Nina Boyarchenko

Intermediary Leverage Cycles and Financial Stability

We develop a theory of financial intermediary leverage cycles in the context of a dynamic model of the macroeconomy. The interaction between a production sector, a financial intermediation sector, and a household sector gives rise to amplification of fundamental shocks that affect real economic activity. The model features two state variables that represent the dynamics of the economy: the net worth and the leverage of financial intermediaries. The leverage of the intermediaries is procyclical owing to risk-sensitive funding constraints. Relative to an economy with constant leverage, financial intermediaries generate higher output and consumption growth and lower consumption volatility in normal times, but at the cost of systemic solvency and liquidity risks. We show that tightening intermediaries’ risk constraints affects the systemic risk-return trade-off, by lowering the likelihood of systemic crises at the cost of higher pricing of risk. Our model thus represents a conceptual framework for cyclical macroprudential policies within a dynamic stochastic general equilibrium model.

The Eigenfunction Expansion Method in Multi-Factor Quadratic Term Structure Models

We propose the eigenfunction expansion method for pricing options in quadratic term structure models. The eigenvalues, eigenfunctions, and adjoint functions are calculated using elements of the representation theory of Lie algebras not only in the self-adjoint case, but in non-self-adjoint case as well; the eigenfunctions and adjoint functions are expressed in terms of Hermite polynomials. We demonstrate that the method is efficient for pricing caps, floors, and swaptions, if time to maturity is 1 year or more. We also consider subordination of the same class of models, and show that in the framework of the eigenfunction expansion approach, the subordinated models are (almost) as simple as pure Gaussian models. We study the dependence of Black implied volatilities and option prices on the type of non-Gaussian innovations.

Ambiguity Shifts and the 2007-2008 Financial Crisis

Faced with doubts about the quality of information and the quality of modeling techniques, ambiguity-averse agents assign higher probabilities to lower utility states, leading to higher CDS premia and lower equity prices. Using data on financial institutions, I find that the sudden increases in credit spreads during the recent crisis can be explained by changes in the amount of ambiguity faced by market participants and changes in how the total amount of ambiguity was distributed between ambiguity about information quality and ambiguity about model quality.

Intermediary Balance Sheets

We document the cyclical properties of the balance sheets of different types of intermediaries. While the leverage of the bank sector is highly procyclical, the leverage of the nonbank financial sector is acyclical. We propose a theory of a two-agent financial intermediary sector within a dynamic model of the macroeconomy. Banks are financed by issuing risky debt to households and face risk-based capital constraints, which leads to procyclical leverage. Households can also participate in financial markets by investing in a nonbank “fund” sector where fund managers face skin-in-the-game constraints, leading to acyclical leverage in equilibrium. The model also reproduces the empirical feature that the banking sector’s leverage growth leads the financial sector’s asset growth, while leverage in the fund sector does not precede growth in financial-sector assets. The procyclicality of the banking sector is due to its risk-based funding constraints, which give a central role to the time variation of endogenous uncertainty.

Understanding mortgage spreads

Because most mortgages in the United States are securitized in agency mortgage-backed securities (MBS), yield spreads on MBS are a key determinant of homeowners’ funding costs. We study variation in MBS spreads in the time series and across securities and document that MBS spreads show a pronounced cross-sectional smile with respect to the securities’ coupon rates. We present a new pricing model that uses “stripped” MBS prices to identify the contribution of non-interest-rate prepayment risk to spreads and find that this risk explains the smile, whereas the time-series spread variation is mostly accounted for by nonprepayment risk factors.Received March 30, 2015; editorial decision November 21, 2018 by Editor Leonid Kogan. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Taking Orders and Taking Notes: Dealer Information Sharing in Treasury Markets

