2007•Fudan xuebao. Ziran Kexue banRequires access

Time-Varying Liquidity and Market Depth

Qiu Shi-liang

Open publisher page 0 citations

Abstract

With high frequency data and the market liquidity depth indicator VNET, the dynamic features and the determinative factors of market liquidity are studied, and the market microstructure theories are verified. The results support the asymmetry information theory, and reveal that patient trading can decrease transaction costs for institutional investors.

About this research paper

What this paper is about

With high frequency data and the market liquidity depth indicator VNET, the dynamic features and the determinative factors of market liquidity are studied, and the market microstructure theories are verified. The results support the asymmetry information theory, and reveal that patient trading can decrease transaction costs for institutional investors.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

With high frequency data and the market liquidity depth indicator VNET, the dynamic features and the determinative factors of market liquidity are studied, and the market microstructure theories are verified. The results support the asymmetry information theory, and reveal that patient trading can decrease transaction costs for institutional investors.

Key concepts: Market liquidity, Market microstructure, Information asymmetry, Determinative, Transaction cost, Market impact, Liquidity crisis, Monetary economics

Related papers

Back to paper searchBrowse research topicsOriginal source
Time-Varying Liquidity and Market Depth — Research Paper | ScholarLens