Current Events Flashcards
what are the differences between Traditional AI and Gen AI
Traditional AI excels in analyzing and automating tasks.
Gen AI specializes in creative content generation.
What are the uses of AI in Portfolio Management: define Factor Investment analysis;
Real-time market monitoring;
Alternative data analysis;
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Factor Investment Analysis: AI assists in identifying and evaluating investment criteria like value, size, momentum, quality, or volatility.
(i.e. APT models or “smart-beta” models!) - Real-time Market Monitoring: AI continuously evaluates sources like news, social media, and market data to identify emerging trends and events.
- Alternative Data Analysis: AI analyzes alternative data sources to fill in gaps in knowledge that traditional financial research may miss.
Benefits of AI for Portfolio Management
Advanced data analysis: AI detects patterns, trends, and correlations in large datasets for better investment decisions.
Automation and efficiency: AI automates typical portfolio management processes, allowing managers to focus on high-level strategies.
Continuous Learning and Improvement: AI systems learn from experience, adapting and evolving continually to enhance investment strategies.
Why is Nividia so successful? And why is there a need for a human element in investing?
Why it’s so successful:
- NVIDIA’s graphics processing units (GPUs) ]are highly suited for AI workloads, especially for deep learning.
○ which had made it become one of the most valuable company
Why there is a need for a human element in investing:
- Advisors help clients identify their risk tolerance, set realistic goals, and establish plans for life changes—whether saving for children’s education, navigating career shifts, or planning for retirement. They offer judgment calls that blend market insights with the human element of empathy, understanding, and experience
- AI lacks all of this
What does Mackenzie investments use in terms of Ai? How often?
Mackenzie investments use quantitative models and artificial intelligence to analyze roughly 20,000 global securities at a time/ TWICE A DAY
What are two risk management risks thats ai can idnetify?
Market Risk: AI uses algorithms to forecast market movements and spot trends that human research might miss.
Credit Risk: AI algorithms assess the creditworthiness of a potential investment or borrower by analyzing financial data and credit histories.