Optimal Financial Transaction Taxes
Pages: 5-61 | Published: 11/2022 | DOI: 10.1111/jofi.13188 | Cited by: 7
EDUARDO DÁVILA
This paper characterizes the optimal transaction tax in an equilibrium model of financial markets. If investors hold heterogeneous beliefs unrelated to their fundamental trading motives and the planner calculates welfare using any single belief, a positive tax is optimal, regardless of the magnitude of fundamental trading. Under some conditions, the optimal tax is independent of the planner's belief. The optimal tax can be implemented by adjusting its value until total volume equals fundamental volume. Knowledge of (i) the share of nonfundamental trading volume and (ii) the semielasticity of trading volume to tax changes is sufficient to quantify the optimal tax.
Less Mainstream Credit, More Payday Borrowing? Evidence from Debt Collection Restrictions
Pages: 63-103 | Published: 12/2022 | DOI: 10.1111/jofi.13189 | Cited by: 6
JULIA FONSECA
Governments regulate debt collectors to protect consumers from predatory practices. These restrictions may lower repayment, reducing the supply of mainstream credit and increasing demand for alternative credit. Using individual credit record data and a difference‐in‐differences design comparing consumers in states that tighten restrictions on debt collection to those in neighboring states that do not, I find that restricting collections reduces access to mainstream credit and increases payday borrowing. These findings provide new evidence of substitution between alternative and mainstream credit and point to a trade‐off between shielding consumers from certain collection practices and pushing them into higher cost payday lending markets.
Pages: 105-139 | Published: 11/2022 | DOI: 10.1111/jofi.13187 | Cited by: 1
BO BECKER, VICTORIA IVASHINA
We show that over the past half‐century, innovative disruptions were central to understanding corporate defaults. In a given year, industries experiencing abnormally high venture capital or initial public offering activity subsequently see higher default rates, higher segment exits by conglomerates, and higher yields on bonds issued by the firms in these industries. Overall, we find that disruption is a broad phenomenon, negatively affecting incumbent firms across the spectrum of age, valuation, and levers, with the exception of very large and low‐leverage firms, in line with our central hypothesis.
How Risky Are U.S. Corporate Assets?
Pages: 141-208 | Published: 1/2023 | DOI: 10.1111/jofi.13196 | Cited by: 1
TETIANA DAVYDIUK, SCOTT RICHARD, IVAN SHALIASTOVICH, AMIR YARON
We use market data on corporate bonds and equities to measure the value of U.S. corporate assets and their payouts to investors. In contrast to equity dividends, total corporate payouts are highly volatile, turn negative when corporations raise capital, and are acyclical. At the same time, corporate asset returns are similar to returns on equity, and both are exposed to fluctuations in economic growth. To reconcile this evidence, we argue that acyclical but volatile net repurchases mask the exposure of total payouts' cash components to economic growth risks. We develop an asset pricing framework to quantitatively illustrate this economic channel.
International Yield Curves and Currency Puzzles
Pages: 209-245 | Published: 12/2022 | DOI: 10.1111/jofi.13191 | Cited by: 7
MIKHAIL CHERNOV, DREW CREAL
The currency depreciation rate is often computed as the ratio of foreign to domestic pricing kernels. Using bond prices alone to estimate these kernels leads to currency puzzles: the inability of models to match violations of uncovered interest parity and the volatility of exchange rates. This happens because of the FX bond disconnect, the inability of bonds to span exchange rates. Incorporating innovations to the pricing kernel that affect exchange rates but not bonds helps resolve the puzzles. This approach also allows one to relate news about cross‐country differences between international yields to news about currency risk premiums.
Decentralization through Tokenization
Pages: 247-299 | Published: 12/2022 | DOI: 10.1111/jofi.13192 | Cited by: 34
MICHAEL SOCKIN, WEI XIONG
We examine decentralization of digital platforms through tokenization as an innovation to resolve the conflict between platforms and users. By delegating control to users, tokenization through utility tokens acts as a commitment device that prevents a platform from exploiting users. This commitment comes at the cost of not having an owner with an equity stake who, in conventional platforms, would subsidize participation to maximize the platform's network effect. This trade‐off makes utility tokens a more appealing funding scheme than equity for platforms with weak fundamentals. The conflict reappears when nonusers, such as token investors and validators, participate on the platform.
