Browsing by Author "Tapia, Claudio"

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    Credit Spreads in Illiquid Markets: Model and Implementation
    (ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2012) Cortazar, Gonzalo; Schwartz, Eduardo S.; Tapia, Claudio
    This paper presents a methodology for estimating a family of credit spread term structures in a market with few transactions. The authors propose partitioning the market into risk classes and modeling credit spread term structures for each risk class using a multifactor Vasicek model with some common and some risk class-specific factors. The approach uses information on the cross section and time series of corporate bonds in all the risk classes to estimate the term structure of credit spreads in each risk class. The model is jointly estimated using an extended Kalman filter and implemented using Chilean corporate and government bonds.
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    Impact of Visual Biofeedback of Trunk Sway Smoothness on Motor Learning during Unipedal Stance
    (2020) Cruz-Montecinos, Carlos; Cuesta-Vargas, Antonio; Munoz, Cristian; Flores, Dante; Ellsworth, Joseph; De la Fuente, Carlos; Calatayud, Joaquin; Rivera-Lillo, Gonzalo; Soto-Arellano, Veronica; Tapia, Claudio; Garcia-Masso, Xavier
    The assessment of trunk sway smoothness using an accelerometer sensor embedded in a smartphone could be a biomarker for tracking motor learning. This study aimed to determine the reliability of trunk sway smoothness and the effect of visual biofeedback of sway smoothness on motor learning in healthy people during unipedal stance training using an iPhone 5 measurement system. In the first experiment, trunk sway smoothness in the reliability group (n = 11) was assessed on two days, separated by one week. In the second, the biofeedback group (n = 12) and no-biofeedback group (n = 12) were compared during 7 days of unipedal stance test training and one more day of retention (without biofeedback). The intraclass correlation coefficient score 0.98 (0.93-0.99) showed that this method has excellent test-retest reliability. Based on the power law of practice, the biofeedback group showed greater improvement during training days (p = 0.003). Two-way mixed analysis of variance indicates a significant difference between groups (p < 0.001) and between days (p < 0.001), as well as significant interaction (p < 0.001). Post hoc analysis shows better performance in the biofeedback group from training days 2 and 7, as well as on the retention day (p < 0.001). Motor learning objectification through visual biofeedback of trunk sway smoothness enhances postural control learning and is useful and reliable for assessing motor learning.