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1 to 10 of 370 Results
Oct 2, 2013
John Y. Campbell; Luis Viceira, 2007, "Replication data for: Who Should Buy Long-Term Bonds?", https://doi.org/10.7910/DVN/8KLQPO, Harvard Dataverse, V3, UNF:3:S/WHW96SHNHXv0jyZv+vMA== [fileUNF]
According to conventional wisdom, long-term bonds are appropriate for conservative long-term investors. This paper develops a model of optimal consumption and portfolio choice for infinite-lived investors with recursive utility who face stochastic interest rates, solves the model using an approximate analytical method, and evaluates conventional wi...
Oct 2, 2013
John Y. Campbell; Lettau Martin; Malkiel Burton; Xu Yexiao, 2008, "Replication data for: Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk", https://doi.org/10.7910/DVN/YSL0TW, Harvard Dataverse, V3, UNF:3:Nw2HpVshIW4qJ3vGLEyD1A== [fileUNF]
This study uses a disaggregated approach to study the volatility of common stocks at the market, industry, and firm levels. Over the period from 1962 to 1997 there has been a noticeable increase in firm-level volatility relative to market volatility. Accordingly, correlations among individual stocks and the explanatory power of the market model for...
Oct 2, 2013
John Y. Campbell; John Cochrane, 2007, "Replication data for: By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior", https://doi.org/10.7910/DVN/3UHSJR, Harvard Dataverse, V2, UNF:3:0awoLDm/Dy6gYy+DQnNXSA== [fileUNF]
We present a consumption-based model that explains a wide variety of dynamic asset pricing phenomena, including the procyclical variation of stock prices, the long-horizon predictability of excess stock returns, and the countercyclical variation of stock market volatility. The model captures much of the history of stock prices from consumption data...
Oct 2, 2013
John Y. Campbell; Yeung L. Chan; and Luis Viceira, 2007, "Replication data for: A Multivariate Model of Strategic Asset Allocation", https://doi.org/10.7910/DVN/8ED29S, Harvard Dataverse, V2, UNF:3:ZnYhHkZe2veTJAWaBDpPKA== [fileUNF]
We develop an approximate solution method for the optimal consumption and portfolio choice problem of an infinitely long-lived investor with Epstein-Zin utility who faces a set of asset returns described by a vector autoregression in returns and state variables. Empirical estimates in long-run annual and post-war quarterly U.S. data suggest that th...
Oct 2, 2013
John Y. Campbell, 2007, "Replication data for: Consumption-Based Asset Pricing", https://doi.org/10.7910/DVN/CKTV5E, Harvard Dataverse, V2, UNF:3:wDZfht0d++JDkQXKUkkgng== [fileUNF]
This study examines the behavior of financial asset prices in relation to consumption. The study highlights some important stylized facts that characterize U.S. data, and relates them to recent developments in equilibrium asset pricing theory. Data from other countries are examined to see which features of the U.S. experience apply more generally....
Oct 2, 2013
John Y. Campbell, 2007, "Replication data for: Asset Prices, Consumption, and the Business Cycle", https://doi.org/10.7910/DVN/44JCWA, Harvard Dataverse, V2, UNF:3:y+1GSnV24fvGv7+S7BcLtw== [fileUNF]
This chapter reviews the behavior of financial asset prices in relation to consumption. The chapter lists some important stylized facts that characterize US data, and relates them to recent developments in equilibrium asset pricing theory. Data from other countries are examined to see which features of the US experience apply more generally. The ch...
Adobe PDF - 856.3 KB - MD5: f78e56e70c4ffd01201325d3017ea9b2
1. Documentation
The original article for this study, pdf format
Tabular Data - 8.4 KB - 3 Variables, 426 Observations - UNF:3:3ARxg9245WKgzD4xUjC+wA==
2d. Data - monthly volatility series - value-weighted
FIRM volatility based on daily returns
Plain Text - 547.5 KB - MD5: 8f4eec99f35f67501fcf5228b714fc9d
2c. Data - monthly volatility series for individual industries
IND volatility based on daily returns, ASCII raw numbers file
Tabular Data - 466.0 KB - 4 Variables, 20796 Observations - UNF:3:U2GsdS6A/5/0wP9vE+IgAg==
2c. Data - monthly volatility series for individual industries
IND volatility based on daily returns
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