The half-life is used to estimate the adjustment speed of a variable to a new equilibrium point after being affected by the impulse response of a unit of shocks. The paper examines the adjustment speed of COVID19, investor sentiment, and the stock market through half-life estimates over the...

While investors demand a premium to hold stocks with high illiquidity level and risk, they underreact to stock-level liquidity shocks and idiosyncratic liquidity. Built on Baker and Stein (2004) market liquidity model, this paper: (i) reports a significant relationship between market liquidity...

Stock market movements are the results of changes in investor sentiment (INSEN) which can even be induced by non-economic events. We consider international cricket events to empirically investigate the notions. Implementing portfolio approach, we conduct the event study along with OLS regression...

Momentum, size, and low volatility in emerging markets regularly exhibit increased correlations across factors and markets in periods of negative returns. I provide a framework to distinguish a unique source of risk from a set of factors in the stage of portfolio formation. The framework is...

We are familiar with the maximum score estimator of (Manski, C.F., 1975, Journal of Econometrics 3, 205-228). A generalization of the maximum score estimator is the maximum profit estimator of (Skouras, S., 2003, Computational Statistics and Data Analysis 42, 349-361). The general case is the...

Using high-frequency data, we decompose the time-varying beta for stocks into beta for continuous systematic risk and beta for discontinuous systematic risk. Estimated discontinuous betas for S&P500 constituents between 2003 and 2011 generally exceed the corresponding continuous betas. We...

The paper empirically analyzes stock market integration and the benefit possibilities of international portfolio diversification across the Southeast Asia (ASEAN) and U.S. equity markets. It employs daily sample of 6 ASEAN equity market indices and S&P 500 index as a proxy of U.S. market index...

We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are...

We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are...

We develop a novel machine learning method to estimate large dimensional time-varying GMM models via our newly designed ridge fusion regularization scheme. Our method is a one-step procedure and allows for abrupt, smooth and dual type time variation with a fast rate of convergence. It...