|
on Financial Markets |
|
Issue of 2024‒04‒29
six papers chosen by |
| By: | Isil Erel; Thomas Flanagan; Michael S. Weisbach |
| Abstract: | Private debt funds are the fastest growing segment of the private capital market. We evaluate their risk-adjusted returns, applying a cash-flow based method to form a replicating portfolio that mimics their risk profiles. Using both equity and debt benchmarks to measure risk, a typical private debt fund produces an insignificant abnormal return to its investors. However, gross-of-fee abnormal returns are positive, and using only debt benchmarks also leads to positive abnormal returns as funds contain equity risks. The rates at which private debt funds lend appear to be high enough to offset the funds’ fees and risks, but not high enough to exceed both their fees and investors' risk-adjusted rates of return. |
| JEL: | G12 G21 G23 |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32278&r=fmk |
| By: | Nina Boyarchenko; Leonardo Elias |
| Abstract: | Do global credit conditions affect local credit and business cycles? Using a large cross-section of equity and corporate bond market returns around the world, we construct a novel global credit factor and a global risk factor that jointly price the international equity and bond cross-section. We uncover a global credit cycle in risky asset returns, which is distinct from the global risk cycle. We document that the global credit cycle in asset returns translates into a global credit cycle in credit quantities, with a tightening in global credit conditions predicting extreme capital flow episodes and declines in the stock of country-level private debt. Furthermore, global credit conditions predict the mean and left tail of real GDP growth outcomes at the country level. Thus, the global pricing of corporate credit is a fundamental factor in driving local credit conditions and real outcomes. |
| Keywords: | global financial cycle; corporate bond returns; return predictability; international capital flows; credit and real activity outcomes |
| JEL: | F30 F44 G15 G12 |
| Date: | 2024–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednsr:98024&r=fmk |
| By: | Lukas Schmid (Marshall School of Business, University of Southern California; Centre for Economic Policy Research (CEPR)); Vytautas Valaitis (University of Surrey); Alessandro T. Villa (Federal Reserve Bank of Chicago) |
| Abstract: | Can governments use Treasury Inflation-Protected Securities (TIPS) to tame inflation? We propose a novel framework of optimal debt management with sticky prices and a government issuing nominal and real state-uncontingent bonds. Nominal debt can be monetized giving ex-ante flexibility, whereas real bonds are cheaper but constitute a commitment ex-post. Under Full Commitment, the government chooses a leveraged and volatile portfolio of nominal liabilities and real assets to use inflation to smooth taxes. With No Commitment, it reduces borrowing costs ex-ante using a stable real debt share strategically to prevent future governments from monetizing debt ex-post. Such policies rationalize the small and persistent real debt share in U.S. data, with higher TIPS shares effectively curbing inflation. Reducing future governments’ temptation to monetize debt renders debt and inflation endogenously sticky. |
| Keywords: | Optimal Fiscal Policy, Monetary Policy, Debt Management, TIPS, Incomplete Markets, Inflation, Limited Commitment, Time-consistency, Markov-perfect Equilibria |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:cfm:wpaper:2413&r=fmk |
| By: | Jun Xu |
| Abstract: | The burgeoning integration of Artificial Intelligence (AI) into Environmental, Social, and Governance (ESG) initiatives within the financial sector represents a paradigm shift towards more sus-tainable and equitable financial practices. This paper surveys the industrial landscape to delineate the necessity and impact of AI in bolstering ESG frameworks. With the advent of stringent regulatory requirements and heightened stakeholder awareness, financial institutions (FIs) are increasingly compelled to adopt ESG criteria. AI emerges as a pivotal tool in navigating the complex in-terplay of financial activities and sustainability goals. Our survey categorizes AI applications across three main pillars of ESG, illustrating how AI enhances analytical capabilities, risk assessment, customer engagement, reporting accuracy and more. Further, we delve into the critical con-siderations surrounding the use of data and the development of models, underscoring the importance of data quality, privacy, and model robustness. The paper also addresses the imperative of responsible and sustainable AI, emphasizing the ethical dimensions of AI deployment in ESG-related banking processes. Conclusively, our findings suggest that while AI offers transformative potential for ESG in banking, it also poses significant challenges that necessitate careful consideration. The final part of the paper synthesizes the survey's insights, proposing a forward-looking stance on the adoption of AI in ESG practices. We conclude with recommendations with a reference architecture for future research and development, advocating for a balanced approach that leverages AI's strengths while mitigating its risks within the ESG domain. |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.05541&r=fmk |
| By: | Panteleimon Kruglov; Charles Shaw |
| Abstract: | This study explores the relationship between R&D intensity, as a measure of innovation, and financial performance among S&P 500 companies over 100 quarters from 1998 to 2023, including multiple crisis periods. It challenges the conventional wisdom that larger companies are more prone to innovate, using a comprehensive dataset across various industries. The analysis reveals diverse associations between innovation and key financial indicators such as firm size, assets, EBITDA, and tangibility. Our findings underscore the importance of innovation in enhancing firm competitiveness and market positioning, highlighting the effectiveness of countercyclical innovation policies. This research contributes to the debate on the role of R&D investments in driving firm value, offering new insights for both academic and policy discussions. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.10982&r=fmk |
| By: | Matteo Foglia (Department of Economics and Finance, University of Bari ``Aldo Moro", Italy); Vasilios Plakandaras (Department of Economics, Democritus University of Thrace, Komotini, Greece); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Qiang Ji (Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China) |
| Abstract: | In this paper, we examine the potential spillovers between returns, volatility, skewness and kurtosis of developed stock markets under the lenses of rare disaster events, proxied by climate risks. The goal of this study is to depict the transmission mechanism of rare disaster events involving moments within and between advanced equity markets. In doing so, we provide estimates of the aforementioned moments based on model-implied distributions of stock returns, derived from the quantile autoregressive distributed lag mixed-frequency data sampling (QADL-MIDAS) method, using a long span of data. Our research framework includes the G7 and Switzerland over the period December 1924 to February 2023, where we apply a multilayer approach to spillovers, adding the effect of climate risk to our analysis. Our empirical findings are as follows: firstly, spillovers are significant within- and across stock markets for each of the four moments. Secondly, based on a nonparametric causality-in-quantiles approach, changes in temperature anomalies, have the predictive power to shape the entire conditional distribution of various metrics of spillover involving single- and multiple-layers of returns and risks layers. In sum, we show that the multi-layer approach offers a comprehensive and nuanced view of how stock market-related information is transmitted across the stock markets of advanced economies, carrying implications for investors and policymakers. |
| Keywords: | Returns and risk spillovers, advanced equity markets, multi-layer spillover approach, nonparametric causality-in-quantiles method, climate risks, predictability |
| JEL: | C22 C32 C53 G15 Q54 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:202415&r=fmk |