arXiv subjects

Salvador Cruz Rambaud

Publications and source records attributed to Salvador Cruz Rambaud.

3 recordsLinked to original sources

arXiv2026

Financial Literacy and the Functional Shape of Subjective Time Deformation in Intertemporal Choice

Intertemporal decisions are commonly summarized by a single discount parameter, although individuals with similar overall discounting intensity may value short-, medium-, and long-term delays differently. This study investigates whether financial literacy is associated with these horizon-specific differences by treating reconstructed subjective time as a functional rather than scalar outcome. Data were collected through a multilingual online questionnaire administered to a convenience and snowball sample of 140 adults, who provided hypothetical equivalence judgments for a future reward of EUR 100 over 13 horizons from 7 days to 5 years, a three-item financial-literacy measure, and measures of temporal perception. Individual discount trajectories were reconstructed and analyzed with function-on-scalar regression, allowing the association with financial literacy to vary across the temporal domain. Because the normalized subjective-time trajectory is not identifiable for flat or reconstruction-degenerate discount profiles, the primary functional analysis included 59 participants, while complementary analyses used the full analytical sample. The primary model provided no evidence of a robust linear association between financial literacy and subjective-time deformation. An exploratory categorical specification indicated heterogeneity across financial-literacy levels and departure from a linear-score representation, although individual contrasts were imprecise and sensitive to specification. The relationship between financial literacy and intertemporal valuation may thus be more complex than a monotonic score effect, and functional data analytics can reveal horizon-specific structure that scalar summaries obscure. Given the convenience sample and the reduced identified sample, the results are exploratory and require validation in larger independent samples.

stat.AP↗

arXiv2026

Subjective Time Deformation in Intertemporal Choice: A Functional Data Analysis Approach

Intertemporal choice data are usually summarized through scalar discount-rate parameters or fitted by predetermined parametric discount functions, although relevant information may lie in the shape of the whole discounting trajectory. This paper proposes a Functional Data Analysis framework for reconstructing and analyzing implicit subjective-time trajectories from discrete intertemporal equivalence judgments. Monetary equivalence responses from a multilingual questionnaire are transformed into individual discount curves, regularized by monotone smoothing, and used to recover normalized implicit subjective-time trajectories. The trajectories are examined through derivative summaries, Functional Principal Component Analysis, and clustering on standardized component scores. The empirical application, based on 107 participants, shows that heterogeneity in intertemporal choice is not fully captured by scalar discount-rate variation. The first two functional principal components explain 97.44% of the variability, indicating a low-dimensional structure. Functional clustering identifies three stable profiles of temporal deformation, supported by bootstrap stability analysis and sensitivity checks on components, algorithms, distances, smoothing specifications, and outlier treatment. Parametric benchmarks based on exponential, Weber-Fechner, and Stevens specifications provide accurate fits for many individuals, but do not fully recover the functional clustering structure. The comparison with explicit subjective-time perception measures reveals only partial alignment between implicit trajectories reconstructed from choices and directly reported temporal perception. Functional Data Analysis provides an applied statistical framework for representing intertemporal choice heterogeneity as variation in functional shape, complementing scalar discount-rate and parametric subjective-time models.

stat.AP↗

arXiv2024

Functional Clustering of Discount Functions for Behavioral Investor Profiling

Classical finance models are based on the premise that investors act rationally and utilize all available information when making portfolio decisions. However, these models often fail to capture the anomalies observed in intertemporal choices and decision-making under uncertainty, particularly when accounting for individual differences in preferences and consumption patterns. Such limitations hinder traditional finance theory's ability to address key questions like: How do personal preferences shape investment choices? What drives investor behaviour? And how do individuals select their portfolios? One prominent contribution is Pompian's model of four Behavioral Investor Types (BITs), which links behavioural finance studies with Keirsey's temperament theory, highlighting the role of personality in financial decision-making. Yet, traditional parametric models struggle to capture how these distinct temperaments influence intertemporal decisions, such as how individuals evaluate trade-offs between present and future outcomes. To address this gap, the present study employs Functional Data Analysis (FDA) to specifically investigate temporal discounting behaviours revealing nuanced patterns in how different temperaments perceive and manage uncertainty over time. Our findings show heterogeneity within each temperament, suggesting that investor profiles are far more diverse than previously thought. This refined classification provides deeper insights into the role of temperament in shaping intertemporal financial decisions, offering practical implications for financial advisors to better tailor strategies to individual risk preferences and decision-making styles.

q-fin.ST↗