CONTENTS

INTRODUCTION.....................................................4

ADVISORY BOARD..................................................5

ABOUT EPAT™ .......................................................6

THE CURRICULUM.................................................7

WHY EPAT™...........................................................9

ALUMNI PROFILE.................................................10

THE FACULTY.......................................................12

ALUMNI SPEAK...................................................15

ADMISSION.........................................................16

FAQs....................................................................17

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INTRODUCTION

With the advent of Algorithmic Trading and the benefits it brings to traders, it is imperative to develop the domain knowledge and expertise in quantitative and qualitative Algorithmic Trading skills.

QuantInsti® (QI) is Asia’s pioneer Algorithmic Trading Research and Training Institute, conducting professional programmes in this domain. We are focused on preparing professionals in the financial industry for the contemporary field of Algorithmic and Quantitative Trading.

We, at QuantInsti®, provide practical education on algorithmic trading, using online real-time video-sharing and interactive learning tools.

Our flagship programme EPATTM (Executive Programme in Algorithmic Trading) and our other educational initiatives have successfully imparted quantitative skills required for Algorithmic & Quantitative Trading to thousands of people across the globe.

We have also designed education modules/conducted workshops for various exchanges in South and South-East Asia as well as for various educational and financial institutions. Our faculty are frequently invited to provide their perspectives at conferences and seminars on algorithmic and high-frequency trading across Asia, Europe and America.

Apart from imparting knowledge about advanced strategy concepts, we also provide practical insights into aspects like system architecture & latency, standardized protocols, trading strategy design methodologies, risk management for HFT and exposure to new developments/tools in this domain.

QuantInsti® is headquartered in Mumbai.

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Professor Gautam Mitra Distinguished Professor, CARISMA, Brunel University Founder & MD, OptiRisk Systems

Prof. Mitra has been awarded the title ‘Distinguished Professor’ by Brunel University, in recognition

of his contributions in the domain of computational optimization, risk analytics and modelling.

He is an internationally renowned Research Scientist in the field of Operational Research in general

and computational optimization and modelling in particular. Professor Mitra is also the founder

and chairman of UNICOM Seminars. He has developed a world class research group in his area of

specialization with researchers from Europe, UK, USA and India.

He has published five books and over 150 research articles and is an alumnus of UCL and currently

a visiting professor there.

ADVISORY BOARD

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Dr. Ernest P. Chan

Managing Member, QTS Capital Management, LLCAuthor of ‘Quantitative Trading: How to Build Your Own Algorithmic Trading Business’ and

‘Algorithmic Trading: Winning Strategies & Their Rationale’

Dr. Chan is a commodity pool operator and trading advisor. Since 1994, he has been focusing on the

development of statistical models and advanced computer algorithms to find patterns and trends

in large quantities of data.

He has applied his expertise in statistical pattern recognition, to projects ranging from textual

retrieval at IBM Research, mining customer relationship data at Morgan Stanley, and statistical

arbitrage trading strategy research at Credit Suisse, Mapleridge Capital Management and other

hedge funds.

THE CURRICULUM

The Executive Programme in Algorithmic Trading (EPATTM) by

QuantInsti® provides the most comprehensive training for

professionals looking to grow or planning to start their careers

in the field of algorithmic and quantitative trading.

EPATTM will reshape the concept and knowledge of the

essential data available to develop trading algorithms and

systems, creating and implementing trading strategies on

different asset classes, and performing back and forward

testing. It focuses on moulding traders towards a successful

trading career, by focusing on derivatives, quantitative trading,

electronic market-making, trading related technology and

risk management.

EPATTM enables the high-achieving capital market

professionals and individuals interested in learning about

the market, to attain benefits and networking power of the

programme. Over the past six years, the alumni network has

grown to include hundreds of successfully placed individuals

from over 50 countries.

EPATTM provides a unique chance to its participants, to work

under the mentorship of renowned practicing domain

experts. Other opportunities include practical training in

designing and implementing of advanced algorithmic trading

strategies, using popular and effective tools and platforms.

In addition to EPAT™ for individuals, EPAT™ for Business is

a recent initiative by QuantInsti® that aims towards helping

organizations stay ahead of the changing landscape and

offers the right platform to launch as well as flourish in

the quantitative and algorithmic trading domain. We at

QuantInsti® partner with organizations to enhance the skill set

of their workforce and help them develop quantitative trading

skills. Students for this programme get to learn from an

acclaimed team of industry experts and market practitioners

in the field.

