Knowledge that Transforms

We show that widely used macroprudential regulations that rely on historical cost accounting (HCA) to insulate banks’ balance sheets from financial market volatility significantly affect the transmission of monetary policy onto bank lending. Using detailed supervisory data from Italian banks, we find that HCA mutes the transmission of quantitative easing and other monetary policies that affect the long end of the yield curve, weakening the effectiveness of interventions aimed at reducing firm credit constraints. We suggest alternative policies that have the benefits of HCA but allow monetary policy to pass through.

We analyze effects of tacit collusion in a dynamic general equilibrium model of oligopolistic sectors with capital investment and real frictions. Through their effects on equilibrium- and off-equilibrium stock prices, fundamental shocks affect incentives for defection from tacit collusion, amplifying the interaction between the real economy and financial markets as well as firms’ risk exposure. The model implies ambiguous relationship between industry concentration and equity returns depending on operating leverage, which helps reconcile conflicting evidence in the literature. We find quantitative and empirical support for novel theoretical predictions regarding the effects of concentration on returns and investment.

We study how bank advertising practices contribute to racial disparities in financial markets by steering minorities toward inferior products. We exploit a regulatory change that incentivizes deposit collection at the Freedman’s Savings Bank, the first institution to collect deposits from African Americans post-Emancipation, by facilitating misuse of depositor funds. After deregulation, advertising volume rises, particularly in African American newspapers, leading to increased deposits from Black depositors despite the bank’s insolvency. We identify persuasion as a key mechanism; prescriptive stereotypes and false claims likely amplify advertising’s impact on African Americans, exacerbating historically large depositor losses after the bank’s collapse.

Exchange-traded funds (ETFs) are typically viewed as passive index trackers. In contrast, we show that corporate bond ETFs actively manage their portfolios, trading off index tracking against liquidity transformation. In our model, ETFs optimally choose creation and redemption baskets that include cash and only a subset of index assets, especially if those assets are illiquid. Our evidence supports the model. We find that ETFs dynamically adjust their baskets to correct portfolio imbalances while facilitating ETF arbitrage. Basket inclusion improves bond liquidity in general, but worsens it in periods of large imbalance between creations and redemptions, such as the COVID-19 crisis.

We show current market practices relating to odd-lot quotes create a large “inside” market where better prices routinely exist relative to the National Best Bid or Offer. We show that odd-lot quotes play a price discovery role, and these quotes provide valuable information to traders with access to proprietary data feeds. Using a XGBoost machine learning algorithm that uses odd-lot data to predict future prices, we demonstrate a simple and profitable trading strategy. We argue the SEC’s proposed round-lot redefinition reduces—but does not eliminate—the high incidence of superior odd-lot quotes within the NBBO.

This paper presents an approach for pricing gold from investors’ perspective. The model is based on no-arbitrage principles with minimal structural assumptions. There is no need to specify investor preferences. When fitted to match 10-year real U.S. Treasury rates, the model can replicate the salient fluctuations in the time series of gold prices since 2007. The model is also able to capture key patterns of CME Comex gold futures prices. The model implies that the majority of the value of gold is due to its role as an investment asset.

We study the effects of going public using a unique panel of firms in 16 European countries for which we observe financial data before and after initial public offering (IPO) attempts. We compare completed and withdrawn IPO attempts. We instrument the decision to complete the IPO using prior market returns. After instrumenting, we isolate a positive causal effect of going public on profitability. We also find a post-IPO expansion in sales per employee, subsidiaries, and countries in which firms operate. Overall, our results are consistent with going public relaxing financial constraints and inducing a shift in strategy towards increased commercialization.

Does the performance of advisors’ recommendations influence investors’ propensity to seek advice again? I investigate a sample of calls between 10,063 German brokerage clients and financial advisors from 2005–2015. If advisors’ recommendations in the initial meeting led to positive (vs. negative) performance, investors are 2.1 times more likely to arrange a second meeting. This effect is driven by the performance of the recommendations the investor decided to follow. Investors with positive performance follow recommendations to a greater degree. The findings show that experiences matter in the advisory context and shape the demand for advice.

We study the dynamics of trading volume and bid-ask spread using a multiperiod trading model with oligopolistic market makers. Traders smooth out their trading even though they are not strategic, and thus trading persists after the arrival of information or liquidity shocks. Traders act quickly on their private information while postponing hedging trades until later periods. The market power of market makers enables them to widen bid-ask spreads when trading incentives are heightened. Consequently, both trading volume and bid-ask spread may exhibit U-shaped patterns. Our model calibration aligns with the empirical intraday patterns observed in bid-ask spreads and trading volumes. (JEL D53, D61, D82, G12, G14, G18)

Utilizing real-time newswire data, together with a robustly estimated intraday stochastic discount factor (SDF), we identify and quantify the economic news that is priced. News related to monetary policy and finance on average accounts for most of the variation in the SDF, followed by news about international affairs and macroeconomic data. We also document nontrivial temporal variation in the relative importance of the news, along with marked differences in the estimated news risk premiums in the “factor zoo.” To further highlight the economic mechanisms at work, we associate the different news effects with interest rate, growth, and risk premium shocks.