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Integrated Program in Finance and Financial Technologies (IPFT – Full Time)

India’s only industry focussed, comprehensive full-time online finance program.

About the Program

Hero Vired’s Integrated Program in Finance and Financial Technologies is built to help you find your niche as a financial analyst and become the one who can predict the trends of tomorrow. With this course, you get the headstart you need to become a game-changer in the world of Finance and Financial Technologies.

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Live Online Classes

Program Delivery

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11 Months

Program Duration

“Program

October, 2021

Program Start Date

Program Fees” width= INR 6,00,000+ Applicable Taxes

Program Fees (0% EMIs Available*)

Undergraduate Degree” width=

UG Degree In STEM OR Finance-Economics Background With Maths and/or Stats

Program Eligibility

     

    Program Snapshots

    Program Snapshot 1

    Experience the very first comprehensive finance, quantitative finance and financial technology program

    Program Snapshot 3

    Learn the entire gamut of finance from basic accounting to the global financial markets

    Program Snapshot 2

    Understand economic impacts and financial technologies including analytics, AI-ML, blockchain, cryptocurrencies, non traditional data sources

    This is for You

    Your choice

    Are you interested in a career in high finance, quantitative finance, or fintech, who might come from a finance, economics, science, technology or mathematics background? This program is for you!

    Your opportunity

    In India, an education in Finance and Technology can lead you to work as an Equity Research Analyst, Financial Analyst, Investments Analyst, Marketing Manager, Investment Banker, Business Analyst, Market Analyst, Operations Manager, and more.

    Your domain

    If you want to develop razor-sharp analytical ability and stellar interpersonal skills, plus sharp understanding of industry-standard software, this program is for you!

    Your eligibility

    If you have the ability to communicate, financial reporting skills, good analytical ability, problem solving skills, good knowledge of IT software, management experience, an interest in commercial acumen and the capacity for innovation, this program is for you!

    Program Curriculum

    This is what you will learn from the program

    Foundations of Modern Finance I

    About the Module:

    It provides a rigorous and comprehensive introduction to the fundamentals of modern finance and their applications to business challenges in valuation, investments, and corporate financial decisions under a unified framework.

     

    Learning Outcomes:

    Valuation of fixed income securities and common stocks
    Risk analysis, the Arbitrage Pricing Theory (APT), and the Efficient Market Hypothesis
    Introduction to corporate finance and capital budgeting
    Valuation of derivative securities
    Portfolio theory and the Capital Asset Pricing Model (CAPM)
    Corporate financial decisions
    Real options, capital structure, payout policy, corporate bonds;
    Interaction between investment and financing decisions

    Foundations of Modern Finance II

    About the Module:

    We build on the core set of basic principles taught in the first part, and continue to develop a powerful and general framework for making financial decisions in business and in personal financial planning. We introduce financial derivative securities, and their valuation models, discuss the capital structure decision of firms, and explore the interaction between investing and financing.

     

    Learning Outcomes:

    Forwards and Futures
    Options
    Portfolio Theory
    Capital Asset Pricing Model (CAPM)
    Capital Budgeting and Real Options
    Financing/Capital Structure
    Interaction between Investing and Financing
    Payout and Risk Management

    Financial Accounting

    About the Module:

    It provides a rigorous introduction to the principles of financial accounting. We focus on the preparation and analysis of financial statements, and on why financial statements take the form they do. We cover the basic structure of financial reports and the process of recording transactions. We will also learn how investors, creditors, and other users analyze financial statements to assess corporate performance. The course focuses on using financial statements to gather inputs to valuation models and for corporate finance decisions.

     

    Learning Outcomes:

    Introduction, accrual accounting, balance sheet/income statement, allowance accounting, and revenue recognition.
    Inventory/COGS, depreciation/property, plant, and equipment, statement of cash flows, introduction to financial statement analysis.
    Marketable securities, accounting for banks, intangible assets, and acquisitions.
    Income taxes, long-term debt, leases, shareholders’ equity, ethics, and conclusion.

    Financial Modelling (in Excel)

    About the Module:

    This module focuses on creating a variety of valuation and investment banking models using MS Excel.

     

    Learning Outcomes:

    Time Value of Money (NPV and IRR).
    How to build an Investment Banking equities valuation model from scratch.
    Writing equities research reports.
    Top-down valuation models for Venture Capitalists.
    Industry research and modelling.
    Ratios based valuation models.
    Valuation models and rating models for bonds and fixed income securities.
    Modelling currencies and commodities

    Behavioural Finance and Technical Analysis

    About the Module:

    This module is about the psychological foundations of market behaviour and finance, and how trends and patterns tend to repeat themselves

     

    Learning Outcomes:

    Introduction to Behavioural Finance and Heuristics and Biases.
    Prospect Theory, Loss Aversion and Hyperbolic Discounting.
    Bubbles and Crashes.
    Fundamentals of Charting and Technical Analysis and how it connects to Market Psychology.
    Self-fulfilling prophecies.

