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Abstract:
One key stylized fact in the empirical option pricing literature is the existence of an implied volatility surface (IVS). The usual approach consists of fitting a linear model linking the implied volatility to the time to maturity and the moneyness, for each cross section of options data. However, recent empirical evidence suggests that the parameters characterizing the IVS change over time. In this paper, we study whether the resulting predictability patterns in the IVS coefficients may be exploited in practice. We propose a two-stage approach to modeling and forecasting the S&P 500 index options IVS. In the first stage, we model the surface along the cross-sectional moneyness and time-to-maturity dimensions, similarly to Dumas, et. al., (1998). In the second-stage, we model the dynamics of the cross-sectional first-stage implied volatility surface coefficients by means of vector autoregression models. We find that not only the S&P 500 implied volatility surface can be successfully modeled, but also that its movements over time are highly predictable in a statistical sense. We then examine the economic significance of this statistical predictability with mixed findings. Whereas profitable delta-hedged positions can be set up that exploit the dynamics captured by the model under moderate transaction costs and when trading rules are selective in terms of expected gains from the trades, most of this profitability disappears when we increase the level of transaction costs and trade multiple contracts off wide segments of the IVS. This suggests that predictability of the time-varying S&P 500 implied volatility surface may be not inconsistent with market efficiency.

Implied volatility surface, predictability, trading rules

Abstract:
One key stylized fact in the empirical option pricing literature is the existence of an implied volatility surface (IVS). The usual approach consists of fitting a linear model linking the implied volatility to the time to maturity and the moneyness, for each cross section of options data. However, recent empirical evidence suggests that the parameters characterizing the IVS change over time. In this paper we study whether the resulting predictability patterns in the IVS coefficients may be exploited in practice. We propose a two-stage approach to modeling and forecasting the S&P 500 index options IVS. In the first stage we model the surface along the cross-sectional moneyness and time-to-maturity dimensions, similarly to Dumas et al. (1998). In the second-stage we model the dynamics of the cross-sectional first-stage implied volatility surface coefficients by means of vector autoregression models. We find that not only the S&P 500 implied volatility surface can be successfully modeled, but also that its movements over time are highly predictable in a statistical sense. We then examine the economic significance of this statistical predictability with mixed findings. Whereas profitable delta-hedged positions can be set up that exploit the dynamics captured by the model under moderate transaction costs and when trading rules are selective in terms of expected gains from the trades, most of this profitability disappears when we increase the level of transaction costs and trade multiple contracts off wide segments of the IVS. This suggests that predictability of the time-varying S&P 500 implied volatility surface may be not inconsistent with market efficiency.

Implied volatility surface, predictability, trading strategies

Abstract:
This paper proposes a new tractable approach to solving asset allocation problems in situations with a large number of risky assets which pose problems for standard approaches. Investor preferences are assumed to be defined over moments of the wealth distribution such as its mean, variance, skew and kurtosis. Time-variations in investment opportunities are represented by a flexible regime switching process. We develop analytical methods that only require solving a small set of difference equations and can be applied even in the presence of large numbers of risky assets. In the context of a four-moment international CAPM specification that relates stock returns in five regions to returns on a global market portfolio, we find evidence of distinct bull and bear states. Ignoring regimes, an unhedged US investor's optimal portfolio is strongly diversified internationally. The presence of regimes in the return distribution leads to a large increase in the investor's optimal holdings of US stocks as does the introduction of skew and kurtosis preferences. Our paper therefore offers an explanation of the strong home bias observed in US investors' asset allocation based on regime switching and skew and kurtosis preferences.

International asset allocation, regime switching, return predictability, skew and kurtosis preferences, home bias

Abstract:
This paper proposes a new tractable approach to solving multi-period asset allocation problems. We assume that investor preferences are defined over moments of the terminal wealth distribution such as its skew and kurtosis. Time-variations in investment opportunities are driven by a regime switching process that can capture bull and bear states. We develop analytical methods that only require solving a small set of difference equations and thus are very convenient to use. These methods are applied to a simple portfolio selection problem involving choosing between a stock index and a risk-free asset in the presence of bull and bear states in the return distribution. If the market is in a bear state, investors increase allocations to stocks the longer their time horizon. Conversely, in bull markets it is optimal for investors to decrease allocations to stocks the longer their investment horizon.

