Frank K. Reilly

Analysis of the Interest Rate Sensitivity of Common Stocks

The association between interest rate changes and stock returns has long been of interest to investors, all the more so recently as investors and the financial and popular press have zeroed in on the effect of Federal Reserve actions on interest rates. The interest rate sensitivity of common stocks can be measured using an alternative specification of duration, empirical duration, a measure that has become accepted by fixed-income analysts and portfolio managers. Analysis of the interest rate sensitivity of the aggregate stock market considers alternative economic sectors and many industries and stock indexes that reflect different sizes and investment styles. Five important results are documented: 1) dramatic changes over time in the empirical duration of common stocks; 2) substantial differences in the total-period empirical duration for different economic sectors and different industries; 3) a significant negative relation between market risk and interest rate risk for different industries; 4) significantly different patterns of empirical duration over time for different sectors and industries; and 5) differences in interest rate sensitivity for various economic sectors, industries, and investment styles that are generally consistent with economic expectations.

Bond Market Volatility Compared to Stock Market Volatility

The high volatility of rates of returns on bonds during the 1980s received a great deal of attention because it is readily acknowledged that bond return volatility is critical to the analysis and management of bonds. Yet there has been no detailed analysis of bond market volatility for the pre–1980 period that would allow the experience during the 1980s and the 1990s to be put into perspective. The authors analyze the changing volatility of the government bond market over the past 50 years and examine how these changes compare to the well–documented volatility changes for the stock market. A comparison of Treasury bond market volatility to stock market volatility indicates that the volatility for these two markets has differed dramatically over time. The difference in volatility is confirmed by an analysis of the systematic risk of bonds versus stocks and the moving correlations between bonds and stock over time. In both instances, the pattern indicates a very cyclical series with wide ranges, but also a positive trend. An analysis of the time series properties of bond and stock volatility likewise indicates significant differences.

The Benchmark Error Problem with Global Capital Markets

the University of Notre Dame at the time h s article was written. D uring the late 1970s and early 1980s, Richard Roll in several articles voiced concern with the testing of the Capital Asset Pricing Model (CAPM), as well as with use of the model to evaluate investment performance (Roll [1977, 1978, 1980, 19811). Roll referred to t h s latter problem as a benchmark error, because the practice has been to compare the performance of a portfolio manager to the performance of an unmanaged portfolio of equal risk. The benchmark typically has been a security market index adjusted for risk, where the risk measure is the one implied by the CAPM (i.e., beta). Roll shows that if the benchmark employed in this evaluation is mistakenly specified, you cannot measure the performance of portfolio managers properly. An inappropriate proxy for the market portfolio (benchmark) can have two effects. First, the systematic risk measures (beta) computed for individual assets and for alternative portfolios will be wrong, because the betas are derived using an inappropriate proxy for the market portfolio. Second, the security market line (SML) derived to measure the relative risk-adjusted performance of alternative portfolios d be misspecitied because the SML. is then the line h m the risk-free return through an improperly specified proxy for the market portfolio. Roll shows that, assuming the proxy used to represent the market portfolio of risky assets is not as mean-variance efficient as the “true” market portfolio, it is possible that the performance of a portfolio using the inappropriate SML would be considered superior,

The Impact of Inflation on Roe, Growth and Stock Prices

Using the constant growth dividend discount model (DDM), it can be shown that the critical factor which determines whether common stocks will be able to be an inflation hedge is the growth rate of dividends. In turn, the growth of dividends is mainly impacted by the aggregate return on equity (ROE). Using the DuPont formula it is clear that the main variable that drives the aggregate ROE is an inflationary environment is the profit margin. Following from this background, this article updates and extends an earlier analysis that involves an analysis of ROE and its components for the 40-year period 1956-1995. The analysis demonstrates that the aggregate ROE is currently at about the same level as in the 1960s, but the components have changes - i.e., there has been a decline in total asset turnover and profit margin, but a significant increase in financial leverage that has compensated for the declines in turnover and profit margin. It is further shown that there have been periods of high and low inflation since 1956 and the negative impact of inflation on the implied growth rate is confirmed, which helps explain why investigators find consistent empirical results that common stock are poor inflation hedges.

