This webinar gives a brief introduction to Algorithmic Trading followed by the changing skill sets that are required in the new age trading business by mapping the required skill sets. This is followed by Industry trends in Algorithmic and Quantitative Trading. It also gives a detailed view of how Quantinsti's Algorithmic and Quantitative Trading programme: Executive Programme in Algorithmic Trading can assist the participants aspiring to enter the domain of Algorithmic and Quantitative Trading.

1. Algorithmic & Quantitative
trading
Learn @QuantInsti
Webinar 14th March, 2013
5:30 pm to 6:30 pm IST
Mr Nitesh Khandelwal

2. Webinar agenda
 Algorithmic Trading: Introduction
 The Changing Trading Environment: Skills
 QuantInsti’s Executive Program in Algorithmic
trading (E-PAT)
 Algorithmic Trading Platform Architecture
 A peek into Algorithmic Trading Platform
 Q&A
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3. What is Algorithmic Trading
 Electronic Trading:
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4. What is Algorithmic Trading
 Electronic Trading: Sending orders over an electronic
network instead of calling a broker
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

5. What is Algorithmic Trading
 Electronic Trading: Sending orders over an electronic
network instead of calling a broker
 Algorithmic Trading:
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

6. What is Algorithmic Trading
 Electronic Trading: Sending orders over an electronic
network instead of calling a broker
 Algorithmic Trading: Using Algorithms to generate
trading signals and manage portfolios
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

7. What is Algorithmic Trading
 Electronic Trading: Sending orders over an electronic
network instead of calling a broker
 Algorithmic Trading: Using Algorithms to generate
trading signals and manage portfolios
 High-Frequency Trading:
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

8. What is Algorithmic Trading
 Electronic Trading: Sending orders over an electronic
network instead of calling a broker
 Algorithmic Trading: Using Algorithms to generate
trading signals and manage portfolios
 High-Frequency Trading: A special category of
algorithmic trading characterized by unusually brief
position-holding periods, low-latency response times,
and high trading volumes in a day
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

9. What is Algorithmic Trading
 Electronic Trading: Sending orders over an electronic
network instead of calling a broker
 Algorithmic Trading: Using Algorithms to generate
trading signals and manage portfolios
 High-Frequency Trading: A special category of
algorithmic trading characterized by unusually brief
position-holding periods, low-latency response times,
and high trading volumes in a day
 Quant Trading:
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

10. What is Algorithmic Trading
 Electronic Trading: Sending orders over an electronic
network instead of calling a broker
 Algorithmic Trading: Using Algorithms to generate
trading signals and manage portfolios
 High-Frequency Trading: A special category of
algorithmic trading characterized by unusually brief
position-holding periods, low-latency response times,
and high trading volumes in a day
 Quant Trading: Usage of advanced statistical
methodologies - no user discretion
 Could be low frequency / high frequency
 Could be manual / electronic
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

11. Global Trends in Algorithmic Trading
 HFT Contribution in US Equities
Source: Celent (Marsh & McLennan), 2011
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12. Global Trends in Algorithmic Trading
 HFT contribution across geographies
Source: Celent (Marsh & McLennan), 2011
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited

13. Become an Algo trader
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14. E-PAT course structure
Core content
Statistics and
Econometrics
Financial
Computing &
Technology
Algo & Quant
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trading

15. E-PAT Course Structure: Statistics and
Econometrics
Statistics & Econometrics
Advanced Statistics
Correlation vs. Cointegration
ARIMA, ARCH-GARCH Models
Multiple Regression
Time Series Analysis
Stochastic Math
Causality
Forecasting
Basic Statistics
Probability & Distribution
Statistical Inference
Linear Regression
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16. E-PAT course structure: Financial Computing &
Technology
Financial Computing & Technology
Programming
Intro to Programming Language(s)
Programming on Algorithmic Trading Platforms
Linear Regression
Statistical Tools
Excel & VBA
Financial Modeling using R
Using R & Excel for Back-testing
Technology for Algorithmic Trading
System Architecture
Understanding an Algo Trading Platform
Handling HFT Data
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17. E-PAT course structure: Algorithmic & Quantitative
Trading
Algo & Quant Trading
Trading Strategies
Statistical Arbitrage
Market Making Strategies
Execution Strategies
Forecasting & Artificial Intelligence
Based Strategies
Machine readable News based
Strategies
Trend following Strategies
Derivatives & Market Microstructure
Option Pricing Models
Time Structure of Volatility
Dispersion Trading
Volatility Forecasting &
Interpretations
Managing Risk using Greeks
Position Analysis
Order Book Dynamics
Market Microstructure
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Desk Operations
Hardware & Network
Regulatory Framework
Exchange Infrastructure &
Financial Planning (Costing)
Handling Risk Management in
Automated systems

18. E-PAT course mapping
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19. Program Delivery
 Part-time program
 3 hrs sessions on Saturday & Sunday both
 4 months long program
 100 contact hours including practical sessions
 Convenience - webinars
 Open Source
 Virtual Classroom integration
 Student Portal
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20. Algorithmic Trading Platform: A Sneak
Peek
Source: marketcetera
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21. Algorithmic Trading: System
Architecture
Application Server Exchange
Application
Market Data
F
I
X
Complex Event Processing
engine
Order Manager
MktData
Store
Event
History
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Exchange
1
Storage
Strategy
Settings
UI
State
Mgmt (PnL
+ Position)
Order /
Execution
Monitor
Within
application
RMS
Maths
Calc
RMS
Admin
Monitor
Exchange
2
F
I
X
Data
Normalizer
Order
Router
Back
office
record
Adaptor for
third party
apps – R,
Matlab, etc
Data
Retrieval
Data
Vendor
Replay
of stored
data
Simulator
exchange

22. Going beyond the curriculum
 Faculty supervision
 Placement assistance
 Forum
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23. Coming dates
 http://www.quantinsti.com/importantdates.html
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24. Q&A
 Please type your questions in the chat window.
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25. Thanks!
 For more information visit:
Youtube channel
LinkedIn group
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