Practical Exposure

Acquire the knowledge and learn tools &

techniques used by traders in the real world

Expert Teaching & SupportThe EPAT™ faculty is an acclaimed team of academicians

and professionals who are all specialists in the field

Career Services

Our career services and job resources become available

to you the moment you sign-up and last throughout your

professional career

Get CertifiedOn successful completion of the programme participants

will receive certification from QuantInsti Quantitative

Learning Pvt. Ltd.

ADDITIONAL BENEFITS The perks of joining EPAT™ is not just limited to access to

our course material. Our associates offer exclusive discounts

on a range of services that help you on your path to

becoming a successful algorithmic trader.

- Quantra®: Up to 20% discount on self-paced learning courses

offered by Quantra®

- Quantpedia: Subscription-based access to high quality trading

strategies at 40% discount

- Global Financial Datafeeds LLP: Access to real-time stock market

data at a discounted price of 20%

- Forex and CFD Market Data: Free access to historic Volume,

Sentiment and Tick Data

- Other Benefits: Lifelong guidance from market experts, lifelong

career assistance and much more

STUDENT PORTAL QuantInsti® is at the forefront of interactive online learning.

Our comprehensive learning programme gives 24-hour access to all recorded lectures and programme materials,

accessible through your laptop, tablets & phones. Classes are recorded and uploaded onto our portal.

Participants get a personal account, allowing them to access:

KEY FEATURES ABOUT EPATTM

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Other features include the following:

Learning management system: Tracks your learning and

provides immediate feedback on your progress

Open source: Most tools and softwares are available for free

- Live lectures

- Sample code and spreadsheets

- Dedicated 7 days a week support team

- Quizzes and exercises

THE CURRICULUM

[Prior to start of lectures]

[Lecture]

[Lecture]

[Lecture]

[Lecture]

7

Module 1

Module 2

Module 3

Module 4

Module 5

Primer

Intro

Stats

ODR (Options, Derivatives and Risk)

Business Environment

• Basics of Excel: Starting from the very basics, moving on to available options and functions used with lots of examples

to give you full clarity and understanding

• Probability Distributions: Normal Distribution, Standard Normal Distribution; Related parameters like Z-score,

confidence interval and their use and Hypothesis Testing

• Covariance, Correlations and Regression and their physical significance in financial markets with reference to Stocks

and other tradable securities

• Understand measures of central tendency – Mean/Median/Mode

• Basics of Options

• Understand in detail, the System Architecture of a Traditional Trading System and compare it to an Automated Trading

System

• Understand the need, requirements, process, advantages and applications of Algorithmic Trading

• Detailed understanding of ‘Orders’, ‘Pegging’, ‘Discretion Order’, ‘Blended Strategy’

• Introduction to key strategy ideas and other important aspects of an algorithmic trade

• Basics of excel, application of some trading strategies in excel. Using excel to create back-testing model for a given

hypothesis

• The art of visualizing data. Statistics and Probability concepts (Bayesian and Frequentist Methodologies), Moments of

Data and Central Limit Theorem

• Applications of Statistics- Random Walk Model for predicting future stock prices using simulations and understanding

results, Capital Asset Pricing Model

• Short Introduction to Modern Portfolio Theory - statistical approximations of risk/reward

• Detailed understanding and comparison of various option pricing models and the applicability of different models in

various scenarios

• Characteristics of different Option Greeks - their sensitivity to different factors. Option price sensitivities to various

market factors. Building option portfolios on the basis of Option

• Greeks

• Implied volatility, smile, skew and forward volatility

• Dispersion trading concept, implementation and road-blocks. Hands on experience in designing a risk management

tool to show sensitivity of options portfolio to different conditions and allow the trader to modify his/her options

portfolio to meet future market scenarios better

• Understanding the infrastructure requirements

• Understanding the business environment (including regulatory environment, financials, etc.) for Algorithmic Trading

desks

[Lecture]

[Lecture]

[Lecture]

[Post Lectures]

Module 6

Module 7

Module 8

Project

Strategies

ATP (Algorithmic Trading Platform)

R (Optional)

EPAT™ Project (Optional)

