Excess Return Volatility Research Articles

Sustainable Systematic Credit

Interest in sustainable investing has exploded in recent years, initially focused on public equity markets but now evolving into fixed income. We assess various aspects of sustainable investing for developed market corporate bond markets (both Investment Grade and High Yield). Using a representative set of sustainability measures spanning environment, societal, and governance (ESG) constructs we find (1) credit spreads are only marginally associated with ESG measures, (2) ESG measures are only marginally associated with standard return forecasting measures for corporate bonds, (3) ESG measures are not reliably associated with future credit excess returns, and (4) ESG measures are negatively associated with the future volatility of credit excess returns. While the direct investment impact of sustainability is modest, there still is considerable interest from asset owners to ensure credit allocations are sustainable. We find that it is possible to incorporate both static and dynamic exclusion screens, positive tilts toward more sustainable issuers, and economically meaningful reduction in carbon intensity, with minimal portfolio distortions. Thus, a well-implemented systematic approach has the potential to offer attractive risk-adjusted returns in a sustainable manner.

Can the variance after-effect distort stock returns?

Variance after-effect is a perceptual bias in the dynamic assessment of variance. Experimental evidence shows that perceived variance is decreased after prolonged exposure to high variance and increased after exposure to low variance. We introduce this effect in an otherwise standard financial model where information about variance is incomplete and updated sequentially. We introduce a variance after- effect adjustment factor in a bayesian learning model and derive the associated predictive variance. We show theoretically how this adjustment factor affects both average and volatility of excess returns. We construct a proxy of the adjustment factor using the sequence of dispersion of analysts earnings forecast. We provide empirical evidence using US stock data over the sample 1982 - 2019, that fluctuations in this measure are significantly and positively related to excess volatility as predicted by the model. Further confirming the model's implications, we also show how stock returns are positively impacted by the adjustment factor and construct long short strategies that generate significant positive alpha with respect to the Fama-French 5 factor model.

Term Structure of Equity and Bond Yields over Business Cycles

Recent findings on the term structure of equity and bond yields pose serious challenges to existing equilibrium asset pricing models. This paper presents a new equilibrium model of subjective expectations to explain the joint historical dynamics of equity and bond yields (and their yield spreads). Equity/bond yields movements are mainly driven by subjective dividend/GDP growth expectations. Yields on short-term dividend claims are more volatile because short-term dividend growth expectation mean-reverts to its less volatile long-run counterpart. Procyclical slope of equity yields is due to the counter-cyclical slope of dividend growth expectations. The correlation between equity returns/yields and nominal bond returns/yields switched from positive to negative after the late 1990s, mainly owing to a stronger correlation between real GDP growth and real dividend growth expectations, and only partially due to procyclical inflation. Dividend strip returns are predictable and the strength of predictability decreases with maturity due to predictable dividend forecast errors and revisions. The model is also consistent with the data in generating persistent and volatile price-dividend ratios, and excess return volatility.

Sustainable Systematic Credit

Interest in sustainable investing has exploded in recent years, initially focused on public equity markets, but now evolving into fixed income. We assess various aspects of sustainable investing for developed market corporate bond markets (both Investment Grade and High Yield). Using a representative set of sustainability measures spanning environment, societal and governance (ESG) constructs we find: (i) credit spreads are only marginally associated with ESG measures, (ii) ESG measures are only marginally associated with standard return forecasting measures for corporate bonds, (iii) ESG measures are not reliably associated with future credit excess returns, and (iv) ESG measures are negatively associated with the future volatility of credit excess returns. While the direct investment impact of sustainability is modest, there is still considerable interest from asset owners to ensure credit allocations are sustainable. We find that it is possible to incorporate (i) both static and dynamic exclusion screens, (ii) positive tilts toward more sustainable issuers, and (iii) economically meaningful reduction in carbon intensity, with minimal portfolio distortions. Thus, a well-implemented systematic approach has the potential to offer attractive risk-adjusted returns in a sustainable manner.

