Education

A.I. Forecast Engineer @ 9H ONLINE COURSE

+ TEAM-BUILD & NETWORKING

SKILLSFUTURE@PA (ONLINE) FORECAST FINANCIAL MARKETS with RISK-DATA & ANALYTICS (Course Code: LLBEBUSDB06289A / TGS-2024043885) with Generative A.I. @ SINGAPORE’S VIP FORECAST CENTRE leading to a successful career as a Prompt Engineer in Forecasting.

  • You may not be able to predict the future, but you can certainly prepare for it! This online course demystifies the ins and outs of forecasting financial markets and equips you with essential skills and knowledge to level up within the finance world. These include anticipating trends and making projections based on data analysis techniques.
  • ONLINE COURSE / WORKSHOP (SkillsFuture@PA): FORECASTING FINANCIAL MARKETS WITH RISK-DATA & ANALYTICS (+ ChatGPT / Bing Chat / Bard A.I. integration): COURSE OUTLINE (or see below).
  • The leading course in machine learning & risk optimization is dedicated to equity/stock, FX, and other financial markets. Learn how Math can unlock the value of data. Receive a Certificate of Completion and become a RISK-DATA ANALYST for forecasting financial markets.
  • Apply: submit FORM / MySkillsFuture (visit any Community Centre to make payment with your SkillsFuture credits).

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Applying the best-in-class risk analytics to the financial data of the top 100 tech companies such as Apple, Microsoft, Google, Amazon, Tesla, Facebook, etc.

From the leading NASDAQ-100 Risk-Tech Database (since 1985) of Singapore, Finamatrix.NET, which won three global awards in 2018-2019 for Best A.I. Technology.

MINIMUM QUALIFICATIONS

  • GCE O-Level or equivalent and above. All technical jargon will be explained in simple language making this course appropriate for all levels.

WHO SHOULD ENROL

  • People who want to learn statistical skills in financial markets.
  • Individuals with varying risk appetites who want to develop careers in roles such as analyst, trader, etc.
  • Entrepreneurs who want to learn more about practical methods in risk management.

COURSE INFORMATION

  • Course Title: FORECASTING FINANCIAL MARKETS WITH RISK-DATA & ANALYTICS (with ChatGPT/Google Bard/Bing Chat A.I. integration)
  • Course duration: 9 hours (3 sessions of 3 hours online)
  • Modes of training: Online (Zoom)
  • Course Structure: 7pm-10pm (Mon/Tue/Thu)
  • Trainer: Dr. Lanz Chan, PhD, Singaporean, ex-UBS banker and professor, has coached more than 5,000 students in universities and in public lectures while he has extensive experience from Macau, Switzerland and Singapore in gaming and financial forecasting.

COURSE OUTLINE

  1. Understanding Risk Factors & Measurement vs Gambling
  2. How to make Decisions with Martingale System / Portfolio Risks
  3. Statistics: Mean / Standard Deviation / Variance / Skewness / Kurtosis
  4. Defining & Measuring Value-at-Risk (VaR)
  5. Risk measures: Expected Shortfall / Conditional VaR
  6. More Risk measures: Marginal VaR / Incremental VaR
  7. Quantifying & Forecasting Risk with Parsimonious Market Models / CAPM
  8. Other measures: Covariance / Coskewness / Cokurtosis Approach
  9. Advanced methods: Monte Carlo Simulation / Ex-Post (after the event) vs Ex-Ante (before the event) Algorithmic Optimization (NAS100 ETF + long/short CFD Strategy with data from 1985, in support of the Financial Modelers’ Manifesto to avoid over-complexity that leads to math-led failures) / A.I. integration examples provided throughout the workshop.

HARDWARE & SOFTWARE REQUIREMENTS

  • Computer with 4GB RAM and above.
  • Zoom.

LEARNING MATERIALS

  • All materials will be provided digitally.

LEARNING OUTCOMES

  • Participants will learn to appreciate how to operationalize an appropriate risk model to assist in financial decisions so as to enhance career options such as analyst, trader, etc.
  • Participants will recognize the limitations of complicated models with assumptions of normality in return distributions, in line with the Financial Modelers’ Manifesto, to prevent model failures.
  • Participants will understand how to create and implement optimization techniques with suitable algorithms (set of instructions) which provide the most useful and robust results.
  • Participants will experience that optimization (finding solutions under limited conditions) is the foundation of machine-learning (artificial intelligence) which is integrated with simulation methods that require no assumptions of return distributions.
  • Participants will appreciate that analytical skills are transferable across industries with different datasets.
  • Participants will be able to access our vGRE* statistics with no expiration for life-long learning.
  • Participants will have access to our alumni community for global networking.
  • Participants may apply for our certification/partner program as a career option.

Key References:

  • Risk Management, A Practical Guide, RiskMetrics Group / MSCI (1999).
  • Nasdaq Market Simulation: Insights On A Major Market From The Science Of Complex Adaptive Systems. Vincent Darley, Alexander V Outkin (2007).
  • Finamatrix.NET Risk-Tech Database; Risk-Cybernetics Protocol; Genetic-Algorithm Neural-Network (GANN); Atomic Portfolio Selection (APS) MVSK Utility Optimization (1985-2023).

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