Algorithmic Trading Course - Training for Traders, Quants & Programmers (2022)

programme benefits

Algorithmic Trading Course - Training for Traders, Quants & Programmers (1)

World-Class Faculty

Learn from the best in the industry

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Dedicated Support

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We have a 4.7 rating out of 130+ Google reviews

Algorithmic Trading Course - Training for Traders, Quants & Programmers (4) Jad Mawlawi
United Kingdom Algorithmic Trading Course - Training for Traders, Quants & Programmers (5)

EPAT has been a great experience for me. It is definitely the best programme out there to learn quantitative finance and algorithmic trading. The… See More

EPAT has been a great experience for me. It is definitely the best programme out there to learn quantitative finance and algorithmic trading. The team was and still is very helpful and caring. The course itself is a combination of different disciplines including programming, finance, and statistics taught by very knowledgeable and experienced faculty.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (6) Billy Davila
United States Algorithmic Trading Course - Training for Traders, Quants & Programmers (7)

I recently completed the EPAT programme from QuantInsti, and it was a rich experience. I learned more here than I did on my university curriculum… See More

I recently completed the EPAT programme from QuantInsti, and it was a rich experience. I learned more here than I did on my university curriculum. This is mainly since the EPAT course is very practical and I was able to learn a lot in such a short time. It provided me with a lot of theoretical and practical knowledge in the algorithmic trading domain. Besides their excellent curriculum, the support team is friendly, dedicated, and always there to support you during your EPAT journey. They also have a placement team that keeps you updated with career opportunities. However, keep in mind that your background will influence how well you fit into those career opportunities. They also have a self-paced learning portal named Quantra which I really enjoy. Overall, they are excellent at what they do.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (8) Marcus Coleman
United States Algorithmic Trading Course - Training for Traders, Quants & Programmers (9)

QuantInsti is the best place to learn professional algorithmic and quantitative trading. The EPAT programme is a highly structured and hands-on l… See More

QuantInsti is the best place to learn professional algorithmic and quantitative trading. The EPAT programme is a highly structured and hands-on learning experience and it's being updated frequently. The faculty and staff are extremely competent and available to address any concerns you may have. Upon completion of the EPAT programme you will have the necessary tools to begin a career in algorithmic/quantitative trading.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (10) Jim Ike
Singapore Algorithmic Trading Course - Training for Traders, Quants & Programmers (11)

From basic knowledge of quantitative finance to practical hands-on python session of back testing trading strategies, EPAT course covers a large … See More

From basic knowledge of quantitative finance to practical hands-on python session of back testing trading strategies, EPAT course covers a large portion of knowledge needed to join algorithmic trading industry. Good introduction to dive in.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (12) Ronnie Varghese
United Arab Emirates Algorithmic Trading Course - Training for Traders, Quants & Programmers (13)

The Executive Programme in Algorithmic Trading (EPAT) is a well structured, intensive course which takes approx. 6 months to complete. The core f… See More

The Executive Programme in Algorithmic Trading (EPAT) is a well structured, intensive course which takes approx. 6 months to complete. The core focus areas of the course are stock market theories and quantitative principles, statistical analysis and programming. With the current trend of businesses moving towards implementing Artificial Intelligence (AI) or data-centric approaches to solving difficult problems, the skills gained from this course can be used to solve any AI-related problem (i.e. these skills can be used for any domain other than algorithmic trading). Having these skills in your repertoire will likely increase the probability of finding employment. Further, the Institute actively works towards the placement of the students enrolled (or alumni) in the course. The faculty are experts in their respective fields. In order to successfully complete this course, the student must be committed to completing the assignments and projects to cement their understanding of the course material. An added advantage is that there is lifetime access to the course materials, which will enable any alumni of the EPAT course to stay updated on the developments in this field. Overall, in my opinion, EPAT provides value for your money.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (14) Avi Nandwani
United States Algorithmic Trading Course - Training for Traders, Quants & Programmers (15)

I found the EPAT course to be exactly what I was looking for – the right mix of statistics, financial markets and coding. The faculties were exce… See More

I found the EPAT course to be exactly what I was looking for – the right mix of statistics, financial markets and coding. The faculties were excellent, and most importantly, the support team was exceptional with their efforts towards my learning.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (16) Rajeev Chahar
India Algorithmic Trading Course - Training for Traders, Quants & Programmers (17)

Your one-stop solution for the niche and opaque domain of Algorithmic Trading. Be it faculty, student support service, training content & resourc… See More

Your one-stop solution for the niche and opaque domain of Algorithmic Trading. Be it faculty, student support service, training content & resources or communication, they match the standards of international repute!

Algorithmic Trading Course - Training for Traders, Quants & Programmers (18) Raymond Philips
South Africa Algorithmic Trading Course - Training for Traders, Quants & Programmers (19)

I had a great experience through QuantInsti Learning. If you are passionate about Algorithmic/Quantitative Trading, or you want to start your jou… See More

I had a great experience through QuantInsti Learning. If you are passionate about Algorithmic/Quantitative Trading, or you want to start your journey in this amazing discipline, this is a great place to begin and grow your knowledge and interest. The administration and faculty were outstanding. Lectures are well-delivered and informative and there is always additional help should you require it. There is a wide array of learning material both through coursework and through the community as a whole.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (20) Eriz Zárate
Spain Algorithmic Trading Course - Training for Traders, Quants & Programmers (21)

Only great words to say about QuantInsti and my learning path during the EPAT programme. Always curious, always listening and improving. All the … See More

Only great words to say about QuantInsti and my learning path during the EPAT programme. Always curious, always listening and improving. All the staff, starting from the CEO down to the support people were very nice 120% of the time (the 20% excess goes to all the help that they have given me after concluding the course, every time with a consistent will to help others).

Regarding the EPAT programme content, the key thing I would like to say is that is a wide covering approach. During six months, industry experts (i.e. real practitioners, not Gurus) dive into a variety of topics from scratch, so that, after that, you can choose in which field are you going to focus.

My final thoughts for new EPATians are: it is a must-do course if you are beginning in the field of algorithmic trading and quantitative finance. Although the real value is in the people that drive the institution. Be sure that you will have to take more courses after EPAT to succeed in this field, but you won't find the life-long learning support that they will give you anywhere else.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (22) Nicolò Pirozzi
Italy Algorithmic Trading Course - Training for Traders, Quants & Programmers (23)

The course is very organized, both theoretical and practical, the staff is very competent and helpful, I found myself at ease during the whole co… See More

The course is very organized, both theoretical and practical, the staff is very competent and helpful, I found myself at ease during the whole course of study, I learned the basics to start a career in algorithmic trading and finance in general. What I appreciated the most were the lessons held with prominent personalities from the world of finance and trading, who shared their knowledge and experiences with the students. I would definitely recommend the course to anyone wishing to pursue a career in trading and finance.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (24) Jad Mawlawi
United Kingdom Algorithmic Trading Course - Training for Traders, Quants & Programmers (25)

