The Journal of Finance

Investing for the Long Run when Returns Are Predictable

Published: 2/2000,  Volume: 55,  Issue: 1  |  DOI: 10.1111/0022-1082.00205  |  Cited by: 975

Nicholas Barberis

We examine how the evidence of predictability in asset returns affects optimal portfolio choice for investors with long horizons. Particular attention is paid to estimation risk, or uncertainty about the true values of model parameters. We find that even after incorporating parameter uncertainty, there is enough predictability in returns to make investors allocate substantially more to stocks, the longer their horizon. Moreover, the weak statistical significance of the evidence for predictability makes it important to take estimation risk into account; a long‐horizon investor who ignores it may overallocate to stocks by a sizeable amount.

What Drives the Disposition Effect? An Analysis of a Long‐Standing Preference‐Based Explanation

Published: 3/13/2009,  Volume: 64,  Issue: 2  |  DOI: 10.1111/j.1540-6261.2009.01448.x  |  Cited by: 598

NICHOLAS BARBERIS, WEI XIONG

We investigate whether prospect theory preferences can predict a disposition effect. We consider two implementations of prospect theory: in one case, preferences are defined over annual gains and losses; in the other, they are defined over realized gains and losses. Surprisingly, the annual gain/loss model often fails to predict a disposition effect. The realized gain/loss model, however, predicts a disposition effect more reliably. Utility from realized gains and losses may therefore be a useful way of thinking about certain aspects of individual investor trading.

Mental Accounting, Loss Aversion, and Individual Stock Returns

Published: 8/2001,  Volume: 56,  Issue: 4  |  DOI: 10.1111/0022-1082.00367  |  Cited by: 686

Nicholas Barberis, Ming Huang

We study equilibrium firm‐level stock returns in two economies: one in which investors are loss averse over the fluctuations of their stock portfolio, and another in which they are loss averse over the fluctuations of individual stocks that they own. Both approaches can shed light on empirical phenomena, but we find the second approach to be more successful: In that economy, the typical individual stock return has a high mean and excess volatility, and there is a large value premium in the cross section which can, to some extent, be captured by a commonly used multifactor model.

Prospect Theory and Stock Market Anomalies

Published: 6/18/2021,  Volume: 76,  Issue: 5  |  DOI: 10.1111/jofi.13061  |  Cited by: 183

NICHOLAS BARBERIS, LAWRENCE J. JIN, BAOLIAN WANG

We present a new model of asset prices in which investors evaluate risk according to prospect theory and examine its ability to explain 23 prominent stock market anomalies. The model incorporates all of the elements of prospect theory, accounts for investors' prior gains and losses, and makes quantitative predictions about an asset's average return based on empirical estimates of the asset's return volatility, return skewness, and past capital gain. We find that the model can help explain a majority of the 23 anomalies.

Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility

Published: 3/17/2014,  Volume: 69,  Issue: 2  |  DOI: 10.1111/jofi.12126  |  Cited by: 187

CARY FRYDMAN, NICHOLAS BARBERIS, COLIN CAMERER, PETER BOSSAERTS, ANTONIO RANGEL

We conduct a study in which subjects trade stocks in an experimental market while we measure their brain activity using functional magnetic resonance imaging. All of the subjects trade in a suboptimal way. We use the neural data to test a “realization utility” explanation for their behavior. We find that activity in two areas of the brain that are important for economic decision‐making exhibit activity consistent with the predictions of realization utility. These results provide support for the realization utility model. More generally, they demonstrate that neural data can be helpful in testing models of investor behavior.

