Knowledge that Transforms

This paper studies the intraday relationship between ultra-fast machine-driven activity (UFA) and market quality in automated equity markets. We find that higher UFA is associated with lower intraday market quality (greater quoted and effective spreads and lower depth). This effect is economically significant, and robust to different specifications, endogeneity tests, and alternative measures of UFA. Our results hold after controlling for volatility, periods of unusually high UFA (a proxy for quote stuffing), and periods where UFA is primarily driven by fleeting orders inside the spread (a proxy for spoofing and competition between liquidity providers).

We examine the cleansing effect of financial crises via their contribution to the exit of inefficient US commercial banks from 1984 to 2013. We find a larger increase in the exit likelihood of less efficient banks as compared to more efficient banks in the years of the Savings and Loans Crisis but not during the Global Financial Crisis. We highlight how the magnitude of the shock of the Global Financial Crisis and the subsequent, broad government interventions might explain these different results. Furthermore, we highlight that both crisis periods have a disproportionate effect on young banks regardless of their efficiency levels and that they do not generate any positive spillover effects on surviving banks in the three years post-crises in spite of some reallocation benefits in favor of new entry banks. Our findings highlight that forms of prudential regulation designed to strengthen bank resilience in good times might contribute to mitigating the effects of crisis on the longer-term productivity of the banking industry.

We introduce new semi-parametric models for the analysis of rates and proportions, such as proportions of default, (expected) loss-given-default and credit conversion factor encountered in credit risk analysis. These models are especially convenient for the stress test exercises demanded in the current prudential regulation. We show that the Least Impulse Response Estimator, which minimizes the estimated effect of a stress, leads to consistent parameter estimates. The new models with their associated estimation method are compared with the other approaches currently proposed in the literature such as the beta and logistic regressions. The approach is illustrated by both simulation experiments and the case study of a retail P2P lending portfolio.

Unique features and market frictions can lead to idiosyncratic pricing for some US Treasury securities. This study uses a linear programming (LP) model to measure aggregate idiosyncratic pricing of T-notes and T-bonds from 1980 to 2016. We document an average idiosyncratic pricing of $0.11 per $100 par, as compared to an average bid-ask spread of $0.08. Further, idiosyncratic pricing declined dramatically from the early 1980s to the 2010s. Empirical evidence suggests that the 1986 Tax Reform Act, increasing issue sizes and improving market liquidity contribute to the decline. At the individual security level, we identify factors contributing to and mitigating idiosyncratic pricing.

We consider how size matters for banks in three size groups: small community banks with assets less than 1 billion, large community banks with assets between 1 billion and 10 billion, and midsize banks with assets between 10 billion and 50 billion. To illustrate the differences between these banks and larger banks whose business models are distinctly different, we examine large banks with assets between 50 billion and 250 billion and the largest banks with assets exceeding 250 billion. Community banks have potential advantages in relationship lending compared with large banks. However, increases in regulatory compliance and technological burdens may have disproportionately increased community banks’ costs, raising concerns about small businesses’ access to credit. Our evidence suggests several patterns: (1) while small community banks exhibit relatively more valuable investment opportunities, larger community banks, midsize banks, and larger banks exploit theirs more efficiently and achieve better financial performance; (2) average operating costs that include costs related to regulatory compliance and technology decrease with size; (3) unlike small community banks, large community banks have financial incentives to increase lending to small businesses; and (4) for business lending and commercial real estate lending, compared with small community banks, large community banks, midsize banks, and larger banks assume higher inherent credit risk and exhibit more efficient lending. Thus, concern that small business lending would be adversely affected if small community banks find it beneficial to increase their scale is not supported by our results.

Collectively organized pension plans must increasingly demonstrate that the risk preferences of their members are adequately reflected in the plans’ asset allocations. However, whether funds should elicit individual members’ risk preferences to achieve this goal, or whether they can rely on other indicators, such as socio-demographics, remains unclear. To address this question, we apply a tailored augmented lottery choice method to elicit individual pension income risk preferences from 7,894 members from five different pension plans. The results show that member risk preferences are strongly heterogeneous and can only partially be predicted from individual and plan characteristics. Differences in risk preference imply different optimal asset allocations. We find large welfare losses for heterogeneous members in pension plans with their current asset allocation because these allocations are safer than implied by members’ preferences. We provide a framework for pension plans to gauge the need to elicit risk preferences among their members.

We investigate the takeover strategies of high default risk acquirers and their value impact. We find that these bidders select bigger, less profitable and unrelated targets, pursue transactions during recessions, and pay with shares by offering target shareholders high premiums. Their long-term buy-and-hold returns are extremely negative, and reflect fundamentally their substantial drop in profitability combined with high leverage. We show that the well-established long-run underperformance of acquiring firms is largely driven by this sub-set of acquirers. The results are similar when we use alternative measures of default risk and performance, and a global sample of non-US bidders.

The decision to syndicate investments in entrepreneurial finance has been explained through financial, networking, and resource-based perspectives. We posit that a personality perspective exists next to these three perspectives and hypothesize that the personality of business angels influences syndication behavior. Using data from 3,234 syndication decisions of 1,348 business angels, we find evidence for some of our predictions. By measuring personality through a comprehensive language analysis based on digital footprints in Twitter statements of business angels, we show that extraversion makes syndication more likely, whereas conscientiousness reduces the likelihood of syndication. Several sensitivity analyses underline the robustness of our main results. Further exploratory analyses assess the relationship between personality and syndicate composition as well as that between personality and venture success. Our study contributes to the entrepreneurial finance literature by adding and validating a new perspective to explain syndication behavior. In addition, our study contributes to research on the personality of business angels.

We examine how time-varying macroeconomic conditions affect firms’ financing decisions. A principal components decomposition of several macroeconomic variables characterizes three phases of the business cycle relative to recessions: early recovery, robust recovery, and economic crest; a fourth represents “windows of opportunity” in capital markets that are unrelated to recessions. This characterization yields results that traditional approaches miss. Specifically, debt issuance exhibits a non-monotonic pattern during the upward phase of the business cycle: it declines in robust recovery relative to recessions but peaks at the economic crest. Financially constrained firms issue more equity during windows of high stock market valuation, whereas unconstrained firms time debt issuance in response to debt market spreads.

This paper analyzes the strong comovement between real stock and nominal bond yields at generational frequencies. Using a stochastic overlapping generations model with cash-in-advance constraints, we show that the simulated life-cycle patterns in savings behavior make both real stock and nominal bond yields comove with the changing population age structure. These persistent comovements account for the equilibrium relation between stock and bond markets. A stochastic Fisher decomposition of nominal bond yields reveals that, while having a moderate effect on both the inflation risk premium and expected inflation, demographic changes affect nominal yields mainly through real bond yields. Using both U.S. data and a cross-country panel, we find empirical support for these theoretical predictions. Finally, we show that the strength of the demographic effect on real yields explains cross-country differences in the comovement between stock and bond markets, while alternative demographic channels fail to explain such cross-country heterogeneity.