Certificate Program in Financial Engineering

Module No.	Module Name		Details		Type
Primer 1	Introduction to Investment Finance		Finance and Financial Institutions Capital Markets Debt Markets Introduction to Derivatives Markets		Optional
Primer 2	Introduction to Financial Mathematics		Introduction to Linear Algebra Introduction to Differential Calculus Introduction to Integral Calculus Introduction to Ordinary Differential Equations		Optional
Primer 3	Introduction to Probability & Statistics		Introduction to Probability Probability Distributions Descriptive and Inferential Statistics		Optional
Primer 4	Introduction to Programming		Programming in Python		Optional
Module 101	Introduction to Financial Engineering		Introduction to Financial Economics Introduction to Bond Mathematics Options Fundamentals Introduction to Exotic Options		Compulsory
Module 102	Financial Mathematics		Probability Theory Basic Stochastic Processes Brownian Motion Stochastic Calculus Black-Scholes-Merton Model		Compulsory
Module 103	Machine Learning for Quantitative Finance		Regression Models Time Series Models Volatility Forecasting		Compulsory
Module 104	Numerical Methods		Numerical Methods for Partial Differential Equations Monte Carlo Simulation Methods		Compulsory
Module 105	Derivatives Valuations 1		Equity Derivatives Currency Derivatives		Compulsory
Module 106	Derivatives Valuations 2		Interest Rate Derivatives Credit Derivatives		Compulsory
Module 107	Risk Analytics		Introduction to Financial Risk Market Risk Credit Risk Operational and Compliance Risk		Compulsory

Course duration
Main Modules	320 Hours (7 Compulsory Modules)
Primers	Each primer is of approx. 40 Hours duration. Students gets free access to recordings of all 4 Primers on course registration.
Course schedule	Saturdays and Sundays (5 Hours per day)

Course Fee	INR 155,000/- USD 2400

Location	Batch	Start Date
Live Online	Fall 2021	4th December, 2021

Modern Investment Finance is hugely dependent on the implementations of the theories and techniques of financial engineering. Financial Engineering, or Quantitative Finance as it is alternately known, is a multidisciplinary field involving the application of theories from financial economics, physics, mathematics, probability, statistics, operations research and econometrics using the methods and tools of engineering and the practice of computer programming to solve the problems of Investment Finance.

Generally the language of choice for Quant implementations traditionally has been C++ along with tools like Matlab, Mathematica, Stata, etc. However of late Python language have become more popular.

Financial Engineering has emerged as a very prospective career prospect for people with strong mathematical background like those coming from engineering, mathematics, statistics, physics or econometrics background. The best of the global financial institutions like Investment Banks, Hedge Funds, etc. hire people having strong quantitative skills for “Quant” jobs. This is also a very rewarding and exciting career option for such people as there is ample scope for applying their numerical and creative skills to design new things, be it like devising new investment strategies or be it structuring new financial instruments or be it finding methods to value them. They are continuously competing with their peers and some of the best of minds in the market and have to out-perform them to generate superior returns, which is intellectually a very challenging work, and this makes it all the more thrilling.

The Certificate Program in Financial Engineering (CP-FE) prepares students for technically sophisticated jobs with financial institutions, financial service providers, financial consulting services and financial software companies. The program is intended for students seeking comprehensive technical knowledge of vanilla and exotic derivatives pricing, hedging, trading and investment strategies and portfolio management in equity, currency, interest rates, credit and mortgages.

This is a short-term course that requires seven months of study for the core modules, which makes it attractive to students with strong quantitative skills who are willing to make a quick head start in the investment finance industry. The applied nature of the program implies the fact that there is great emphasis in it to impart the practical implementation skills and techniques that are actually used by practitioners in top financial institutions in the industry, so a considerable part of the course time is devoted to teaching implementation skills along with rigorous theoretical discourse.

As an applied discipline, financial institutions look for the following skill sets in the candidates for positions in their Quant teams :

Strong quantitative background

Sound knowledge of the underlying financial theories

Very good implementation skills

This course is designed specifically to meet these exact needs. This is a course on modelling and applications of mathematics, statistics and econometrics in investment finance. The program covers the all the technical and quantitative aspects of investment finance used in top financial institutions.

The combination of skills imparted through this program viz. understanding of complex financial theories, rigorous exposure to the underlying mathematical and statistical theories, practical financial modeling ability and computer implementation proficiency, is in high demand in the industry, and which the employers do not generally find in graduates of standard MBA or engineering programs.

What You Study

Participants learn Stochastic Calculus, Numerical Techniques, Monte Carlo Simulation, Derivative Valuations and Derivatives Trading Strategies which are used in Investment Finance by professionals in the field and how to implement them in practice. They study the underlying financial theories like financial economics, portfolio theory, derivatives pricing models. Then they learn to write financial application programs making use of the theories and methods they have learned for valuations of Vanilla and Exotic Derivatives on equities, currency, interest rates, etc.

Who Should Attend

Finance Professionals like Analysts / Fund Managers / Traders / Risk Professionals / Fund Accountants / Consultants / Derivatives structurers / Dealers / Arbitrageurs

Software professionals.

Graduate students.