EPAT has been a great experience for me. It is definitely the best programme out there to learn quantitative finance and algorithmic trading. The team was and still is very helpful and caring. The course itself is a combination of different disciplines including programming, finance, and statistics taught by very knowledgeable and experienced faculty.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (26) Billy Davila
United States Algorithmic Trading Course - Training for Traders, Quants & Programmers (27)

I recently completed the EPAT programme from QuantInsti, and it was a rich experience. I learned more here than I did on my university curriculum. This is mainly since the EPAT course is very practical and I was able to learn a lot in such a short time. It provided me with a lot of theoretical and practical knowledge in the algorithmic trading domain. Besides their excellent curriculum, the support team is friendly, dedicated, and always there to support you during your EPAT journey. They also have a placement team that keeps you updated with career opportunities. However, keep in mind that your background will influence how well you fit into those career opportunities. They also have a self-paced learning portal named Quantra which I really enjoy. Overall, they are excellent at what they do.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (28) Marcus Coleman
United States Algorithmic Trading Course - Training for Traders, Quants & Programmers (29)

QuantInsti is the best place to learn professional algorithmic and quantitative trading. The EPAT programme is a highly structured and hands-on learning experience and it's being updated frequently. The faculty and staff are extremely competent and available to address any concerns you may have. Upon completion of the EPAT programme you will have the necessary tools to begin a career in algorithmic/quantitative trading.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (30) Jim Ike
Singapore Algorithmic Trading Course - Training for Traders, Quants & Programmers (31)

From basic knowledge of quantitative finance to practical hands-on python session of back testing trading strategies, EPAT course covers a large portion of knowledge needed to join algorithmic trading industry. Good introduction to dive in.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (32) Ronnie Varghese
United Arab Emirates Algorithmic Trading Course - Training for Traders, Quants & Programmers (33)

The Executive Programme in Algorithmic Trading (EPAT) is a well structured, intensive course which takes approx. 6 months to complete. The core focus areas of the course are stock market theories and quantitative principles, statistical analysis and programming. With the current trend of businesses moving towards implementing Artificial Intelligence (AI) or data-centric approaches to solving difficult problems, the skills gained from this course can be used to solve any AI-related problem (i.e. these skills can be used for any domain other than algorithmic trading). Having these skills in your repertoire will likely increase the probability of finding employment. Further, the Institute actively works towards the placement of the students enrolled (or alumni) in the course. The faculty are experts in their respective fields. In order to successfully complete this course, the student must be committed to completing the assignments and projects to cement their understanding of the course material. An added advantage is that there is lifetime access to the course materials, which will enable any alumni of the EPAT course to stay updated on the developments in this field. Overall, in my opinion, EPAT provides value for your money.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (34) Avi Nandwani
United States Algorithmic Trading Course - Training for Traders, Quants & Programmers (35)

(Video) Algorithmic Trading Using Python - Full Course

I found the EPAT course to be exactly what I was looking for – the right mix of statistics, financial markets and coding. The faculties were excellent, and most importantly, the support team was exceptional with their efforts towards my learning.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (36) Rajeev Chahar
India Algorithmic Trading Course - Training for Traders, Quants & Programmers (37)

Your one-stop solution for the niche and opaque domain of Algorithmic Trading. Be it faculty, student support service, training content & resources or communication, they match the standards of international repute!

Algorithmic Trading Course - Training for Traders, Quants & Programmers (38) Raymond Philips
South Africa Algorithmic Trading Course - Training for Traders, Quants & Programmers (39)

I had a great experience through QuantInsti Learning. If you are passionate about Algorithmic/Quantitative Trading, or you want to start your journey in this amazing discipline, this is a great place to begin and grow your knowledge and interest. The administration and faculty were outstanding. Lectures are well-delivered and informative and there is always additional help should you require it. There is a wide array of learning material both through coursework and through the community as a whole.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (40) Eriz Zárate
Spain Algorithmic Trading Course - Training for Traders, Quants & Programmers (41)

Only great words to say about QuantInsti and my learning path during the EPAT programme. Always curious, always listening and improving. All the staff, starting from the CEO down to the support people were very nice 120% of the time (the 20% excess goes to all the help that they have given me after concluding the course, every time with a consistent will to help others).

Regarding the EPAT programme content, the key thing I would like to say is that is a wide covering approach. During six months, industry experts (i.e. real practitioners, not Gurus) dive into a variety of topics from scratch, so that, after that, you can choose in which field are you going to focus.

My final thoughts for new EPATians are: it is a must-do course if you are beginning in the field of algorithmic trading and quantitative finance. Although the real value is in the people that drive the institution. Be sure that you will have to take more courses after EPAT to succeed in this field, but you won't find the life-long learning support that they will give you anywhere else.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (42) Nicolò Pirozzi
Italy Algorithmic Trading Course - Training for Traders, Quants & Programmers (43)

The course is very organized, both theoretical and practical, the staff is very competent and helpful, I found myself at ease during the whole course of study, I learned the basics to start a career in algorithmic trading and finance in general. What I appreciated the most were the lessons held with prominent personalities from the world of finance and trading, who shared their knowledge and experiences with the students. I would definitely recommend the course to anyone wishing to pursue a career in trading and finance.

120+

Hours Live Lectures

20+

World Class Faculty

300+

Hiring Partners

90+

Participant Countries

PLACEMENT PARTNERS

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programme features

Algorithmic Trading Course - Training for Traders, Quants & Programmers (50) Project work opportunity

Algorithmic Trading Course - Training for Traders, Quants & Programmers (51) Scholarships and Financial Aid

Algorithmic Trading Course - Training for Traders, Quants & Programmers (52)Lifetime access to latest course content

Algorithmic Trading Course - Training for Traders, Quants & Programmers (53) Verified Certification

Algorithmic Trading Course - Training for Traders, Quants & Programmers (54) Exclusive EPAT Community benefits

Algorithmic Trading Course - Training for Traders, Quants & Programmers (55) Credit Points for continuous professional development

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Algorithmic Trading Course - Training for Traders, Quants & Programmers (56) +91-8291945958
+1-312-761-8620 (Global)

Algorithmic Trading Course - Training for Traders, Quants & Programmers (57) contact@quantinsti.com