• Detailed analysis of Trading Strategies in terms of, In-Sample and Out sample data, performance and optimization of

parameters, Stop-Loss and Profit taking criteria

• Understanding of Equities Derivative Markets, various parameters like OI, Volume, etc. and impact of market players on the

derivative parameters

• Designing the rules for trading including discussion on special situation events occurring on the expiry day

• Trend Strategy and Pair Trading Strategy modelling in detail

• Different methodologies of evaluating portfolio & strategy performance. Managing portfolio of option instruments

Expressing views of concepts like correlation through options

• Understanding Market Microstructure Basics, Order Book, developing High Frequency trading strategy based on Market

Microstructure Theory

• Understanding statistical properties of HFT data, Bid-ask bounce behaviour

• Learning how to use AI to model data (including weka for data modelling), hands-on experience with modelling nifty and

predicting tomorrow’s closing price

• Properties of Financial Time Series, Prediction of future returns using ARIMA

• Estimates of volatility, predict volatility using GARCH model, implement a trading strategy using GARCH filter & plot returns

• Python For Trading: Architecture, back testing, build customized trading indicators and basics

• Quantitative Analysis Using Python: Compute Statistical parameters, perform regression analysis and PCA, calculate VaR

• Object Oriented Programming In Python: Learn about Object Oriented Programming, Understand programming layout of

various packages, appreciate usage of classes over procedural programming

• Learn to code and backtest different strategies using various quant packages

• Broker APIs: Set up a Broker Demo Account to automate trading, learn to execute with automation

• R data types, statistical functions, graphs, extracting data from online platforms

• Programming conceptualization and implementation, useful tips to work with big data sets

• Build a back testing model using Quant Strat on R

• Write your own working strategy starting from ideation, data analysis, strategy formulation, back testing, coding

• Mentorship under a trading expert/practitioner

• Successful project topics: Pair trading strategies, Dispersion Trading (https://www.quantinsti.com/category/project-work-epat/)

• Submission Requirements

- Working Strategy Model

- Project Report 2000-5000 words long

[Post Lectures]Exam EPAT™ Final Exam

• Passing the EPAT™ Final Examination is a minimal requirement to be eligible for EPAT™ Certification of Excellence

• Total duration of this exam is 3 hours and total marks allotted are 100. It's divided into 2 sections EPAT™ Final Test and

EPAT™ Final Assignment

• Final Test contains 30 multiple choice questions for 1 mark each. EPAT Final Assignment contains 8 Questions for 70 Marks

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Get trained within a short span of 4 to 6 months

Theoretical knowledge and practical exposure to the concepts of the domain

Learn from leadingindustry practitionersfrom across the globe

Domain expertise, be it trading, analysis or technology

Opportunity to work on a project work under the

mentorship of practitioners with rich experience

Get certified from one of the most prominent quantitative trading training institute

