and follow-up with mentor to discuss the project idea and its scope if it is to be completed on schedule (in week 2)



Week #3-5

A.      Service Oriented Architecture Strategy and Methodology: Business process management; enterprise architecture; innovation and entrepreneurship; program management methodology; entrepreneurship frameworks of program management methodology; and governance, communication, and modeling of web services in a life insurance firm and in an investment banking firm


B.      Project: Team project presentation and project approval; strategic problem solving techniques; case studies of algorithmic solutions to practical problems; overview of the elements of an effective business plan; plan and design an algorithmic solution to a financial problem with big data; develop an effective marketing plan; and entrepreneurship, creativity, and innovation.


C.      Assignment 2a: Guest lecturer – Creativity, innovation and entrepreneurship, and elements of an effective business plan (in week 3)

Assignment 2b: Team project idea presentation, submission, and approval as well as the role and function of each team member on a team (in week 3)

Assignment 2c: Begin work on project (in week 4)

Assignment 2d: Meeting with mentor (in week 5)



Week #6-9

A.      Financial Markets, Trading Process, Instruments, and Institutional Trading: Exchanges and floor markets; over the counter markets and alternative trading systems; decline of brick and mortar; crossing networks and upstairs markets; quotation, inter-markets and clearing systems; brokerage operations; fixed income securities and money markets; markets around the world; currency exchange and markets; institutions and market impact; registered and unregistered investments companies; best execution, execution costs, and price improvement; algorithmic trading; dark pools; stealth and sunshine trading; and high frequency trading


B.      Project: Continue with work on project (algorithmic problem solving – design and development of prototype); preprocessing of raw data; develop an understanding of financial statements and prepare a financial plan; develop and present idea of a new business to the professor and mentor; academic, technical, and moral supports to teams; and guest speaker


C.      Assignment 3a: Regular meetings with mentors (in weeks 7 and 9)

Assignment 3b: Guest Lecturer -- Understanding financial statements and preparing a financial plan for inclusion into a business plan as well as technical support for teamwork and develop pitch of new business (in weeks 6 and 9)

Assignment 3c: Project update – team project presentation of progress report (in weeks 6 and 9)



Week #10-11

A.      High Frequency, Electronic, and Algorithmic Trading: Market inefficiency and profit opportunities at different frequencies; working with tick data; algorithmic strategies; program and algorithmic trading for different assets classes; and entrepreneurial advantages of algorithmic trading and possibilities from trading at different frequencies


B.      Prototype of algorithmic solution for problem of project assignment completed and presented to class for review and feedback from class and the professor; teams contemplate how to implement the algorithm in software; teams are aware of how the resulting software product of the algorithmic solution to the identified problem would test on real data as well as the implications of such testing; and case study of information technology entrepreneurship.


C.      Assignment 4a: Meeting with mentors (in week 11)

Assignment 4b: Project update – team project presentation of progress report (in week 11)

Assignment 4c: Guest Lecturer – pitching a new business idea to potential investors in hopes of receiving seed funding (in week 11)




Week # 12

A.      Project: Completion of implementation of algorithmic solution to the financial big data problem of the project and the related business plan; have reasonable expectation of how the resulting software product from the prototype algorithm would perform on real data, as well as the evaluation and feedback on the completed prototype of the algorithm and business plan from professor and mentors; and case study of information technology entrepreneurship.


B.      Assignment 5a:Meeting with mentors and share completed project with mentors and solicit their feedback

Assignment 5b: Prepare project presentation and complete product documentation



Week # 13

Project presentation and pitch of the business plan as well as submission of project report in the form of a well-conceived business plan and learning journal inclusive of product documentation.



Week #14

Final exam




Note: All presentations and submissions of project must include Microsoft PowerPoint presentation; supplementary documentation may also be included if your team deem it necessary to enhance your presentation.





Note 1: This course is structured around small collaborative teams in a cooperative project-based learning environment. A main objective of the course is to have heterogeneous teams of mixed gender and of different academic, experiential, cultural, and ethnic backgrounds work together to develop a software financial service or product (up to the algorithm stage) with market potential. Students are encouraged to work together in their respective teams to form effective and very productive entrepreneurial enterprises that share the learning experience within the context of the course and its expected outcome, help each other with learning difficulties, and spend sufficient time to get to know each other. Each team member is expected to partake in the research, problem identification, and decision making of its team project and is responsible for the project’s successful completion and submission. Importantly, a condition for a project’s approval is that through the advice of industry experts, a team will identify and consult with companies in need of a solution to its chosen problem.  Each team member will be individually graded in proportion to his or her contribution to the project. Team members must budget their available time to ensure that they can devote the necessary amount of time needed to successfully complete the project in accordance with the deliverable dates.


Note 2: During the first class session, student background information will be collected for the purpose of forming the teams and assessing students’ knowledge of the relevant subject areas. Students will be placed in teams by the second class meeting. These are entrepreneurial teams in training that are analogous to progressive small business enterprises and as such may assign itself a name.


Note 3: Provisions will be made to have the completed projects posted on a website specifically designed for this purpose.


Note 4: To ensure that each team completes its project in a timely fashion, a strict time schedule will be followed. There will be deliverable dates for each team to have specific components of the project completed in the form of problem definition, scoping the problem, algorithmic problem solution, documentation, and development of technology company business plan. 


Teams: Each team will consist of three to four students who will participate in the necessary research, planning, design, and development of the team’s project and associated technology business plan. The prototyped product or service algorithm resulting from the project must be done such that it can be easily implemented using a high-level programming language. In addition, each team will maintain proper documentation of all activities relating to the project including a business plan, marketing plan, and a financial statement for the associated computing technology company. There will also be a website devoted to the course.


Web support: This course will be supported with Blackboard postings of instruction and guidelines pertaining to the course as well as short class presentations, small business related news, team and class discussions, email correspondence about the course, questions relating to individual projects, and miscellaneous course related activities and information. 


Supplementary materials: There will be handouts in class or web postings of current events and issues that affect Modeling Financial Processes and Systems.  Some books that might be helpful for the course will be posted on Blackboard along with links to pertinent websites.


Entrepreneurship, creativity, and innovation


Who creates a new activity in the face of risk and uncertainty for the purpose of achieving success and growth by identifying opportunities and putting together the required resources to benefit from them?


Creativity is the ability to develop new ideas and to discover new ways to of looking at problems and opportunities


Innovation is the ability to apply creative solutions to those problems and opportunities to enhance or to enrich people’s lives.


Entrepreneurial mindset: Each student is required to take an entrepreneur personality test during the first week of class and again, during the last week of class. The entrepreneur personality pre-test will be used to assist in the team formation.


What is your team’s name?


What is your team’s average entrepreneur personality score?



[1] K. Allen (2010). Entrepreneurship for Scientists and Engineers, Pearson Prentice Hall.