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298
Risks for the long run: A potential resolution of asset pricing puzzles
 JOURNAL OF FINANCE
, 1994
"... We model consumption and dividend growth rates as containing (i) a small longrun predictable component and (ii) fluctuating economic uncertainty (consumption volatility). These dynamics, for which we provide empirical support, in conjunction with Epstein and Zin’s (1989) preferences, can explain ke ..."
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Cited by 350 (30 self)
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We model consumption and dividend growth rates as containing (i) a small longrun predictable component and (ii) fluctuating economic uncertainty (consumption volatility). These dynamics, for which we provide empirical support, in conjunction with Epstein and Zin’s (1989) preferences, can explain key asset markets phenomena. In our economy, financial markets dislike economic uncertainty and better longrun growth prospects raise equity prices. The model can justify the equity premium, the riskfree rate, and the volatility of the market return, riskfree rate, and the pricedividend ratio. As in the data, dividend yields predict returns and the volatility of returns is timevarying.
Illiquidity and Stock Returns: Crosssection and Timeseries Effects
 Journal of Financial Markets
, 2002
"... This paper shows that over time, expected market illiquidity positively affects ex ante stock excess return, suggesting that expected stock excess return partly represents an illiquidity premium. This complements the crosssectional positive return–illiquidity relationship. Also, stock returns are n ..."
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Cited by 297 (3 self)
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This paper shows that over time, expected market illiquidity positively affects ex ante stock excess return, suggesting that expected stock excess return partly represents an illiquidity premium. This complements the crosssectional positive return–illiquidity relationship. Also, stock returns are negatively related over time to contemporaneous unexpected illiquidity. The illiquidity measure here is the average across stocks of the daily ratio of absolute stock return to dollar volume, which is easily obtained from daily stock data for long time series in most stock markets. Illiquidity affects more strongly small firm stocks, thus explaining time series variations in their premiums over
Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk
 THE JOURNAL OF FINANCE • VOL. LVI
, 2001
"... This paper uses a disaggregated approach to study the volatility of common stocks at the market, industry, and firm levels. Over the period 1962–1997 there has been a noticeable increase in firmlevel volatility relative to market volatility. Accordingly, correlations among individual stocks and the ..."
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Cited by 270 (13 self)
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This paper uses a disaggregated approach to study the volatility of common stocks at the market, industry, and firm levels. Over the period 1962–1997 there has been a noticeable increase in firmlevel volatility relative to market volatility. Accordingly, correlations among individual stocks and the explanatory power of the market model for a typical stock have declined, whereas the number of stocks needed to achieve a given level of diversification has increased. All the volatility measures move together countercyclically and help to predict GDP growth. Market volatility tends to lead the other volatility series. Factors that may be responsible for these findings are suggested.
Modeling and Forecasting Realized Volatility
, 2002
"... this paper is built. First, although raw returns are clearly leptokurtic, returns standardized by realized volatilities are approximately Gaussian. Second, although the distributions of realized volatilities are clearly rightskewed, the distributions of the logarithms of realized volatilities are a ..."
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Cited by 265 (34 self)
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this paper is built. First, although raw returns are clearly leptokurtic, returns standardized by realized volatilities are approximately Gaussian. Second, although the distributions of realized volatilities are clearly rightskewed, the distributions of the logarithms of realized volatilities are approximately Gaussian. Third, the longrun dynamics of realized logarithmic volatilities are well approximated by a fractionallyintegrated longmemory process. Motivated by the three ABDL empirical regularities, we proceed to estimate and evaluate a multivariate model for the logarithmic realized volatilities: a fractionallyintegrated Gaussian vector autoregression (VAR) . Importantly, our approach explicitly permits measurement errors in the realized volatilities. Comparing the resulting volatility forecasts to those obtained from currently popular daily volatility models and more complicated highfrequency models, we find that our simple Gaussian VAR forecasts generally produce superior forecasts. Furthermore, we show that, given the theoretically motivated and empirically plausible assumption of normally distributed returns conditional on the realized volatilities, the resulting lognormalnormal mixture forecast distribution provides conditionally wellcalibrated density forecasts of returns, from which we obtain accurate estimates of conditional return quantiles. In the remainder of this paper, we proceed as follows. We begin in section 2 by formally developing the relevant quadratic variation theory within a standard frictionless arbitragefree multivariate pricing environment. In section 3 we discuss the practical construction of realized volatilities from highfrequency foreign exchange returns. Next, in section 4 we summarize the salient distributional features of r...
The Distribution of Realized Exchange Rate Volatility
 Journal of the American Statistical Association
, 2001
"... Using highfrequency data on deutschemark and yen returns against the dollar, we construct modelfree estimates of daily exchange rate volatility and correlation that cover an entire decade. Our estimates, termed realized volatilities and correlations, are not only modelfree, but also approximately ..."