Unique Risk-Return Characteristics of High-Yield Bonds

As the high-yield (HY) bond market has grown in size and significance, it is important to examine its place in the total capital market and to develop a better understanding of its composition and characteristics. This article considers differences between the investment-grade and the HY bond market, unique characteristics within the HY bond market, and changes in the correlations between asset class sectors and their volatilities over time. There is strong evidence that HY bonds have a very significant equity component that makes them a different asset class from investment-grade bonds. Within the HY bond universe, BB bonds are heavily affected by market interest rates with some equity effect; B-rated bonds have more equity-like characteristics than an interest rate effect; and CCC-rated bonds have virtually no market interest rate effect. There is also clear evidence of changes in correlations among asset classes over time. There have been significant changes in volatility over time, with striking changes duing the 1990–1991 recession, the 1998 Russian credit crisis, and the year 2000 credit crunch. The authors discuss the significant implications of these results for bond analysts and portfolio managers.

Alternative Small-Cap Stock Benchmarks

With continuing interest in the small–cap stock anomaly and in the size–related style of investing, several financial services firms have created size–related stock indexes intended to measure the risk–return results for these stocks. The authors compare the alternative benchmarks, and provide updated risk–return results for the small–cap sector. They note some differences among the small–cap stock benchmarks, but mainly show there are strong similarities among them. The updated risk–adjusted performance results indicate that small–cap stocks lag other asset classes, and there are major differences in interest rate sensitivity. Finally, there have been significant changes in the correlations and risk measures over time; notable are weaker trends in the correlations with large–cap stocks and in the systematic risk (beta) of the small–cap stocks.

Analysis of Risk-Adjusted Performance of Global Market Assets

The broad set of 38 global capital market assets examined here includes U.S. and international stocks and bonds, real estate, commodities, and a composite index of global stocks and bonds. Relationships between returns and risk reported are consistent with theoretical expectations. The risk-adjusted performance measures indicate a wide range of performance for alternative assets. Rankings of alternative assets, though, depend on the specific risk-adjusted performance measure used.

How institutional trading reduces market volatility

M any observers believe that there should be a strong positive relationship between institutional trading and stock price volatility. Since institutions trade in large blocks, they reason that such a pattern of trading causes a decline in the liquidity of securities markets and, hence, an increase in stock price volatility. A prior study by one of the authors [17] covered the time period 1964-1974, considered three measures of stock price volatility, and analyzed total transactions for all institutions combined. The results clearly did not support the general expectation regarding the positive relationship. Because of the interest in the relationship and the importance of the results to public policy decisions, this study examines the relationship between institutional trading and stock price volatility measures and more detailed institutional transactions data. Moreover, additional observations are now available through 1976. The initial section briefly discusses the prior study on this topic. The following section describes the new institutional trading variables and additional measures of stock price volatility. This is followed by a presentation and discussion of the results. The concluding section summarizes the results and discusses the implications of the results for those concerned with the effect of institutional trading on the functioning of the capital markets.

Institutions on Trial: Not Guilty!

T he substantial increase in equity trading by large institutional investors and an increase in the proportion of total trading done by the institutions [see footnotes 1,2,5,6,8,9,18,26,30] have disturbed many observers who feel that trading by institutions leads to increases in the variability of stock prices. They believe that this happens either because institutions trade large blocks of stock or because institutions tend to trade together [l, 4, 12, 14, 16, 17, 231. Unfortunately, there is very little direct empirical evidence on this important question of the relationship between trading by institutions and stock price volatility. Moreover, the prevailing ad hoc belief on Wall Street is that there is a positive relationship between institutional trading and aggregate stock price volatility. This belief prevails even though severalstudies on the specific effect of block trades on the price of the individual stocks have generally indicated there is not a significant liquidity cost involved in block trades [7, 10, 19, 241. Further, another study indicated that institutions do not trade together [ll]. Apparently, there is a very real divergence between the prevailing belief on Wall Street and indirect empirical evidence. Because of such a divergence, this paper is concerned with a direct analysis of the relationship between institutional transactions and stock price volatility during the past twelve years. Although further analysis is hindered by the lack of data, this empirical examination of the relationship for the recent period provides some insights into the influence of institutional trading on stock price volatility.

Estimating the Interest Rate Sensitivity of Mixed-Asset Portfolios

The purpose of this article is to show how the different measures of duration can be employed to estimate the interest rate sensitivity of a mixed-asset portfolio. The authors start by reviewing alternative measures of duration, indicating the appropriate measures to use for different asset classes. They then discuss the calculation of equity duration, provide examples of equity durations for several widely traded equity securities, and then illustrate a possible computation of duration for a mixed asset portfolio. Having discussed the limitations of this methodology, they observe in the conclusion that the relationship between changes in interest rates and financial asset returns has been of significant interest to investment professionals for many years.