Long-horizon regressions: theoretical results and applications

By Rossen Valkanov. 2003

497 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/f6c95a5fe29eaa097252787e77bdf73692235a15

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Citations in the corpus

The Baltic Dry Index as a Predictor of Global Stock Returns, Commodity Returns, and Global Economic Activity (2010, background): “…to inference issues that afflict other predictors, such as the aggregate dividend yield, that may exhibit near-unit-root dynamics (e.g., Cavanagh, Elliott, and Stock (1995), Stambaugh (1999), Valkanov (2003), Ferson, Sarkissian, and Simin (2003), Lewellen (2004), and Campbell and Yogo (2006)).”
Out-of-Sample Predictions of Bond Excess Returns and Forward Rates: An Asset Allocation Perspective (2010, unknown): “Hence, the estimates of R2 reported in the existing literature are inadequate measures of the true in-sample predictability (Kirby, 1997; Valkanov, 2003, Campbell and Yogo, 2006; Boudoukh et al., 2008; Wei and Wright, 2010 and the references therein).”
Parametric Portfolio Policies: Exploiting Characteristics in the Cross Section of Equity Returns (2009, unknown): “All coefﬁcients are still statistically signiﬁcant, both individually and jointly.”
Panel cointegration tests of the Fisher effect (2006, background): “Thus, the power of tests that depend on estimating βi from the level data is expected to decrease with the number of regressors in a way that the power of the new tests is not, see Westerlund and Edgerton (2006).(9) Remark 4.”
Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices (2008, methodology): “Non-overlapping data are used so as to avoid the problems in the statistical inference that are encountered in the case of long horizon predictive regressions with overlapping data (see e.g., Valkanov, 2003).”
Output and expected returns (2006, methodology): “With values such as these, Valkanov (2003) reports the 1% confidence level to be −0.405 at the 1% level (Valkanov's results are based on T = 750 however), i.e. the rescaled t-statistics in Table 4 of this paper are significant when judged in relation to the critical values simulated by Valkanov…”
Predictive regression under various degrees of persistence and robust long-horizon regression (2013, methodology): “Unlike earlier work on predictive regression such as Valkanov (2003), the regressors in the empirical model can be multivariate and their autoregressive roots may fall into any of the following classes: near integration (I2), unit roots (I3), or locally explosive roots (I4).”
Climate risks and market efficiency (2017, unknown): “Our focus on 12-month horizon returns for FOOD brings up the usual worries of longhorizon excess return predictability (Valkanov (2003)).”
Advances in Consumption-Based Asset Pricing: Empirical Tests (2011, unknown): “HHL and Malloy, Moskowitz, and Vissing-Jorgensen (2009) (MMV) pursue an approximate solution developed in Kogan and Uppal (2000), which works by substituting a”
Institutional and individual sentiment: Smart money and noise trader risk? (2006, background): “Several authors (see Stambaugh, 1999, Valkanov, 2003, or Ferson et al., 2003) have documented this problem, which is mainly caused by highly persistent regressors that evolve as stochastic processes themselves.”