Introduction to Algorithmic Trading

This program is designed to introduce participants to the core concepts and practical aspects of algorithmic and quantitative trading. It aims to build a solid foundation by covering essential topics such as trading strategies, market microstructure, and back testing techniques. Through hands-on sessions, participants will gain experience with the tools and platforms used to design, test, and deploy trading algorithms. The program also sets the stage for advanced learning in areas like high-frequency trading and AI-driven strategies, making it ideal for aspiring quants, traders, and finance professionals looking to enhance their skill set in this rapidly evolving domain.

The overall design will be experiential learning for participants. Theyll be trained and developed in understanding financial variables in the initial session. In the second stage, the use of different cost techniques, finance and management tools essential to strategic decision-making will be the topic of sessions. Finally, participants will discuss real-life-based cases provided by the instructor from prominent sources.

Day 01: 29/01/2026

Date

Topic

Faculty

Time

29/01/2026

Inaugural, Overview of the Programme, Setting Expectations for Learning Outcomes

Dean / PIC – IC & EE / Prof. AJP/RKV/RM

9.00a.m. to 10.30a.m

Foundations of Algorithmic Trading;

Evolution of Algo Trading: From Manual to Automated, Role of Algorithms in Modern Markets

GF/ AJP/RKV/RM

11.15am to 12.45p.m.

Market Microstructure Basics;

Order books, bid-ask spread

Types of Orders: Market, Limit, Stop

Trading Venues and Execution Systems, Pros and Cons of Algo Trading

GF/ AJP/RKV/RM

2.00pm to 5.15pm

Day-2: 30

th

Jan 2026

30/01/2026

Types of Algorithmic Strategies:

Trend-following: Moving Averages, Arbitrage: Statistical, Triangular, Index, Mean Reversion: Pairs Trading, RSI-based, Market Making & Liquidity Provision

GF/ AJP/RKV/RM

9.00a.m. to 10.30a.m

Risk Management Basics;

Stop Loss, Position Sizing, Value-at-Risk (VaR), Introduction to Strategy Evaluation Metrics; Sharpe Ratio, Alpha, Beta, Drawdown

GF/ AJP/RKV/RM

11.15p.m. to 12.45p.m.

Introduction to Back testing Platforms; Avoiding Overfitting and Look-ahead Bias, Walk-forward Testing and Paper Trading, Performance Metrics and Strategy Review.

GF/ AJP/RKV/RM

2.00pm to 5.00p.m.

Objectives:

To understand the fundamentals of algorithmic and quantitative trading.

To explore trading strategies, market microstructure, and back testing.

To get hands-on exposure to tools used in building and testing trading algorithms.

To provide a foundation for further exploration into high-frequency and AI-driven trading.

The overall design will be experiential learning for participants. Theyll be trained and developed in understanding financial variables in the initial session. In the second stage, the use of different cost techniques, finance and management tools essential to strategic decision-making will be the topic of sessions. Finally, participants will discuss real-life-based cases provided by the instructor from prominent sources.