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This paper aims to examine the connectedness between green and conventional assets, particularly during the period of economic downturn. Specifically, we examine quantile-based time-varying connectedness between the green bond market and other financial assets using quantile vector autoregression (QVAR) from 9 March 2018 to 10 March 2021. We use daily prices of S&P U.S. Treasury Bond Index, S&P US Aggregate Bond Index, S&P US Treasury Bond Current 10Y Index, S&P 500 Bond Index, S&P 500 Financials index, S&P 500 Energy Bond Index and S&P 500, giving a total of 784 observations, and using Composite Index as a representative of conventional assets classes and S&P Green Bond Index to denote the green bond market. Results shows the connectedness between green bonds and the conventional asset classes intensified during the outbreak of the Coronavirus pandemic (COVID-19) as investors shifted their investment towards fixed income assets due to the plunge in the prices of stocks and commodities. The results also shows that green bonds are strongly connected with treasury bonds, aggregate bonds and bond index, as they share similarities with respect to issuance, risk and governance. Connectedness is weak in the case of composite index and energy bond index, as their prices do not have substantial influence on the green bond market. The study highlights the hedging and diversification benefits of green bonds. We have several implications for portfolio managers, policy makers and researchers. [ABSTRACT FROM AUTHOR]

This paper tests for seasonal patterns in corporate bond returns using the Dow Jones Composite Bond Average. Each seasonal pattern documented for equities is investigated. For the period 1963-1986, corporate bond returns exhibit January, turn-of-the-year, and week-of-the-month effects, but no significant day-of-the-week or turn-of-the-month effects. In contrast, for the S&P 500 stock index, the turn-of-the-month and day-of-the-week effects are highly significant, but the week-of-the-month effect is less significant, and the January and turn-of-the-year effects are insignificant. The behavior of an equity index constructed using companies in the bond index is similar to that of the S&P, except the turn-of-the-year effect is significant. [ABSTRACT FROM AUTHOR]

Grammatical Evolution (GE) is a novel data driven, model induction tool, inspired by the biological geneto-protein mapping process. This study provides an introduction to GE, and demonstrates the methodology by applying it to model the corporate bond-issuer credit rating process, using information drawn from the financial statements of bond-issuing firms. Financial data and the associated Standard & Poor's issuer-credit ratings of 791 US firms, drawn from the year 1999/2000 are used to train and test the model. The best developed model was found to be able to discriminate in-sample (out-of-sample) between investment-grade and junk bond ratings with an average accuracy of 87.59 (84.92)% across a five-fold cross validation. [ABSTRACT FROM AUTHOR]

This paper examines the risks and returns of long-term low-grade bonds for the period 1977-1989. We find: (1) low-grade bonds realized higher returns than higher-grade bonds and lower returns than common stocks, and low-grade bonds exhibited less volatility than higher-grade bonds due to their call features and high coupons; (2) there is no relation between the age of low-grade bonds and their realized returns; cyclical factors explain much of the observed relation between default rates and bond age; and (3) low-grade bonds behave like both bonds and stocks. Despite this complexity there is no evidence that low-grade bonds are systematically over- or under-priced. [ABSTRACT FROM AUTHOR]

In a context characterized by an increasing integration among financial markets, we aim to analyze whether the ECB unconventional monetary policy shields the Eurozone stock markets against spillovers of volatility from the US stock market. We augment the Markov switching Asymmetric Multiplicative Error Model (MS-AMEM) with exogenous variables to measure transmissions of volatility from the S&P500 index, on the one hand, and the announcement and implementation effects of unconventional policy, on the other hand. By estimating our model, the MS-AMEMX, on a sample of daily observations of the realized volatility of four Eurozone stock indices (CAC40, DAX30, FTSEMIB and IBEX35), we find how the increase in volatility brought about by volatility spillovers was mitigated by the implementation of unconventional policy, with a higher benefit for high-debt countries' stock indices (FTSEMIB and IBEX35). Finally, the out-of-sample analysis certifies the suitability of our proxies also for forecasting purposes. [ABSTRACT FROM AUTHOR]

This article presents a report of the American Economic Association's (AEA) budget and finance committee on the portfolio allocations of the AEA. The committee decided in early May 2004 to modify the portfolio benchmarks slightly, reducing the Standard & Poor's 500 index allocation from 50 to 45 percent, increasing the international equities allocation from 5 to 10 percent, decreasing the mid-cap allocation from 10 to 5 percent, increasing the small-cap allocation from 0 to 5 percent, and diversifying the investment-grade bond portfolio by dividing it into one-third long-term corporate bonds, and two-thirds total bond index. The Committee divided the international allocation equally between a European equities mutual fund and a Pacific equities mutual fund.

