This paper proposes a Near Explosive Random-Coefficient autoregressive model for asset pricing which accommodates both the fundamental asset value and the recurrent presence of autonomous deviations or bubbles. Such a process can be stationary with or without fat tails, unit-root nonstationary...

In order to examine non-linear predictability of the US and Japanese dividend-yield ratio, smooth transition regression model analysis is applied to an extended time period of data. The theoretical basis for investigating non-linear behaviour in stock returns can be based on the interaction...

We survey the literature on stock return forecasting, highlighting the challenges faced by forecasters as well as strategies for improving return forecasts. We focus on U.S. equity premium forecastability and illustrate key issues via an empirical application based on updated data. Some studies...

This paper aims to characterize the time series dynamics of asset price under the statistical probability measure in the presence of bubbles (defined according to the local martingale theory). We advocate that quadratic-variation risk premium can serve as a mechanism leading to forward-looking...

This study evaluates whether exchange traded funds (ETFs) threaten fnancial market stability by testing two hypotheses relating the growing importance of ETFs to increased market volatility and rising equity valuations. We estimate quantile cointegration models using Standard & Poor's 500 Index...

This paper proposes a Near Explosive Random-Coefficient autoregressive model for asset pricing which accommodates both the fundamental asset value and the recurrent presence of autonomous deviations or bubbles. Such a process can be stationary with or without fat tails, unit-root nonstationary...

We develop a methodology for detecting asset bubbles using a neural network. We rely on the theory of local martingales in continuous-time and use a deep network to estimate the diffusion coefficient of the price process more accurately than the current estimator, obtaining an improved detection...

It is well known that intraday volatilities and trading volumes exhibit strong seasonal features. These seasonalities are usually modeled using dummy variables or deterministic functions. Here, we propose a test for seasonal long memory with a known frequency. Using this test, we show that...

This paper examines the volatility of banks equity weekly returns for six banks (coded B1 to B6) using GARCH models. Results reveal the presence of ARCH effect in B2 and B3 equity returns. In addition, the estimated models could not find evidence of leverage effect. On evaluating the estimated...

This paper examines the effect of foreign exchange news announcements on the volatility of stock returns in Nigeria, using the daily closing All-Share Index from The Nigerian Stock Exchange from 2000 to 2015. We extended existing literature by augmenting the EGARCH econometric model with...