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  • Basics of Algorithmic Trading: Know and understand the terminology
  • Excel: Basics of MS Excel, available functions and many examples to give you a good introduction to the basics
  • Basics of Python: Installation, basic functions, interactive exercises, and Python Notebook
  • Options: Terminology, options pricing basic, Greeks and simple option trading strategies
  • Basic Statistics including Probability Distributions
  • MATLAB: Tutorial to get an hands-on on MATLAB
  • Introduction to Machine Learning: Basics of Machine Learning for trading and implement different machine learning algorithms to trade in financial markets
  • Two preparatory sessions will be conducted to answer queries and resolve doubts on Statistics Primer and Python Primer
  • Data Visualization: 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 inferring outcomes, Capital Asset Pricing Model
  • Modern Portfolio Theory - statistical approximations of risk/reward
  • Data types, variables, Python in-built data structures, inbuilt functions, logical operators, and control structures
  • Introduction to some key libraries NumPy, pandas, and matplotlib
  • Python concepts for writing functions and implementing strategies
  • Writing and backtesting trading strategies
  • Two Python tutorials will be conducted to answer queries and resolve doubts on Python
  • Overview of Electronic and Algorithmic Trading.
  • Various order types, order book dynamics, Spoofing, Price Time Priority Algorithm and Guerilla Algorithm.
  • Execution strategy to trade large volumes.
  • The algorithmic trading process from a market microstructure perspective.
  • Understanding of Equities Derivative market
  • VWAP strategy: Implementation, effect of VWAP, maintaining log journal
  • Different types of Momentum (Time series & Cross-sectional)
  • Trend following strategies and Statistical Arbitrage Trading strategy modeling with Python
  • Arbitrage, market making and asset allocation strategies using ETFs
  • Implement various OOP concepts in python program - Aggregation, Inheritance, Composition, Encapsulation, and Polymorphism
  • Back-testing methodologies & techniques and using Random Walk Hypothesis
  • Quantitative analysis using Python: Compute statistical parameters, perform regression analysis, understanding VaR
  • Work on sample strategies, trade the Boring Consumer Stocks in Python
  • Two tutorials will be conducted after the initial two lectures to answer queries and resolve doubts about Data Analysis and Modeling in Python
  • Decision Trees, Support Vector Machine, Neural Networks, Forward propagation, Backward propagation, Various neural network architectures.
  • Building a “Principal Component Analysis” manually, conducting a pairs-trading back-test using PCA, Simulation of multiple co-integrated assets, and Sector statistical arbitrage using PCA.
  • Using Python and Jupyter notebooks to create features, evaluate models, use feature selection and test raw performance.
  • Overview of Alternate Data: Sources, data formats, storage and retrieval choices, Understanding RDF and Knowledge Graph, Tagging Unstructured Data with relevant metadata.
  • Using spaCy for common Text processing tasks, Understanding Topic Modeling and Topic Classification.
  • Understanding Machine Readable News Programmatic consumption of news.
  • Machine Readable News in the Financial Industry: Sample in Production use cases, Sentiment Data in the Financial Industry: Sample in Production use cases.
  • Basic ideas of deep reinforcement learning such as reward, explore/exploit, Bellman equation and memory replay.
  • Challenges and problems with RL in trading, Implementation of RL in a simple strategy using "gamification".
  • System Architecture of an automated trading system
  • Infrastructure (hardware, physical, network, etc.) requirements
  • Understanding the business environment (including regulatory environment, financials, business insights, etc.) for setting up an Algorithmic Trading desk
  • Time series analysis and statistical functions including autocorrelation function, partial autocorrelation function, maximum likelihood estimation, Akaike Information Criterion
  • Stationarity of time series, Autoregressive Process, Forecasting using ARIMA
  • Difference between ARCH and GARCH and Understanding volatility
  • Introduction to Interactive Brokers platform and Blueshift
  • Code and back-test different strategies on various platforms
  • Using IBridgePy API to automate your trading strategies on Interactive Brokers platform
  • Interactive Brokers Python API
  • Different methodologies of evaluating portfolio & strategy performance
  • Risk Management: Sources of risk, risk limits, risk evaluation & mitigation, risk control systems
  • Trade sizing for individual trading strategy using conventional methodologies, Kelly criterion, Leverage space theorem
  • Options Pricing Models: Conceptual understanding and application to different strategies & asset classes
  • Option Greeks: Characteristics & Greeks based trading strategies
  • Implied volatility, smile, skew and forward volatility
  • Sensitivity analysis of options portfolio with risk management tools
  • Self-study project work under mentorship of a domain/expert
  • Project topic qualifies for area of specialization and enhanced learning
  • EPAT exam is conducted at proctored centers in 80+ countries

Certificate

This programme has been accredited by The Institute of Banking and Finance (IBF, Singapore) under the IBF Standards. IBF-STS provides upto 70% funding for direct training costs subject to a cap of S$ 7,000 per candidate per programme subject to all eligibility criteria being met. This is applicable to Singapore Citizens or Singapore Permanent Residents, physically based in Singapore. Find out more on www.ibf.org.sg

EPAT is accredited by CPD, UK (Continuing Professional Development, UK)

QuantInsti has registered this program with GARP for Continuing Professional Development (CPD) credits. Attending this program qualifies for 30 GARP CPD credit hours. If you are a Certified Financial Risk Manager (FRM®), or Energy Risk Professional (ERP®), please record this activity in your Credit Tracker.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (58)

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Faculty Members

Algorithmic Trading Course - Training for Traders, Quants & Programmers (59)

Anil Yadav

Anil 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.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (60)

Brian Christopher

Brian is a Quantitative researcher, Python developer, CFA charter holder, and the founder of Blackarbs LLC, a quantitative research firm. He attained a BSc in Economics from North-eastern University in Boston, MA and received the Chartered Financial Analyst (CFA) designation in 2016.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (61)

Dr. Ankur Sinha

Dr. Sinha is associated with IIM Ahmedabad, India as a faculty as well as heading various departments. He has taught at Aalto University School of Business, Finland & Michigan State University, United States. He holds a PhD in Business Technology from Aalto University School of Business, Helsinki, Finland, and has done Mechanical Engineering from IIT Kanpur, India.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (62)

Dr. Ernest P. Chan

Ernie is the Managing Member of QTS Capital Management, LLC. He is also the Founder and CEO of PredictNow.ai. He has authored multiple books, teaches courses and conducts workshops in trading and finance in Australia, Canada, Singapore, the United Kingdom, and the United States.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (63)

Dr. Euan Sinclair

Dr. Euan has more than 2 decades of Options trading experience. He's currently the partner at Talton Capital Management, a volatility trading fund. He holds a Ph.D. in theoretical physics from the University of Bristol and has written two books, “Volatility Trading” and “Option Trading”, both published by Wiley, as well as numerous papers and articles.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (64)

Dr. Gaurav Raizada

Dr. Gaurav is a Director at iRage Capital Advisory Pvt Ltd, the Chief Investment Officer for iRage Master Trust Investment Managers LLP and a Designated Partner for iRage Broking LLP. He has consulted extensively with core focus on strategy development and execution, including trading systems development, optimization and transaction cost analysis.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (65)

Dr. Hui Liu

Dr. 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.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (66)

Dr. Robert Kissell

Dr. Kissell is a global leader and industry expert with top management experience spanning 25+ years at some of the largest financial institutions like UBS, JP Morgan, and Citigroup. He teaches/taught at Fordham University, Molloy College, Baruch College and Cornell University. He is an international speaker and author of 4 books and countless financial research papers.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (67)

Ishan Shah

Ishan 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

Algorithmic Trading Course - Training for Traders, Quants & Programmers (68)

Nitesh Khandelwal

Nitesh 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 leads the overall business & is in-charge of new initiatives & ventures by QuantInsti®.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (69)

Nitin Aggarwal

Nitin is the Founder and CEO of Alphom Advisory Pvt. Ltd. (a trading firm), prior to which he has led the Operations team in Pentagon Advisory, has been a quant at iRageCapital and a Leadership Associate with the Aditya Birla Group. His gamut of experience ranges from developing novel breakthrough chemical technologies to creating proprietary trading strategies.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (70)

Prodipta Ghosh

Before joining QuantInsti as Vice President, Prodipta spent more than a decade in the banking industry – in various roles across trading and structuring desks for Deutsche Bank in Mumbai & London, and as a corporate banker with Standard Chartered Bank. Prior to that, Prodipta worked as a scientist in India’s Defence R&D Organization (DRDO).

