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19 OctMon
Mon
CFA Institute Research and Policy Center: PublicationsAI Score5454
A former equity strategy partner and independent investment firm operator used AI in retirement to backtest his long-standing personal strategy, which combined Peter Lynch's growth stock selection, Hilary Kramer's undervalued obscure stock selection, and earnings revision discipline. He corrected for survivorship bias, used point-in-time data, calculated pre-fee returns, and compared it against random stock selection from the same investment pool. The results showed that the strategy did not outperform random selection, with ordinary index funds performing better than the strategy.
The AI boom is becoming an ESG test. The water and electricity consumption of AI data centers will affect corporate profit margins, capital expenditures, and return on investment. Cross-industry investment portfolios may collectively face ESG exposure from data center expansion and power bottlenecks.
Moontower host Kris Abdelmessih breaks down an interview with LTCM co-founder Victor Haghani, arguing that investment decisions consist of two parts: instrument selection and position sizing, and that LTCM's failure stemmed from flawed position sizing rather than poor instrument selection.
Author Kris Longmore shares content from his 72-minute interview on The Algorithmic Advantage podcast, looking back on an early experience at a Sydney traders' meetup where he was unable to answer a proprietary trader's question about his own trading edge. He later joined that proprietary firm as a researcher and partner, and summarized relevant insights after leaving to trade independently.
Most portfolio managers and analysts in the investment industry have not yet adopted large language models in their daily work, with only a few well-resourced large institutions having implemented them. The article notes that LLMs can improve investment decision hit rates and long-term productivity, and that current barriers to adoption stem primarily from non-technical factors such as organizational processes, incentive structures, and psychological safety.
Rob Carver has completed the final edits on his fifth trading book, "The Art And Science of Trading," scheduled for official publication on December 1 and now available for pre-order. Aimed at the mass market, this book serves as the unleveraged counterpart to his third book, "Leveraged Trading." It covers an introduction to trading delta-one instruments such as stocks, ETFs, and cryptocurrencies, explains trading science concepts like backtesting and the Kelly Criterion, and explores the integration of art and science within a semi-automated trading framework.
Aswath Damodaran, a valuation professor at New York University, uses the complete journey of Leopold Aschenbrenner's Situational Awareness hedge fund—from explosive growth to liquidation following a blowup—as a case study to systematically break down the definition, sources, and real-world impact of investment conviction.
The author notes that AI has dramatically lowered the barrier to developing quantitative strategies, enabling fully coded and backtested strategies to be generated within minutes. However, cheap experimentation amplifies the multiple-testing problem, producing a flood of false backtest results that appear effective but are actually overfit to noise.
