Why Generative AI Still Can’t Trade | David Wright on How Quant Alpha Actually Is Done With Machine Learning, Decision Trees, and Gradient Boosting

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May 10, 2026

David Wright, co-head of Quantitative Investments at Pictet Asset Management, runs a $30B quant franchise using machine-learning-driven equity strategies. He explains why tree-based models and gradient boosting beat generative AI for return forecasts. The chat covers 400+ features, 20-day relative return forecasts, ETF design aiming for index-like beta plus 1–2% outperformance, and a push for transparent, interpretable models.

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INSIGHT

Why Trees Beat Generative AI For Return Forecasts

Generative AI excels at producing text/images but is poorly suited to reliable return forecasts.
David Wright prefers thousands of decision trees and gradient boosting for tabular financial data because they are testable and interpretable.

ANECDOTE

Gen AI Used For Support Not Alpha Generation

Pictet uses generative AI in non-investment support: coding help, meeting summaries, client materials.
David Wright says gen AI hasn't changed their core AI-enhanced investment process but improved operational efficiency.

INSIGHT

Look Ahead Bias Makes LLMs Risky For Backtests

Language models risk look-ahead bias because they need continual retraining to reflect only past text at each simulation date.
Wright calls this testing leakage the equivalent of hallucination for investors and a practical barrier to using LLMs for backtests.

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This interview is brought to you by Pictet Asset Management. To learn more about Pictet AI-Enhanced International Equity ETF ($PQNT), click here: https://etf.am.pictet.com/pqnt/

To learn more about Pictet AI Enhanced US Equity ETF ($PQUS), click here: https://etf.am.pictet.com/pqus/

Jack Farley sits down with David Wright, co-head of Quantitative Investments at Pictet Asset Management, to discuss the machine learning techniques his team uses in their $30 billion quant franchise, and the degree to which AI has impacted serious quantitative investing. Wright explains why he prefers to utilize many decision trees and use gradient boosting rather than Generative AI to generate return forecasts, citing the need to avoid "hallucinations" and ensure models remain interpretable. The conversation explores their sophisticated investment process, which analyzes over 400 features, including accounting data, market trends, and analyst sentiment, to predict relative stock performance over 20-day horizons. These strategies, which now are included in new ETFs $PQNT (Pictet AI Enhanced International Equity ETF) and $PQUS (Pictet AI Enhanced US Equity ETF) are designed as "passive replacements," aiming to maintain a Beta of 1.0 while aiming to deliver an additional 1–2% annual outperformance over the relevant benchmarks, S&P 500 and MSCI EAFE indices. Finally, Wright addresses the common "black box" misconception of quantitative finance, advocating instead for a "crystal box" approach that provides full transparency into the economic rationale behind every trade. Recorded April 21, 2026.

For important information about the fund, please click: https://etf.am.pictet.com/”

Important Information

Before investing, carefully consider the fund’s investment objectives, risks, charges, and expenses. This and other information can be found in the fund’s prospectus or, if available, the summary prospectus, which may be obtained by calling (855) 994-4778 or visiting www.pictet.com/etf. Read it carefully before investing. (In Italic or Bold)

Investing in Exchange Traded Funds (ETFs) involves risk, including possible loss of principal. The fund's principal investment risks include Artificial Intelligence Models and Data Risk, Non-Diversification Risk, Convertible Securities Risk, Rights and Warrants Risk, Real Estate Investment Trusts (REITs) Risk and Sustainability & ESG Data Risk. For additional information about these and other fund risks, please refer to the "Principal Investment Risks" section of the prospectus.

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Definitions of terms used in the interview:

1. S&P 500 Index

The Standard & Poor’s 500 Index (S&P 500) is a market-capitalization-weighted index of 500 leading publicly traded companies in the United States. It is widely regarded as the best single gauge of large-cap U.S. equities. Because it is weighted by market value, larger companies have a greater impact on the index's performance than smaller ones.

2. MSCI EAFE Index

The MSCI EAFE Index is a stock market index that tracks the performance of large- and mid-cap securities across developed markets around the world, excluding the U.S. and Canada. The acronym stands for Europe, Australasia, and the Far East. It is commonly used as a benchmark for international equity funds.

3. Alpha

Alpha represents the "excess return" of an investment relative to the return of a benchmark index. It is a measure of performance on a risk-adjusted basis. "Positive Alpha: indicates the investment outperformed its benchmark after accounting for risk and "Negative Alpha" indicates the investment underperformed relative to the benchmark.

4. Beta

Beta measures the volatility—or systematic risk—of a security or portfolio in comparison to the market as a whole (usually the S&P 500, which has a Beta of 1.0) A Beta > 1.0 indicates the investment is more volatile than the market (e.g., if the market rises 10%, the investment might rise 12%) A Beta < 1.0 indicates the investment is less volatile than the market (e.g., if the market falls 10%, the investment might only fall 8%).

5. Basis Points (bps)

A Basis Point is a standard unit of measure for interest rates and other percentages in finance. One basis point is equal to 1/100th of 1%, or 0.01%.