#130+ #36+Countries have professionals

trained by QuantInsti®'s educational initiatives

Successful batches of EPAT™ programme

WHY EPAT™

GEOGRAPHIC LOCATIONS OF EPAT™ ALUMNI AROUND THE WORLD

CROSS SECTION OF EPAT™ ALUMNI EMPLOYERS1. ABN Amro

2. Anand Rathi Commodities

3. Algowire Technologies Private Limited

4. Alpha Six Capital

5. Angel Broking

6. Asit Mehta Investment

7. Axis Bank

8. Bank of America

9. Barclays

10. BNP Paribas

11. Bombay Stock Exchange

12. Centro De Investigaciones Inmobiliarias

13. China Security

ALUMNI PROFILE

14. Citibank

15. CitiCorp

16. CME Group

17. Credit Suisse

18. Crimson Financial Services Ltd

19. Deloitte

20. Deutsche Bank

21. Edelweiss Finance Limited

22. Federal Bank

23. Fortinet Technology

24. Golden Compass

25. Goldman Sachs

26. GPSK Investment Group

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ECONOMICS

STATISTICS

COMPUTATIONAL

FINANCE

ACTUARIAL

SCIENCEFINANCE &

ACCOUNTINGENGINEERING

SCIENCE

BUSINESS

MANAGEMENT

HEDGE FUNDMANAGERS

DATA PROVIDERS

FINANCIAL PRODUCT

DEVELOPERS

TRADERS

BROKERAGE SERVICE

PROVIDERS

RISK

MANAGERS

ANALYSTS

CONSULTANTS

27. HCL Technologies

28. HDFC Securities

29. HSBC

30. IBM

31. ICICI Bank

32. ICICI Securities

33. JP Morgan

34. JP Morgan Chase

35. Kasikom Asset Management

36. Kotak Securities

37. Marwadi Group

38. Merrill Lynch

39. Merrill Lynch Commodities

40. Michelin India

41. Morgan Stanley

42. Multiplex

43. NCDEX

44. Nirmal Bang

45. Nomura

46. NSE IT

47. Oracle

48. Philip Capital

49. PRB securities

50. Pro Alpha Advisors

51. Quant One Technologies

52. QuantX technologies

53. RBT Algo Systems

54. Reliance Communications

55. Royal Bank of Scotland

56. Sandisk

57. Singapore Exchange (SGX)

58. Sigma Value

59. Sharekhan Limited

60. SMC Globals

61. Tata Consultancy Services

62. Tech Mahindra

63. Theoria Capital Management

64. Thomson Reuters

65. UBS

66. UD trading, Hong Kong

67. Way to Wealth

68. Wipro Technologies

69. World Bank

ACADEMIC DISCIPLINE PROFILES

“The practical aspects of EPAT™ and material is excellent. I am grateful to the institute for quality of the course, and hard work they have put in to make it such a great experience.”

- NOUREDDINE TALEBQuantitative Analyst at Nomura, London

THE FACULTY

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ABHISHEK KULKARNIAbhishek is the Head of Quantitative department at QuantInsti®. He pursued Masters in Financial Mathematics at Dublin City University, Ireland. When he is not glued to time series analysis, he spends time playing chess, drawing portraits and trying very hard to play flute. He is currently teaching Quantitative modules in EPAT™.

BRIAN CHRISTOPHERBrian is a Quantitative researcher, Python developer, CFA charter holder, and

the founder of Blackarbs LLC, a quantitative research firm. Six years ago he started coding using Python to create algo trading strategies. Four years ago he

self-published his research which focused on trading algorithm research and development. He attained a BSc in Economics from North-eastern University in

Boston, MA and received the Chartered Financial Analyst (CFA) designation in 2016.

ERIC HAMEREric is a serial entrepreneur with degrees in Physics and Computer Science and experience in Machine Learning, Cloud Computing, and Python programming. Before joining Quantiacs, Eric was the founding CTO at NetInformer, a mobile media company prior to which he worked at Keynote Systems where he invented their patented Transactive Perspective which measured and monitored the performance of the Internet.

AVIRATH KAKKARAvirath started his career at the quantitative trading/structuring desk at JP Morgan after which he moved to Standard Bank to trade precious metals. After about 3 years with Standard Bank, he headed to Balyasny asset management, Hong Kong to trade systematic strategies and returned to Singapore to partner with a few friends to start Limnah Capital. Limnah capital is a systematic fund looking to trade various liquid instruments in a systematic way.

ANIL YADAVAnil Yadav is a member of the algo strategy advisory team at iRageCapital and is

responsible for building and benchmarking strategies for the clients across various asset classes. Prior to iRage, Anil has worked as an independent commodities trader

managing a portfolio of metals and energy products.

DR. ERNEST CHANErnie is the Author of ‘Quantitative Trading: How to Build Your Own Algorithmic

Trading Business’ and ‘Algorithmic Trading: Winning Strategies and their Rationale’, both published by John Wiley & Sons. Ernie also teaches courses and conducts workshops in trading and finance in Australia, Canada, Singapore, the

United Kingdom, and the United States.

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NITIN AGGARWALNitin has done B.Tech in Chemical Engineering from IIT Roorkee and PGDM from IIM Calcutta. Nitin is a partner with Pentagon Advisory Ltd. His gamut of experience ranges from developing novel breakthrough chemical technologies to creating proprietary trading strategies. Prior to leading the Operations team in Pentagon Advisory, he has been a quant at iRageCapital and a Leadership Associate with the Aditya Birla Group.

NITESH KHANDELWALNitesh has a rich experience in financial markets spanning across various asset classes in different roles. He is also the Co-founder of iRageCapital Advisory Pvt Ltd and QuantInsti Quantitative Learning Pvt Ltd. At QuantInsti® he also leads the overall business & is in-charge of new initiatives & ventures by QuantInsti®.