ENDOGENOUS PARTICIPATION, RISK, AND LEARNING IN THE STOCK MARKET

A simple asset pricing model with both endogenous stock market participation and subjective risk can explain the negative cross-country correlation between participation rates and the volatility of excess returns, along with the time-varying participation rates in the data. Belief-driven learning dynamics can explain the interplay between participation rates, subjective risk, and stock price volatility. When agents adaptively learn about the risk and return, my model generates 25% of the excess volatility observed in US stock prices, while also matching key moments. With learning about risk, excess volatility of stock prices is driven by fluctuations in the participation rate that arise because agents’ risk estimates vary with prices. I find that learning about risk is quantitatively more important than learning about returns.

Endogenous Participation, Risk, and Learning in the Stock Market

A simple asset pricing model with endogenous participation and subjective risk can explain both the negative cross-country correlation between participation rates and the volatility of excess returns along with the time-varying participation rates in the data. Belief-driven learning dynamics are key to explaining the interplay between participation, subjective risk, and price volatility. When agents adaptively learn about the risk and return, the model can generate 25% of the excess volatility in stock prices observed in U.S. data while matching key moments. With learning about risk, excess volatility of prices is driven by fluctuations in the participation rate that arise because agents' risk estimates vary with prices. I find that learning about risk is quantitatively more important than learning about returns.

Equity Risk Premium Puzzle: Evidence from Indonesia and Sri Lanka

This paper investigates the equity risk premium puzzle in the Indonesian and Sri Lankan stock markets in order to identify the relationship between the volatility of excess returns and the equity risk premium. The asymmetric impact of negative shocks on the equity risk premium is also examined using threshold and exponential GARCH-M models. We analyse data on the excess returns of the Indonesian and Sri Lankan stock markets from 2004 to 2013, and we find that the impact of the conditional volatility of excess returns on the equity risk premium is not significant in either country. Instead, we find an impact from negative return shocks on the equity risk premium only in Sri Lanka. Therefore, we conclude that investors are not compensated for the conditional volatility of the excess returns in these two markets, while Sri Lankan investors are compensated for the risk of negative shocks.

Predicting stock market movements with a time-varying consumption-aggregate wealth ratio

We develop a time-varying measure of cay (cayTVP) using time-varying cointegration, and then compare the predictive ability of cayTVP with cay and a Markov-switching cay (cayMS) for excess stock returns and volatility in the US over the period 1952:Q2-2015:Q3, using a k-th order nonparametric causality-in-quantiles test. We find that time-varying cointegration exists between consumption, asset wealth, and labor income. In addition, while there is no evidence of predictability of volatility of excess returns from cay, cayMS, or cayTVP, they tend to act as strong predictors of stock returns, with cayTVP being important during the bearish phases of the equity market.

Term structure dynamics in a monetary economy with learning

This paper investigates a continuous-time monetary asset-pricing model of the term structure of nominal interest rates. In a pure exchange economy with incomplete information, investors cannot observe the expected growth rates of both exogenous real output and money supply. Therefore, they apply dynamic Bayesian inference. The model obtains explicit solutions for equilibrium prices of consumption goods and nominal bonds, and the stochastic process of an investor’s beliefs. The dependence of term premia on beliefs allows the model to introduce a GARCH property, which interacts with the volatility of the macro variables. In particular, the volatility of excess returns is inversely related to noise in the macro variables, suggesting that their imprecise information does not increase fluctuations in interest rates. Using beliefs as the factor of uncertainties in economic states, the model also shows that there is a negative correlation between the new measure of uncertainty and the velocity of money, consistent with Friedman’s explanation that demand for money for precautionary motives has a negative impact on the velocity.

Persistence of Hedge Fund Returns and Fee-Aware Portfolio Construction

The author presents an empirical study of the persistence of manager returns for two core hedge fund categories: equity long–short and macro/managed futures. The author finds that although beta to core risk factors and volatility of excess returns were indeed persistent over time for these strategies, it appeared to be difficult to reliably predict outperformance of one fund over another based on past results. The author suggests portfolio construction assumptions that are consistent with these empirical findings and incorporate another feature of hedge fund performance that is highly persistent: manager fees. The author believes that the suggested portfolio construction process offers several advantages for institutional investors: It is robust because it is anchored in those properties of hedge fund historical returns that are persistent, and it allows incorporation of active views and hedge fund manager fees into portfolio decisions in a transparent and consistent manner.