Optimal Asset Allocation, Regime Switching, Skew and Kurtosis Preference

Abstract:
This paper finds strong evidence of time-variations in the joint distribution of returns on a stock market portfolio and portfolios tracking size- and value effects. Mean returns, volatilities and correlations between these equity portfolios are found to be driven by underlying regimes that introduce short-run market timing opportunities for investors. The magnitude of the premia on the size and value portfolios and their hedging properties are found to vary across regimes. Regimes are shown to have a large impact both on the optimal asset allocation-especially under rebalancing-and on investors' utility. Regimes also have a considerable impact on hedging demands, which are positive when the investor starts from more favorable regimes and negative when starting from bad states. Recursive out-of-sample forecasting experiments show that portfolio strategies based on models that account for regimes dominate single-state benchmarks.

G12, G11, C32, hedging demands, optimal portfolio choice, regimes, size and value portfolios

Abstract:
This paper finds strong evidence of time-variations in the joint distribution of returns on a stock market portfolio and portfolios tracking size- and value effects. Mean returns, volatilities and correlations between these equity portfolios are found to be driven by underlying regimes that introduce short-run market timing opportunities for investors. The magnitude of the premia on the size and value portfolios and their hedging properties are found to vary across regimes. Regimes are shown to have a large impact on the optimal asset allocation - especially under rebalancing - and on investors' utility. Regimes also have a considerable impact on hedging demands, which are positive when the investor starts from more favorable regimes and negative when starting from bad states. Recursive out-of-sample forecasting experiments show that portfolio strategies based on models that account for regimes dominate single-state benchmarks.

optimal portfolio choice, regimes, hedging demands, size and value portfolios

Abstract:
This paper studies asset allocation decisions in the presence of regime switching in asset returns. We find evidence that four separate regimes - characterized as crash, slow growth, bull and recovery states - are required to capture the joint distribution of stock and bond returns. Optimal asset allocations vary considerably across these states and change over time as investors revise their estimates of the state probabilities. In the crash state, buy-and-hold investors allocate more of their portfolio to stocks the longer their investment horizon, while the optimal allocation to stocks declines as a function of the investment horizon in bull markets. The joint effects of learning about state probabilities and predictability of asset returns from the dividend yield give rise to a non-monotonic relationship between the investment horizon and the demand for stocks. Out-of-sample forecasting experiments confirm the economic importance of accounting for the presence of regimes in asset returns.

Regime switching, Portfolio choice, Predictability

Abstract:
This paper studies asset allocation decisions in the presence of regime switching in asset returns. We find evidence that four separate regimes - characterized as crash, slow growth, bull and recovery states - are required to capture the joint distribution of stock and bond returns. Optimal asset allocations vary considerably across these states and change over time as investors revise their estimates of the state probabilities. In the crash state, buy-and-hold investors allocate more of their portfolio to stocks the longer their investment horizon, while the optimal allocation to stocks declines as a function of the investment horizon in bull markets. The joint effects of learning about state probabilities and predictability of asset returns from the dividend yield give rise to a non-monotonic relationship between the investment horizon and the demand for stocks. Welfare costs from ignoring regime switching can be substantial even after accounting for parameter uncertainty. Out-of-sample forecasting experiments confirm the economic importance of accounting for the presence of regimes in asset returns.

regime switching, portfolio choice, predictability

Abstract:
This paper shows that many of the empirical biases of the Black and Scholes option pricing model can be explained by Bayesian learning effects. In the context of an equilibrium model where dividend news evolve on a binomial lattice with unknown but recursively updated probabilities we derive closed-form pricing formulas for European options. Learning is found to generate asymmetric skews in the implied volatility surface and systematic patterns in the term structure of option prices. Data on S&P 500 index option prices is used to back out the parameters of the underlying learning process and to predict the evolution in the cross-section of option prices. The proposed model leads to lower out-of-sample forecast errors and smaller hedging errors than a variety of alternative option pricing models, including Black-Scholes and a GARCH model.