Beyond Basis Basics: Liquidity Demand and Deviations from the Law of One Price
Pages: 301-345 | Published: 12/2022 | DOI: 10.1111/jofi.13198 | Cited by: 2
TODD M. HAZELKORN, TOBIAS J. MOSKOWITZ, KAUSHIK VASUDEVAN
Deviations from the law of one price between futures and spot prices—the futures‐cash basis—capture information about liquidity demand for equity market exposure in global markets. We show that the basis comoves with dealer and investor futures positions, is contemporaneously positively correlated with futures and spot market returns, and negatively predicts futures and spot returns. These findings are consistent with the futures‐cash basis reflecting liquidity demand that is common to futures and cash equity markets. We find persistent supply‐demand imbalances for equity index exposure reflected in the basis, giving rise to an annual premium of 5% to 6%.
Pages: 347-387 | Published: 12/2022 | DOI: 10.1111/jofi.13199 | Cited by: 11
BRYAN KELLY, SEMYON MALAMUD, LASSE HEJE PEDERSEN
We propose a new asset pricing framework in which all securities' signals predict each individual return. While the literature focuses on securities' own‐signal predictability, assuming equal strength across securities, our framework includes cross‐predictability—leading to three main results. First, we derive the optimal strategy in closed form. It consists of eigenvectors of a “prediction matrix,” which we call “principal portfolios.” Second, we decompose the problem into alpha and beta, yielding optimal strategies with, respectively, zero and positive factor exposure. Third, we provide a new test of asset pricing models. Empirically, principal portfolios deliver significant out‐of‐sample alphas to standard factors in several data sets.
Pages: 389-425 | Published: 1/2023 | DOI: 10.1111/jofi.13200 | Cited by: 1
MATTHIAS FLECKENSTEIN, FRANCIS A. LONGSTAFF
We present a new approach for estimating small business equity returns. This approach applies the Merton (1974) credit model to the returns on entrepreneurial business credit card debt securitizations and solves for the implied equity returns for the small businesses owned by the cardholders. The estimated small business equity premium is 10.74%. The standard deviation of small business equity returns is 56.37%. We validate the methodology by applying it to investment‐grade corporate bonds and recovering a public equity premium of 6.17%.
Beliefs Aggregation and Return Predictability
Pages: 427-486 | Published: 12/2022 | DOI: 10.1111/jofi.13195 | Cited by: 1
ALBERT S. KYLE, ANNA A. OBIZHAEVA, YAJUN WANG
We study return predictability using a model of speculative trading among competitive traders who agree to disagree about the precision of private information. Although traders apply Bayes' Law consistently, returns are predictable. In addition to trading on long‐term fundamental value, traders also trade on perceived short‐term opportunities arising from foreseen future disagreement, as in a Keynesian beauty contest. Contradicting conventional wisdom, this short‐term speculation dampens price fluctuations and generates time‐series momentum. Model calibration shows quantitatively realistic patterns of return dynamics. Consistent with empirical evidence, our model predicts more pronounced momentum for stocks with higher trading volume.
Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models
Pages: 487-557 | Published: 12/2022 | DOI: 10.1111/jofi.13197 | Cited by: 42
SVETLANA BRYZGALOVA, JIANTAO HUANG, CHRISTIAN JULLIARD
We propose a novel framework for analyzing linear asset pricing models: simple, robust, and applicable to high‐dimensional problems. For a (potentially misspecified) stand‐alone model, it provides reliable price of risk estimates for both tradable and nontradable factors, and detects those weakly identified. For competing factors and (possibly nonnested) models, the method automatically selects the best specification—if a dominant one exists—or provides a Bayesian model averaging–stochastic discount factor (BMA‐SDF), if there is no clear winner. We analyze 2.25 quadrillion models generated by a large set of factors and find that the BMA‐SDF outperforms existing models in‐ and out‐of‐sample.
Preliminary Program AFA 2023 ANNUAL MEETING EIGHTY‐THIRD ANNUAL MEETING AMERICAN FINANCE ASSOCIATION
Pages: 560-605 | Published: 1/2023 | DOI: 10.1111/jofi.13193 | Cited by: 0
Participant Schedule for the AFA 2023 Preliminary Program January 6–8, 2023
Pages: 606-685 | Published: 1/2023 | DOI: 10.1111/jofi.13194 | Cited by: 0
Pages: 686-687 | Published: 1/2023 | DOI: 10.1111/jofi.13038 | Cited by: 0