    Mathematical Methods for Quantitative Finance

    About the Module:

    Modern finance is the science of decision making in an uncertain world, and its language is mathematics. This course develops the tools needed to describe financial markets, make predictions in the face of uncertainty, and find optimal solutions to business and investment decisions.

    This course will help anyone seeking to confidently model risky or uncertain outcomes. Its topics are essential knowledge for applying the theory of modern finance to real-world settings.
    You will learn the following in this course:
    Probability
    Statistics
    Time-series models
    Continuous time stochastic processes
    Linear algebra
    Optimization
    Numerical methods

     

    Learning Outcomes:

    Review of laws probability; common distributions of financial mathematics; CLT, LLN, characteristic functions, asymptotics.
    statistical inference and hypothesis tests; time series tests and econometric analysis; regression methods.
    random walks and Bernoulli trials; recursive calculations for Markov processes; basic properties of linear time series models (AR(p), MA(q), GARCH(1,1)); first-passage properties; applications to forecasting and trading strategies.
    continuous time limits of discrete processes; properties of Brownian motion; introduction to Itô calculus; solving differential equations of finance; applications to derivative pricing and risk management.
    review of axioms and operations on linear spaces; covariance and correlation matrices; applications to asset pricing.
    Lagrange multipliers and multivariate optimization; inequality constraints and quadratic programming; Markov decision processes and dynamic programming; variational methods; applications to portfolio construction, algorithmic trading, and best execution Monte Carlo techniques; quadratic programming.

    Mathematical Methods for Quantitative
    Finance

    About the Module:

    Modern finance is the science of decision making in an uncertain world, and its language is mathematics. This course develops the tools needed to describe financial markets, make predictions in the face of uncertainty, and find optimal solutions to business and investment decisions.

    This course will help anyone seeking to confidently model risky or uncertain outcomes. Its topics are essential knowledge for applying the theory of modern finance to real-world settings.
    You will learn the following in this course:
    Probability
    Statistics
    Time-series models
    Continuous time stochastic processes
    Linear algebra
    Optimization
    Numerical methods

     

    Learning Outcomes:

    Review of laws probability; common distributions of financial mathematics; CLT, LLN,
    characteristic functions, asymptotic, statistical inference and hypothesis tests; time series tests and econometric analysis; regression methods
    random walks and Bernoulli trials; recursive calculations for Markov processes; basic properties of linear time series models (AR(p), MA(q), GARCH(1,1)); first-passage properties; applications to forecasting and trading strategies.
    continuous time limits of discrete processes; properties of Brownian motion; introduction to Itô calculus; solving differential equations of finance; applications to derivative pricing and risk management.

    Review of axioms and operations on linear spaces; covariance and correlation matrices; applications to asset pricing.
    Lagrange multipliers and multivariate optimization; inequality constraints and quadratic programming; Markov decision processes and dynamic programming; variational methods; applications to portfolio construction, algorithmic trading, and best execution Monte Carlo techniques; quadratic programming.

    Derivatives Markets: Advanced Modeling and Strategies

    About the Module:

    Financial derivatives are ubiquitous in global capital markets, and those products and the institutions around them continue to evolve at a rapid pace. This course is is designed for students seeking to develop a sophisticated and durable understanding of valuation and hedging methods, and a basic familiarity with major markets and instruments. Tools for quantifying, hedging, and speculating on risk are emphasized.

    Topics include forwards, futures and options in the stock, fixed income and commodity markets, exotic options, real options, interest rate and currency swaps, mortgages, credit risk, securitization, the yield curve, duration and convexity.

     

    Learning Outcomes:

    Advanced derivatives pricing approaches adaptable to valuing new products.
    The many ways to shape risk exposure with derivatives.
    Important facts about the world’s largest financial markets.

    Derivatives Markets: Advanced
    Modeling and Strategies

    About the Module:

    Financial derivatives are ubiquitous in global capital markets, and those products and the institutions around them continue to evolve at a rapid pace. This course is is designed for students seeking to develop a sophisticated and durable understanding of valuation and hedging methods, and a basic familiarity with major markets and instruments. Tools for quantifying, hedging, and speculating on risk are emphasized.

