Knowledge that Transforms

Based on a unique dataset provided by a retail bank, we analyze borrower heterogeneity in the debt response to interest rate decreases and credit limit increases in revolving consumer credit. Our key findings show that 1) the debt response to interest rate decreases by borrowers who choose voluntary minimum repayments (VMR) is about four times as large as the response by borrowers not choosing this option, 2) VMR borrowers demand credit limit increases which are more than twice as high as those of non-VMR borrowers following interest rate cuts, and 3) VMR borrowers’ marginal propensity to consume out of credit limit increases is almost 30% stronger. These results are most likely to be caused by sophisticated present-biased individuals choosing to commit and shed new light on the role of non-standard borrower preferences in consumer credit.

We study the effects of U.S. interest rates and other factors on risk-taking in the global market for U.S. dollar syndicated term loans. We find that, before the Global Financial Crisis, both U.S. and non-U.S. lenders originated ex ante riskier loans to non-U.S. borrowers in response to a decline in short-term U.S. interest rates and, after the crisis, in response to a decline in longer-term U.S. interest rates. After the crisis, this behavior was more prominent for shadow banks and less prominent for banks with relatively low capital. Separately, before the crisis, lenders originated less risky loans in response to U.S. dollar appreciation. Across the periods, the responses to risk appetite and economic uncertainty varied. To the extent that the Federal Reserve affects U.S. interest rates, we provide evidence of global risk-taking spillovers of U.S. monetary policy, which are important but not dominant factors for risk-taking in the market.

In this study, we provide empirical evidence that firm-level jump-induced tail risk (measured by a jump-implied variance contribution index [JIVX]) prospectively predicts cross-sectional stock returns around earnings announcements. The effect size is nontrivial. A practical trading strategy that buys announcers with high pre-news JIVX values and sells announcers with low pre-news JIVX values, earns a net risk-adjusted average return of 82 basis points (bps) three days after the news release. Notably, the empirical success of the JIVX predictor is distinct from model-free implied skewness and kurtosis measures and withstands a battery of robustness checks.

Unlike traditional asset categories (e.g., industry classifications) that are generally defined clearly, some groups of stocks are tied to certain loosely defined “concepts” (e.g., e-commerce). When investors find it difficult to analyze ambiguous concept-oriented information, information diffuses slowly, creating “concept momentum”. Based on unique concept data in the Chinese stock market, this study constructs a concept-momentum strategy that involves buying stocks from past winning concepts and selling stocks from past losing concepts, which can generate pronounced abnormal returns. Neither risk factors, firm-level momentum, nor industry-level momentum can explain concept momentum. Furthermore, we find that both the underreaction and cross-stock lead-lag effect channels can cause slow information diffusion and drive concept momentum. Moreover, the concept momentum effect is stronger for relatively ambiguous concepts, for concepts that attract less investor attention, and following high-sentiment periods.

We develop a term structure model that decomposes nominal yields into the sum of an expectation, term premium, and convexity term and in turn of their real and inflation counterparts. The model explicitly captures the interrelation between yield-only and macroeconomic factors while allowing for aggregate stochastic volatility. We extract the components from the nominal and real yield curve of the United States, the Euro Area, the United Kingdom, and Japan. We find that short-rate expectations have steadily declined over the last two decades and account for the bulk of yield dynamics. Term premia increase with maturity but explain a smaller fraction of yield forecast error variance than previously documented. With regard to yield comovement, the United States generates the strongest spillovers at the long end of the yield curve, whereas the Japanese market is the top importer of shocks.

While investor sentiment has been shown to have a robust, direct impact on stock returns, we know little about how it impacts returns through an indirect channel from conditional volatility. We conduct a global study of investor sentiment across 40 international stock markets to examine the impact of investor sentiment on stock returns via both direct and indirect channels and how the impact varies across bull and bear market regimes. Using turnover ratio as the sentiment proxy and applying GARCH-type models, we confirm a conditional impact of investor sentiment on stock returns via both channels: In bull regimes, optimistic (pessimistic) shifts in investor sentiment would increase (decrease) stock returns, while in bear regimes, optimistic (pessimistic) shifts would decrease (increase) stock returns.

ABSTRACT In this paper we carry out a cross-country analysis of the correlation risk premium. We examine the statistical properties of the implied and realized correlation in European equity markets and relate the resulting premium to US equity market correlation risk and a global correlation risk premium. We find evidence of strong co-movement of correlation risk premiums in European and US equity markets. Our results support the existence of a strong empirical relationship between the global correlation risk premium and international equity market option returns. We document the dependence of the correlation risk premium on macroeconomic uncertainty and related variables.

White papers are likely the primary source of information provided to potential Initial Coin Offering (ICO) investors in platform-based ventures that may reduce information asymmetry between ICO issuers and investors. We use textual analysis to measure the information content of white paper documents. We examine how an informative white paper content signal and a concurrent potentially biased expert rating signal correlate with measures of ICO funding success, ICO underpricing, and post-ICO performance. Our empirical results suggest that high-quality ICO issuers signal their type by providing more informative white paper content, i.e., excess or new textual information not contained in recent and peer white papers. However, investors rely on the expert ratings signal in their decision to buy tokens that “jams” the white paper informative content signal. Once listed tokens receive a market valuation, white paper informative content is positively associated with our measures for underpricing, returns, and liquidity, while the expert ratings signal is rendered irrelevant.

Tail-correlation matrices are an important tool for aggregating risk measurements across risk categories, asset classes and/or business segments. This paper demonstrates that traditional tail-correlation matrices—which are conventionally assumed to have ones on the diagonal—can lead to substantial biases of the aggregate risk measurement’s sensitivities with respect to risk exposures. Due to these biases, decision-makers receive an odd view of the effects of portfolio changes and may be unable to identify the optimal portfolio from a risk-return perspective. To overcome these issues, we introduce the “sensitivity-implied tail-correlation matrix”. The proposed tail-correlation matrix allows for a simple deterministic risk aggregation approach which reasonably approximates the true aggregate risk measurement according to the complete multivariate risk distribution. Numerical examples demonstrate that our approach is a better basis for portfolio optimization than the Value-at-Risk implied tail-correlation matrix, especially if the calibration portfolio (or current portfolio) deviates from the optimal portfolio.

When making investment decisions, people rely heavily on price charts displaying the past performance of an asset. Price charts can come with any time frame, which the provider might strategically choose. We analyze the impact of the time frame on retail investors’ behavior, particularly trading activity and risk-taking, in a controlled experiment with 1041 retail investors. We find that shorter time frames are associated with more trading activity, resulting in higher transaction fees and investor welfare losses. However, the time frame does not affect average risk-taking.