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Santa-Clara, Pedro

Works: 21 works in 122 publications in 1 language and 663 library holdings
Roles: Author
Classifications: HB1, 330.072
Publication Timeline
Publications about Pedro Santa-Clara
Publications by Pedro Santa-Clara
Most widely held works by Pedro Santa-Clara
International risk sharing is better than you think : or exchange rates are much too smooth by Michael W Brandt( Book )
12 editions published in 2001 in English and held by 48 libraries worldwide
Exchange rates depreciate by the difference between the domestic and foreign marginal utility growths. Exchange rates vary a lot , as much as 10% per year. However, equity premia imply that marginal utility growths vary much more, by at least 50% per year. This means that marginal utility growths must be highly correlated across countries -- international risk sharing is better than you think. Conversely, if risks really are not shared internationally, exchange rates should vary more than they do -- exchange rates are much too smooth. We calculate an index of international risk sharing that formalizes this intuition in the context of both complete and incomplete capital markets. Our results suggest that risk sharing is indeed very high across several pairs of countries
Two trees : asset price dynamics induced by market clearing by John H Cochrane( Book )
11 editions published in 2003 in English and held by 42 libraries worldwide
If stocks go up, investors may want to rebalance their portfolios. But investors cannot all rebalance. Expected returns may need to change so that the average investor is still happy to hold the market portfolio despite its changed composition. In this way, simple market clearing can give rise to complex asset market dynamics. We study this phenomenon in a very simple model. Our model has two Lucas trees.' Each tree has i.i.d.dividend growth, and the representative investor has log utility. We are able to give analytical solutions to the model. Despite this simple setup, price-dividend ratios, expected returns, and return variances vary through time. A dividend shock leads to underreaction' in some states, as expected returns rise and prices slowly adjust, and overreaction' in others. Expected returns and excess returns are predictable by price-dividend ratios in the time series and in the cross section, roughly matching value effects and return forecasting regressions. Returns generally display positive serial correlation and negative cross-serial correlation, leading to 'momentuem,' but the opposite signs are possible as well. A shock to one asset's dividend a.ects the price and expected return of the other asset, leading to substantial correlation of returns even when there is no correlation of cash flows and giving the appearance of contagion.' Market clearing allows the inverse portfolio' problem to be solved, in which the weights of the assets in the market portfolio are inverted' to solve for the parameters of the assets' return generating process
Dynamic portfolio selection by augmenting the asset space by Michael W Brandt( Book )
10 editions published in 2004 in English and held by 42 libraries worldwide
We present a novel approach to dynamic portfolio selection that is no more difficult to implement than the static Markowitz model. The idea is to expand the asset space to include simple (mechanically) managed portfolios and compute the optimal static portfolio in this extended asset space. The intuition is that a static choice among managed portfolios is equivalent to a dynamic strategy. We consider managed portfolios of two types: "conditional" and "timing" portfolios. Conditional portfolios are constructed along the lines of Hansen and Richard (1987). For each variable that affects the distribution of returns and for each basis asset, we include a portfolio that invests in the basis asset an amount proportional to the level of the conditioning variable. Timing portfolios invest in each basis asset for a single period and therefore mimic strategies that buy and sell the asset through time. We apply our method to a problem of dynamic asset allocation across stocks, bonds, and cash using the predictive ability of four conditioning variables
There is a risk-return tradeoff after all by Eric Ghysels( Book )
13 editions published between 2003 and 2004 in English and held by 40 libraries worldwide
This paper studies the ICAPM intertemporal relation between the conditional mean and the conditional variance of the aggregate stock market return. We introduce a new estimator that forecasts monthly variance with past daily squared returns %u2013 the Mixed Data Sampling (or MIDAS) approach. Using MIDAS, we find that there is a significantly positive relation between risk and return in the stock market. This finding is robust in subsamples, to asymmetric specifications of the variance process, and to controlling for variables associated with the business cycle. We compare the MIDAS results with tests of the ICAPM based on alternative conditional variance specifications and explain the conflicting results in the literature. Finally, we offer new insights about the dynamics of conditional variance
Predicting volatility : getting the most out of return data sampled at different frequencies by Eric Ghysels( Book )
13 editions published in 2004 in English and held by 40 libraries worldwide
We consider various MIDAS (Mixed Data Sampling) regression models to predict volatility. The models differ in the specification of regressors (squared returns, absolute returns, realized volatility, realized power, and return ranges), in the use of daily or intra-daily (5-minute) data, and in the length of the past history included in the forecasts. The MIDAS framework allows us to compare models across all these dimensions in a very tightly parameterized fashion. Using equity return data, we find that daily realized power (involving 5-minute absolute returns) is the best predictor of future volatility (measured by increments in quadratic variation) and outperforms model based on realized volatility (i.e. past increments in quadratic variation). Surprisingly, the direct use of high-frequency (5-minute) data does not improve volatility predictions. Finally, daily lags of one to two months are sucient to capture the persistence in volatility. These findings hold both in- and out-of-sample
Jump and volatility risk and risk premia : a new model and lessons from S & P 500 options by Pedro Santa-Clara( Book )
11 editions published in 2004 in English and held by 38 libraries worldwide
