Key details
Mode of delivery: Classroom-based
Course code: AFB63C
Duration: 3 days
Fee: £2,765.00 + VAT
CPD Hours: 18
Course Overview
This course covers investor psychology, ESG principles, and financial innovation. Participants will learn how biases affect market behaviour, how to integrate ESG risks into portfolios, and explore disruptive technologies like blockchain, AI, and algorithmic trading. The focus is on understanding market anomalies, responsible investing, and the long-term implications of new tech in finance.
Agenda
Day 1 — Behavioural Finance and Investor Psychology
- Cognitive Biases and Heuristics
- Irrational Market Behaviour
- Behavioural Portfolio Construction
Day 2 — Sustainable and ESG Investing
- Principles of ESG and Responsible Investing
- ESG Risk Integration into Portfolios
- Green Bonds and Impact Funds
Day 3 — Financial Innovation and Fintech in Markets
- Blockchain and Tokenized Assets
- Algorithmic Trading and Robo-Advisors
- Big Data, AI, and Predictive Analytics
Course Review
- Summary and recap of key learning objectives
- Action Planning
Target Audience
This course is suitable for:
- Senior Portfolio and Wealth Managers, Investment Strategists, and Asset Allocation Specialists
- Investment Committee Members, Chief Investment Office Professionals, and Senior Investment Advisors
- Quantitative Analysts, Financial Engineers, Behavioural Finance, and Market Strategy Professionals
- ESG Investment Managers, Sustainable Finance Leaders, Impact Investment, and Green Bond Professionals
- FinTech Strategy Leaders, Blockchain, Tokenised Asset, Algorithmic Trading, and Robo-Advisory Professionals
- Financial Big Data Analysts, Investment AI Specialists, AI Governance, and Model Risk Professionals
- Risk Directors, Market Ethics, Conduct, and Financial Market Infrastructure Professionals
- Financial Consultants, Finance Executives, and Sustainable Product Structuring Specialists
Learning Outcomes
By the end of this course, you will be able to implement a successful strategy that enables you to:
- Identify biases like loss aversion, anchoring, and herding.
- analyse market bubbles through behavioural lenses.
- Incorporate behavioural factors into portfolio design.
- Describe ESG scoring frameworks and impact metrics.
- Evaluate how ESG risks affect portfolio risk-return.
- Analyse instruments aligned with sustainability goals.
- Describe how DLT enables asset tokenization.
- Evaluate the pros/cons of automated investment platforms.
- Apply data science concepts to forecast market moves.
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