Algorithmic Trading Course - Training for Traders, Quants & Programmers (71)

Rajib Ranjan Borah

Rajib is the Co-founder & Director of iRageCapital Advisory Pvt Ltd & QuantInsti Quantitative Learning Pvt Ltd. He has conducted workshops in the United States, Europe and Asia and is a visiting faculty in finance & accounting department for the flagship MBA program at IIM-A, one of the globally leading B-School.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (72)

Dr. Thomas Starke

Tom is the CEO of AAAQuants and the co-founder of pSemi. With a remarkable career spanning working with Vivienne Court, Memjet Australia, and Rolls-Royce Plc (UK), he has conducted workshops and presentations on algorithmic trading around the world. A PhD Physics degree holder, he was a senior research fellow at Oxford University.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (73)

Vivek Krishnamoorthy

Vivek has a Bachelors' in Engineering, an MBA, and a Graduate Certificate in Public Policy. He is also an aspiring actuary and has cleared six papers of the Institute of Actuaries (and was a country topper in one of them). He has over 12 years of experience across India, Singapore and Canada in industry, academia and research.

Algorithmic Trading Course - Training for Traders, Quants & Programmers (74)

Dr. Yves J. Hilpisch

Dr. Yves Hilpisch is an expert in Python & Mathematical Finance and covers topics related to Python coding & strategy backtesting. He also covers Object-Oriented Programming concepts in Python. Yves is the founder and the CEO of The Python Quants as well as The AI Machine. He is also an Adjunct Professor for Computational Finance—Miami, USA & Riga, Latvia.

(Video) Full Algorithmic Trading Course | Trade Using Python (Part 1 of 3)

ADMISSION PROCESS

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and get started

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(Video) Algorithmic Trading Courses conducted by IIQF

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Before admission, we will facilitate a one-on-one counselling session that will focus on understanding the strengths and weaknesses of the participant. These sessions do not necessarily decide the participants' eligibility but help counsellors assist them with informed guidance prior to enrollment.

$ 7,999

Scholarship and Financial Aid available for eligible participants

Pay your Fees

Schedule

We have four batches in a year. Duration of the programme is 6 months. The tentative programme start dates are:

BatchStart Date
5516 July, 2022
5615 October, 2022

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  • Programme
  • Funding EPAT
  • Learning Experience
  • Career Guidance
  • About QuantInsti
For the EPAT® programme batch starting from 15 October, 2022, the standard fee is $7499. For Indian resident participants, the discounted fee is ₹2,90,000 (plus taxes). The updated fees details are available here. Qualified applicants are provided with financial assistance and flexible payment plans. EPAT fee will be updated to $7999 from Batch 56 starting in October 2022.
Financial assistance provided to qualified applicants include but are not limited to the following:
  • Merit based scholarship - QuantInsti offers scholarship to deserving candidates who score well in the test available here
  • Student discounts - QuantInsti believes in investing in the future of tomorrow, the students of today. We have a discounted fee for full-time students.
  • Participants from Emerging Markets - Special consideration is given to participants from Emerging Markets so that the programme is more affordable.
  • Flexible Payment Plans - QuantInsti is partnered with financial institutes that provide education-related flexible payment plans to Indian resident participants.
  • This programme has been accredited under the IBF Standards, and is eligible for funding under the IBF Standards Training Scheme (IBF-STS), subject to all eligibility criteria being met. A participant must successfully complete the EPAT programme (including passing all relevant assessments and examinations) in order to be eligible. Prospective participants are advised to assess the suitability of the programme and its relevance to participants’ business activities or job roles.

    IBF-STS provides upto 70% funding for direct training costs subject to a cap of S$ 7,000 per candidate per programme subject to all eligibility criteria being met. This is applicable to Singapore Citizens or Singapore Permanent Residents, physically based in Singapore. Find out more on www.ibf.org.sg

Get in touch with our programme counselors here.
QuantInsti has partnered with government approved NBFCs to facilitate 0% financial assistance with minimal documentation for the Indian resident participants. To apply for the assistance, you would be required to share following documents with QuantInsti:
  1. First and Last Name
  2. Scanned Copy of PAN Card & Aadhaar Card - This will help to generate your CIBIL score
  3. Last three months pay slip (in case of a salaried employee) or last three year filed ITR (in case of self-employed)
  4. Last 4 months bank statement
Once you share the mentioned documents, your programme manager will connect you with the respective NBFC associates. Respective NBFC will share the sanction letter (loan approval letter) on loan approval, and you can proceed with the downpayment as per the plan agreed with the NBFC associate.
On receipt of a defined downpayment and the payment from partnered NBFC, you'll get access to the Learning Management System (Primer Modules) to kick off your Algo and Quant learning journey.

It is an online test comprising of college-level questions from relevant disciplines: Statistics, Financial Markets, Options, and Programming. For high scorers, a merit-based discount is applicable to their EPAT fees. You can take the test here. Please note, that you get only one attempt for the test.
It is a simple three step process:
  1. Submit your application form here.
  2. Wait for your application to get accepted.
  3. Pay the fees.
Soon after the successful receipt of your EPAT fees & acceptance, you are given access to the learning management system (LMS portal) and your EPAT journey begins!
Before admission, we offer to facilitate a one-on-one counselling session that will focus on understanding the strengths and weaknesses of the participant. These sessions do not necessarily decide the participants’ eligibility but help counsellors assist them with informed guidance prior to enrolment.

We provide an opportunity to clear all your doubts about the programme prior to enrollment. Also, you get access to a dedicated team support even before your EPAT programme starts. Therefore, we follow a no refund policy.
Yes, you can apply. College students can benefit from EPAT by making themselves “more recruitable” with the required practical skills in the financial markets domain. EPAT alumni include college students who bagged good roles after successful completion of their college degree and EPAT.
Please note that while QuantInsti offers lifetime placement services to all EPAT alumni, it does not guarantee any placements.
QuantInsti offers student discounts to all full-time students, which can be availed by sharing the valid college ID proof and other required documents.
Send us your details by filling the application form here and we will arrange a counselling call for you.

Traders and financial market professionals who don’t have programming experience, can benefit & prepare themselves for their EPAT journey with the help of the primer content shared upon your successful enrollment. This is a self-study, interactive module which helps you code, understand basics and prepare yourself for the classroom sessions which cover advance and complex concepts as well. The primer module also contains a test which helps participants assess their learning.

