Fernando – Commonality In Liquidity-Transmission Of Liquidity Shocks Across Investors And Securitie

002Recent findings of common factors in liquidity raise many issues pertaining to the determinants of commonality and its impact on asset prices. We explore some of these issues using a model of liquidity trading in which liquidity shocks are decomposed into common(systematic) and idiosyncratic components. We show that common liquidity shocks do not give rise to commonality in trading volume, raising questions about the sources of commonality that is detected in the literature. Indeed,trading volume is independent of systematic liquidity risk, which is always priced independently of the liquidity in the secondary market. In contrast, idiosyncratic liquidity shocks create liquidity demand and volume, and investors can diversify their risk by trading. Hence, the pricing of the risk of idiosyncratic liquidity shocks depends on the market’s liquidity, with idiosyncratic liquidity risk being fully priced only in perfectly illiquid markets. While tr

ading volume is increasing in the variance of idiosyncratic liquidity shocks, price volatility is increasing in the variance of both systematic liquidity shocks and idiosyncratic liquidity shocks. Surprisingly, our results are largely independent of the number of different securities traded in the market. When asset returns are uncorrelated, there is no transmission of liquidity across assets even when investors experience common (systematic) liquidity shocks, suggesting that such liquidity shocks may not be the source of commonality in liquidity across assets detected in the literature. However, under limited conditions, more liquid securities can act as substitutes for less liquid securities. Overall, our findings suggest that common factors in liquidity may be the outcome of covariation in investor heterogeneity (e.g. as measured by co-movements in the volatility of idiosyncratic liquidity shocks) rather than of common liquidity shocks. Moreover, we find that different liquidity proxies measure different things, which has implications for future empirical analysis.

File Size:411kB
File Type: PDF
pages: **

 

0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.