Showing 1 - 10 of 14,269
We propose a Bayesian procedure for exploiting small, possibly long-lag linear predictability in the innovations of a finite order autoregression. We model the innovations as having a log-spectral density that is a continuous mean-zero Gaussian process of order 1/√T. This local embedding makes...
Persistent link: https://www.econbiz.de/10012461943
forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting … ARCH or stochastic volatility models, which often perform poorly at intraday frequencies. Use of realized volatility … and forecasting. Building on the theory of continuous-time arbitrage-free price processes and the theory of quadratic …
Persistent link: https://www.econbiz.de/10012470566
We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study … although the conditional correlation between the mean and volatility is negative, the unconditional correlation is positive due …
Persistent link: https://www.econbiz.de/10012469657
Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good … forecasts of future volatility are critical for the implementation and evaluation of asset pricing theories. In response to this …, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily …
Persistent link: https://www.econbiz.de/10012472795
We compare the out-of-sample forecasting performance of univariate homoskedastic, GARCH, autoregressive and nonparametric models for conditional variances, using five bilateral weekly exchange rates for the dollar, 1973-1989. For a one week horizon, GARCH models tend to make slightly more...
Persistent link: https://www.econbiz.de/10012474328
econometric issues are addressed including estimation of the number of dynamic factors and tests for the factor restrictions …
Persistent link: https://www.econbiz.de/10012467213
This paper develops a vector autoregression (VAR) for time series which are observed at mixed frequencies - quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to...
Persistent link: https://www.econbiz.de/10012458951
We study the relation between inflation and real activity over the business cycle. We employ a Trend-Cycle VAR model to control for low-frequency movements in inflation, unemployment, and growth that are pervasive in the post-WWII period. We show that cyclical fluctuations of inflation are...
Persistent link: https://www.econbiz.de/10014247995
We use a broad set of Chinese economic indicators and a dynamic factor model framework to estimate Chinese economic activity and inflation as latent variables. We incorporate these latent variables into a factor-augmented vector autoregression (FAVAR) to estimate the effects of Chinese monetary...
Persistent link: https://www.econbiz.de/10012458147
inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an …
Persistent link: https://www.econbiz.de/10012466341