Investment selection based on behavior patterns
BBVA Asset Management, the investment management arm of BBVA Group, is taking a proactive approach to climate-related risks, incorporating them into long-term strategic allocation decisions. This forward-thinking stance is part of a broader shift in the company's investment strategy, which is based on behavioural economics principles and a rules-driven framework.
The global head of asset allocation at BBVA Asset Management, Jaime Martínez, has led the transformation of the team's approach. This new strategy is designed to mitigate emotional and cognitive biases in decision-making, ensuring clarity, simplicity, and objectivity.
The investment decisions at BBVA Asset Management are structured across two time horizons. Strategic allocation (3-5 years) is focused on valuation, while tactical allocation (1-9 months) is based on dynamic signals. Diversification and transparency are central to the strategy, with quantitative tools used to reinforce discipline and consistency.
Institutional clients have higher thresholds for private markets exposure, with commitments of 8-15% being typical. In contrast, BBVA Asset Management caps private markets exposure in retail portfolios at around 3-4%, favouring investments with shorter durations and higher cash distributions.
Incorporating AI and machine learning has been part of BBVA Asset Management's evolution. Advanced mathematical and statistical methods are used in a multidisciplinary research collaboration with the University of Navarra, called the Fair Learning project. This initiative aims to mitigate bias in AI data and models by preventing discriminatory patterns during training and ensuring fairness, transparency, privacy, and respect for human autonomy.
BBVA Asset Management is also leveraging AI in thematic equity portfolios, using clustering techniques to enhance construction, and working with external providers on early detection of emerging themes using AI.
Institutional clients of BBVA Asset Management are moving their equity benchmarks to climate transition benchmarks, aiming to reduce carbon footprint significantly. BBVA Asset Management's investment process embeds ESG at the security selection level, and they have developed an internal ESG rating system.
Tactical decisions are considered vulnerable to behavioural biases, leading the team to use rule-based models for most of their tactical calls. A more ambitious machine learning-based dynamic asset allocation model covering 21 asset classes is currently in development.
In alternatives, BBVA Asset Management applies strict criteria to ensure only liquid, transparent, and robust long-short strategies are included. The asset manager's approach to portfolio construction consists of three core pillars: strategic asset allocation, a disciplined tactical framework, and security selection through efficient investment vehicles.
Martínez emphasizes the importance of objectifying decisions to mitigate emotional and cognitive biases, particularly in today's fragmented and volatile macro environment. BBVA Asset Management has introduced goal-based model portfolios as part of its discretionary portfolio management, providing clients with personalised investment solutions tailored to their specific financial objectives.
[1] BBVA Asset Management. (n.d.). Behavioural Economics: The Key to a More Objective Decision-Making Process. Retrieved from https://www.bbva-assetmanagement.com/en/insights/behavioural-economics-the-key-to-a-more-objective-decision-making-process/
[2] BBVA Asset Management. (n.d.). Fair Learning: Mitigating Bias in AI Data and Models. Retrieved from https://www.bbva-assetmanagement.com/en/insights/fair-learning-mitigating-bias-in-ai-data-and-models/
[4] BBVA Asset Management. (n.d.). Building Responsible AI Systems: Aligned with European Regulations. Retrieved from https://www.bbva-assetmanagement.com/en/insights/building-responsible-ai-systems-aligned-with-european-regulations/
- BBVA Asset Management's new investment strategy, led by Jaime Martínez, aims to mitigate emotional and cognitive biases in decision-making, using rule-based models for most of their tactical calls, and introducing goal-based model portfolios as part of its discretionary portfolio management.
- Incorporating AI and machine learning has been part of BBVA Asset Management's evolution, with the Fair Learning project, a multidisciplinary research collaboration with the University of Navarra, aiming to mitigate bias in AI data and models.
- Institutional clients of BBVA Asset Management are moving their equity benchmarks to climate transition benchmarks, while the asset manager's approach to portfolio construction in alternatives includes strict criteria for liquid, transparent, and robust long-short strategies.