Eligibility Requirements

Undergraduate degree in engineering / mathematics / statistics / physics / finance / economics / econometrics / chartered accountancy / computer science / MBA / CFA / FRM / PRM.

Applicants in their final year bachelor's/master's degree course (as applicable) are also eligible to apply.

Faculty

Dr. Amit Ram Vice President, Quantitative Risk Ph.D. (Statistical Physics and Computational Methods) Stanford University (USA) B. Tech. (Engineering Physics) IIT (Bombay) Over 10 years of experience working in Lehman Brothers (New York), JP Morgan Chase (New York), Standard Chartered (Singapore), Nomura (Mumbai)

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Dr. Samir Ranjan Associate Professor and Director Integrated MBA Ph.D. (Theoretical Physics) Purdue University (USA) MS (Mathematical Finance) Columbia University (New York) Over 10 years of experience working as Financial Engineer with Bonddesk Group in New Jersey (USA)

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Dr. Narayana Darapaneni Adjunct Faculty IIT-Bhubaneshwar Chief Data Scientist, Data Science Engineering Solutions Ph.D. (Mathematics) University of Paris VI (France) and Indian Institute of Science (Bangalore, India) M.S. (Mathematics) Pondicherry University (India) Over 9 years of industry and 3 years of academic research experience

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Dr. Debashis Guha Founder and Managing Director, Big Sky Quantitative Research Pvt. Ltd Ph.D. (Operations Research) Columbia University (New York, USA) M.A. (Physics) Texas Christian University (Texas, USA) B.Tech. (Electronics and Communication Engineering) IIT (Kharagpur) Over 25 years of experience working and teaching as a Quantitative Finance professional and economist in New York

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Kalyan Roy Electronic Trading Quantitative Analyst with Nomura Doctoral Studies and Research in Mathematical Statistics and Probability Indiana University Bloomington (USA) M. Stat. Indian Statistical Institute (Kolkata) B. Stat. (Hons.) Indian Statistical Institute (Kolkata) Over 18 years of experience working in the industry as Quantitative Analyst at Citibank, Bank One and IMS Health in the USA, Nomura, Capital Metrics & Risk Solutions, Deep Value Solutions, IMRB and Symphony Services in India

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Ritesh Chandra Executive Vice President – Corporate Credit Risk MBA IIM Calcutta B. Tech. IIT Kanpur and CFA (Level 3 Pass) More than 11 years of experience in Credit Risk, Corporate Finance & Technology and has worked in India, China and Canada in a variety of roles

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Career Opportunities

Modern Investment Management has become very much mathematical and statistical in nature, it is now much more of science than arts, specially where investments in complex financial instruments and complex trading/investment strategies are concerned. That is the reason that high-end investment firms that invest in derivatives are opting for people who have strong quantitative skills for structuring or valuation of complex financial instruments and for devicing superior investment strategies.

This has opened up very exciting and rewarding career opportunities in the field of Quantitative Investment Management for candidates who come with academic background in engineering, mathematics, and other numerical specializations. Needless to say, that apart from the stimulating intectual challenges that careers in this field offer to the mathematically talented individuals, the compensations are quite handsome indeed.

The course prepares candidates for careers as quantitative investment managers or quantitative analysts with financial institutions like investment banks, hedge funds, private equity firms, large broking houses, investment research and analytics firms, etc.

Candidates having a strong numerical background have a very bright chance of making a very rewarding career in this field with the largest of investment banks and other financial institutions. Salaries of quantitative analysts vary depending on their experience and background. In India presently, salaries for this profile may range from 8 Lacs p.a. for freshers to 30 Lacs p.a. for candidates with a few years of experience.

Placement

Students successfully completing the course will get placement assistance subject to fulfillment of applicable conditions.

Testimonials

Harjinder Singh Software Development Engineer, Audible Inc., New York Previously Technology Analyst, Goldman Sachs, New York

“I will recommend the 'Certificate Program in Applied Mathematics for Engineers' to those who want to start their careers in the field of quantitative finance. The program teaches you basics as well as advanced concepts of quantitative finance keeping you abreast with the latest developments in the field. It also focuses on the practical implementation of the models using Excel/VBA. The faculty at IIQF is comprised of both academicians and practitioners who bring their research and experience into the teaching. This program has helped me understand the esoteric field of derivatives and pricing models. After completing my B. Tech. from Punjab Technical University, I was working as a Software Engineer in TCS, that is when I joined the CP-AMFE, it has certainly helped me enhance my career aspirations.”

Haraprasad Dash Associate, Copal Amba (A Moody's Analytics Company) Previously Research Analyst, I-Peritus Solutions and Services

“After completing my M.Sc in computational finance, I joined the AMFE program at IIQF. It was really a practical and industry oriented program. The things I learnt during the course helped me getting my first job at I-Peritus. The faculty members are leading practitioners from the industry, IIQF also provides good placement support. Thanks for the guidance and support given by the IIQF faculty team for their guidance, which has really helped me in improving my interpersonal and technical skills that was required for cracking interviews. I will recommend this course to all those students who want to build a career in Quant/Structured product/Risk Management. In fact I have already recommended this course to my juniors.”

Admission Process

Candidates may apply online for admission to the course. Admission will be based on the candidate’s academic background, professional experience and personal interview.