Gaurav Bubna gave a talk on careers in algorithmic trading. He discussed his background working in derivative pricing and algorithmic trading at Morgan Stanley. The talk covered an introduction to algorithmic trading, different types including large order execution, market making, and proprietary trading. Bubna also provided examples of trading strategies and advice for pursuing a career in algorithmic trading, emphasizing skills in programming and statistics. He concluded by briefly describing ZLemma.com and its tools for assessing job suitability.

1. Careers in Algorithmic
Trading
Gaurav Bubna
IIT Delhi, Feb 2013

2. My Background
● B.Tech. Computer Science. IIT Bombay
○ Internships at Cornell and INRIA Grenoble
● Associate. Morgan Stanley
○ Worked on derivative pricing and algorithmic trading
● Product Strategist. ZLemma.com

3. Overview of this talk
● Introduction to Algo Trading
● Different types of Algo Trading
● Examples of some strategies
● Career notes
● Briefly about ZLemma

4. Introduction to Algo Trading
● Executing trades based on algorithms
● Originally arose to execute large orders
● Majority of vanilla trades based on algos
● Fixed income going electronic
● Algo trading is the future!

5. Different Types and Purposes
● Large order execution
● Market Making
● Proprietary trading
● Mutual funds
● Different Frequencies

6. Large Order Execution
● Client wants to sell 1MM shares of Apple
● Selling all at once can move market prices
● Selling in small chunks exposes you to risk
● VWAP, TWAP

7. Market Making
● This is the primary role of a dealer
● Quote buy and sell prices
● Active and Passive trading
● Manage inventory and risk

8. Proprietary Trading
● Thin line between marketing making & prop
● Hedge Funds and Prop trading firms
● Very little regulation
● Vast array of strategies

9. Mutual Funds
● Operates under strict investment directive
● Regulatory issues
● Portfolio Optimization problems
● Work with more stable closing price data
● Minimize various portfolio risks

10. Some examples
● Index Arbitrage
● Pairs Trading
● Trading on financial events
● Sparse Portfolio Optimization techniques

11. Types of roles
● Technologist
● Quant Researcher
● Quant Trader
● Career Progression : Portfolio Manager
● Compensation = % of PnL

12. Difference with other quant roles
● Derivatives Modeling
● Desk Strategist
● PnL responsibility
● Stoch Calculus vs Statistics
● Efficient Coding, Low Latency

13. Advice for careers in algo trading
● Love for programming
● Strong background in Statistics
● Interesting problems across disciplines
● Lots of creative freedom
● It's very competitive - Constant Innovation

14. ZLemma.com
● Suitability score for every job
● Help differentiate even between similar roles
● We will soon have jobs and internships
● Any questions?
● gaurav@zlemma.com