Asset Pricing with Housing Booms and Disasters

By extending Cumulant Generating Function-based pricing formulas to a two-good economy (non-housing and housing), we obtain closed-form solutions for asset prices. The presence of housing impacts risk aversion and induces time variation that is priced in the model. Since housing also brings about composition risk, we show that it introduces endogenously a long-run risk component into the consumption bundle dynamics. Estimating the model over the period 1959 -– 2020, we show that rare booms and busts events in housing expenditures is determinant in obtaining moderate housing risk premium and housing excess return volatility, both in line with empirical results. The real interest rate and both the level and volatility of the equity risk premium also fit the data owing to the presence of the COVID period into our sample period.

The Disagreement with Herding, Market Bubble, and Excess Volatility

We construct a general equilibrium “disagreement with herding” model to identify the joint effect of the disagreement and herding among investors on the price bubble and excess return volatility. There are two classes of analysts one of which can capture the information in the public signal. An another analyst, on the other hand, do not have an enough ability to refine the public signal to exploit the information and therefore herd. i.e. tend to revise his opinion by moving toward the other’s opinion. As a consequence of the combinational dynamics of the disagreement and herding, the price bubble and the excess volatility is exaggerated especially when they are both huge.

Switching Regime Beta Analysis of Global Financial Crisis: Evidence from International Public Real Estate Markets

We examine whether the recent subprime/global financial crisis caused some significant changes in the excess return distribution and volatility spillover, as well as the link between them and the world market for a select group of international public real estate markets from January 6, 2000 to June 25, 2015. Employing univariate and multivariate switching regime beta models, our results suggest that the public real estate markets examined responded significantly to the financial crisis with a significant increase in the volatility parameter compared to normal period. Moreover, the linkages of the public real estate markets with the two world market indices have been altered differently by the financial crisis, and are enhanced in the post-crisis period for the European region. In contrast, the three major Asian public real estate markets display reduced risk spillover effect in the low volatility state from the world market in recent years. Our findings offer important and yet different implications for investors in their pursuit for portfolio diversification and policymakers in contagion management in the Asian and European public real estate and stock markets after a recent major financial crisis.

Idiosyncratic volatility and excess Return: Evidence from the Greater China region

This study uses monthly data from the Greater China region from 1996 to 2010 to examine the relation between idiosyncratic volatility (IV) and excess returns (ER). We show an insignificant IV-ER relation in the Hong Kong and Taiwan stock markets. A positive relation is found in the Shanghai stock market, but the positive relation disappears after the market liberalization in April 2005. Our finding supports Merton's (1987) theory that excess return and idiosyncratic volatility are positively related when asset diversification is restricted.

Investor sentiment, stock market returns and volatility: evidence from National Stock Exchange of India

This study explores the relationship between investor sentiment and stock return volatility using monthly data from National Stock Exchange (NSE) of India over July 2001 to December 2013 period. Using seven market-related implicit indicators a sentiment index has been constructed with the help of principal component analysis. Then the analysis has been done by employing ordinary least squares methods, vector autoregression, Granger causality and EGARCH-M models. Findings show that sentiment index significantly influences market excess returns. At the first glance it was found that sentiment has negative influence on the conditional volatility. However, when the sentiment index is decomposed into positive sentiment and negative sentiment changes, the study reveals that positive and negative sentiments have asymmetric impacts on excess return volatility. The Granger causality results suggest a bi-directional causality between excess return and investor sentiment at the third lags.

Short-horizon excess returns and exchange rate and interest rate effects

We examine the effects of foreign exchange (FX) and interest rate changes on the excess returns of U.S. stocks, for short-horizons of 1–40 days. Our new evidence shows a tendency for the volatility of both excess returns and FX rate changes to be negatively related with FX rate and interest rate effects. Both the number of firms with significant FX rate and interest rate effects and the magnitude of their exposures increase with the length of the return horizon. Our finding seems inconsistent with the view that firms hedge effectively at short-return horizons.

