Post Graduate Program in Algorithmic Trading (PGPAT)
Build your career as Quant Trader
FinoQ Executive Program
Indian Institute of Quantitative Finance
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PGPAT Program - Algorithmic Trading Course Highlights
- Highly qualified industry practitioner faculty
- Advanced Curriculum
- Thoroughly hands-on training in programming algorithmic trading strategies in Python
- Training on industry leading algorithmic trading platforms
- Training in Simulation Lab
- Live Trading experience in real market
Post Graduate Program in Algorithmic Trading Course Online
The PGPAT course or Post graduate program in Algorithmic trading online conducted by IIQF is taught by highly qualified and experienced market practitioners and is a job-oriented Masters in Algorithm Trading online course that aims to produce industry-ready Algo-Traders, who can join trading desks of various financial institutions or setup their own independent algorithmic prop trading desks. We do offer Certificate Program in Algorithmic Trading (CPAT) online with world class faculties. Enroll now.
The Financial Markets the world over have seen a major paradigm shift in how trading is done. Algorithmic Trading (abv. Algo Trading) also known as Program Trading or Automated Trading, essentially implies that the trading is done by computer programs. Currently a vast majority of the trades in some of the markets are algorithmic in nature.
These algorithms depend on quantitative finance techniques for formulating trading strategies, detection of profitable trade opportunities, generating trade signals, generating the trades and trade order execution. At each stage there is extensive use of technologies.
Algorithm Trading, both High-Frequency as well as Low Frequency, using Quantitative Methods is now a very lucrative career. A breed of traders known as the Algo-Traders or Quant-Traders has emerged who have certain skill-sets that are much sought after in the industry.
- Students gets free access to recordings of all 4 Primers on course registration.
Who should attend
- Fresh Graduates
- Management Students
- Finance Professionals
- Prop Traders
- Retail Traders
Why choose this course?
View what our learners have to say...
"I had enrolled for the CPQFRM course at IIQF. It was six months of pure pleasure learning cutting edge, current market relevant Quant and Risk Management practises, philosophies and techniques. Brilliant team of lecturers coming straight from leading market entities in the Investment and Risk space. After completing this course I was able to successfully realise my desire to effect a career change towards Risk Analytics and Risk Modelling, after almost 13 years of experience. It has given me a successful start and also equipped me to consolidate my career as a result of hands on skills acquired. Not just CQFRM but other courses also I would say are very apt and highly recommended!!"
"The course on Financial Engineering that I attended at IIQF is one of the best courses available in the Indian market. Much more rigorous than CQF and more Quant Finance orientated than a CFA. It has a wonderful faculty most of whom are former PhDs from Stanford or Professors in Indian Statistical Institute (ISI). The course offers various insights and allows multiple programming languages. It allows Open book Testing culture which allows students to focus on applying the theory to very real problems. This course overall has provided me with a solid mathematical foundation, enabled me to understand how the theory translates to practical problems and finally to get a great offer in a equity quant research team."
"I had attended the Certificate Program in Derivative Valuations and Risk Analytics conducted by Indian Institute of Quantitative Finance. I was previously working with a Registered Investment Advisory (proprietary firm) as a Quantitative Analyst. This program is very relevant for risk professionals with a specialization in OTC valuations. The content of he course is very practical for various asset class derivative valuation models and the codes and resources of the model can be utilized to build a foundation for Derivative Valuation Modelling. Lectures are very interactive with its content being useful for python modelling from scratch and prepare for Valuation and Model Validation quant roles... "
Rohan Deodhar, FRM
"I am thankful to IIQF for helping me achieve my goal to move to quant risk role. What attracted me to Financial Engineering course at IIQF was the content of the program. It covered Mathematics, Machine Learning, Numerical Methods with Python modelling and helped me to move to Quant Risk role something I wanted to achieve."
"I had attended the Program in Derivative Valuations and Risk Analytics conducted by Indian Institute of Quantitative Finance. Before joining I was working with one the of broking firm for long time and was looking for change the field. IIQF's relevant & up to date program helped me a lot in sharpening my skills and getting desired profile at NOMURA. I would highly recommend this program for its content, which is very relevant for professionals in finance & risk. Additionally Nitish Mukherjee from IIQF has put in lots of efforts to share & recommend my profile to various organizations and finally I got opportunity to work with Nomura, where also my profile was considered after Nitish's personal recommendation."