Yes, you can apply. If you are from engineering or quantitative sciences background, you might already have some basic exposure to the skills required for Algorithmic trading domain. To check your eligibility in EPAT, apply for the scholarship test here. EPAT counsellors will get in touch with you and guide you further.
For beginners in Quantitative domain, EPAT offers primer modules on Statistics, Econometrics, Options, Financial markets, Excel computation and Python programming along with assessment tests in each of these categories.

Historically, we have been running 4 batches of EPAT in a year.
The updated dates and fees related information is available here.

Although, the course duration is of six months, you get more time for self-study and prepare for the course if you enroll early.
The enrollment for a batch starts around four months prior to the actual programme start date. As soon as you enroll successfully, you are provided with access to the student portal where you start with the primer content. You prepare on topics like Statistics, Econometrics, Options, Financial markets basics, Excel computation and Python programming.
From the batch starting date till batch closing date, you will get a period of six months to attend lectures, complete assignments, tests, project work and take the final examination.
  1. This programme has been accredited under the IBF Standards, and is eligible for funding under the IBF Standards Training Scheme (IBF-STS), subject to all eligibility criteria being met. A participant must successfully complete the EPAT programme (including passing all relevant assessments and examinations) in order to be eligible. Prospective participants are advised to assess the suitability of the programme and its relevance to participants’ business activities or job roles.

    IBF-STS provides upto 70% funding for direct training costs subject to a cap of S$ 7,000 per candidate per programme subject to all eligibility criteria being met. This is applicable to Singapore Citizens or Singapore Permanent Residents, physically based in Singapore. Find out more on www.ibf.org.sg

  2. EPAT is accredited by CPD, UK (Continuing Professional Development, UK)
  3. QuantInsti has registered this program with GARP for Continuing Professional Development (CPD) credits. Attending this program qualifies for 30 GARP CPD credit hours. If you are a Certified Financial Risk Manager (FRM®), or Energy Risk Professional (ERP®), please record this activity in your Credit Tracker.
Before the starting of a batch or/and during the first month, the primer topics in the fields of Statistics, Econometrics, Options, Financial markets basics, Excel computation and Python programming are covered. There are short tests on each of these topics which allow participants to test their knowledge in these fields.

2 preparatory lectures have been introduced to EPAT: Lecture 1 - Python and Lecture 2 - Statistics. These lectures would be conducted 2 weeks prior to the beginning of EPAT lectures and would be extremely beneficial in establishing your base in these topics.

The first month is on introductory topics in Algorithmic Trading such as basic statistics, programming basics and understanding of order book & execution strategies so that a strong foundation is laid for the rest of the programme.

Advanced topics include time series analysis, machine learning in trading, event-based execution, market making, equities and ETF trading based strategies, market microstructure, event driven backtesting, trading with mixture models among others. Different programming languages and tools used in the programme include Excel, R, Python, and Matlab. The programme allows participants to specialize in an asset class/strategy paradigm through project work which includes working under a trader’s mentorship. To receive the detailed curriculum, please do write to us at sales@quantinsti.com.

Typically 8-12 hours of self study, along with 6-8 hours of live lectures are required weekly to do well in the programme.

Your dedicated Support Manager will help you throughout the programme to ensure that you do not lag behind. Even if it happens, then depending on the completion date, you may choose the self-paced learning option available with a few months of extension. If you meet the minimum criterion for certification, you might be given the Certification of Participation in case you do not pass the final examination.

You can apply for a batch defer to a later one, before the starting date of your enrolled batch. If your application is complete along with all required documents and it fulfills the required criteria, you could be moved to a later batch.

The course participants who complete the coursework along with the final EPAT exam successfully are awarded ‘Certification of Excellence’. In case a participant is not able to clear the exam due to any reason but has completed most of the course work, (s)he would be awarded with a ‘Certification of Participation’.
The minimum requirements to be eligible for ‘Certification of Excellence’ includes certain percentage of
  • Attendance in lectures or time spent in watching the recordings
  • Score in quizzes and assignments
  • Score in the mid-term examination
  • Score in the final examination

EPAT Project is practical, self-driven, strategy creation or business related research work that participants carry out under mentorship of the respective domain expert. The project work is optional and carries no weightage in the final score. However, it serves as an excellent opportunity for the driven and motivated candidates to specialize in an asset class or strategy paradigm by working with relevant data and quant platform(s). Collaborative project work allows participants to work together with fellow classmates.

You will be required to work on different platforms and softwares in the programme. Most of these platforms and softwares are either open-sourced or their free/demo versions are available for EPAT participants. You would not be required to purchase any product for learning purposes. QuantInsti doesn’t sell or endorse any product used in the programme. It is only recommended for learning purposes.

You will be taught different strategy paradigms by experts in their domains. QuantInsti does not claim to offer ‘profitable strategies’. EPAT aims to deliver the concepts & advanced techniques to create various types of Quantitative Strategies.

EPAT curriculum includes topics on business environment and setting up on your trading desk in which participants get to interact live with faculty and experts who have domestic and international experience in running Algorithmic & Quantitative trading, including HFT business. The participants are exposed to the dynamics involved in setting up an algorithmic trading desk.
(Video) Trading strategy revealed 🚀 as a Quant trader!
You need to have:
  1. A personal computer with the minimum configuration as: Operating system such as Windows: (Windows 8, Windows 8.1, Windows 10) or Mac: Mac (v 10.10), Mac(v 10.11), Mac(v 10.12), Mac(v 10.13). Additionally, you will need some software/programming languages installed on your system in order to have hands-on experience as well as finishing the program. List of required software and the installation manuals will be shared with you before the programme starts.
  2. Language skills: You should be able to understand spoken and written English well.
  3. Enough time and motivation: You should be able to devote 10-15 hours on a weekly basis at the least. The more the better!
Career Assistance: Continual career guidance from the experts! One of the EPATians got placed after 6 years of completing EPAT.
Lifelong learning content: EPAT alumni keep themselves up-to-date with the latest EPAT content curated by the experts.
Ancillary resources and services (Quantra, Blueshift): EPAT alumni are given access to ancillary services including access to the trading platform, special discounts on quantitative trading related events & resources, invitations to conferences, sometimes exclusively!
Access to Quant network: Opportunity to connect with EPATians from 70+ countries, helping to create a global network of Quants and Algo traders. Country specific meetups are arranged for participants/alumni and faculty to get together occasionally.
Exclusive Invites to Webinars and Workshops for EPAT alumni: They attend the Guest lectures conducted by industry stalwarts.
You can find more details on our Alumni page.

Yes, you can attend a few classroom sessions in Mumbai, India, when the concerned faculty is based in Mumbai. Since most of the faculty members are located outside Mumbai, even if you are present in the QuantInsti classroom, you will be attending the lecture online. The weekly announcements mentions about the sessions happening in Mumbai.

Yes, you can attend the sessions on the go using the required apps on smartphones and tablets. But we recommend attending sessions on your laptop/desktop as most of the sessions are hands-on.