Asset Price Effects of Peer Benchmarking: Evidence from a Natural Experiment

We estimate the effects of peer benchmarking by institutional investors on asset prices. To identify trades purely due to peer benchmarking as separate from those based on fundamentals or private information, we exploit a natural experiment involving a change in a government-imposed under-performance penalty applicable to Colombian pension funds. This change in regulation is orthogonal to stock fundamentals and only affects incentives to track peer portfolios, allowing us to identify the component of demand that is caused by peer benchmarking. We find that these peer effects generate excess stock return volatility, with stocks exhibiting short-term abnormal returns followed by returns reversal in the subsequent quarter. Additionally, peer benchmarking produces an excess in co-movement across stock returns beyond the correlation implied by fundamentals.

Market Reaction to XBRL Filings

In 2009, the SEC mandated XBRL filings in an effort to enhance interpretation and analysis of financial statements. Recently, however, there have been complaints by some Fortune 500 companies that XBRL filings have not proven useful and have advocated for the SEC to scale down its implementation. This study investigates whether XBRL filings provide useful information to capital markets. We test predictions from Bayesian-inspired theory suggesting that individuals underreact to information releases initially if they expect subsequent follow-up disclosures to improve on the quality of the initial release. We investigate this prediction by examining differences in how the market reacts to quarterly earnings announcements between firms that issued XBRL filings during the Voluntary Filing Program (VFP) period and a matched sample of firms that did not. Using a differences-in-differences research design, we find that the market reacted significantly less to earnings announcements of firms that issued XBRL filings compared to a matched sample that did not issue filings during the VFP period but not during the period preceding it. We also find that firms that issued XBRL filings exhibited significantly lower excess return volatility compared to non-filers.

Information in the Term Structure for the Conditional Volatility of One Year Bond Returns

The term structure of interest rates captures a significant amount of the time variation in the conditional volatility of 1-year excess returns of bonds of 2- to 5-year maturity. A single linear combination of the forward rates captures most of the variation in the conditional volatilities across maturities. The term structure drivers of the expected excess returns and the conditional volatilities are distinct. The overall level of interest rates captures a significant amount of the variation in the conditional volatility of excess returns. The 4-5 year yield spread, which is an important positive predictor of expected excess returns, has an opposing effect on the conditional volatility. Thus, the tent-shaped linear combination of forward rates driving the expected excess returns captures either the market price of risk, or the correlation with the market, but not the conditional volatility.

The Investors' Belief in Stock Returns and Volatilities

Motivated by the asset pricing implications of the regime-switching equilibrium models in the literature, this paper investigates empirically the effects of regime switches in aggregate stock returns and volatilities. The investors' belief, defined as the posterior probability of the bear regime, is estimated based on a regime-switching model where the regime of the economy follows a two-state hidden Markov process. Veronesi (1999) shows that both the expected excess return and the volatility of the returns are the concave, bell-shaped functions of the investors' belief if risk aversion is a constant.The empirical findings in this paper suggest that the expected excess return and the volatility are monotonically increasing functions of the investors' belief. Therefore, a reasonable explanation for the empirical finding is that risk aversion is time-varying and the representative agent is more risk averse in the bear regime so that a higher expected excess return and higher volatility in the bad regime are generated. A second empirical finding is that the stock return predictors, such as the term spread, the in flation rate, and the T-bill rate, have significant business cycle patterns in the predictive regressions. For example, the term spread is positively related to the stock market returns in the boom regime, but is negatively related to the stock market returns in the bear regime. This suggests that the increasing term spread is good news in the bear regime because it indicates that the economy is improving and will recover soon, thus the investors require a lower equity premium. In addition, the equity premium is more sensitive to the predictors in the bear regime because the bear regime is short lived. Similar results are also found in the predictive regressions for the variance of the stock market returns.