This paper develops the asymptotic theory for stable autoregressive models in which the noise variance grows in a polynomial-like fashion. It is shown that the asymptotic distribution of the OLS estimator of the coefficient vector is multivariate normal with a covariance matrix that depends on...

The estimation of dynamic causal effects is one of the crucial challenges of econometrics. In the macroeconomic literature, dynamic causal effects are conceived as the effect, over time, of an intervention that propagates through the economy. This is usually modeled via impulse response analysis...

This paper conducts a comprehensive investigation of the "forecast combination puzzle" in the context of the heterogeneous autoregressive (HAR) model for volatility forecasting. The widely-used HAR model can be considered as a theoretically optimal combination of three random-walk forecasts...

The Schwartz-Smith two-factor model (Schwartz & Smith, 2000) was commonly used in the pricing of commodity futures in the last two decades. In 2016, (Filipovic & Larsson, 2016) introduced a polynomial diffusion framework which allows a more complex struc- ture of spot price. This framework has...

Accurate prediction of high-dimensional covariance matrices is crucial for portfolio and risk management. In the model developed in this work, high-frequency financial data is used to obtain the realized covariance matrix, and the realized semicovariance is used to decompose the covariance...

Under contemporary market conditions in China, the stock index has been volatile and highly reflect trends in the coronavirus pandemic, but rare scientific research has been conducted to model the nonlinear relations between the two variables. Added, on the advent that covid-related news in one...

Standard estimates of risk premiums in traditional linear asset pricing models are subject to bias, primarily because of the omission of certain factors. The three-pass method is a promising approach that has been proposed to estimate the risk premium of observable factors. This method remains...

In this study, we consider a four-regime bubble model under the assumption of time-varying volatility and propose the algorithm of estimating the break dates with volatility correction: First, we estimate the emerging date of the explosive bubble, its collapsing date, and the recovering date to...

This paper considers a time-varying vector error-correction model that allows for different time series behaviours (e.g., unit-root and locally stationary processes) to interact with each other to co-exist. From practical perspectives, this framework can be used to estimate shifts in the...

In the presence of fixed threshold effects, the least squares (LS) estimator of the threshold parameter poses challenges for statistical inference due to its non-standard limiting distribution, which also presents challenges for bootstrap methods. To address this issue, we propose a novel...