GAURAV RAIZADAGaurav is a Director at iRage Capital Advisory Pvt Ltd and leads the firm’s advisory practice in India on systems, performance and strategies. He has consulted extensively with core focus on strategy development and execution, including trading systems development, optimization and transaction cost analysis.

DR. HUI LIUDr. Liu is the author of IbridgePy and founder of Running River Investment LLC. His

major trading interests are US equities and Forex market. Running River Investment LLC is a private hedge fund specialized in the development of automated trading

strategies using Python.

ISHAN SHAHIshan has done B.E. Information Technology from D J Sanghvi College of Engineering and PGDBM from Sydenham Institute of Management. He has a rich experience in financial markets spanning across various asset classes in different roles. He works with Quantra® content development team and has prior experience in Barclays, Bank of America Merrill Lynch and RBT Algo Systems.

RADHA KRISHNA PENDYALARadha works as a Data Scientist at Thomson Reuters. His work involves applying

machine learning and quantitative financial modeling techniques to large datasets in order to solve specific problems in the financial sector. He obtained his masters in

financial engineering from City University of New York.

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DR. YVES HILPISCHHilpisch is the founder and managing partner of The Python Quants GmbH, Germany, as well as co-founder of The Python Quants LLC., New York. He is a graduate in Business Administration with a Dr.rer.pol. in Mathematical Finance.

VIVEK KRISHNAMOORTHYVivek has done B.E. from VESIT (University of Mumbai) and MBA from NTU, Singapore.

He is an aspiring actuary having cleared three papers of the Institute of Actuaries. Before QuantInsti®, he was pursuing his PhD in Finance from McMaster University,

Canada. He has about 7.5 years of experience in industry and about 4.5 years in academia across India, Singapore and Canada in Banking and Finance Sectors.

SAMEER KUMARSameer is a C++ evangelist who designs and builds financial strategies with built-in intelligence. He leads the infrastructure development team along with the low

latency programming division at iRage, he shares his experience on low latency systems as well as strategies involving artificial intelligence.

VARUN DIVAKARVarun Divakar is a member of the Quantra® Research and Development team at QuantInsti®, and is responsible for creating the content for trading strategies, using Quantitative and Machine Learning techniques. Prior to QuantInsti®, Varun worked as an associate commodities trader managing international energy and softs markets at Futures First.

RAJIB RANJAN BORAHRajib is the Co-founder & Director of iRageCapital Advisory Pvt Ltd & QuantInsti Quantitative Learning Pvt Ltd. At iRage, he leads the derivatives practice and works with exchanges, financial & educational institutions to design educational programs. He has conducted workshops in United States, Europe and Asia.

I loved how EPAT™ covers a wide range of topics. When I started the course I had plans to go back

to university to pursue math further, but just before finishing the course I got hired by a coveted

quantitative hedge fund as a quantitative analyst. A special thanks to the faculty!

Jacques Francois Joubert | Quantitative Analyst, NMRQL | South Africa

The way the EPAT™ course has been designed and the vastly experienced faculty they have on

board makes EPAT™ one of the best in the world. Also, the LMS (online learning platform) is super

user-friendly and allows you to connect to your batchmates from across the globe. EPAT™ has

added a lot of value to my career as it has added a new quantitative dimension to my existing

skill-set which was mostly fundamental.

Rohit Gupta | Derivatives Trader at UIL Singapore | Hong Kong

EPAT™ helped me to interact with a growing community of alumni. If you are looking for a

professional overview of the space, or already an expert looking at some new topics EPAT™ can

help you learn something new. I look forward to seeing a continued growth in QuantInsti® as well

as the network of clever people coming out of the program.

Derek Wong | Director of Systematic and Options Trading | China

Classes were concise & to the point & varied example from real life has been illustrated in

commendable manner. I got good insight into Algo-trading stuff & would like to get back to

respective mentors for consultation as & when required.

Aman Kumar Saxena | Manager Quants HSBC Global Banking and Markets | India

The insights that the faculty bring to the classroom from their own experiences as

consultants, are very valuable and make each lesson very effective. The QuantInsti® team too,

always keeps in touch to update your knowledge with new learning sessions and additions

to the programme, which is a great thing.