The Demand for Life Insurance: An Application of the Economics of Uncertainty: A Comment

Published: 12/1982,  Volume: 37,  Issue: 5  |  DOI: 10.1111/j.1540-6261.1982.tb03621.x  |  Cited by: 3

NICHOLAS ECONOMIDES

INFORMATION‐PRODUCTION AND CAPITAL MARKET EQUILIBRIUM

Published: 6/1975,  Volume: 30,  Issue: 3  |  DOI: 10.1111/j.1540-6261.1975.tb01854.x  |  Cited by: 13

Nicholas J. Gonedes

EXCHANGE RATE FLEXIBILITY AND DEMAND FOR MONEY

Published: 5/1977,  Volume: 32,  Issue: 2  |  DOI: 10.1111/j.1540-6261.1977.tb03291.x  |  Cited by: 2

Nicholas P. Sargen

A PORTFOLIO ANALYSIS OF STRADDLE OPERATIONS IN THE FUTURES MARKETS: AN APPLICATION OF THE EXPECTED RETURNS‐VARIANCE OF RETURNS HYPOTHESIS*

Published: 6/1969,  Volume: 24,  Issue: 3  |  DOI: 10.1111/j.1540-6261.1969.tb00378.x  |  Cited by: 0

Nicholas W. Schrock

CAPITAL MARKET EQUILIBRIUM FOR A CLASS OF HETEROGENEOUS EXPECTATIONS IN A TWO‐PARAMETER WORLD†

Published: 3/1976,  Volume: 31,  Issue: 1  |  DOI: 10.1111/j.1540-6261.1976.tb03191.x  |  Cited by: 3

Nicholas J. Gonedes

The Market for Equity Options in the 1870s

Published: 9/1997,  Volume: 52,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1997.tb01128.x  |  Cited by: 23

JOSEPH P. KAIRYS, NICHOLAS VALERIO

The introduction of exchange‐traded options in 1973 led to explosive growth in the stock options market, but put and call options on equity securities have existed for more than a century. Prior to the listing of option contracts, trading was conducted in an order‐driven over‐the‐counter market. From 1873 to 1875, quotes for options contracts were published weekly in The Commercial and Financial Chronicle during a period that saw extensive marketing efforts by a number of brokerage firms. In this article we examine these quotes to determine why this seemingly sophisticated market existed for only a brief period in financial history.

THE CAPITAL MARKET, THE MARKET FOR INFORMATION, AND EXTERNAL ACCOUNTING

Published: 5/1976,  Volume: 31,  Issue: 2  |  DOI: 10.1111/j.1540-6261.1976.tb01910.x  |  Cited by: 4

William Beaver, Nicholas J. Gonedes

Sequential Learning, Predictability, and Optimal Portfolio Returns

Published: 3/17/2014,  Volume: 69,  Issue: 2  |  DOI: 10.1111/jofi.12121  |  Cited by: 185

MICHAEL JOHANNES, ARTHUR KORTEWEG, NICHOLAS POLSON

This paper finds statistically and economically significant out‐of‐sample portfolio benefits for an investor who uses models of return predictability when forming optimal portfolios. Investors must account for estimation risk, and incorporate an ensemble of important features, including time‐varying volatility, and time‐varying expected returns driven by payout yield measures that include share repurchase and issuance. Prior research documents a lack of benefits to return predictability, and our results suggest that this is largely due to omitting time‐varying volatility and estimation risk. We also document the sequential process of investors learning about parameters, state variables, and models as new data arrive.

Stimulating Housing Markets

Published: 11/12/2019,  Volume: 75,  Issue: 1  |  DOI: 10.1111/jofi.12847  |  Cited by: 86

DAVID BERGER, NICHOLAS TURNER, ERIC ZWICK

We study temporary fiscal stimulus designed to support distressed housing markets by inducing demand from buyers in the private market. Using difference‐in‐differences and regression kink research designs, we find that the First‐Time Homebuyer Credit increased home sales by 490,000 (9.8%), median home prices by $2,400 (1.1%) per standard deviation increase in program exposure, and the transition rate into homeownership by 53%. The policy response did not reverse immediately. Instead, demand comes from several years in the future: induced buyers were three years younger in 2009 than typical first‐time buyers. The program's market‐stabilizing benefits likely exceeded its direct stimulus effects.