The consideration of social and environmental factors in companies' supply chain is a prevalent research topic because stakeholders are now inquisitive about the social and environmental impacts of companies' suppliers. Using a sample of S&P 500 firms, we find that board gender composition and board independence are positively associated with sustainable supply chain responsibility (SSCR). We also identify three channels (CEO duality, sustainability committee and sensitive industries) through which board gender composition and board independence affect SSCR, where board gender composition consistently explains SSCR, but the effect of board independence is less pronounced in firms with CEO duality and firms with a sustainability committee. Finally, we explore the reason for the less‐pronounced findings for board independence in our subsample analyses and find that, compared with independent female directors who continue to display significant associations with SSCR, independent male directors do not engender SSCR across the three subsample tests. [ABSTRACT FROM AUTHOR]

We find that repeated borrowing from the same lender translates into a 10–17 bps lowering of loan spreads and that relationships are especially valuable when borrower transparency is low. These results hold using multiple approaches (propensity score matching, instrumental variables, and treatment effects model) that control for the endogeneity of relationships. We also provide a demarcation line between relationship and transactional lending. Spreads charged for relationship loans and nonrelationship loans are statistically identical if the borrower is in the largest 30% by asset size; has public rated debt; or is part of the S&P 500 index. Past relationships reduce collateral requirements and are also associated with obtaining larger loans. Our results imply that, even for firms that have multiple sources of outside financing, borrowing from a prior lender obtains better loan terms. [ABSTRACT FROM PUBLISHER]

Using data on the investments a large number of individual investors made through a discount broker from 1991 to 1996, we find that households exhibit a strong preference for local investments. We test whether this locality bias stems from information or from simple familiarity. The average household generates an additional annualized return of 3.2% from its local holdings relative to its nonlocal holdings, suggesting that local investors can exploit local knowledge. Excess returns to investing locally are even larger among stocks not in the S&P 500 index (firms for which information asymmetries between local and nonlocal investors may be largest). [ABSTRACT FROM AUTHOR]

Several recent writings have raised questions concerning the effectiveness of commonly used analytical measures and techniques which have their basis in Modern Portfolio Theory. Questions have been raised about the use of beta in the interpretation of risk adjusted equity performance and about the usefulness of the capital asset pricing model (CAPM) as a tool for measuring and interpreting investment performance. This paper restricts itself to questions concerning beta and CAPM as they relate to performance measurement. In the process of this examination it discusses some basic principles of performance measurement as they relate to judgments of investment management skill and ability. It has been shown that simple applications of beta used in adjusting equity performance for risk can possibly produce misleading or incorrect interpretations of risk adjusted performance. Errors have been shown to be related to the market index used as a basis for the determination of beta. These findings are independent of the validity of CAPM, but the line of reasoning which leads to these conclusions is not totally antithetical to the derivation of CAPM. This paper has three major sections: 1. The capital asset pricing model is assumed to be valid, and a broader index of capital assets is constructed. This index is “better” in the sense that it includes many more assets than the S&P 500 and hence is more complete. 2. The better index is then used to “game” performance measurement using current investment technology and the Standard & Poor's 500. 3. Some conclusions are drawn as to the effectiveness of gaming and the ways in which performance measurement numbers should be interpreted in general. General issues are discussed in the text. A parallel, more detailed and more technical argument is presented in the appendix. [ABSTRACT FROM AUTHOR]

Bond rating agencies, such as Moody's and Standard and Poor's, attempt to classify bonds according to their ex ante probability and magnitude of financial distress (e.g., incidence of default or loss of market value due to deterioration of the firm's prospects). The importance of these agencies' ratings is demonstrated in many cases where such ratings have a significant effect on the offering yield of the bond. Such ratings are also often used by institutional portfolio managers as a guideline to reflect the level of bond risk. Increasingly, researchers are using financial information published by the firm which pertains to the bond issue to predict bond rating via statistical techniques. Unfortunately, a common characteristic of all these studies is that each has attempted to predict the agencies' ratings. Each has perceived the agencies' ratings as some sort of standard and has attempted to compare its model's prediction with the agencies' ratings which are also predictions. Thus, the crucial question of whether the statistical models or the agencies' ratings are superior has never been answered. Furthermore, since various statistical models applied data from different samples and time periods, inference as to their difference is impossible. Before more time and effort are spent on finding new variables and applying new statistical techniques, the adequacy of all rating methods, both those of the statistical methods and those of the agencies in predicting the probability of financial distress must be determined. The purpose of this study is twofold: (1) To compare the available statistical bond rating methods on their ability to duplicate the Moody's; and (2) To compare all bond rating methods, including Moody's, on their ability to predict financial distress over different lead times. To further assess the predictive ability of these models, the performance of various methods is compared with two random selection methods. [ABSTRACT FROM AUTHOR]