"I recently pursued the certificate program in financial engineering course online from IIQF. Structuring of topics was focused and also in order to enable one learn from the primary to the advanced concepts. Faculty members were very good and offered to assist at all points and covered the aspects of the curriculum in a concise manner. Primer for this course is very helpful for beginners as a prerequisite. The program as a whole was very nice and useful and all the faculty members were very good. My sincere thanks to all faculty members namely Edelbert, Rupal, Vivek, Ritesh, Srijoy, Ujwal."
"I had attended the program in Certificate Program in Derivative Valuations and Risk Analytics using MS Excel and VBA Programming for Finance by Indian Institute of Quantitative Finance. I would highly recommend for professionals in finance, risk and statistics. I have gained immensely from the program specially from Credit and Market Risk, got a job in Credit Risk Modeling profile in Mumbai due to this course and like to thank IIQF for the same. Special Thanks to "Abhijit Biswas" he was excellent, dedicated and very Knowledgeable. I wish them success in all their future programs."
"Overall experience in IIQF is just superb. IIQF is best as it provides quality education. I did the PGPAT course after completing my engineering. My experience at iiqf has given me a chance to sharpen my skills in my field of my choice ie algorithmic trading. I want to express my sincere thanks to nitish sir for your help in getting me placed. Nitish Sir took special care in convincing my prospective recruiter that I will fit in to required profile and I was successfully placed as python developer at Tesnatech Pvt Ltd. I didn’t realize the realm of your placement services until I stepped into your office. Needless to say,I was amazed at the abundance of opportunities that your institute provides. Thank you for your tremendous help!."
"Thanks a lot IIQF and the lecturers. PGPFE course helped me in moving to Semi Quant team internally. Lectures are very informative and covered wide range of complex topics building from fundamentals to very advanced levels. Very refreshing experience."
Brief PGPAT Course Outline
Module 301Introduction to Algorithmic and Quantitative Trading
- What is "Algorithmic" Trading?
- Market Structures
- Evolution: Algorithmic Trading trends and their impact on the markets
- Types of Algorithmic Trading Strategies
- Lifecycle of Algorithmic Trading
- Market Microstructure and Concepts
- Order Book Dynamics
- Bid-Ask Spread
- Bid-Ask Bounce
- Introduction to jupyter notebook
- Introduction to IntelliJ IDE
- Installing intelliJ
- Basics of IntelliJ
- Read stock data with IntelliJ and basic functionality
Module 302Technical Trading Strategies
- 1. Overview of Systematic Trading indicators in Technical Analysis
- 2. Trend following Strategies
- 3. Momentum based Strategies
- 4. Exploring strategies on stock price data
- 5. Exploring such strategies on bitcoin data
Module 303Strategy Development and Back-testing
- 1. Ideation and Strategy Creation
- 2. Architecture of a back-testing System
- 3. Common Pitfalls (Look-ahead bias, survivorship bias etc.)
