Robert J. Richmond


I am an Associate Professor of Finance at NYU Stern and a Faculty Research Fellow at the National Bureau of Economic Research (NBER).

My research interests are in international finance and asset pricing.

More information is available in my CV.

NYU Stern School of Business
44 West Fourth Street, 9-81
New York, NY 10012
E-mail: rrichmon@stern.nyu.edu

Working Papers

Understanding the Strength of the Dollar

Coauthors: Zhengyang Jiang and Tony Zhang

  • NBER Digest
  • Vienna Symposium on Foreign Exchange Markets best paper award (2023).

We attribute variation in the strength of the U.S. dollar and its covariance with other major currencies to economic primitives using a demand system for global portfolio holdings. We take global investor savings, asset supply, and monetary policy as exogenous primitives, and show how these variables explain dollar exchange rate behavior. Prior to the global financial crisis, global savings and demand shifts explain dollar depreciation, whereas they explain dollar appreciation afterwards. Interest rates and cross-border bank loans explain short-term fluctuations in the dollar, but decline in significance over longer horizons. When explaining the dollar factor structure, we find that global savings drive common variations across foreign currencies, whereas investor demand shifts explain cross-sectional heterogeneity in dollar betas.
Divided We Fall: International Health and Trade Coordination During a Pandemic

Coauthors: Viral Acharya, Zhengyang Jiang, and Ernst-Ludwig von Thadden

We analyze the role of international trade and health coordination during a pandemic by developing a two-economy, two-good trade model integrated into a micro-founded SIR model of infection dynamics. Governments can adopt containment policies to suppress infection spread domestically, and levy import tariffs to prevent infection coming from abroad. The efficient, i.e., coordinated, risk-sharing arrangement dynamically adjusts both policy instruments to share infection and economic risks internationally. However, in the Nash equilibrium of uncoordinated governments with national mandates, trade policies robustly feature inefficiently high tariffs that peak with the pandemic in the foreign economy. This distorts terms-of-trade dynamics and magnifies the welfare costs during a pandemic, featuring lower levels of consumption and production, as well as smaller gains via diversification of infection curves across economies.
Asset Embeddings

Coauthors: Xavier Gabaix, Ralph Koijen, and Motohiro Yogo

Firm characteristics are ubiquitously used in economics. These characteristics are often based on readily-available information such as accounting data, but those reflect only a part of investors’ information set. We show that useful information about firm characteristics is embedded in investors’ holdings data and, via market clearing, in prices, returns, and trading data. Based on insights from the recent artificial intelligence (AI) and machine learning (ML) literature, in which unstructured data (e.g., words or speech) are represented as continuous vectors in a potentially high-dimensional space, we propose to learn asset embeddings from investors’ holdings data. Indeed, just as documents arrange words that can be used to uncover word structures via embeddings, investors organize assets in portfolios that can be used to uncover firm characteristics that investors deem important via asset embeddings. This broad theme provides a natural bridge to connect recent advances in the fields of AI and ML to finance and economics. Specifically, we show how language models, including transformer models that feature prominently in large language models such as BERT and GPT, can handle numerical information, and in particular holdings data to estimate asset embeddings. We provide initial evidence on the value added of asset embeddings through a series of applications in the con- text of firm valuations, return comovement, and uncovering asset substitution patterns. As a by-product, the models generate investor embeddings, which can be used to measure investor similarity. We propose a programmatic list of potential applications of asset and investor em- beddings to finance and economics more generally.
Reserve Asset Competition and the Global Fiscal Cycle

Coauthors: Zhengyang Jiang

Governments tend to increase their borrowing at the same time, giving rise to a global fiscal cycle. This global fiscal cycle has a large component that is unexplained by global business cycle variables. We propose a novel explanation for the emergence of the common variation based on governments engaging in competition over the provision of reserve assets. Competition in the provision of safe assets gives rise to strategic complementarity in the issuance decision, even when the reserve assets are substitutes in partial equilibrium. We show our reserve-asset-competition channel gives rise to economically significant common variations in fiscal variables, beyond the common variations induced by correlated business cycles. In doing so, our model of reserve asset demand and supply also shines light on the sources of variations in the convenience yields and seigniorage revenues earned on government debt.
Convenience Yields and Asset Pricing Models

Coauthors: Zhengyang Jiang

Convenience yields on safe assets affect the constraints that asset price data impose on asset pricing models. We show that high Sharpe ratios imply either a volatile stochastic discount factor or a high convenience yield, which generalizes the Hansen-Jagannathan bound. We apply this insight to the Treasury market by incorporating convenience yields into affine term structure models. The solutions link yields across the entire term structure to SDF and convenience yield dynamics. We show that introducing convenience yields rules in more economically sensible models. This improvement becomes more pronounced as we adopt more realistic convenience yield measures.