Aris Skilros | Quant Researcher at World Quant LLC | Hungary

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ALUMNI SPEAK

The EPAT™ participants are equipped with high intellectual

curiosity, possess strong interest in finance and have

analytical skills. Although there is no specific degree

requirement, but most participants joining the programme

come from various quantitative disciplines such as

mathematics, statistics, physical sciences, engineering,

operational research, computer science, finance or

economics. Participants from other disciplines should

be familiar with basic financial markets understanding,

spreadsheets and computational problem solving, if they

wish to pursue EPAT™.

COUNSELLINGPrior to admission, a counselling session is conducted that

focuses on understanding the strengths and weaknesses

of participants, wherever applicable. These sessions do not

decide the participants’ eligibility, however they do help the

counsellors to assist them with informed guidance prior to

enrolment.

Learn more about scholarships, payment options & discount plans on www.quantinsti.com/epat/

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Duration - 4 months Coursework

2 months of Project work (optional) +

Standard Program Fees - $ 4720

Admission

How many people have benefited from this course in the past? Hundreds of course participants from over 55 countries working

across different sectors such as financial markets, technology, and

quantitative finance have benefited from the programme in various

ways.

What will I be able to do after successful completion of the course?On successful completion of the course, participants would be

conceptually comfortable with:

which has a pool of algo traders making around USD 120k+ as per

industry average. Benefit from Placement Services at QuantInsti®

after successful completion of the programme.

Log on to www.quantinsti.com/quant-jobs/ for more information.

What is the future of Algorithmic Trading?Over the past decade, Algorithmic trading has been adapted

by various institutions and exchanges globally. The market

share of Algorithmic trading has been increasing ever since.

It is expected that markets will become more efficient and

exchanges will manage risk better in coming years as the

industry adapts more technological advancements.

What will I gain from this programme?Benefits of this programme include:

• Exposure to the various strategy paradigms,

which are used globally for Algorithmic trading

• Automate your trading strategies, by learning the tools

& skills required to write and implement the strategies

• Get trained to start Algorithmic Trading on your own,

as you learn everything from networking and the

hardware aspect of Algorithmic Trading to regulatory

environment for handling desk operations

• Get industry exposure from inducing market

practitioners as guest lecturers

• Career progression to algorithmic trading Industry

• Managing and analysing data for algorithmic trading and

building econometric models

• Learn how to back-test, implement and trade advanced

quantitative trading strategies

• Using programming skills to work on algorithmic trading

systems

• Using statistical packages and integrating them to your

trading system

• Understanding of market making, spread optimization,

transaction cost analytics and advanced risk management

• Using Option pricing models for running volatility books and

making markets

• Electric blend of practical and theoretical knowledge

What are the course requirements?A personal machine with good internet connection is all that is

required to get started immediately. As soon as you enrol, you will

be provided with learning material that will assist you through the

entire duration of the programme. Successful students have given

15-20 hours per week to review and complete the course work

within a period of 4 months before proceeding to the final exam in

the next 2-month duration.

FAQs

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Will QuantInsti® help me get a job?QuantInsti®’s Career Management & Career Development

Resources, offer support that is specifically designed for students

and working professionals seeking new opportunities, as well as

to add immediate value to their employers or their own trading

business.

You can avail our placement services once you join the program;

and you will be eligible for lifetime placement assistance.

What does EPAT™ Practical Project include?

The two-months long project work provides an

opportunity to specialize in a specific asset class or

strategy paradigm under the mentorship of a trader/

practitioner with rich experience in a similar domain.

EPAT™ participants have successfully implemented their

project work in live markets and availed benefits in their

respective workplaces.

How does EPAT™ compare with Masters in Financial Engineering? EPAT™ is a specialization programme for market

professionals interested in Algorithmic, Quantitative and

High-Frequency Trading. There is some overlap between

the curriculum covered in EPAT™ and MFE or Quantitative

Finance courses. EPAT™ focuses on practical and hands-on

knowledge with theoretical understanding of the tools and

strategies that are applied in practice.

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QuantInsti Quantitative Learning Pvt. Ltd.

India A-309, Boomerang, Chandivali Farm Road, Powai, Mumbai, India - 400072

Contact: +91-22- 61691400, +91 9920448877

Website: www.quantinsti.com Email: contact@quantinsti.com