We use a novel pricing model to filter times series of diffusive volatility and jump intensity from S & P 500 index options. These two measures capture the ex-ante risk assessed by investors. We find that both components of risk vary substantially over time, are quite persistent, and correlate with each other and with the stock index. Using a simple general equilibrium model with a representative investor, we translate the filtered measures of ex-ante risk into an ex-ante risk premium. We find that the average premium that compensates the investor for the risks implicit in option prices, 10.1 percent, is about twice the premium required to compensate the same investor for the realized volatility, 5.8 percent. Moreover, the ex-ante equity premium that we uncover is highly volatile, with values between 2 and 32 percent. The component of the premium that corresponds to the jump risk varies between 0 and 12 percent
Parametric portfolio policies : exploiting characteristics in the cross section of equity returns by Michael W Brandt( Book )
10 editions published in 2004 in English and held by 37 libraries worldwide
"We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset's characteristics. The coefficients of this function are found by optimizing the investor's average utility of the portfolio's return over the sample period. Our approach is computationally simple, easily modified and extended, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. Our approach also provides a new test of the portfolio choice implications of equilibrium asset pricing models. We present an empirical implementation for the universe of all stocks in the CRSP-Compustat dataset, exploiting the size, value, and momentum anomalies"--National Bureau of Economic Research web site
Simulated liklihood estimation of diffusions with an application to exchange rate dynamics in incomplete markets by Michael W Brandt( Book )
9 editions published in 2001 in English and held by 24 libraries worldwide
We present an econometric method for estimating the parameters of a diffusion model from discretely sampled data. The estimator is transparent, adaptive, and inherits the asymptotic properties of the generally unattainable maximum likelihood estimator. We use this method to estimate a new continuous-time model of the Joint dynamics of interest rates in two countries and the exchange rate between the two currencies. The model allows financial markets to be incomplete and specifies the degree of incompleteness as a stochastic process. Our empirical results offer several new insights into the dynamics of exchange rates
Professor Zipf goes to Wall Street by Yannick Malevergne( Book )
8 editions published between 2009 and 2010 in English and held by 14 libraries worldwide
The heavy-tailed distribution of firm sizes first discovered by Zipf (1949) is one of the best established empirical facts in economics. We show that it has strong implications for asset pricing. Due to the concentration of the market portfolio when the distribution of the capitalization of firms is sufficiently heavy-tailed, an additional risk factor generically appears even for very large economies. Our two-factor model is as successful empirically as the three-factor Fama-French model
Forecasting stock market returns : the sum of the parts is more than the whole by Miguel A Ferreira( Book )
8 editions published in 2008 in English and held by 11 libraries worldwide
We propose forecasting separately the three components of stock market returns: dividend yield, earnings growth, and price-earnings ratio growth. We obtain out-of-sample R-square coefficients (relative to the historical mean) of nearly 1.6% with monthly data and 16.7% with yearly data using the most common predictors suggested in the literature. This compares with typically negative R-squares obtained in a similar experiment by Goyal and Welch (2008). An investor who timed the market with our approach would have had a certainty equivalent gain of as much as 2.3% per year and a Sharpe ratio 77% higher relative to the historical mean. We conclude that there is substantial predictability in equity returns and that it would have been possible to time the market in real time
Default risk and interest rate risk : the term structure of default spreads by Lewis T Nielsen( Book )
2 editions published between 1993 and 2001 in English and held by 2 libraries worldwide
A simulation approach to dynamic portfolio choice with an application to learning about return predictability by Michael W Brandt( Book )
4 editions published in 2004 in English and held by 2 libraries worldwide
We present a simulation-based method for solving discrete-time portfolio choice problems involving non-standard preferences, a large number of assets with arbitrary return distribution, and, most importantly, a large number of state variables with potentially path-dependent or non-stationary dynamics. The method is flexible enough to accommodate intermediate consumption, portfolio constraints, parameter and model uncertainty, and learning. We first establish the properties of the method for the portfolio choice between a stock index and cash when the stock returns are either iid or predictable by the dividend yield. We then explore the problem of an investor who takes into account the predictability of returns but is uncertain about the parameters of the data generating process. The investor chooses the portfolio anticipating that future data realizations will contain useful information to learn about the true parameter values
The exposure of international corporate bond returns to exchange rate risk by Gordon Delianedis( Article )
1 edition published in 1999 in English and held by 2 libraries worldwide
Dynamic portfolio selection by augmenting the asset space ( Computer File )
1 edition published in 2004 in English and held by 1 library worldwide
Flexible multivariate GARCH modeling with an application to international stock markets ( Computer File )
1 edition published in 2001 in English and held by 1 library worldwide
The MIDAS touch : mixed data sampling regression models by Eric Ghysels( Book )
2 editions published in 2004 in English and held by 1 library worldwide
Simulated likelihood estimation of diffusions with an application to exchange rate dynamics in incomplete markets ( Computer File )
1 edition published in 2001 in English and held by 1 library worldwide
Earnings announcements are full of surprises ( Computer File )
1 edition published in 2008 in English and held by 1 library worldwide
Flexible multivariate GARCH modeling with an application to international stock markets by Olivier Ledoit( Computer File )
2 editions published in 2001 in English and held by 0 libraries worldwide
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Alternative Names
Clara, Pedro Santa-
Santa-Clara, P.
English (120)
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