It is 100% online. You can opt for writing the exam at your nearby centre of our exam partner or remotely from home, given the pre-requisites are met.
In many ways:
  • The curriculum is practice oriented. It is designed by practitioners who try to ensure that you learn the concepts really well from practitioner perspective.
  • During practical sessions, the faculty would ask you to work along on your machine and might even quiz you in between and interact with you personally
  • We believe in data, data, data. Almost every concept is discussed around data from financial markets.
  • You would need to practice a lot on your own. This will be ensured through assignments which are open-ended and are individually graded.

No, you will not trade in live markets during the lecture hours or in the classroom sessions. However, you will be taught to paper trade and experts will share nuances that differ paper and live trading environment. When you take your strategies live and have doubts, as EPAT participant/alumni, you can get the required guidance from the faculty.
In many ways:
  • During the lecture you get to interact with the faculty
  • Post or before the lecture, you get to share your doubts and queries which will be resolved by the faculty
  • During EPAT project work, you get to work under mentorship of a faculty member
  • You can also interact with faculty through your support manager anytime!
  • A dedicated Support Manager who will guide you for the entire period of six months. Your manager will resolve your doubts and keep you motivated and engaged in this new and demanding career path
  • You will get advice and answers from the faculty members who are industry practitioners
  • You get career assistance from the career team, you will get help in building your resume, career counselling and more. You will start receiving job postings from the very first month
  • We will share with you additional links & content to further enhance your learning
  • Dedicated alumni cell is available post completion to help them grow in the algo domain and network with fellow alumnus
  • Life long access to updated lecture notes and videos after you complete EPAT course successfully.
QuantInsti provides you with two books to be referred to during the programme.
  • Trading and Exchanges: Market Microstructure for Practitioners - Larry Harris
  • Algorithmic Trading: Winning Strategies and Their Rationale - Dr. Ernest P. Chan (Also a faculty member)
Before starting EPAT, we provide primer modules to give you a head start and familiarize you with basics concepts and tools used during the programme. We also share additional links & content to further enhance your learning.
The total duration of the course is 6 months. It comprises of 4 parts:
  • Live Lectures
  • Test & Assignments
  • Live Project (optional)
  • Final Examination
Each lecture would ideally be of around 3 hours in duration, with two lectures in a week. The lectures take place over the weekends. To receive the detailed curriculum, please do write to us at sales@quantinsti.com.

EPAT Exams are conducted at the Prometric centres globally. Every year, there are four exam windows/weeks, during which you can schedule your own exam based on the availability of the slot at the nearest Prometric centre in your country. You may also write exam using the Remote proctoring basis availability.

Your account manager will help you with the details. Just share your city, country and the postal code with your account manager and (s)he will share the nearest centre. Also, with every batch, new centres are added, hence, you should check for the exam centre for the upcoming exams only.

We understand your concern and respect the efforts that you put to learn. So, we may provide you with a chance for re-attempting the exam. You can check with your support manager for detailed process. Re-scheduling charges may be applicable for the scheduling the exam beyond your batch exam window.

One month prior to the exam, you will get an email from the Support team, explaining the process for scheduling your exam. Additionally, you may call your support manager who will guide you to schedule your exam.

We have a dedicated in-house career cell that addresses any career related queries. The career cell receives job openings from 300+ placement partner firms from different countries.
Apart from sharing job opportunities, career cell conducts resume strengthening trainings, mock interviews, and provides you with sample assignment questions to prepare you for selection procedure. Placement assistance starts from the very first month and continues post course completion.

Short answer: No. We give placement assistance to all interested participants and alumni and try our best to find the appropriate match, however we don't guarantee getting a job, as it depends on many factors including but not limited to participants’ skillsets, past experience, performance in interview among others.

We do have placement partner firms in various parts of the world. We see most opportunities coming from US, India, Singapore, and Hong Kong.
QuantInsti strives to bring all possible roles in Algorithmic Trading to our participants. Some of these profiles include:
  • Developer
  • Quant Analyst
  • Quant Researcher
  • Trader
  • Strategist
You can read more about this here.

Knowing programming languages and coding is required for backtesting & automating your strategies hence candidates from coding background have an advantage. Companies are on a lookout for candidates with exposure to technology and finance both.The most suitable profile for them is a Quant Developer or Coder, however they can explore other roles as well.

Yes, we get internship, full-time employment, & freelancing opportunities from our partnered firms.
We see a few candidates placed almost every month. Some of these details are shared in our monthly newsletters. Please do write to us at sales@quantinsti.com if you want more information.
Job opportunities and offers depend on a number of factors such as educational background, Graduate/Post Graduate College/University, Certifications/Internships/Projects, past work experience, etc. Companies are generally looking for someone who has exposure to Tech & Finance background both.
Some examples of recent job opportunities & salary packages that we have shared with our participants through QuantInsti’s career cell are
  • Data Scientist: INR 1.5 million per annum,
  • Algo Trader: INR 800,000 per annum + incentives,
  • HFT trader: up to INR 2 million per annum,
  • Quant Research Analyst: INR 2 million per annum,
  • Quantitative Research: AED 1,00,000 + up to 40 % incentives per annum,
  • Trader: SGD 120,000 + performance linked bonus per annum,
  • Trader Derivatives: HKD 384,000 per annum + performance linked bonus
We are currently partnered with 300+ companies, that includes Algo trading/HFT firms, investment banks, trading and brokerage houses, consulting companies. A partial list is available here.
QuantInsti provides innovation and solutions to bridge the gap between finance and technology in the changing phase of the industry. It serves individuals, businesses, exchanges, data providers, brokers and other technology providers to achieve their common goal of excelling in Quant & Algo trading. QuantInsti provides both paid and free services to the industry.
  • Dedicated programme for professional & career growth: EPAT®
EPAT® certification & placement services allow motivated individuals to build an exciting career in Algorithmic & Quantitative trading.
  • Learn interactively at your own pace: Quantra®
Quantra is an e-learning portal that offers short, self-paced, interactive courses in topics such as Python for Trading, Machine Learning, Options Trading and many more, allowing a participant and businesses to pick and choose the skill set(s) they want to specialize into.
  • Backtesting platform with historical data: Blueshift
You can code & backtest your strategies for the Indian & US markets (on daily & minute level data) with Blueshift.
Free Services
  • Webinars
  • Blogs, tutorials and trading models
  • Algorithmic trading workshops, events and modules for exchanges and industry

It is located in India. The complete address is A-309, Boomerang, Chandivali Farm Road, Powai, Mumbai – 400 072.
QuantInsti® was founded by Algorithmic & High Frequency Traders and Experts, who also founded iRage, a leading HFT firm in Asia. On the advisory board are Dr. Ernest P. Chan and Prof. Gautam Mitra, both practitioners and academicians, globally renowned in their domains. The dedicated team of traders, trainers, developers and renowned expert faculty members from all across the world run the show currently. Know more here.
About IBF Certification
IBF Certification is an industry endorsed mark of quality for finance professionals in Singapore. Individuals who successfully complete an eligible IBF-Standards Training Scheme ("IBF-STS") accredited training and assessment programme and meet the relevant criteria may apply for IBF Certification. More information on IBF Certification can be found in here.

