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Certificate Program in Financial Engineering (CPFE)

Build your career in Quants & Financial Engineering Program

Live Online Instructor-led Weekend Program

Quick Facts

  • Program Duration
  • Program Schedule
  • Program Timing
  • Program Start Date

CPFE Program | Financial Engineering Course Highlights

  • World Class Faculty: Learn from highly acclaimed Quant practitioners and academics in Quantitative Finance who have worked with topmost global investment banks and firms in New York, London, Singapore, Sydney and more, with academic background from some of the world’s top universities like Stanford (USA), Columbia (USA), IIM, IIT, ISI.
  • Industry focused curriculum: Advanced curriculum designed by Quant practitioners from top Wall Street Investment Banks and financial institutions and industry experts to prepare job-ready professionals who are highly sought after by International Banks, Hedge Funds, Consulting Firms and other Financial Institutions.
  • Rigorous Practical Implementation: Learn how to combine theory and computational methods with strong emphasis on practical implementation in Python of the real-world application areas of these skills.

About The CPFE Course

Financial Engineering Courses(CPFE) prepare 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.

CPFE 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 Financial Engineering 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 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 financial engineering programs.

CPFE Course Calendar

  • Main Modules 320 Hours (7 Compulsory Modules)
  • Primers Each primer is of approx. 40 Hours duration.
BatchStart DateFeeModeTime

Why choose CPFE Program?

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Faculty

Financial Engineering

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 the Python language has become more popular.

Financial Engineering has emerged as a very prospective career prospect for people with a 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 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 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.

Brief Financial Engineering Courses Outline

  • Primer 1
    Introduction to Investment Finance (Optional)
    • Introduction to Finance and Financial Institutions
    • Introduction to Capital Markets
    • Introduction to Debt Markets
    • Introduction to Derivatives Markets
  • Primer 2
    Introduction to Financial Mathematics (Optional)
    • Introduction to Linear Algebra
    • Introduction to Differential Calculus
    • Introduction to Integral Calculus
    • Introduction to Ordinary Differential Equations
  • Primer 3
    Introduction to Probability & Statistics (Optional)
    • Introduction to Probability
    • Probability Distributions
    • Descriptive and Inferential Statistics
  • Primer 4
    Introduction to Programming (Optional)
    • Programming in Python
  • Module 101
    Introduction to Financial Engineering (Compulsory)
    • Introduction to Financial Economics
    • Introduction to Bond Mathematics
    • Options Fundamentals
    • Introduction to Exotic Options
  • Module 102
    Financial Mathematics (Compulsory)
    • Probability Theory
    • Basic Stochastic Processes
    • Brownian Motion
  • Module 103
    Financial Mathematics II (Compulsory)
    • Stochastic Calculus
    • Black-Scholes-Merton Models
  • Module 104
    Machine Learning for Quantitative Finance (Compulsory)
    • Regression Models
    • Time Series Models
    • Volatility Forecasting
  • Module 105
    Numerical Methods (Compulsory)
    • Monte Carlo Simulation Methods
    • Numerical Methods for Partial Differential Equations
  • Module 106
    Derivatives Valuations 1(Compulsory)
    • Equity Derivatives
    • Currency Derivatives
  • Module 107
    Derivatives Valuations 2(Compulsory)
    • Interest Rate Derivatives
    • Credit Derivatives
    • Operational and Compliance Risk
  • Module 108
    Risk Analytics (Compulsory)
    • Introduction to Financial Risk
    • Market Risk
    • Credit Risk
    • Operational and Compliance Risk

Financial Engineering 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.

CPFE Course Placement

Students successfully completing best Financial Engineering online courses will get placement assistance subject to fulfillment of applicable conditions.

Admission Process in Financial Enginneering Program

  • Send Your Application

  • Get on a call with a counsellor

  • Wait for Application Acceptance

  • Pay the fee & join the upcoming batch

Finance your Study

Educational Loans

We are very happy to help you progress to greater heights in your career in every way possible. Education loans available at 0% interest for full time Indian residents. Easy EMI plans available.

Student Aid

Encourages the full time students to enter this domain, benefits, if you are still pursuing formal education.

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Get Answers

  • What are the prerequisites for this program?

    Undergraduate degree in finance / engineering / mathematics / statistics / physics / economics / econometrics / chartered accountancy / computer science / MBA / CFA / FRM / PRM.
    Proficiency in spoken and written English. Basic knowledge of Statistics. Working knowledge of Excel
    Computer and an internet connection. We teach in Windows based platform. Mac users will need to Install Windows in Parallels Desktop for Mac.

  • Is the program suitable for those without a background in finance?

    People with a quantitative background are more qualified to pursue careers in financial engineering than pure finance professionals because the discipline heavily relies on mathematical modelling. Therefore, while having any prior knowledge is always helpful, the course has been created so that even those without a background in finance can enrol and benefit from it. Additionally, when you enrol in the course, you will get access to a finance primer module that you must complete.