Exchange-traded funds (ETFs) represent one of the most important financial innovations in decades. An ETF is an investment vehicle, with a specific architecture that typically seeks to track the performance of a specific index. The first US-listed ETF, the SPDR, was launched by State Street in January 1993 and seeks to track the S&P 500 index. It is still today the largest ETF by far, with assets of $178 billion. Following the introduction of the SPDR, new ETFs were launched tracking broad domestic and international indices, and more specialized sector, region, or country indexes. In recent years, ETFs have grown substantially in assets, diversity, and market significance, including substantial increases in assets in bond ETFs and so-called 'smart beta' funds that track certain investment strategies often used by actively traded mutual funds and hedge funds. In this paper, we begin by describing the structure and organization of exchange-traded funds, contrasting them with mutual funds, which are close relatives of exchange-traded funds, describing the differences in how ETFs operate and their potential advantages in terms of liquidity, lower expenses, tax efficiency, and transparency. We then turn to concerns over whether the rise in ETFs may raise unexpected risks for investors or greater instability in financial markets. While concerns over financial fragility are worth serious consideration, some of the common concerns are overstated, and for others, a number of rules and practices are already in place that offer a substantial margin of safety. [ABSTRACT FROM AUTHOR]

This paper observes effect of money supply on the stock market through the portfolio balance channel as a transmission mechanism of monetary policy. National flow of funds accounts, specifically assets from US households' portfolios, represent a key data source. Johansen's cointegration methodology is employed in the empirical part of the paper to analyze both short term and long term relationships among researched variables. Estimates of vector error correction model help to reliably quantify intensity of the effect. Results show money supply excercises influence on valuation of S&P 500 index with 6 months lag. The impact is also distinguishable in the long run, whereas all observed asset classes can positively influence price of S&P 500. Findings are then contextualized in the concluding part of the paper using a monetary policy framework. [ABSTRACT FROM AUTHOR]

We analyze the effect of business and financial market cycles on credit ratings using a sample of firms from the Russell 3000 index that are rated by Standard and Poor's over the period 1986-2012. We also examine investor reaction to credit rating actions in different stages of business and financial market cycles. We document that credit rating agencies are influenced by business and financial market cycles; they assign lower credit ratings during downturns of business and financial market cycles and higher ratings during upturns. Our study is the first to find strong evidence of pro-cyclicality in credit ratings using a long window. We also document stronger investor reaction to negative credit rating actions during downturns. Our results confirm theoretical predictions and inform regulators. [ABSTRACT FROM AUTHOR]

American options on the S&P 500 index futures that violate the stochastic dominance bounds of Constantinides and Perrakis (2009) from 1983 to 2006 are identified as potentially profitable trades. Call bid prices more frequently violate their upper bound than put bid prices do, while violations of the lower bounds by ask prices are infrequent. In out-of-sample tests of stochastic dominance, the writing of options that violate the upper bound increases the expected utility of any risk-averse investor holding the market and cash, net of transaction costs and bid-ask spreads. The results are economically significant and robust. [ABSTRACT FROM AUTHOR]

We represent credit spreads across ratings as a function of common unobservable factors of the Vasicek form. Using a state-space approach we estimate the factors, their process parameters, and the exposure of each observed credit spread series to each factor. We find that most of the systematic variation across credit spreads is captured by three factors. The factors are closely related to the implied volatility index (VIX), the long bond rate, and S&P500 returns, supporting the predictions of structural models of default at an aggregate level. By making no prior assumption about the determinants of yield spread dynamics, our study provides an original and independent test of theory. The results also contribute to the current debate about the role of liquidity in corporate yield spreads. While recent empirical literature shows that the level and time-variation in corporate yield spreads is driven primarily by a systematic liquidity risk factor, we find that the three most important drivers of yield spread levels relate to macroeconomic variables. This suggests that if credit spread levels do contain a large liquidity premium, the time variation of this premium is likely driven by the same factors as default risk. [ABSTRACT FROM AUTHOR]