A Tale of Two Runs: Depositor Responses to Bank Solvency Risk

Published: 11/10/2016,  Volume: 71,  Issue: 6  |  DOI: 10.1111/jofi.12424  |  Cited by: 171

RAJKAMAL IYER, MANJU PURI, NICHOLAS RYAN

We examine heterogeneity in depositor responses to solvency risk using depositor‐level data for a bank that faced two different runs. We find that depositors with loans and bank staff are less likely to run than others during a low‐solvency‐risk shock, but are more likely to run during a high‐solvency‐risk shock. Uninsured depositors are also sensitive to bank solvency. In contrast, depositors with older accounts run less, and those with frequent past transactions run more, irrespective of the underlying risk. Our results show that the fragility of a bank depends on the composition of its deposit base.

The Impact of Jumps in Volatility and Returns

Published: 5/6/2003,  Volume: 58,  Issue: 3  |  DOI: 10.1111/1540-6261.00566  |  Cited by: 1257

Bjørn Eraker, Michael Johannes, Nicholas Polson

AbstractThis paper examines continuous‐time stochastic volatility models incorporating jumps in returns and volatility. We develop a likelihood‐based estimation strategy and provide estimates of parameters, spot volatility, jump times, and jump sizes using S&P 500 and Nasdaq 100 index returns. Estimates of jump times, jump sizes, and volatility are particularly useful for identifying the effects of these factors during periods of market stress, such as those in 1987, 1997, and 1998. Using formal and informal diagnostics, we find strong evidence for jumps in volatility and jumps in returns. Finally, we study how these factors and estimation risk impact option pricing.

Do Municipal Bond Dealers Give Their Customers “Fair and Reasonable” Pricing?

Published: 3/8/2023,  Volume: 78,  Issue: 2  |  DOI: 10.1111/jofi.13214  |  Cited by: 40

JOHN M. GRIFFIN, NICHOLAS HIRSCHEY, SAMUEL KRUGER

Municipal bonds exhibit considerable retail pricing variation, even for same‐size trades of the same bond on the same day, and even from the same dealer. Markups vary widely across dealers. Trading strongly clusters on eighth price increments, and clustered trades exhibit higher markups. Yields are often lowered to just above salient numbers. Machine learning estimates exploiting the richness of the data show that dealers that use strategic pricing have systematically higher markups. Recent Municipal Securities Rulemaking Board rules have had only a limited impact on markups. While a subset of dealers focus on best execution, many dealers appear focused on opportunistic pricing.

Cream‐Skimming or Profit‐Sharing? The Curious Role of Purchased Order Flow

Published: 7/1996,  Volume: 51,  Issue: 3  |  DOI: 10.1111/j.1540-6261.1996.tb02708.x  |  Cited by: 248

DAVID EASLEY, NICHOLAS M. KIEFER, MAUREEN O'HARA

Purchased order flow refers to the practice of dealers or trading locales paying brokers for retail order flow. It is alleged that such agreements are used to “cream skim” uninformed liquidity trades, leaving the information‐based trades to established markets. We develop a test of this hypothesis, using a model of the stochastic process of trades. We then estimate the model for a sample of stocks known to be used in order purchase agreements that trade on the New York Stock Exchange (NYSE) and the Cincinnati Stock Exchange. Our main empirical result is that there is a significant difference in the information content of orders executed in New York and Cincinnati, and that this difference is consistant with cream‐skimming.

Liquidity, Information, and Infrequently Traded Stocks

Published: 9/1996,  Volume: 51,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1996.tb04074.x  |  Cited by: 1247

DAVID EASLEY, NICHOLAS M. KIEFER, MAUREEN O'HARA, JOSEPH B. PAPERMAN

This article investigates whether differences in information‐based trading can explain observed differences in spreads for active and infrequently traded stocks. Using a new empirical technique, we estimate the risk of information‐based trading for a sample of New York Stock Exchange (NYSE) listed stocks. We use the information in trade data to determine how frequently new information occurs, the composition of trading when it does, and the depth of the market for different volume‐decile stocks. Our most important empirical result is that the probability of information‐based trading is lower for high volume stocks. Using regressions, we provide evidence of the economic importance of information‐based trading on spreads.