- 4. Implementing a back-tester
- 5. Strategy Module
- 6. Performance Measurement Statistics
- 7. Parameter Optimization
- 8. Transaction Cost Analysis
Module 304Money Management and Risk Management
- 1. Optimal Capital Allocation
- 2. Risk Management
Module 305Algorithm Trading Infrastructure Setup
- 1. Algorithm Trading Mechanics
- 2. Architectural design
- 3. Basic platform design and architectural setup
- 4. Operational considerations and pitfalls
Module 306Algorithmic System Design and Implementation
- 1. Implementing Strategies
- 2. Order Management
- 3. Risk Management
- 4. Error Handling
- 5. API Integration
Module 307Options Trading Strategies
- 1. Options Pricing
- 2. Options Greeks
- 3. Options Trading Strategies
- a. Market Neutral Strategies
- b. Bullish Strategies
- c. Bearish Strategies
- d. Arbitrage Strategies
- i. Cash Future Arbitrage
- ii. Conversion Reversal / Put-Call Parity
Module 308Machine Learning for Quantitative Trading Using Python
- 1. Introduction to Machine Learning
- 2. Regression Models
- a. Simple Linear Regression
- i. Example with stock data and why linear regression not a good fit
- b. Multiple Linear Regression
- i. Example with stock data
- b. Multiple Linear Regression
- c. Logistic Regression
- d. Decision Tree Regression
- e. Random Forest Regression
- a. Simple Linear Regression
3. Classification Models
- a. Decision Tree Classification
- b. Random Forest Classification
- 4. Few examples on what not do fit to stock data
Module 309Optimization Methods
- 1. Analytical vs Numerical Optimization
- 2. Cost Functions for Regression
- 3. Cost Functions for Classification
- 4. Gradient Descent
- 5. Stochastic Gradient Descent
- 6. Adam Gradient Descent
Module 310Time Series Analysis Using Python
- 1. Auto Regressive Models (AR)
- 2. Moving Average Models (MA)
- 3. MA as basic model for stock data predictions
- 4. Auto Regressive Moving Average Models (ARMA)
- 5. Auto Regressive Integrated Moving Average Models (ARIMA)
- 6. Exponentially Weighted Moving Average Models (EWMA)
- 7. Generalized Auto Regressive Conditional Heteroskedasticity Models (GARCH)
- 8. Stock data examples
Module 311Deep Learning for Quantitative Trading Using Python
- 1. Introduction to Deep Learning – Artificial Neural Networks (ANN)
- a. Traditional Machine Learning Vs Deep Learning
- b. Universal Approximation Theorem
- c. Perceptron
- d. Activation Functions
- e. Cost Functions
- f. Back Propagation
- 2. Feed Forward Neural Network (FFN)
- 3. Recurrent Neural Network (RNN)
- 4. Long Short Term Memory (LSTM) Network
- 1. Introduction to Deep Learning – Artificial Neural Networks (ANN)
Module 312Quantitative Trading Strategies
- 1. Introduction to Quantitative Trading
- 2. Quantitative Directional Strategies
- 3. Statistical Arbitrage Strategies
- a. Pairs Trading Strategies
- 4. Arbitrage Strategies
- a. Index Arbitrage
- b. Spread Arbitrage
- 5. Gamma Scalping
- 6. Volatility Trading
- a. Risk Reversal / Volatility Skew Trading
- b. Dispersion Trading
- 7. Electronic Market Making Strategies
Module 313Algorithmic Execution Strategies
- 1. Execution Algorithms
- a. Percentage of Volume (POV)
- b. Volume Weighted Average Price (VWAP)
- c. Time Weighted Average Price (TWAP)
- 1. Execution Algorithms
Algorithmic Trading Lab
Both Simulated Trading Lab as well as Live Trading Lab fully equipped with advanced algorithmic trading platforms and statistical analysis systems.
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Get on a call with a counsellor
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Pay the fee & join the upcoming batch
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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.
Encourages the full time students to enter this domain, benefits, if you are still pursuing formal education.
What are the prerequisites for this program?
For Indian Participants – Minimum Graduation in science / economics / commerce / engineering / management (students in Final Year of Graduation may also may apply) with mathematics as one of the subjects.
For International Participants – Minimum Graduation or equivalent degree in science / economics / commerce / engineering / management from any recognized University or Institution in their respective country with mathematics as one of the subjects.
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 non-programmers?
Lot of people say, particularly those who do not have a programming background that it is extremely difficult to learn algorithmic trading. There is no denying the fact that if someone is technically sound then it is imperative that he will learn the techniques of algo trading much faster and they have a higher chance of succeeding in this field.
While the truth is that though this is something not very easy to learn particularly for non-programmers, however if taught in a right way and in right context it is not impossible as well provided the learner is serious enough and given the modern tools that are available at ones disposal nowadays. What is required is serious and sincere effort and a zeal to learn.
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, the access to the lecture recordings for the Python Primer module will be provided free of cost.
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 program 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.
Is the program suitable for people having no background in finance?
While any prior knowledge is always useful, however the course has been designed in a way that even people having no knowledge of finance can attend and learn from this program.
