A Transparency Standard for Derivatives

Derivatives exposures across large financial institutions often contribute to – if not necessarily create – systemic risk. Current reporting standards for derivatives exposures are nevertheless inadequate for assessing these systemic risk contributions. In this paper, I explain how a transparency standard, in contrast to the current standard, would facilitate such risk analysis. I also demonstrate that such a standard is implementable by providing examples of existing disclosures from large dealer firms in their quarterly filings. These disclosures often contain useful firm-level data on derivatives, but due to a lack of standardization, they cannot be aggregated to assess the risk to the system. I highlight the important contribution that reporting the “margin coverage ratio” (MCR), namely the ratio of a derivatives dealer’s cash (or liquidity, more broadly) to its contingent collateral or margin calls in case of a significant downgrade of its credit quality, could make toward assessing systemic risk contributions.

Are banks passive liquidity backstops? deposit rates and flows during the 2007-2009 crisis

Can banks maintain their advantage as liquidity providers when they are heavily exposed to a financial crisis? The standard argument - that banks can - hinges on deposit inflows that are seeking a safe haven and provide banks with a natural hedge to fund drawn credit lines and other commitments. We shed new light on this issue by studying the behavior of bank deposit rates and inflows during the 2007-09 crisis. Our results indicate that the role of the banking system as a stabilizing liquidity insurer is not one of the passive recipient, but of an active seeker, of deposits. We find that banks facing a funding squeeze sought to attract deposits by offering higher rates. Banks offering higher rates were also those most exposed to liquidity demand shocks (as measured by their unused commitments, wholesale funding dependence, and limited liquid assets), as well as with fundamentally weak balance-sheets (as measured by their non-performing loans or by subsequent failure). Such rate increases have a competitive effect in that they lead other banks to offer higher rates as well. Overall, the results present a nuanced view of deposit rates and flows to banks in a crisis, one that reflects banks not just as safety havens but also as stressed entities scrambling for deposits.

Asset Pricing with Liquidity Risk

This paper solves explicitly an equilibrium asset pricing model with liquidity risk -- the risk arising from unpredictable changes in liquidity over time. In our liquidity-adjusted capital asset pricing model, a security's required return depends on its expected liquidity as well as on the covariances of its own return and liquidity with market return and market liquidity. In addition, the model shows how a negative shock to a security's liquidity, if it is persistent, results in low contemporaneous returns and high predicted future returns. The model provides a simple, unified framework for understanding the various channels through which liquidity risk may affect asset prices. Our empirical results shed light on the total and relative economic significance of these channels.

A Theory of Income Smoothing When Insiders Know More Than Outsiders

We consider a setting in which insiders have information about income that outside shareholders do not, but property rights ensure that outside shareholders can enforce a fair payout. To avoid intervention, insiders report income consistent with outsiders' expectations based on publicly available information rather than true income, resulting in an observed income and payout process that adjust partially and over time towards a target. Insiders under-invest in production and effort so as not to unduly raise outsiders' expectations about future income, a problem that is more severe the smaller is the inside ownership and results in an "outside equity Laffer curve". A disclosure environment with adequate quality of independent auditing mitigates the problem, implying that accounting quality can enhance investments, size of public stock markets and economic growth.

Julia: A Fresh Approach to Numerical Computing

Bridging cultures that have often been distant, Julia combines expertise from the diverse fields of computer science and computational science to create a new approach to numerical computing. Julia is designed to be easy and fast. Julia questions notions generally held as "laws of nature" by practitioners of numerical computing: 1. High-level dynamic programs have to be slow. 2. One must prototype in one language and then rewrite in another language for speed or deployment, and 3. There are parts of a system for the programmer, and other parts best left untouched as they are built by the experts. We introduce the Julia programming language and its design --- a dance between specialization and abstraction. Specialization allows for custom treatment. Multiple dispatch, a technique from computer science, picks the right algorithm for the right circumstance. Abstraction, what good computation is really about, recognizes what remains the same after differences are stripped away. Abstractions in mathematics are captured as code through another technique from computer science, generic programming. Julia shows that one can have machine performance without sacrificing human convenience.Comment: 37 page