Yes, EPAT is accredited by The Institute of Banking and Finance (IBF, Singapore) under the IBF Standards. This is applicable to Singapore Citizens or Singapore Permanent Residents, physically based in Singapore.
EPAT is accredited by IBF-STS.
This programme has been accredited under the IBF Standards, and is eligible for funding under the IBF Standards Training Scheme (IBF-STS), subject to all eligibility criteria being met. A participant must successfully complete the EPAT programme (including passing all relevant assessments and examinations) in order to be eligible. Prospective participants are advised to assess the suitability of the programme and its relevance to participants’ business activities or job roles.
IBF-STS provides upto 70% funding for direct training costs subject to a cap of S$ 7,000 per candidate per programme subject to all eligibility criteria being met. This is applicable to Singapore Citizens or Singapore Permanent Residents, physically based in Singapore.
Find out more on www.ibf.org.sg.
  1. You need to be a Singapore Citizen or Permanent Resident, physically based in Singapore
  2. You must successfully complete the EPAT programme (including passing all relevant assessments and examinations) in order to be eligible
  3. You must attend at least 75% of the training
For more details, please book a call with counsellor.

No, it will remain the same.
Singapore Citizens or Singapore Permanent Residents, physically based in Singapore are eligible for STS funding, given they meet the defined criteria. Find out more on www.ibf.org.sg.

No, you cannot claim any other grant if you are claiming this subsidy from IBF. You should not be claiming for any other grants, subsidies, or tax concessions, provided either by the Financial Sector Development Fund (FSDF) and/or Singapore government agencies, unless explicitly permitted.

Batch deferment and self-study is not allowed for participants applying for grants from IBF-STS. You need to complete the programme by writing examinations being conducted with your batch.

As per the process, you need to confirm your application for the IBF-STS grant before you enroll into the programme, as the same needs to be communicated to the IBF-STS team at the time of batch registration.

(Video) Which is good for Retail or Intraday Traders - R or Python programming? Dr. Ernest Chan explains!

The grant would be rejected, if you fail to meet the 50% score criterion. In which case, you would be required to pay the balance amount.

The programme works on a Nett fee model, i.e. you need to pay only the difference between the fee, and the funding amount at the time of enrollment. QuantInsti will claim the funding amount from IBF-STS on completion of the programme. In case you fail to complete the programme with the required score in programme, or if the claim raised by QuantInsti is rejected by IBF, then you are liable to pay the funding amount to QuantInsti.

FAQs

Do quants use algorithmic trading? ›

Programming skills: Quant traders must be familiar with data mining, research, analysis, and automated trading systems. They are often involved in high-frequency trading or algorithmic trading.

Which programming language is best for algorithmic trading? ›

Top 10 Programming Languages that Traders Should Learn in 2022
  • Python. Python is an open-source programming language that follows a functional programming approach. ...
  • Java. Java is one of the most sought-after programming languages for traders. ...
  • JavaScript. ...
  • Scala. ...
  • C++ ...
  • C# ...
  • R. ...
  • PHP.
Jan 23, 2022

Is Quant trading same as algo trading? ›

Algorithmic (algo) traders use automated systems that analyse chart patterns then open and close positions on their behalf. Quant traders use statistical methods to identify, but not necessarily execute, opportunities. While they overlap each other, these are two separate techniques that shouldn't be confused.

Do quants make a lot of money? ›

What do Quants Earn? Compensation in the field of finance tends to be very high, and quantitative analysis follows this trend. 45 It is not uncommon to find positions with posted salaries of $250,000 or more, and when you add in bonuses, a quant likely could earn $500,000+ per year.

Do quants make more than traders? ›

In fact, algorithmic trading has led to a spike in demand for Quants, with major financial firms employing more Quants than Equity traders themselves. No wonder companies are lining up and doling out a quant salary so high. Depending on your skills and interests, you have a plethora of options in the Quant domain.

Is Python good for algo trading? ›

Python makes it easier to write and evaluate algo trading structures because of its functional programming approach. Python code can be easily extended to dynamic algorithms for trading. Python can be used to develop some great trading platforms whereas using C or C++ is a hassle and time-consuming job.

Do algo traders make money? ›

The answer to the feasibility of generating profit by an individual doing algorithm trading is yes.

Is algorithmic trading hard? ›

Algorithmic trading is not difficult. On the contrary, it makes things easier for the traders. For instance, you want to calculate the returns of a few stocks in 2020 which you had bought in 2009.

What programming language do quant traders use? ›

What Programming Languages Do Quants Need to Know? C++ and Java are the main programming languages used in trading systems. Quants often need to code in C++, in addition to knowing how to use tools like R, MatLab, Stata, Python, and to a lesser extent Perl.

Is C++ used in trading? ›

As we've noted before, C++ has historically been used for a particular set of functions in investment banks and financial services firms. By virtue of its low level memory access and therefore speed, it's often the language of choice for high speed trading systems.

Do quant traders need to code? ›

A quant developer is required to code the algorithms for executing the trading strategies developed by algorithmic traders. An aspiring quant developer, as well as an algorithmic trader, must learn a coding language, especially out of the most common ones such as Python, C++, R and Java.

What percentage of trading is algorithmic? ›

In the U.S. stock market and many other developed financial markets, about 60-75 percent of overall trading volume is generated through algorithmic trading according to Select USA.

What strategies do quant traders use? ›

Quantitative trading consists of trading strategies based on quantitative analysis, which rely on mathematical computations and number crunching to identify trading opportunities. Price and volume are two of the more common data inputs used in quantitative analysis as the main inputs to mathematical models.

Can I become a quant at 40? ›

Can You Still Become a Quant in Your Thirties? Absolutely. In fact, a good fraction of quantitative analysts, traders and developers make the change to finance only in their late twenties or early-to-mid thirties.

Can you become a quant trader without degree? ›

You can be a good quant without undergrad degree. You don't see that often or at all because it doesn't make sense to skip it 99.9% of the time. Self-taught mathematicians (or put any field instead of math here) are proof of this, what are 'good quants' in comparison with world-class mathematicians.

What type of math do quants use? ›

These quantitative analysts tend to rely more on numerical analysis than statistics and econometrics. One of the principal mathematical tools of quantitative finance is stochastic calculus.

Can quant traders make millions? ›

But how much do quants make; can they make millions? Yes, quants are one of the highest-paid professionals on Wall Street and can also make a lot of money trading for themselves; however, many of them do fail to make money. Whatever the approach, success in trading requires a lot of hard work and dedication.

How many hours do quants work? ›

Working Hours

Quants have a rather healthy work life balance. The typical day usually last from 8 AM to around 6 PM. The average workweek is around 50 to 60 hours with only rare spikes in case of some project deadline approaching or other such special circumstance.

Do quants use machine learning? ›

Machine Learning techniques are statistically driven and have been used by quants for a long time. Advances in computer processing power, availability of big data and media attention have created hype.