The program includes modules on relevant areas of basic finance like theories of technical analysis, charting, financial markets, derivatives, option strategies etc. theories are brushed-up before we go into the advanced areas.
The course is taught in an easy, lucid and structured way. We teach from basic to advanced levels in a way where people with limited background can also pick-up the skills.
Who should attend?
If you are someone who is interested in making a career as a trader, whether you wish to take-up a job or you wish to trade on your own, then learning Algorithmic Trading is no longer a matter of choice it is almost a compulsion now.
We have built this course with aim to teach Algo Trading to participants of all kinds of background, the only criteria are that the participant should have a zeal to learn.
Whatever is your background, if you are someone who wants to learn Algo Trading and either work in an International Bank, Hedge Fund or Prop Desks or you wish to trade on your own or you wish set-up your own trading desk, we offer you the right course to fulfil all your requirements.
It can be done by Finance, Banking, IT and other Professionals, Dealers, Arbitrageurs, Prop Traders, Retail Traders – those who aspire to become Quant/Algo Traders and work for the trading teams of International Banks, Hedge Funds, Prop Desks of Brokers or Analytics teams of Consulting Firms or IT Companies.
Also, students from Engineering, Mathematics, Statistics, Economics, Finance, Commerce etc. background who aspires to work in International Banks, Hedge Funds, Prop Desks etc. in advanced Quant Trading/Algo Trading roles or in advanced analytical roles in Quant analytics, Derivative Pricing and Valuation, Model Validation, Treasury, etc. should do this course.
Why you should attend this program?
• Highly qualified Industry Practitioner faculty
• Advanced Curriculum including Data Science & Machine Learning
• Covers end-to-end all aspects of Algo-trading, starting from strategy development, extensive back-testing, optimization, order management, risk management, error handling, platform integration
• Training on industry leading algorithmic trading platform
• Free access to Python Programming for Finance course - worth Rs 8000
• Lifetime placement support for all participants
• Hands-on training in Programming Algo-trading strategies in Python
• We don’t believe in template-based teaching, our lectures cover hands-on implementation from scratch during the lectures.
• Taught in an easy, lucid and structured way
• We teach from basic to advanced levels in a way where people with limited background can pick-up the skills
• Post Course support – We believe in imparting complete learning and offering support even after the course gets over
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?
All aspects of Algo Trading, starting from strategy development, extensive back-testing, optimization, order management, risk management, error handling and integration with a trading platform. You also get to learn Quantitative Algorithmic Strategies and Machine Learning for Quantitative Trading Using Python.
Training is provided on industry leading algorithmic trading platform.
We don’t believe in template-based teaching, our lectures cover hands-on implementation of the entire development of algo cycle from scratch during the lectures.
The course has a very advanced curriculum designed by Traders and Quant practitioners from top Wall Street Investment Banks and financial institutions and industry experts to prepare job-ready professionals.
Who are the faculty?
The course is taught by Top-notch Traders, Quant Practitioners and Industry Experts from International Banks and Hedge Funds. The faculty team consists of leading traders and domain experts with top class education background from IIT’s, IIM’s and Ph.D.'s from top institutes.
What is the post course support?
We believe in imparting complete learning and we offer support even after the course gets over. You get whole-hearted support not only during the course but after the completion of the course as well. Our faculty team goes out of their way to extend all possible help to serious learners. You can email us with your doubts and queries and you will be connected to the appropriate faculty for solving your doubts and queries.
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 and Trading Desks of other financial institutions.
You may work as Quant Trader, Algo Trader, Consultant, Domain expert and lead Quant and Trading Teams of International Banks, top Hedge Funds, Proprietary Trading Desks, Fund Managers and or fortune 500 Financial Consulting Firms and Leading IT Companies.
What is the course calendar?
This course is offered 3 times in a year.
How long has this programme been around for?
The first cohort of this program commenced in 2013.
What programming language does this program use?
This program is entirely taught using Python. It provides complete hands-on training in Programming Algo-trading strategies in 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.
You can call us on +91-8976993621 or email us your contact details if you would like a call back
(This service is normally available between 9.00 AM and 9.00 PM all the day. At all other times, please submit an email request.)