This review examines TDFs in Chile's pension reform, recommending dynamic glide paths and diversified benchmarks.
arXiv research
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This study forecasts climate data in Chile using EOFs and machine learning models.
The study improves solar irradiance forecasts for Chile using machine learning.
Boosting algorithms predict financial vulnerability of farmers in Chile and Tunisia.
This is a survey of our program of perturbative quantization of gauge theories on manifolds with boundary compatible with cutting/pasting and with gauge symmetry treated by means of a cohomological resolution (Batalin-Vilkovisky) formalism. We also give two explicit quantum examples -- abelian BF theory and the Poisson…
We utilize long-term memory, fractal dimension and approximate entropy as input variables for the Efficiency Index [Kristoufek & Vosvrda (2013), Physica A 392]. This way, we are able to comment on stock market efficiency after controlling for different types of inefficiencies. Applying the methodology on 38 stock marke…
This article studies the financial integration between the six main Latin American markets and the US market in a nonlinear framework. Using the threshold cointegration techniques of Hansen and Seo (2002), we show significant threshold stock market linkages between Mexico, Chile and the US. Thus, the dynamics of these …
In this paper we use the Brooks and Hinich cross-bicorrelation test in order to uncover nonlinear dependence periods between USA Standard and Poor 500 (SP500), used as benchmark, and six Latin American stock markets indexes: Mexico (BMV), Brazil (BOVESPA), Chile (IPSA), Colombia (COLCAP), Peru (IGBVL) and Argentina (ME…
Study applies HRP to Latin American markets, showing smoother risk-return profile.
This paper ranks Latin American countries based on AI potential.
A graph neural network improves multivariate post-processing of ensemble forecasts.
A declining CVaR glidepath framework for TDF design with Chilean pension system application