Factores, smart beta y bots de IA: ¿qué estás comprando realmente?
Data-Driven Investment Strategies: smart beta, factors, AI bots and goal-based investing
Lista de recursos para preparar la sesión. La primera parte reúne ocho lecturas básicas, artículos y reflexiones de profesionales de primer nivel. La segunda propone pódcast, papers y datos para orientarse en el nuevo mundo de los productos de inversión.
Lecturas básicas
8 recursos · aprox. 1 h 30 min
3 min
Plain definitions of the main factors, and an honest warning: “sharp and lengthy periods of underperformance”.
25 min
The case for factors from one of their best-known practitioners, written after value’s long drawdown.
20 min
The sceptic’s case, from a firm that sells smart beta: much of the recent performance came from rising valuations.
5 min
370 indices tracked by ETFs beat the US market by 10.3% a year in back-filled data, then lagged by 0.9% a year once live.
10 min
The 10 largest stocks were almost 40% of the S&P 500 by mid-2025, a level not seen since the mid-1960s.
8 min
55% of thematic funds failed to survive the 15 years to mid-2024. Read it before buying the next ‘AI’ ETF.
10 min
What European and US regulators tell investors about AI tools and trading bots.
5 min
One risk score for all your money, or one portfolio per goal?
Para profundizar
8 extras opcionales · pódcast, papers y datos
Why sticking with a factor is hard, told from inside a quant fund.
The co-author of the three-factor model on how noisy factor premia are.
Market efficiency from the source, and factors as risk premia.
Why rotating between factors is harder than it looks.
The “factor zoo”: 316 factors, and why most are probably false. Technical.
The long-run evidence, including factor timing.
Why risk questionnaires explain so little of how investors behave.
The factor data itself, free, back to 1926.
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