    Topics include forwards, futures and options in the stock, fixed income and commodity markets, exotic options, real options, interest rate and currency swaps, mortgages, credit risk, securitization, the yield curve, duration and convexity.

     

    Learning Outcomes:

    Advanced derivatives pricing approaches adaptable to valuing new products.
    The many ways to shape risk exposure with derivatives.
    Important facts about the world’s largest financial markets.

    Overview of Machine Learning, Artificial Intelligence and Python Programming for Financial Applications

    About the Module:

    This module will focus on understanding key analytics concepts, solutions, and modus operandi, through real-world finance use-cases.

    The module will additionally also introduce you to the core ideas of Machine Learning, Artificial Intelligence and programming on Python.

     

    Learning Outcomes:

    Understand why and how businesses use analytics through use-cases; the qualities of a good analyst; analytics methodologies and problem definitions; and the CRISP-DM architecture.

    Understand the goal of machine learning; elements of supervised learning, and the difference between the training set and the test set; the difference of classification and regression – two representative kinds of supervised learning. Introduction to algorithms.

    Introduced to python environments and ML packages, concept of Object-Oriented Programming, programming for a live environment, debugging, IDEs, and python basics such as class, objects, functions, conditions, loops/iterators, array, dictionary, lambda, mathematical and statistical operations, numpy for matrix algebra, exception handling, and file handling.

    Overview of Machine Learning, Artificial Intelligence and Python Programming
    for Financial Applications

    About the Module:

    This module will focus on understanding key analytics concepts, solutions, and modus operandi, through real-world finance use-cases.

    The module will additionally also introduce you to the core ideas of Machine Learning, Artificial Intelligence and programming on Python.

     

    Learning Outcomes:

    Understand why and how businesses use analytics through use-cases; the qualities of a good analyst; analytics methodologies and problem definitions; and the CRISP-DM architecture.

    Understand the goal of machine learning; elements of supervised learning, and the difference between the training set and the test set; the difference of classification and regression – two representative kinds of supervised learning. Introduction to algorithms.

    Introduced to python environments and ML packages, concept of Object-Oriented Programming, programming for a live environment, debugging, IDEs, and python basics such as class, objects, functions, conditions, loops/iterators, array, dictionary, lambda, mathematical and statistical operations, numpy for matrix algebra, exception handling, and file handling.

    Financial Regulations and Analytics

    About the Module:

    This module will introduce global financial and data regulation and how it relates to analytical models of risk modelingule will additionally also introduce you to the core ideas of Machine Learning, Artificial Intelligence and programming on Python.

     

    Learning Outcomes:

    Global financial regulations – DFAST, CCAR, IFRS, GARP.
    Probability of default Models, loss given default and exposure at default.
    Risk weighted assets and Credit worthiness of banks and necessary collaterals.

    Financial Technology

    Learning Outcomes:

    Fundamental of Blockchain and Hyperledger, Cryptocurrencies and their valuation, technologies, Non-Fungible Tokens.
    Use of AI-ML in FinTech. Application development in PropTech and InsurTech.
    Use of new data sources including unstructured data for understanding financial risk

    Finance, Fintech, Regulations and Data from an Indian
    Perspective

    About the Module:

    This module will introduce and dive into the details of previous modules from an Indian context.

    Learning Outcomes:

    Financial regulations for banking and non-banking financial corporations in India.
    Data availability in India.
    The Indian fintech, proptech and insurtech landscape.

    Finance, Fintech, Regulations and Datafrom
    an Indian Perspective

    About the Module:

    This module will introduce and dive into the details of previous modules from an Indian context.

     

    Learning Outcomes:

    Financial regulations for banking and non-banking financial corporations in India.
    Data availability in India.
    The Indian fintech, proptech and insurtech landscape.

    In-Person Industry & Learning Meetups

    All participants are invited to a non-compulsory in-person interaction twice a year during the first and the final quarter of the program. This will be at a separate cost to be borne by participants and does not include travel costs to and from the location.

    Interaction 1

    Duration: 6 days (Sun-Fri)
    Location: BMU Campus
    Agenda: Industry Workshops, Networking and Personal Brand Building
    Cost: INR 10,000 + taxes (includes session participation, food & stay)

    Interaction 2

    Duration: 6 days (Sun-Fri)
    Location: BMU Campus
    Agenda: Career Workshops and Guided Mentoring Sessions
    Cost: INR 10,000 + taxes (includes session participation, food & stay)

    Note: These are purely optional sessions, and learners can have access to the same sessions and content through their learning management system as well. Additionally, the scheduling and details of these sessions will be subject to and dependent on external circumstances and prevailing regulations.