According to most theories of financial intermediation, intermediaries diversify risk, transform maturity or liquidity, and screen or monitor borrowers. In U.S. Treasury auctions, none of these rationales apply. Intermediaries submit their customer bids without transforming liquidity or maturity, and they do not screen and monitor borrowers or diversify fiscal policy risk. Yet, most end investors place their Treasury auction bids through an intermediary rather than submit them directly. Motivated by this evidence, we explore a new information aggregation model of intermediation. Intermediaries observe each client’s order flow, aggregate that information across clients, and use it to advise their clients as a group. In contrast to underwriting theories in which intermediaries, by acting as gatekeepers, extract rents but reduce revenue variance, information aggregators increase expected auction revenue, but also make the revenue more sensitive to changes in asset value. We use the model to examine current policy questions, such as the optimal number of intermediaries, the effect of non-intermediated bids, and minimum bidding requirements. ∗The views expressed here are the authors’ and are not representative of the views of the Federal Reserve Bank of New York or of the Federal Reserve System. We thank Ken Garbade, Luis Gonzalez, Richard Tang, Haoxiang Zhu and participants at the 2014 U.S. Treasury Roundtable on Treasury Markets for comments. Nic Kozeniauskas and Karen Shen provided excellent research assistance. Emails: nina.boyarchenko@ny.frb.org; david.lucca@ny.frb.org; lveldkam@stern.nyu.edu. Investors often access financial markets through intermediaries. Sometimes these intermediaries have exclusive access to a trading venue. Other times, they lower risk by screening investments or monitoring borrowers’ behavior. In U.S. Treasury auctions, which are the world’s largest, intermediaries channel investors’ bids, without diversifying or transforming risks. Further, in contrast to public offerings of private issuers (e.g., Beatty and Ritter, 1986; Hansen and Torregrosa, 1992), intermediaries in Treasury auctions cannot screen or monitor the issuer because they do not influence fiscal policy. Despite these limitations, and even though investors can bid directly through an electronic system, most bids are still placed through intermediaries. The prevalence of intermediation in a market where none of the typical rationales apply prompts us to examine a new role for intermediaries and its consequences for asset prices and auction revenue. We present a new theory of financial intermediaries who collect information from order flow, use it to advise clients, and bid for their in-house account.1 Existing work in the initial public offering (IPO) literature studies the effects of concentrated underwriting, which typically involves a single lead, or a handful of co-lead, underwriters. It finds that this structure lowers issuers’ revenues but also revenue variance.2 In Treasury auctions, there are many information intermediaries, investors have the option of bidding directly without an intermediary, and intermediaries are subject to minimum bidding requirements. Finally, intermediaries place very large bids for their own accounts. We show that in this setting, the conventional wisdom of underwriting is reversed: information intermediaries raise expected revenue but also revenue variance. By sharing valuable information with their clients, dealers lower clients’ risk, which encourages them to bid more aggressively and boost expected auction revenue. At the same time, more precise information about the asset value makes beliefs and bids more sensitive to changes in that value. Therefore, auction revenue is also more sensitive to information about the future value and as a result, more variable. Thus, information aggregation intermediaries provide value both for investors and for the asset issuer, but their effects on auction revenue are exactly the opposite from those of a traditional security underwriter. Sovereign auction rules regarding the use of client information vary across countries. In the UK, the Debt Management Office explicitly sanctions that Gilt-edged Market Makers, which have exclusive access to the auction and route orders for all other bidders, “whilst not permitted to charge a fee for this service, may use the information content of that bid to its own benefit” (GEMM Guidebook, 2011). We are not aware of similar rules in the context of U.S. Treasury auctions. In the U.S., a financial intermediary’s use of client information, including sharing such information with other clients or using the information for other benefit to such intermediary, may violate legal requirements, be they statutory, regulatory or contractual, and/or violate market best practices or standards. This paper does not take a view as to whether the described use of client information with respect to Treasury auction activity is legal or proper. The objective of the paper is to study the economic effects of order flow dissemination ahead of the auction as a mechanism to lower auction risk and raise revenues. In a “full commitment IPO,” the underwriter generally earns a large first-day secondary market return, and stabilizes the market value by raising supply elasticity, either offering additional (“greenshoe option”) or buying some of the securities being offered (Ritter and Welch, 2002).

Counterparty Risk in Material Supply Contracts

This paper explores the sources of counterparty risk in material supply relationships. Using long-term supply contracts collected from SEC filings, we test whether three sources of counterparty risk -- financial exposure, product quality risk, and redeployability risk -- are priced in the equity returns of linked firms. Our results show that equity holders require compensation for exposure to all three sources of risk. Specifically, offering trade credit to counterparties and investing in relationshipspecific assets increase a firms exposure to counterparty risk. Further, we show that contracts with protective financial covenants and product warranties mitigate the transmission of risk. Overall, we provide evidence on the channels of supply-chain risk and show that shareholders recognize the role of contractual features in mitigating counterparty risk.

Information Acquisition and Financial Intermediation

Informational advantages of specialists relative to households lead to disagreement between the two in an intermediated market. Although households can acquire additional signals to reduce the informational asymmetry, the additional information is costly, making it rational for households to limit the accuracy of the signals they observe. I show that this leads the equity capital constraint to bind more frequently, making the asset prices in the economy more volatile unconditionally. When disagreement between households and specialists is high, however, return volatility decreases. I find empirical evidence consistent with these predictions.

ESTIMATING EQUATIONS FOR A CLASS OF TIME-IRREVERSIBLE MULTI-FACTOR MODELS

The standard operator approach to the identification problem of diffusions and more general Markov processes relies on the variational principles for self-adjoint operators. If the process is not time reversible, equivalently, the infinitesimal operator of the process is not self-adjoint, these principles are not applicable. We develop the spectral decomposition for multi-factor time-irreversible OU processes, ATSMs and QTSMs, and use it to construct new estimating equations. Using these equations, we construct identification schemes for the leading eigenfunction, stationary distribution, gap between the leading eigenvalue and the real part of the rest of the spectrum, and more involved schemes for all parameters of the process. Finally, we use the variational principles for the self-adjoint operator associated to an appropriate quadratic form to construct the leading eigenfunction and a basis in the vector space of unobserved factors from observed yields in a QTSM, and provide the reduction of the identification problem of a QTSM to the identification problem of an OU model.

Turning Off the Tap: Determinants of Expropriation in the Energy Sector

This paper analyzes the dependence of the decision of a government to expropriate foreign investment in the energy sector on macroeconomic factors and crude oil and natural gas prices. The contribution of the paper is two-fold. First, using data on eight countries that made recent steps to expropriate foreign investment in their respective energy sectors, we identify the factors that are significant for the decision. These factors are assumed to be invariant across countries. Second, we use our results to calculate the probability that the seven major petroleum exporters with at most partial state ownership will nationalize their respective energy sectors in the next month. The results of this paper can be used to design optimal exit strategies for companies invested in energy sectors in developing countries.