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Asset Pricing across Asset Classes and Microstructure Analysis in Equity and Cryptocurrency Market

Feng, L (2021). Asset Pricing across Asset Classes and Microstructure Analysis in Equity and Cryptocurrency Market. (Unpublished Doctoral thesis, City, University of London)

Abstract

In Chapter 1, I form a single cross-section from the USD returns on international equity indices, international sovereign bonds, and currencies; I then sort the entire cross-section according to (standardised) value, momentum, and carry measures. In these international, multi-asset-class portfolios, there are large, significant returns available to carry investors and significant – though somewhat smaller – returns to momentum and value investors. The premiums are not much larger than a simple average of within-asset-class premiums for all three strategies. Asset pricing tests show that volatility risk can explain currency carry returns, but bond and equity carry returns have a different source. Value, carry, and momentum returns of across-asset-class portfolios – including all three asset classes – are difficult to explain using an equilibrium asset pricing model.

In Chapter 2 and 3, I decompose prices into two unobserved processes: fundamental value and pricing error. The former is influenced by private information contained in order flows, while the latter depends on liquidity providers’ inventory control. Analysis of UK equity data during the 2008 financial crisis shows that order flows had a more significant impact on pricing errors during the crisis, indicating that strained inventory absorption capacity of liquidity providers was the main factor in the decline of equity market liquidity. The results also reveal that liquidity provision is reduced in volatile markets due to inventory control, while changes in information asymmetry only affect equities with small market capitalisation and trading volume. The Bitcoin and Ethereum results on two leading exchanges (Bitfinex and Kraken), between January 2017 and January 2018, demonstrate that cryptocurrency price change is determined by order flows through information asymmetry and inventory control. Additionally, when the emerging cryptocurrency market saw a boom and then crashed, the impacts of order flows on fundamental value and pricing errors were greater at the beginning of both the boom and the crash. Cross-cryptocurrency and cross-exchange results indicate that orders of one cryptocurrency on one exchange can also influence the price of another cryptocurrency on another exchange through information.

Publication Type: Thesis (Doctoral)
Subjects: H Social Sciences > HG Finance
Departments: Bayes Business School
Bayes Business School > Finance
Doctoral Theses
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