    Your Faculty

    Dr Anirban Chakraborti

    Dr Anirban Chakraborti

    Awardee of the prestigious Young Scientist Medal of the Indian National Science Academy and professor at the School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi with over 2 decades of experience.

    Dipyaman Sanyal

    Dipyaman Sanyal

    A former hedge fund quant, CFA, an adjunct faculty at Northwestern University, included in the 40-under-40 data scientists in India list of 2019, and counted amongst the leading Data Science Academics in India in 2018 & 2019 who now leads a boutique consulting firm.

    Satyam Arora

    Satyam Arora

    A CFA with specialties in equity, banking, financial services and macro research, he was initially supporting Rafferty Capital Market, LLC as a VP Equity Research before moving on to Phillips where he heads Personal Health, Market Analysis & Forecasting, Strategy M&A and Partnerships.

    Get Certified

    MIT Finance Certification of achievement

    On the successful completion of this program, you will receive a certificate from Hero Vired in collaboration with MIT, MicroMasters® credentials, and postgraduate certification from BML Munjal University*.

    *T&C apply

    Program FAQs

    Who is this program for ?

    This a serious program for those interested in a career in high finance, quantitative finance, or fintech, who might come from a finance, economics, science, technology or mathematics background.

    Why IPFT FT ?

    Most academic programs in finance tend to focus on aspects of accounting and on theoretical aspects of modern finance. While finance theory and accounting are essential for understanding applied finance, ignore practical applications of finance and the technology revolution that the field is facing is leading to a huge skills gap between what the industry is looking for and what institutions are teaching. The IPFT-FT is the first comprehensive finance, quantitative finance and financial technology program which covers the entire arc of finance from basic accounting to the global financial markets and its impact on the economy, and financial technology including analytics, AI-ML, blockchain, cryptocurrencies, non-traditional data sources.

    What do you mean by Indian contextualization ?

    A large part of understanding finance is understanding financial and accounting regulations, market specific nuances, economic factors, plus data and technological availability – which are all location dependent. While the program will cover details on global regulations and standards, which will ready the learner to work for any international clients or organizations, it will also ensure that students are ready to work in Indian markets, for Indian clients and for their own India focused start-ups.

    Do you cover these topics :
    1. Portfolio Theory: Yes. From Capital Asset Pricing Model to the Mean Variance trade-offs and the efficient frontier, the course covers all details of modern finance theory and practice. 
    2. Equity Valuation: There are multiple methods of valuing a stock, from discounted dividends to using multiples (like PE) and ratios. We cover most of the popular models used in Wall St. to value stocks, bonds, currencies and commodities. 
    3. Block Chain: Blockchain and related concepts of distributed ledgers are covered in fair detail for students to be able to understand these concepts and how it affects modern finance. 
    4. Cryptocurrency: Yes. 
    5. Investment Banking/Venture Capital Models: Yes. Investment banks and VCs look for analysts who can create detailed valuation models for listed and private companies, respectively. We cover the most common modelling techniques used by PE Funds, IBanks and VCs. 
    6. JavaScript for Block Chain: No. This is not a programming course. While we do hands-on coding in Python, this is directly for valuations and risk measurement. Core programming enthusiasts may opt for our FT program.
    Do I need to know :
    1. Programming: Ideally yes, though no prior coding experience is required. This is a finance program with significant focus on mathematical modelling and programming, so while all relevant coding material will be taught, as needed, having a knack for programming or algorithms can be extremely helpful.
    2. Excel: Some level of comfort with using basic MS Excel or any other similar spreadsheet tool will be extremely useful. Excel remains the primary tool for finance – whether in auditors offices or in investment banks and hedge funds. 
    3. Machine Learning: No. We will teach relevant machine learning tools and techniques which will be used in the financial analytics domain. 
    4. Accounting: No. We will begin with the basics of accounting and then move on to high finance, investments and fintech. 
    5. Basic Finance: If you are comfortable with basic finance, you might find this course easier. However, it is not a prerequisite, since we will begin at the beginning.
    6. Math: This is a math heavy program. The prerequisite will be basic calculus, probability, statistics and linear algebra for the advance courses. We do expect learners to be comfortable with numbers, since finance and fintech and even basic accounting is all about numbers.
    What would work better for me – the full time or part time program?

    It depends on the time and duration of enrolment you would be able to commit towards the program. If you are a working professional, and intend to keep working through the program, we would recommend the part-time program for you.
    However, if you are committed to a transformational experience, and are looking for a program that can catapult you into an extremely different job role – we would highly encourage enrolling for our full-time program.

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