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]
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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: [email protected]