How long does it take to learn Python for algo trading? ›

It can take around 13 weeks to learn Python for trading with the help of a coding bootcamp. If you apply yourself, this is enough time to learn the syntax as well as some important functions, such as converting a string to integer.

Do quants use Python? ›

Python, MATLAB and R

All three are mainly used for prototyping quant models, especially in hedge funds and quant trading groups within banks. Quant traders/researchers write their prototype code in these languages.

What language is trading algos written? ›

For people who wish to thrive in the competitive market of quantitative trading programming expertise in Python, C++ or Java is a must. The core concepts behind using these programming languages for algorithmic trading are same.

Do banks use algo trading? ›

Banks have made heavy investments in algorithmic trading with top institutions offering a variety of solutions for trading currencies. For example, "adaptive algos", offered by many banks in recent months, can change their trading styles automatically depending on fluctuating market conditions.

Is algo trading easy? ›

Algorithmic trading is a very hard business. You need some competitive edge to succeed. It can either be technology, technical infrastructure, your trading team, access to funds, cost of credit, or strategy. Whenever a firm starts trading they normally have the edge in 2 or 3 spaces and acquire the others as they grow.

How safe is algo trading? ›

Algo trading is safe when you have a proper understanding of the systems, markets, trading strategies, and coding skills. Algo trading is worth it as it helps conduct emotion-free trading by not buying and selling at the wrong prices which, otherwise gets done on account of fear and greed.

Do quants use C++ or Python? ›

Yes. C++ and Java are the main programming languages used in trading systems, especially in High Frequency Trading. For this reason, quants often need to code in C++ as well. They also use other tools like R, MatLab , Python and Perl extensively.

Do I need C++ to be a quant? ›

A good understanding of the language will be a necessary prerequisite to gaining an interview as a derivatives pricing quant. In addition, an understanding of C++ will make learning other programming languages straightforward since it involves more complex concepts, such as manual memory management.

Why do banks use C++? ›

Justifiably known as one of the most difficult coding languages to master, banks need engineers proficient in C++ to work on the low latency trading systems that are key to winning business from quantitative hedge funds.

Should I learn C++ or Python? ›

Python leads to one conclusion: Python is better for beginners in terms of its easy-to-read code and simple syntax. Additionally, Python is a good option for web development (backend), while C++ is not very popular in web development of any kind. Python is also a leading language for data analysis and machine learning.

Is C++ easier than Python? ›

Python is much more beginner-friendly, while C++ is a more complicated, low-level language. C++ has more syntax rules and other programming conventions, while Python aims to imitate the regular English language.

Is C++ or Python better? ›

When it comes down to running the code you write with these two languages, Python runs through an interpreter line by line whereas C++ is pre-compiled. This means that C++ is much faster to run, which can be a key advantage over Python for many users.

Is algo-trading illegal? ›

Yes, algo trading is allowed in India and is legal. India introduced algo trading in 2008 with SEBI opening the doors of algo trading for institutional investors. With the evolution in algo trading, many brokers have extended algo trading to retail investors as well.

Who uses algorithmic trading? ›

Algorithmic trading is mainly used by institutional investors and big brokerage houses to cut down on costs associated with trading. According to research, algorithmic trading is especially beneficial for large order sizes that may comprise as much as 10% of overall trading volume.

Is algo-trading the future? ›

Future of Algorithmic Trading

India has 50-60% penetration of algo trading, but the developed markets have much higher penetration, more complex products, and more accessible regulations. Indian markets and algorithmic trading will continue to grow.

How do you create a trading algorithm in Excel? ›

How To Create Your Own Trading Robot In Excel In 10 Steps
  1. Open an account with Interactive Brokers. ...
  2. Download and install the Interactive Brokers Excel API. ...
  3. Think about how you can turn your trading rules into formulas you can use in Excel. ...
  4. Create and test your formulas.

How do quants trade? ›

Quantitative trading (also called quant trading) involves the use of computer algorithms and programs—based on simple or complex mathematical models—to identify and capitalize on available trading opportunities. Quant trading also involves research work on historical data with an aim to identify profit opportunities.

What programming languages do quants use? ›

Python, MATLAB and R

All three are mainly used for prototyping quant models, especially in hedge funds and quant trading groups within banks. Quant traders/researchers write their prototype code in these languages. These prototypes are then coded up in a (perceived) faster language such as C++, by a quant developer.

Why quant trading has advantages over traditional traders? ›

The vital benefit of quant trading is that users are able to analyze a large market across unlimited data points. Quant traders are able to use mathematics to tackle the factors. On the other hand, traditional traders use few factors to analyze the market.

How much money do algorithmic traders make? ›

The salaries of Algorithmic Traders in the US range from $20,072 to $535,864 , with a median salary of $96,858 . The middle 57% of Algorithmic Traders makes between $96,858 and $243,042, with the top 86% making $535,864.

How many hours do quants work? ›

Working Hours

Quants have a rather healthy work life balance. The typical day usually last from 8 AM to around 6 PM. The average workweek is around 50 to 60 hours with only rare spikes in case of some project deadline approaching or other such special circumstance.

What to study to become a quant? ›

While an undergraduate degree in mathematics, theoretical physics, computer science or EEE are most appropriate for quant roles, there are also other degrees that can lead to a top quant role, usually via a postgraduate route.

Do quants need PhD? ›

The point is that as derivatives markets becomes increasingly difficult and complex to understand, the level of knowledge is required to be reflected in your academic degrees. That's why the employees are requiring PhD from quants.

Is Python enough for quant? ›

Python has become a preferred choice for trading recently as Python is open-source and all the packages are free for commercial use. Python has gained traction in the quant finance community. Python makes it easy to build intricate statistical models with ease due to the availability of sufficient scientific libraries.

Do quants use C++ or Python? ›

Yes. C++ and Java are the main programming languages used in trading systems, especially in High Frequency Trading. For this reason, quants often need to code in C++ as well. They also use other tools like R, MatLab , Python and Perl extensively.

Do I need C++ to be a quant? ›

A good understanding of the language will be a necessary prerequisite to gaining an interview as a derivatives pricing quant. In addition, an understanding of C++ will make learning other programming languages straightforward since it involves more complex concepts, such as manual memory management.

Is algo trading better than trading? ›

The defined sets of instructions are based on timing, price, quantity, or any mathematical model. Apart from profit opportunities for the trader, algo-trading renders markets more liquid and trading more systematic by ruling out the impact of human emotions on trading activities.

Who invented quant trading? ›

More than three decades ago, Jim Simons embraced a radical investing approach by crunching data and creating predictive algorithms—years before these tactics were embraced in Silicon Valley and elsewhere. A former mathematics professor, Simons is worth $23 billion today.

Do quant traders use technical analysis? ›

But quantitative analysis is not often used as a standalone method for evaluating long-term investments. Instead, quantitative analysis is used in conjunction with fundamental and technical analysis to determine the potential advantages and risks of investment decisions.

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6. How To Create A Trading Algorithm From Scratch [Algo Trading Webinar] - 22 July 2021
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