Investor emotional biases and trading volume’s asymmetric response: A non-linear ARDL approach tested in S&P500 stock market

Abstract

This paper investigates the dynamic linkages between trading volume and investors sentiments for the S&P500 stock exchange. Two sentiment indicators are considered, the overconfidence and the net optimism-pessimism indicator. Non-linear dynamic approach, namely the asymmetric autoregressive distributed lag (NARDL) model is used to capture the long-term and short-term non-linear connections between the investor sentiment and the stock market liquidity. Empirical findings suggested an asymmetric long-term market liquidity reaction to investor sentiment. In the short-term, the stock market liquidity react rapidly and asymmetrically to changes in overconfidence sentiment, while the optimism and pessimism sentiment has insignificant short-term impact on trading volume.