Equip yourself with the skills to analyze, invest, automate and lead in today's dynamic financial markets. A comprehensive program combining investment management, financial analytics, and algorithmic trading.
Financial markets are being transformed by technology, data analytics, and automation. Investment professionals today require not only a deep understanding of financial markets but also the ability to leverage analytical tools and technology for informed investment decisions.
The Executive Diploma in Investment Management & Algorithmic Trading reflects our commitment to developing future-ready finance professionals by integrating investment management, portfolio analysis, financial analytics, and algorithmic trading within a rigorous executive education framework. Through live instruction, hands-on coding, and industry-oriented projects, participants learn to translate data into disciplined, technology-enabled investment decisions.
Grounded in the Jesuit tradition of excellence with ethics, the programme encourages participants to view leadership as service to society and to pursue outcomes that are responsible, transparent, and rooted in integrity.
The Executive Diploma in Investment Management & Algorithmic Trading is an 11-month executive programme designed for professionals seeking advanced knowledge in investment analysis, portfolio management, financial analytics, Python programming, and algorithmic trading. The programme combines the principles of modern investment management with technology-enabled decision-making, providing participants with practical skills in analysing financial markets, developing systematic trading strategies, backtesting investment models, and implementing algorithmic trading systems.
Through live online classes, practical assignments, case studies, and an industry-oriented Capstone Project, participants will develop competencies required for today's rapidly evolving financial markets.
A comprehensive curriculum built on three integrated pillars that together deliver a complete investment management education.
Principles of modern investment management, portfolio construction, and asset allocation frameworks grounded in financial theory.
Technology-enabled decision-making using real-world financial datasets, quantitative models, and industry-standard analytical tools.
Systematic strategy design, backtesting investment models, and end-to-end implementation of algorithmic trading systems.
A structured, technology-integrated executive education designed specifically for finance professionals navigating the intersection of investment management and algorithmic decision making.
A credential from one of India's top Jesuit business schools, recognised for academic rigour, ethical leadership, and professional excellence.
A comprehensive, sequenced curriculum progressing from investment foundations through quantitative methods to live strategy execution.
Designed for working professionals - attend live interactive sessions without disrupting your career or professional commitments.
Applied coding for finance - build real tools, automate analysis, and implement trading strategies using Python from the ground up.
Work with real financial market data and industry-relevant tools to develop practical investment analysis and decision-making skills.
A complete investment strategy or algorithmic trading system built and validated by each participant.
A three-term architecture that builds progressively - from investment fundamentals to quantitative methods to live strategy execution and deployment.
| Term I | Term II | Term III |
|---|---|---|
| 1. Financial Markets & Investment Instruments Equity, fixed income, derivatives, and alternative asset classes. Market microstructure, pricing mechanisms, and regulatory frameworks. |
1. Financial Data Analytics Statistical analysis of financial time series, factor modelling, and data-driven investment decision frameworks using Python libraries. |
1. Strategy Development & Backtesting Rigorous historical testing of trading strategies - avoiding overfitting, walk-forward validation, and performance attribution. |
| 2. Python for Finance Core programming concepts applied to financial problems. Data structures, control flow, functions, and financial libraries from first principles. |
2. Algorithmic Trading Strategies Momentum, mean-reversion, statistical arbitrage, and machine-learning-assisted strategy design and systematic signal generation. |
2. Algorithmic Trading Systems & Execution End-to-end system architecture - order management, execution algorithms, latency considerations, and live deployment frameworks. |
| 3. Investment Analysis & Portfolio Management Fundamental and technical analysis, valuation models, portfolio construction, and performance measurement frameworks. |
3. Derivatives & Risk Management Options pricing, Greeks, hedging strategies, VaR, CVaR, and portfolio risk management using quantitative methods. |
3. Capstone Project A complete, independently developed investment strategy or algorithmic trading system designed, tested, and presented to faculty and industry reviewers. |
Upon successful completion, participants will demonstrate mastery across the full investment management and algorithmic trading value chain – from market analysis to systematic execution.
Analyse financial markets and evaluate investment opportunities using both fundamental and quantitative frameworks.
Build and manage diversified investment portfolios applying modern portfolio theory, factor models, and risk-adjusted optimisation.
Apply Python programming to solve real-world finance problems – from data ingestion and cleaning to strategy implementation.
Analyse financial data using industry-standard tools, extracting signals, identifying patterns, and generating actionable insights.
Design and validate backtesting models applying walk-forward testing, performance attribution, and overfitting controls.
Apply derivatives for hedging and risk management. Evaluate investment performance using quantitative risk metrics including VaR and Sharpe Ratio.
Participants work with the same tools used by quantitative analysts, portfolio managers, and algorithmic traders at leading financial institutions worldwide.
Core programming language for quantitative finance
Interactive coding environment for financial data science
Cloud-based Python workspace with GPU access
Foundational libraries for numerical computing
Matplotlib, Seaborn, Plotly for financial charts
Real-time and historical market data
Programmatic access to market data
Execution and strategy testing environments
Financial modelling and analysis
This programme is designed for ambitious professionals at the intersection of finance and technology – those who recognise that the future of investing demands both analytical depth and technological capability.
Seeking to advance into investment roles – portfolio management, asset management, or quantitative research.
Looking to transition into quantitative finance – applying mathematical and programming strengths to algorithmic trading.
Looking to augment fundamental skills with quantitative methods, Python-based analysis, and systematic strategy development.
Looking to transition into quantitative finance – applying their mathematical and programming strengths to financial modelling.
Seeking to deliver more sophisticated, data-driven investment solutions to high-net-worth and institutional clients.
Seeking a structured, professional approach to markets – moving beyond intuition to evidence-based, systematic investment decision-making.
Graduates of this programme are equipped for high-impact roles across investment management, quantitative finance, wealth management, and financial technology – sectors experiencing sustained demand for analytically sophisticated professionals.
Evaluate securities, build investment theses, and support portfolio managers at asset management firms, hedge funds, and family offices.
Manage and optimise investment portfolios – performance attribution, rebalancing, risk monitoring, and client reporting across asset classes.
Design, backtest, and deploy systematic trading strategies – working at proprietary trading firms, hedge funds, or quantitative asset managers.
Produce research reports for institutional clients – sector coverage, earnings modelling, valuation, and investment recommendations.
Manage corporate liquidity, short-term investments, and interest rate or currency risk for large enterprises and financial institutions.
Extract actionable insights from financial datasets – building dashboards, models, and reports that drive investment and business decisions.
Identify, quantify, and mitigate financial and market risks using quantitative models, stress testing, and regulatory risk frameworks.
Build technology-driven financial products – robo-advisors, algorithmic execution platforms, and data analytics solutions.
| Parameter | Details |
|---|---|
| Duration | 11 Months |
| Mode of Learning | Live Online Classes |
| Programme Fee | ₹81,900 + GST |
| Eligibility | Bachelor's Degree in any discipline |
| Assessment | Continuous Evaluation throughout the programme |
| Capstone Project | Mandatory industry-oriented final project |
| Award | Executive Diploma from Loyola Institute of Business Administration (LIBA) |
The future of investing belongs to professionals who combine financial expertise with analytical thinking and technological capability. Join LIBA's Executive Diploma in Investment Management & Algorithmic Trading and prepare yourself for the next generation of investment management.