The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia , the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield – the gilt-equity yield ratio – has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns.     

The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia , the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield – the gilt-equity yield ratio – has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns.     

Capital Asset Pricing Model and Stochastic Volatility: A Case Study of India

The existing literature demonstrates that under a general equilibrium model, the performance of the Capital Asset Pricing Model (CAPM) can be improved significantly by using conditional consumption and market return volatilities as factors. This article tests the validity of these factors explaining stock return differences using a less developed country (India) as a case study. While the earlier studies used panel data to test CAPM, we use portfolios sorted by size and book-to-market equity (BE/ME) ratio. We found that conditional volatility has a limited effect on firms with large capitalization but a significant impact on small-growth and small-value firms.     

Assessing the Economic Significance of Return Predictability: A Research Note

The predictability of stock returns is often assessed using classical statistical significance from predictive regressions. Statistical inference, however, can belie the economic importance with which investors regard various predictors. This paper examines the influence that predictors have on an investor's optimal portfolio allocations. The results show that return predictability is sufficient to induce horizon effects in optimal allocations. After incorporating estimation risk, however, little evidence of predictability remains. We also assess the relative importance of three predictor variables. While dividend yield is the most important predictor, optimal allocations are also sensitive to the term spread and the relative bill rate.     

Consumption growth predictability and asset prices

We derive and test a consumption-based intertemporal asset pricing model in which an asset earns a risk premium if it performs poorly when expected future consumption growth deteriorates. The predictability of consumption growth combined with the recursive preference delivers news about future consumption growth an additional risk factor, in addition to news about current consumption growth. We model the consumption growth dynamics using a vector autoregressive (VAR) structure with a set of instrumental variables commonly used for forecasting future economic growth. Our VAR estimation provides strong empirical support for future consumption growth predictability. The cross-sectional test shows that the model explains reasonably well the dispersion in average excess returns of 25 portfolios sorted on size and book-to-market, as well as 25 portfolios sorted on size and long-term return reversal. Growth stocks and long-term winners underperform value stocks and long-term losers, respectively, because growth stocks and long-term winners hedge adverse changes in the future consumption growth opportunities.     

Short‐Horizon Return Predictability in International Equity Markets

This study measures the degree of short‐horizon return predictability of 50 international equity markets and examines how its variation is related to the indicators of equity market development. Two multiple‐horizon variance ratio tests are employed to measure the degree of return predictability. We find evidence that return predictability is negatively correlated with publicly available indicators of equity market development. Our cross‐sectional regression analysis shows that the per capita gross domestic product, market turnover, investor protection, and absence of short‐selling restrictions are correlated with cross‐market variations in return predictability.     

Foreign Shocks on Chilean Financial Markets: Spillovers and Comovements Between Bond and Equity Markets

Abstract:

The domestic impact of external shocks will depend on the degree of coupling of domestic assets to foreign markets, but also on the spillovers among assets. The covariance between different types of assets could be affected by new information. Changes in the covariance, for example, could come from a stronger rebalancing between stocks and bonds. Therefore, we will analyze four different assets-government bonds, corporate bonds, money market instruments, and equities-and study the conditional correlation between them. We find that the corporate bond market tends to increase coupling in turbulent times, while the money market decreases coupling. We propose to test international spillovers taking into account a methodology for estimating the conditional mean, variance, and covariance on domestic bond and equity markets, while considering that shocks may have asymmetric effects depending on whether the news is good or bad.     

The Variation of Economic Risk Premiums in Real Estate Returns

We examine the predictable components of returns on stocks, bonds, and real estate investment trusts (REITs). We employ a multiple-beta asset pricing model and find that there are varying degrees of predictability among stocks, bonds, and REITs. Furthermore, we find that most of the predictability of returns is associated with the economic variables employed in the asset pricing model. The stock market risk premium is highly important in capturing the predictable variation in stock portfolios, and the bond market risk premiums (term and risk structure of interest rates) are important in capturing the predictable variation in bond portfolios. For REITs, however, both the stock and bond market risk premiums capture the predictable variation in returns. REITs have comparable return predictability to stock portfolios. We conclude that there is an important economic risk premium for REITs that are not captured by traditional multiple-beta asset pricing models.     

Equity Returns and Business Cycles in Small Open Economies

This is the first paper in the dynamic stochastic general equilibrium literature to match key business cycle moments and long‐run equity returns in a small open economy with production. These results are achieved by introducing four modifications to a standard real business cycle model: (i) borrowing and lending costs are imposed to increase the volatility of the marginal rate of substitution over time, (ii) capital adjustment costs are assumed to make equity returns more volatile, (iii) GHH preferences are employed to smooth consumption, and (iv) a working capital constraint to generate countercyclical trade balances. Our results are based on data from Argentina, Brazil, and Chile.     

The Asset Pricing Palette: Cash Flows, Returns and Trading Behavior

Asset pricing is the topic of the 2001 Eastern Finance Association Symposium and the five papers selected for this collection, which are summarized below, span a broad range of subjects that fall under the umbrella of the determinants of market prices. For example, the Schwartz and Moon article that introduces the symposium uses real options methodology to value firms whose cash flows are subject to multiple sources of uncertainty while the Luders and Peisl and Mixon analytical models that close the selections incorporate dual stochastic processes to derive relationships between information flow, trading volume and price volatility that are consistent with empirical evidence. In between, Mishra and O'Brien present new evidence on the important of index and factor selection when estimating the required return on equity and Spahr and Schwebach revisit the issue of time diversification by reintroducing a statistical construct from earlier times. Each of the works included here makes an important contribution to our understanding of the asset pricing process in a distinct area and opens new doors onto avenues for future research.