  • Is the program suitable for non-programmers?

    We use a lot of Python in this course for teaching practical implementation of the models. So, participants having prior programming background definitely have an advantage.
    For participants who do not have a programming background, they will need to attend a primer module on basic Python Programming. For registered participants of the course, when you join the course, you get access to a Primer module on Python.
    The Python primer module is designed for people who do not have any kind of prior programming background and want to learn programming for developing applications related to finance. The aim of this module is to teach python in an easy, lucid and structured way so that people coming from even no-technical or non-programming background can learn and use the python language.

  • Who should attend?

    If you have a good knack for mathematics and want to work in high-end analytics, mathematical modelling, and research-focused, fascinating, and intellectually demanding positions in international banks and hedge funds. Whether you are a newcomer attempting to break into Quantitative Investment Banking or Risk Management or a seasoned professional wanting to master the topic in depth to advance your career chances, this is the ideal curriculum to consider. Additionally, students with backgrounds in engineering, mathematics, statistics, economics, or physics who want to work in international banks, hedge funds, or prop desks in advanced quant trading or advanced analytical roles in quant analytics, derivative pricing and valuation, model validation, Treasury, etc; should consider this course.

  • How is the course delivered?

    This program is conducted as a comprehensive online course offered via online live interactive lecture sessions on weekends. All lectures are recorded also and participants gets access to view the lecture recordings as well.

  • What is covered in the course?

    Optional Primers: Introduction to Investment Finance, Introduction to Financial Mathematics, Introduction to Probability & Statistics, Introduction to Programming (Python).
    Probability Theory, Basic Stochastic Processes, Brownian Motion, Stochastic Calculus, Black-Scholes-Merton Models.
    Machine Learning for Quantitative Finance, Monte Carlo Simulation Methods, Numerical Methods for Partial Differential Equations both theory and implementation in Python.
    Valuation of Equity Derivatives, Interest Rate Derivatives, Currency Derivatives, Credit Derivatives, Swaps both deep understanding of the models and learning the practical implementation and modelling in Python.
    Coverage of Financial Risk Management areas, Market Risk, Credit Risk, Operational and Compliance Risk etc. both theory plus practical modelling.

  • Who are the faculty?

    The course is taught by highly acclaimed Quant practitioners and academics in Quantitative Finance who have worked with topmost global investment banks and firms in New York, London, Singapore, Sydney and more, with academic background from some of the world’s top universities like Stanford (USA), Columbia (USA), London Business School, IIM, IIT, ISI, etc.

  • Will certificate be awarded on completion of the program? What are the certification criteria?

    The participant becomes eligible to get the certificate on completion of a capstone project that is given at the end of the program, participants who attend and follow all the lectures should be able to complete the project. So, to get the certificate you will also have to complete and submit the project.

  • Is there any placement support?

    We have dedicated placement team who provides strong support to all successful participants for getting relevant jobs in International Banks, Hedge Funds, Consulting Firms, IT Companies and other financial institutions.
    You may work in Quantitative Research & Analysis, Development of Quantitative & Analytical Software, Building Valuation Models, Model Validation, Derivatives Structuring, Quant Trading, High Frequency Trading, Algorithmic Trading, Derivatives Trading.

  • What is the course calendar?

    This course is offered 2 times in a year.

  • How long has this programme been around for?

    The first cohort of this program commenced in 2010.

  • What programming language does this program use?

    This program is entirely taught using Python

  • What mode of payments do you accept?

    We accept all online payment modes like Bank Transfer, Credit Card, Debit Card, UPI

  • Is EMI facility available?

    Interest Free EMI payment option is available through our NBFC partners.

  • Why you should attend this program?

    • Comprehensive Program: Learn Financial Engineering from the worlds most comprehensive Financial Engineering certificate program.
    • World Class Faculty: Learn from highly acclaimed Quant practitioners and academics in Quantitative Finance who have worked with topmost global investment banks and firms in New York, London, Singapore, Sydney and more, with academic background from some of the world’s top universities like Stanford (USA), Columbia (USA), London Business School, IIM, IIT, ISI, etc.
    • Industry focused curriculum: Advanced curriculum designed by Quant practitioners from top Wall Street Investment Banks and financial institutions and industry experts to prepare job-ready professionals who are highly sought after by MNC financial institutions. Master latest Quant skills including Machine Learning.
    • Rigorous Practical Implementation: Comprehensive theoretical background and Practical implementation of Derivatives Pricing Models in Python and theoretical understanding and Practical Implementation of risk management concepts
    • Effective Live Interactive Lecture Delivery: The course is delivered through live and interactive lecture sessions.
    • Placement Support: Lifetime placement support for all participants

Book a guidance call Enquire Now Download Brochure Course Calendar