AFA Ph.D. Student Poster Session at the 2020 Annual Meeting(11)

Limited capacity in processing transactions presents one of the most fundamental technical challenges to blockchain-based financial applications (e.g., Bitcoin). We argue that this property also has profound impacts on asset prices by limiting the speed and scale at which capital can flow, which may distort prices in two important and distinctive ways: 1) to limit the speed of information dissemination in normal days, which generates momentum; and 2) to give rise to sharp price shifts and subsequent reversals in hightension periods, which leads to bubbles and crashes. Accordingly, we expect that blockchain-based financial assets—e.g., cryptocurrencies—may be vulnerable to both momentum and bubbles and that the two types of price distortions can be largely exclusive. Based on a sample of 1392 cryptocurrencies, we find that momentum strategy works for normal-stage cryptocurrencies but not for bubble-stage ones. Moreover, contrary to equity-momentum, crypto-momentum is not associated with higher crash risk. If anything, crash risk is associated with, and can be predicted by, the bubble stage of cryptocurrencies. Our results shed new lights on blockchain-based Fintech products and services.

原文链接：

We propose enhanced necessary criteria to select Factor-Mimicking Portolios (FMPs) that genuinely present a true risk factor. Ideally, FMPs should (a) be correlated with underlying factors, (b) be related to the systematic risk in asset returns, (c) explain the cross-sectional of mean returns, and (d) be robust to the included assets. Existing methods do not satisfy these criteria and are exposed to several econometric difficulties such as errors-in-variables bias. We study the improvements based on the Instrumental Variables method (IV) and Stein’s shrinkage method. The IV approach leads to nearly unbiased risk premium estimation in simulations, while other methods have large biases. We find that FMPs constructed with IV satisfy the above criteria for equities when mimicking consumption growth, inflation, and the unemployment rate and for corporate bonds when mimicking consumption growth, industrial production, and the default spread.

原文链接：

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFAPS2020&paper_id=118