Publications

Trade Network Centrality and Currency Risk Premia

The Journal of Finance, 74(3), June 2019.

  • Outstanding PhD Paper Award in Honor of Stuart I. Greenbaum, Olin Business School at Washington University St. Louis (2015).
  • Annual Conference on International Finance Best Paper Award (2016).
  • Cubist Systematic Strategies Award (2016).
  • Data is available here.

I uncover an economic source of exposure to global risk that drives international asset prices. Countries which are more central in the global trade network have lower interest rates and currency risk premia. As a result, an investment strategy that is long in currencies of peripheral countries and short in currencies of central countries explains unconditional carry trade returns. To explain these findings, I present a general equilibrium model where central countries’ consumption growth is more exposed to global consumption growth shocks. This causes the currencies of central countries to appreciate in bad times, resulting in lower interest rates and currency risk premia. In the data, central countries’ consumption growth is more correlated with world consumption growth than peripheral countries’, further validating the proposed mechanism.
Gravity in the Exchange Rate Factor Structure

The Review of Financial Studies, 33(8), August 2020.
Coauthors: Hanno Lustig

We relate the risk characteristics of currencies to measures of physical, cultural, and institutional distance. The currencies of countries which are more distant from other countries are more exposed to systematic currency risk. This is due to a gravity effect in the factor structure of bilateral exchange rates: When a currency appreciates against a basket of all other currencies, its bilateral exchange rate appreciates more against the currencies of distant countries. As a result, currencies of peripheral countries are more exposed to the systematic variation than currencies of central countries. Trade network centrality is the best predictor of a currency's average exposure to systematic risk.
International Trade and Social Connectedness

Journal of International Economics, 129(103418), March 2021.
Coauthors: Michael Bailey, Abhinav Gupta, Sebastian Hillenbrand, Theresa Kuchler, and Johannes Stroebel

  • Replication Package is available here.
  • SCI Data is available here.

We use de-identified data from Facebook to construct a new and publicly available measure of the pairwise social connectedness between 170 countries and 332 European regions. We find that two countries trade more when they are more socially connected, especially for goods where information frictions may be large. The social connections that predict trade in specific products are those between the regions where the product is produced in the exporting country and the regions where it is used in the importing country. Once we control for social connectedness, the estimated effects of geographic distance and country borders on trade decline substantially.
Origins of International Factor Structures

Journal of Financial Economics, 147(1), January 2023.
Coauthors: Zhengyang Jiang

We show that exchange rate correlations tend to be explained by the global trade network while consumption correlations tend to be explained by productivity correlations. Sharing common trade linkages with other countries increases exchange rate correlations beyond bilateral linkages. We explain these findings using a model of the global trade network with market segmentation. Interdependent global production generates international comovements, while market segmentation disconnects the drivers of exchange rate correlations from the drivers of consumption correlations. Moreover, we show that the trade network generates common factors found in exchange rates. Our findings offer a trade-based account of the origins of international comovements and shed light on important frictions in international markets.
A Portfolio Approach to Global Imbalances

The Journal of Finance, Forthcoming.
Coauthors: Zhengyang Jiang and Tony Zhang

  • Western Finance Association NASDAQ Award for Best Paper in Asset Pricing (2022).
  • Vienna Symposium on Foreign Exchange Markets best paper award (2020).

We use a portfolio-based framework to understand what drives the decline of the U.S. net foreign asset (NFA) position and the reversal in returns earned on the US NFA (exorbitant privilege). We show that global savings gluts and monetary policies widened the U.S. NFA position, while investor demand shifts partially offset this widening. Moreover, U.S. privilege declined after 2010, in accordance with increasing foreign demand for U.S. equity. We also highlight a quantity dimension of the U.S. privilege: the U.S. can issue substantially more debt than other countries for a given yield increase.
Which Investors Matter for Equity Valuations and Expected Returns?

Review of Economic Studies, Forthcoming.
Coauthors: Ralph Koijen and Motohiro Yogo

  • Replication Package is available here.

Based on an asset demand system, we develop a framework to quantify the impact of market trends and changes in regulation on asset prices, price informativeness, and the wealth distribution. Our leading applications are the transition from active to passive investment management and climate-induced shifts in asset demand. The transition from active to passive investment management had a large impact on equity prices but a small impact on price informativeness because capital did not flow from more to less informed investors on average. This finding is based on a new measure of investor-level informativeness that identifies which investors are more informed about future profitability. Climate-induced shifts in asset demand have a potentially large impact on equity prices and the wealth distribution, implying capital gains for passive investment advisors, pension funds, insurance companies, and private banking and capital losses for active investment advisors and hedge funds.