Mastering Machine Learning for Cutting-Edge Quantitative Trading Strategies
- Analytics & Tech
- Finance & Investment
- Innovation & Business Improvement
This module is conducted in-person.
3 Full Day (Weekdays)
Who Should Attend
- Quantitative Analysts, Traders, Data Scientists, Portfolio Managers, Risk Managers.
PREREQUISITES
- Participants are encouraged to have a fundamental understanding of Python or R, and those without programming experience should consider taking introductory online courses.
- Basic knowledge of financial concepts, such as interest, compounding, and investment strategies, is recommended to understand the financial applications of machine learning.
- Familiarity with data handling, particularly using tools like Excel or Python for basic data processing.
Overview
In today's fast-paced financial markets, the ability to develop, implement, and evaluate quantitative trading strategies using machine learning models is essential for gaining a competitive advantage. The overall objective of this course is to equip participants with the necessary knowledge and skills to achieve this. By understanding market dynamics and various trading techniques, participants will gain practical experience in developing strategies that can be applied in real-world financial markets. The course emphasises both theoretical understanding and practical application, utilising Python for strategy implementation.
Learning Objectives
At the end of the 3-day course, participants will be able to:
- Distinguish between different types of trading strategies such as low-latency, algorithmic, high-frequency, and quantitative trading
- Understand how to process and work with financial data to develop trading strategies
- Evaluate and implement statistical arbitrage strategies, including pairs trading and momentum-based trading strategies
- Apply risk management techniques in trading, including spread-trading strategies and market-making
- Use Python to implement and backtest trading strategies, assessing their performance in a scientific and systematic manner
- Apply machine learning models to improve the performance of trading strategies
Assessment
As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of the course. The mode of assessment, which is up to the trainer’s discretion, may be an online quiz, a presentation or based on classroom exercises.
Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.
Calculate Programme Fee
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$981 (After SSG Funding 70%) |
$381 (After SSG Funding 70% |
$981 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$381 (After SSG Funding 70% |
$381 (After SSG Funding 70% |
$381 (After SSG Funding 70% |
|
International Participant |
$3,270 (No Funding) |
$3,270 (No Funding) |
$3,270 (No Funding) |
All prices include 9% GST
Please note that the programme fees are subject to change without prior notice.
Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.
Self Sponsored
SkillsFuture Credit
Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.
This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.
Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).Workfare Skills Support Scheme
From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.
Company Sponsored
Enhanced Training Support for SMEs (ETSS)
- Organisation must be registered or incorporated in Singapore
- Employment size of not more than 200 or with annual sales turnover of not more than $100 million
- Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
- Trainees must be Singapore Citizens or Singapore Permanent Residents
- Trainees must not be a full-time national serviceman
- Trainees are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here.
Please click here for more information on ETSS.
Absentee Payroll
Companies who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:
AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)
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