Financial Economics

Paper Session

Friday, Jan. 6, 2017 7:30 PM – 9:30 PM

Hyatt Regency Chicago, Michigan 1A & 1B
Hosted By: American Economic Association
  • Chair: Karlyn Mitchell, North Carolina State University

Asymmetric Information and the Distribution of Trading Volume

Matthijs Lof
Aalto University
Jos Van bommel
University of Luxembourg


We introduce a new measure of information asymmetry in security markets: the trading volume coefficient of variation (VCV). Using the Kyle (1985) model, we show that this easily computable ratio is a function of the proportion of informed trade. We compute the VCV for a cross-section of stocks from time-series of daily volume market shares and find that the VCV correlates strongly with extant measures of informed trade. We also compute time series of VCV from the cross-sections of relative trading volumes to estimate information asymmetries in event- time, and find a clear spike of the volume coefficient of variation around earnings announcements.

Does Funding Liquidity Cause Market Liquidity? Evidence From a Quasi-Experiment

Petri Jylha
Aalto University


Theoretical models of Gromb and Vayanos (2002) and Brunnermeier and Pedersen (2009) predict a causal effect from funding liquidity on market liquidity. However, due to endogeneity, this causality is difficult to establish empirically. In this paper, we use an exogenous shock to the margin requirements of a limited set of securities to show the causal effect of funding liquidity on market liquidity. On July 14, 2005, after a lengthy process, SEC approved a new method for calculating margin requirements for index options. This new portfolio margining method greatly reduced the required margins of index option while, importantly, having no impact at all on the margins of equity options.

The results of this paper clearly show that an improvement in funding liquidity causes an improvement in market liquidity. Using the unaffected equity options as a control group, we show, in a difference-in-difference framework, that the following the margin requirement reduction the market liquidity of index options improves on all three tested dimensions. First, the trading volume of index options increases by 16% to 19%. The growth in volumes is stronger for less liquid puts and out-of-the-money options. Second, the improvement in funding liquidity decreases both direct and indirect costs of trading index options: the bid-ask spreads narrow by about one-eighth and Amihud (2002) type price impact measures decrease by roughly one-third with the implementation of portfolio margining. Overall, the results provide strong causal evidence of funding liquidity being a key driver of market liquidity.

To our knowledge, this is the first paper to use a purely exogenous funding liquidity shock to study this relation and provide causal evidence in support of the predictions put forth by Gromb and Vayanos (2002) and Brunnermeier and Pedersen (2009).

Why Does Idiosyncratic Risk Increase With Market Risk?

Sohnke M. Bartram
University of Warwick
Greg W. Brown
University of North Carolina-Chapel Hill
Rene M. Stulz
Ohio State University


From 1963 through 2015, idiosyncratic risk (IR) is high when market risk (MR) is high. We show that the positive relation between IR and MR is highly stable through time and is robust across exchanges, firm size, liquidity, and market-to-book groupings. Though stock liquidity affects the strength of the relation, the relation is strong for the most liquid stocks. Firm characteristics related to the ability of firms to adjust to higher uncertainty help explain the strength of the relation. Specifically, the relation is weaker for firms with more growth options. This evidence is consistent with the view that growth options provide a hedge against macroeconomic uncertainty.

The Macroeconomic Shock with the Highest Price of Risk

Gabor Pinter
Bank of England


This paper proposes a new orthogonalisation method that uses the cross-section of returns to construct a macroeconomic shock. This λ-shock demands the highest possible risk price per unit of exposure, or equivalently, best approximates the stochastic discount factor with VAR residuals. The method is general and could be applied to any VAR and any test assets. When applying the method to the HML-SMB-industry portfolios, a robust feature of the λ-shock is the delayed effect on output and the sharp impact on the term spread and interest rates. The estimated λ-shock closely resembles (>70% correlation) monetary policy and technology news shocks studied by macroeconomists. In contrast, the λ-shock implied by momentum portfolios is markedly different.

Credit Ratings Overreliance in Municipal Bonds Market

Vita Faychuk
Miami University


In 2010 Moody’s and Fitch underwent a systematic overhaul of their municipal rating scale (recalibration). As a result, the majority of municipal bonds ratings were upgraded mechanically, disregarding their fundamentals. Recalibration was carried over simultaneously for all bonds of a specific type. This setting represents an excellent natural experiment to test heterogeneity of market participants’ reaction to pure ratings change that is free of confounding effects of bond fundamentals and regulatory changes.

If the recalibration was, as announced, a pure change of rating “labels” (i.e. a AA municipal bond became a new AAA), we should not expect any reaction in the efficient market. Even if it was a signal of the major change of the municipal rating model, I show that this information was not new for the market.

In contrast to predictions of the semi-strong efficient market hypothesis, I document significant post-recalibration yield declines for bonds with 19-30 years of maturity. I explain this reaction by the combination of municipal market segmentation by maturity (institutional investors hold the majority of short-term bonds and individual investors (households) hold the majority of long-term municipal bonds) and individual investors' overreliance on credit ratings per se. Municipal bonds are extremely heterogeneous, municipal financial reporting is opaque, so the cost of acquiring and processing information is very large for a non-professional municipal investor. As a result, individual investors rely excessively on credit ratings as a convenient credit risk summary. This is especially worrying, taking into account the quality of credit ratings that has raised a lot of questions in the aftermath of the 2008-2009 financial crisis. It is even more problematic given the fact that the credit rating agencies claim no legal responsibility for the quality of information they provide. These findings have important regulatory implications.
JEL Classifications
  • G1 - Asset Markets and Pricing