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Algo-trading, Theory and Practice [e-Learning]

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  • 19 Nov, 26 Nov & 30 Nov 2020 (9am – 5pm)
  • 21 Apr, 26 Apr & 29 Apr 2021 (9am – 5pm)


3 Days


Course Overview

Building wealth is one of the key priorities that every individual wants to accomplish. However, only a few have sufficient knowledge to successfully build it. It is essential to protect one’s wealth especially in uncertain times like today where the stock markets have experienced a huge drop due to recent uncertain times.

This course provides the participants with ample knowledge in the field of investing and what principles to follow in order to protect and generate wealth sustainably. Participants will learn the best practices in Algo trading and Wealth management.

With the evolution of technology, Algotrading became much more popular and is now used by many financial institutions and retail traders for making trading decisions. Algotrading has numerous benefits over manual trading including the elimination of human emotions and fast computation. However, it requires rigorous backtesting to develop a strategy that follows good practices and is not overfitted.

This course will provide an insight into how more robust algorithm trading models can be developed to generate higher risk-weighted returns.


  • Trading Concepts
    • Financial Markets
    • Exchange Terminology
    • Orders and Orders Matching
    • Leverage
    • Predictions
    • Introduction to Technical Analysis / Fundamental Analysis/ Machine Learning
  • Steps for Investing / Trading (IDMR)
  • APIs and Platforms ( investing.com, yahoo finance, google finance, Tradingview)
  • Drawbacks of Manual Trading
  • Quick Introduction
    • Algotrading
    • Python (Libraries: NumPy, pandas)
    • Atom / Jupyter Notebook /IDLE
    • Quantconnect
  • Fundamentals of Developing Strategies
    • BASS (Beta, Alpha, Std dev, Sharpe)
    • Correlation
    • Risk Reward Ratios
    • Rebalancing
  • Moving Average (MA) Example
  • Developing MA Strategy (Hands-On)
  • Diversification and Risk Management in Algotrading
    • Other Ratios – Sortino and More.
    • Volatility Target
    • Indicators as Variables
    • Trends
    • Portfolio weightage
  • Designing a diversified Portfolio


Who Should Attend
Students/Professionals who want to learn about Financial Markets and Algotrading


1. Interest in Financial Markets

2. Ability to learn new concepts and programming language (python)

Course Fees


International Students

Singapore Citizens and

SkillsFuture Mid-Career Enhanced Subsidy

(Singapore Citizens aged 40 and above)

For more
click here.

Enhanced Training Support for SMEs^

Full course fee

S$ 2850.00

S$ 2850.00

S$ 2850.00

S$ 2850.00

Less: SSG Grant Amount (S$1995.00) (S$ 1995.00) (S$ 1995.00)
Nett Course Fee S$2850.00 S$855.00 S$855.00 S$855.00
GST (7%) on nett course fee

S$ 199.50




Total Nett Course Fee Payable, including GST S$ 3049.50 S$ 914.85 S$ 914.85 S$ 914.85
Less: Additional Funding if eligible under various schemes

(S$ 570.00)

(S$ 570.00)

Total Nett Course Fee Payable, including GST, after additional funding from the various funding schemes

S$ 3049.50

S$ 914.85

S$ 344.85

S$ 344.85

Course Leader

Shashank Shekhar Tripathi

To enquire, please email to stmi@nus.edu.sg




For members of public and NUS Alumnus (without R&G Voucher), please follow the steps below:
Select Short Course / Modular Course -> Apply for Myself -> Browse Academic Modules, Short Courses -> Short Courses

Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.