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Cited by 150 (17 self)
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Using highfrequency data on deutschemark and yen returns against the dollar, we construct modelfree estimates of daily exchange rate volatility and correlation that cover an entire decade. Our estimates, termed realized volatilities and correlations, are not only modelfree, but also approximately free of measurement error under general conditions, which we discuss in detail. Hence, for practical purposes, we may treat the exchange rate volatilities and correlations as observed rather than latent. We do so, and we characterize their joint distribution, both unconditionally and conditionally. Noteworthy results include a simple normalityinducing volatility transformation, high contemporaneous correlation across volatilities, high correlation between correlation and volatilities, pronounced and persistent dynamics in volatilities and correlations, evidence of longmemory dynamics in volatilities and correlations, and remarkably precise scaling laws under temporal aggregation.
Stock Market Overreaction to Bad News in Good Times: A Rational Expectations Equilibrium Model
, 1999
"... This paper presents a dynamic, rational expectations equilibrium model of asset prices where the drift of fundamentals (dividends) shifts between two unobservable states at random times. I show that in equilibrium, investors' willingness to hedge against changes in their own "uncertainty" on the tru ..."
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Cited by 124 (9 self)
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This paper presents a dynamic, rational expectations equilibrium model of asset prices where the drift of fundamentals (dividends) shifts between two unobservable states at random times. I show that in equilibrium, investors' willingness to hedge against changes in their own "uncertainty" on the true state makes stock prices overreact to bad news in good times and underreact to good news in bad times. I then show that this model is better able than con ventional models with no regime shifts to explain features of stock returns, including volatility clustering, "leverage effects," excess volatility and timevarying expected returns.
Estimating Portfolio and Consumption Choice: A Conditional Euler Equations Approach
 JOURNAL OF FINANCE
, 1999
"... This paper develops a nonparametric approach to examine how portfolio and consumption choice depends on variables that forecast timevarying investment opportunities. I estimate singleperiod and multiperiod portfolio and consumption rules of an investor with constant relative risk aversion and a on ..."
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Cited by 119 (11 self)
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This paper develops a nonparametric approach to examine how portfolio and consumption choice depends on variables that forecast timevarying investment opportunities. I estimate singleperiod and multiperiod portfolio and consumption rules of an investor with constant relative risk aversion and a onemonth to 20year horizon. The investor allocates wealth to the NYSE index and a 30day Treasury bill. I find that the portfolio choice varies significantly with the dividend yield, default premium, term premium, and lagged excess return. Furthermore, the optimal decisions depend on the investor’s horizon and rebalancing frequency.
Rangebased estimation of stochastic volatility models
, 2002
"... We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that rangebased volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence rangebased Gaussian qu ..."
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Cited by 114 (11 self)
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We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that rangebased volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence rangebased Gaussian quasimaximum likelihood estimation produces highly efficient estimates of stochastic volatility models and extractions of latent volatility. We use our method to examine the dynamics of daily exchange rate volatility and find the evidence points strongly toward twofactor models with one highly persistent factor and one quickly meanreverting factor. VOLATILITY IS A CENTRAL CONCEPT in finance, whether in asset pricing, portfolio choice, or risk management. Not long ago, theoretical models routinely assumed constant volatility ~e.g., Merton ~1969!, Black and Scholes ~1973!!. Today, however, we widely acknowledge that volatility is both time varying and predictable ~e.g., Andersen and Bollerslev ~1997!!, andstochastic volatility models are commonplace. Discrete and continuoustime stochastic volatility models are extensively used in theoretical finance, empirical finance, and financial econometrics, both in academe and industry ~e.g., Hull and
The risk and predictability of international equity returns
 Review of Financial Studies
, 1993
"... We investigate predictability in national equity market returns, and its relation to global economic risks. We show how to consistently estimate the fraction of the predictable variation that is captured by an assetpricing modelfor the expected returns. We use a model in which conditional betas of t ..."
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Cited by 110 (11 self)
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We investigate predictability in national equity market returns, and its relation to global economic risks. We show how to consistently estimate the fraction of the predictable variation that is captured by an assetpricing modelfor the expected returns. We use a model in which conditional betas of the national equity markets depend on local information variables, while global risk premia depend on global variables. We examine singleand multiplebeta models, using monthly data for 1970 to 1989. The models capture much of thepredictability for many countries. Most of this is related to time variation in the global risk premia. We investigate the sources of risk and predictability of international equity market returns. We examine several global economic risk factors, including a world market portfolio, exchange rate fluctuations, meaPart of this research was conducted while the authors were at the University