Knowledge that Transforms

We investigate the time variation in credit rating standards awarded to financial institutions of commercial bank credit ratings awarded by the three principal CRAs from 1990 to 2015 in a world-wide context by testing for well-defined structural shifts. We focus on the part of the ratings that cannot be accounted using publicly available information. We test whether major financial events are conditioning, ex-post such changes Distinctively in this paper’s timespan our analysis covers four periods: (i) before and (ii) after the 2001–2 corporate collapses, followed by (iii) before the global financial crisis and (iv) after the global financial crisis. We find substantial differences in the assignment of bank credit ratings among the three major agencies, Moody’s, Fitch, and S&P. Agencies differ both in terms of re-adjustment of ratings but also on the speed of response to the evens. All three agencies tightened ratings during the 2008 crisis and kept reducing them in its aftermath.

In this paper, we investigate price exuberance episodes in the main UK commercial real estate sectors – retail, offices and industrials - over the period December 1986–April 2022. Using the Backward Supremum Augmented Dickey Fuller approach of Phillips et al. (2015a,b), we find that episodes of price explosiveness are asynchronous across sectors with only common phase being the period 2003–2007. We also conduct a multivariate probit analysis to identify factors that indicate the occurrence of price exuberance episodes and generate early signals for possible price bubble building. The predictors for price explosiveness differ by sector with more consistent signals obtained from the yield curve for retail and industrials, rent growth for offices and industrials, and inflation for retail and offices. A key implication of this study is that the study of price exuberance and bubbles in private real estate should be sector specific even within the same country.

Most of the foreign exchange intervention literature overlooks the influence of market uncertainty when evaluating effectiveness. In this paper we take a fresh new look at how this uncertainty amplifies exchange rate effects. Our contribution is twofold. We first posit a partial equilibrium model with frictions to illustrate that when uncertainty is low, intervention is less effective, for agents are willing to bet against the central bank. Conversely, when uncertainty is high, intervention faces a weaker countervailing force from speculators and arbitragers. Second, we empirically test for the incremental effects of flimsy exchange rate fundamentals by using a sharp policy discontinuity in the way the Central Bank of Colombia intervened in the FX market. Our results indicate that market uncertainty increases depreciation of domestic currency in approximately 2 percentage points (pp) following central bank purchases of foreign currency and extends its duration in up to 4 weeks. Additionally, these purchases have an incremental effect in curbing exchange rate volatility in close to 5 pp.

Strategic alliances are voluntary corporate arrangements for mutual benefit. Although alliances are common as an alternative to M&As, they require cooperation between alliance partners who continue to operate as independent companies. Thus, relational risk—the probability and consequences of unsatisfactory cooperation or opportunistic behavior—is inherent in alliances and a major determinant of alliance success. In this paper, we examine and find that alliance announcement CARs are higher for companies sharing the same auditor with their alliance partner. Further, our findings suggest that the shared auditor effect is stronger for alliances where potential relational risk between alliance partners is greater. Our findings hold when we use “withdrawn” (i.e., the withdrawal of an announced alliance before its start date) as an alternative, albeit inverse, measure of alliance success. Collectively, we provide novel evidence which suggests that auditors add shareholder value by playing a matchmaking role in alliance formation, building inter-company trust and mitigating relational risk by facilitating the sharing of non-financial information between potential alliance partners among their audit clients.

This paper empirically analyses whether post-global financial crisis regulatory reforms have created appropriate incentives to voluntarily centrally clear over-the-counter (OTC) derivative contracts. We use confidential European trade repository data on single-name sovereign credit default swap (CDS) transactions and show that both seller and buyer manage counterparty exposures and capital costs, strategically choosing to clear when the counterparty is riskier. The clearing incentives seem particularly responsive to seller credit risk, which is in line with the notion that counterparty credit risk (CCR) is asymmetric in CDS contracts. The riskiness of the underlying reference entity also impacts the decision to clear as it affects both CCR capital charges for OTC contracts and central counterparty clearing house (CCP) margins for cleared contracts. Lastly, we find evidence that when a transaction helps netting positions with the CCP and hence lower margins, the likelihood of clearing is higher.

Using unique data from a leading peer-to-peer (P2P) lending platform, we investigate the link between past investment performance and choice of auto-investing tool. Our results suggest that investors who experience fewer defaults in the manual mode are more inclined to switch to automatic investment. Several factors account for this relationship, including investor inattention, decision speed, investment delegation, and experience. Regarding the latter, our results suggest that experienced investors are more likely to continue self-directed bidding, even if they have faced defaults in manual investments in the past. These investors may attribute their previous mistakes to their own actions rather than the limitations of the self-directed bids. Our results are robust to alternative specifications.

We develop a dynamic framework to study banks’ incentives to take excessive risk in an emerging economy, where bank default probability and excess bank risk-taking are modeled endogenously. We calibrate it for the 1998 Peruvian economy. We find that the infinite-period feature amplifies banks’ incentives to take excessive risk. When we simulate the sudden stop that hit Peru in 1998, the model accurately predicts the substantial short-term rise in the non-performing loans ratio through the rise of the bank default probability.

We analyze how capital requirements from environmental risk exposure affect bank lending to the corporate sector, and how these effects transmit to real economic activity and to greenhouse gas emissions. To do so, we exploit the introduction of a policy in Brazil that required banks to incorporate environmental risks in their capital assessments. Using comprehensive credit data, we find that the policy induces large banks to reallocate their lending away from exposed sectors. The credit contraction has no substantial impact on the real activity and greenhouse gas emissions of these sectors, as smaller banks expand their lending afterwards. However, the policy triggers a moderate labor reallocation from small firms (i.e., those with higher costs of switching lenders) and into large firms within environmentally exposed sectors.

We show that financial crises are preceded by changes in specific types of narrative information contained in newspaper article titles. Our novel international dataset and the resulting empirical evidence are gathered by integrating information from a large panel of economic news articles in global newspapers between the years 1870 and 2016 with conventional macroeconomic and financial indicators. We find that the predictive information of newspaper article titles that signals coming crisis episodes is substantial over and above the macroeconomic and financial indicators. Feature contribution analysis and crisis case studies reveal that the new indicators capture more detailed, but still generalizable information on the buildup of crises.

This paper explores the relationship between environmental, social and governance (ESG) information and systemic risk, an increasingly important issue for both regulators and investors. While ESG ratings are widely used to assess a company’s non-financial performance, the impact of these factors on financial stability and systemic risk is still under debate. By extending the Forecast Error Variance Decomposition (FEVD) method with a double regularization on both the underlying vector autoregressive (VAR) parameters and the covariance matrix of the VAR residuals, we are able to address the curse of dimensionality within each estimation. This allows us to examine how vulnerable a company is and how much systemic impact a company has given its specific ESG. Looking at a larger sample of European stocks over the period 2007-2022, we empirically show that both the best and worst ESG performers have the largest impact on the financial system in normal times. However, during a crisis, companies with the best ESG ratings generate significant spillovers throughout the system. These findings highlight the importance of incorporating ESG factors into systemic risk assessments and monitoring companies’ ESG performance to ensure financial stability. Policymakers can benefit from this research by supporting investment in high ESG companies to mitigate relevant spillovers during stressed market conditions, when such companies are more interconnected.