High-yield Funds Research Articles

Modeling Distress in US High Yield Mutual Funds Before and During the Covid-19 Pandemic

Abstract Research background: In March 2020, when the US financial markets were in the grip of the COVID-19 crisis, the Fed instituted various policies and programs to alleviate stress in financial markets. One such program involved the Fed purchase of securities and ETFs in certain market segments, including high yield bonds. This buying action inspired investors to join the Fed (or front-run the Fed) in the high yield bond market, resulting in the tightening of spreads in that market to historically tight levels. Purpose: In this research we investigate whether investors could have seen any signs of higher liquidity risk in US high yield mutual funds since the beginning of COVID-19 pandemic and avoid it. Theoretically, funds with heightened liquidity risk should have higher historical returns (adjusted for interest rate risk and credit risk) because borne risk requires return as compensation. But because of the unusual market conditions during the COVID-19 pandemic investors could look inside funds (to see what bonds the funds owned) and then avoid funds with holdings known to be less liquid. Research methodology: The study is based on data on US mutual funds from the Morningstar Direct database. The authors made a serial correlation model with an AR(1) process and the lagged effects model vs CAPM model to measure two proxies for liquidity risk for each US high yield mutual fund in our fund universe, in order to identify those funds at particular risk for portfolio illiquidity since the beginning of the COVID-19 pandemic. Results: it is found that the proposed measures may be an effective tool for selecting high yield funds against liquidity risk. Therefore, they should be considered by investors or analysts as a practical tool to identify funds that might be illiquid. Novelty: The study focuses on the liquidity risk in US high yield bond mutual funds before and after the outbreak of the COVID-19 pandemic, which was a crisis situation with implications for liquidity risk. The methods used and results achieved may be a basis for studies of other types of funds and markets outside the USA.

Financial Early Warning Model Based Short Selling Product Design - Pharmaceutical Industry

Due to the continued impact of the global new crown epidemic, the current investment in the pharmaceutical track is exceptionally hot, and the demand for high-yield fund products in the pharmaceutical industry has arisen, while its accompanying risks have further increased. In this paper, 18 financial indicators were initially selected from five dimensions, and the Mann-Whitney test was used to eliminate variables that were not significantly different between ST companies and financially normal companies. 7 variables were finally identified for inclusion in the model by combining the principles of indicator selection and stepwise regression method, and finally the financial warning model based on annual reports was obtained through logistic regression and its effect was back-tested. The P-values of all companies are calculated using the financial warning model, after which six companies in the top 10 and bottom 10 of the P-values that can finance and finance securities are selected and their returns during the investment period are t-tested, and it is found that significant positive returns can be obtained during the holding period by short selling stocks, and relevant financial products can be designed accordingly.

Does portfolio concentration affect performance? Evidence from corporate bond mutual funds

This paper examines the relation between portfolio concentration and investment performance in corporate bond mutual funds. Using detailed holdings data, we construct portfolio concentration measures at the firm, industry, and credit rating levels. We find that portfolio concentration is significantly positively related to expected abnormal returns of corporate bond funds, and this relation is mainly driven by investment-grade funds. High-yield funds, however, do not exhibit such a relation, possibly due to the erosion of the value of portfolio concentration by liquidity costs. In support of this conjecture, we document that the concentration-performance relation is less pronounced among funds with higher sensitivities to market-wide illiquidity innovations and during periods of bond market illiquidity shocks and fund-level net money outflows. Finally, we show that more concentrated funds demonstrate stronger performance persistence, and investors appear to consider portfolio concentration in making investment decisions.

Does Portfolio Concentration Affect Performance? Evidence from Corporate Bond Mutual Funds

This paper examines the relation between portfolio concentration and investment performance in corporate bond mutual funds. Using detailed holdings data, we construct portfolio concentration measures at the firm, industry, and credit rating levels. We find that portfolio concentration is significantly positively related to expected abnormal returns of corporate bond funds, and this relation is mainly driven by investment-grade funds. High-yield funds, however, do not exhibit such a relation, possibly due to the erosion of the value of portofio concentration by liquidity costs. In support of this conjecture, we document that the concentration-performance relation is less pronounced among funds with higher sensitivities to market-wide illiquidity innovations and during periods of bond market illiquidity shocks and fund-level net money outflows. Finally, we show that more concentrated funds demonstrate stronger performance persistence, and investors appear to consider portfolio concentration in making investment decisions.

Robust performance measures for high yield bond funds

Abstract We examine performance measures for high yield bond mutual funds, which are a considerable percentage of taxable bond investments, but have not been widely studied. High yield funds exhibit persistence in their monthly returns, so we calculate Sharpe ratios using methods that incorporate the serial correlation of returns. We find that high yield fund rankings using raw returns and conventionally calculated Sharpe ratios are different from those using trailing standard deviations and robust standard errors. High yield fund rankings based on robust Sharpe ratios also differ from those computed using multi-index Jensen's alphas and information ratios. When measured by risk-adjusted returns, high yield bond fund managers do not add much value.

Adverse Information and Allocations: Evidence from the Korean Modified Bookbuilding IPOs

The analyses of the comprehensive IPO bookbuilding information of the Korean KOSDAQ market from 2000 to 2002 show that adverse information from institutional investors drives down the offering price, creating close to a 100 percent initial return on average. Policy makers in the Korean IPO market regulate both price updating during bookbuilding process and allocation to institutional and retail investors. The primary findings of this research include: i) Institutional investors, particularly high yield fund investors, provide adverse information primarily in hot issues, ii) More shares are allocated to institutional investors when strong pre-market demands are revealed, iii) Investment bankers decide the offering price far lower than the market clearing price when institutional investors show strong interests, and iv) Underpricing from the market clearing price is severe, however, the aftermarket initial return is not particularly high when more shares are allocated to institutional investors. The overall results support the adverse information view. Institutional investors game the market by taking advantage of regulatory constraints on price update and allocation and underwriters mandatory stabilization on the post IPO markets.

High-Yield Bond Mutual Funds: Performance, January Effects, and Other Surprises

Here is insight into the investment performance of low-grade light-yield corporate bond mutual funds during 1980 - 1995, which includes the period the high-yield market was recovering from weak performance. There is evidence that low-grade bond mutual funds have both superior and inferior managers and that their portfolio systematic risk is considerably below a commonly used high-yield index.. Total risk for the average high-yield fund exceeds the total risk of the high-yield index, and is not compensated by extra returns. The results also indicate that a January effect holds for high-yield bond funds as well as low-grade bonds, which appears to extend as well to a first six months effect.

High-Yield Bond Mutual Funds

Here is insight into the investment performance of low-grade light-yield corporate bond mutual funds during 1980 - 1995, which includes the period the high-yield market was recovering from weak performance. There is evidence that low-grade bond mutual funds have both superior and inferior managers and that their portfolio systematic risk is considerably below a commonly used high-yield index.. Total risk for the average high-yield fund exceeds the total risk of the high-yield index, and is not compensated by extra returns. The results also indicate that a January effect holds for high-yield bond funds as well as low-grade bonds, which appears to extend as well to a first six months effect.