Rational learning, Black-Scholes biases, option pricing

Abstract:
This Paper shows that many of the empirical biases of the Black and Scholes option pricing model can be explained by Bayesian learning effects. In the context of an equilibrium model where dividend news evolves on a binomial lattice with unknown but recursively updated probabilities, we derive closed-form pricing formulas for European options. Learning is found to generate asymmetric skews in the implied volatility surface and systematic patterns in the term structure of option prices. Data on S&P 500 index option prices is used to back out the parameters of the underlying learning process and to predict the evolution in the cross-section of option prices. The proposed model leads to lower out-of-sample forecast errors and smaller hedging errors than a variety of alternative option pricing models, including Black-Scholes and a GARCH model.

Option prices, Black-Scholes option pricing model, Bayesian learning

Abstract:
This paper shows that many of the empirical biases of the Black and Scholes option pricing model can be explained by Bayesian learning effects. In the context of an equilibrium model where dividend news evolve on a binomial lattice with unknown but recursively updated probabilities we derive closed- form pricing formulas for European options. Learning is found to generate asymmetric skews in the implied volatility surface and systematic patterns in the term structure of option prices. Data on S&P 500 index option prices is used to back out the parameters of the underlying learning process and to predict the evolution in the cross-section of option prices. The proposed model leads to lower out-of-sample forecast errors and smaller hedging errors than a variety of alternative option pricing models, including Black-Scholes.

Abstract:
We show that predictable covariances between means and variances of stock returns may have a first order effect on portfolio composition. In an international asset menu that includes both European and North American small capitalization equity indices,we find that a three-state, heteroskedastic regime switching VAR model is required to provide a good fit to weekly return data and to accurately predict the dynamics in the joint density of returns. As a result of the non-linear dynamic features revealed by the data, small cap portfolios become riskier in bear markets, i.e., display negative co-skewness with other stock indices. Because of this property, a power utility investor ought to hold a well-diversified portfolio, despite the high risk premium and Sharpe ratios offered by small capitalization stocks. On the contrary, small caps command large optimal weights when the investor ignores variance risk, by incorrectly assuming joint normality of returns.

Intertemporal portfolio choice, Return predictability, Co-skewness and co-kurtosis, International portfolio diversification

Abstract:
We show that predictable covariances between means and variances of stock returns may have a first order effect on portfolio composition. In an international asset menu that includes both European and North American small capitalization equity indices, we find that a three-state, heteroskedastic regime switching VAR model is required to provide a good fit to weekly return data and to accurately predict the dynamics in the joint density of returns. As a result of the non-linear dynamic features revealed by the data, small cap portfolios become riskier in bear markets, i.e. display negative co-skewness with other stock indices. Because of this property, a power utility investor ought to hold a well diversified portfolio, despite the high risk premium and Sharpe ratios offered by small capitalization stocks. On the contrary small caps command large optimal weights when the investor ignores variance risk, by incorrectly assuming joint normality of returns. These results provide the missing partial equilibrium rationale for the presence of co skewness in the empirical asset pricing models that have been proposed to explain the cross-section of stock returns.

intertemporal portfolio choice, return predictability, co-skewness and co-kurtosis, international portfolio diversification

Abstract:
We analyze the volatility surface vs. moneyness and time to expiration implied by MIBO options written on the MIB30, the most important Italian stock index. We specify and fit a number of models of the implied volatility surface and find that it has a rich and interesting structure that strongly departs from a constant volatility, Black-Scholes benchmark. This result is robust to alternative econometric approaches, including generalized least squares approaches that take into account both the panel structure of the data and the likely presence of heteroskedasticity and serial correlation in the random disturbances. Finally we show that the degree of pricing efficiency of this options market can strongly condition the results of the econometric analysis and therefore our understanding of the pricing mechanism underlying observed MIBO option prices. Applications to value-at-risk and portfolio choice calculations illustrate the importance of using arbitrage-free data only.

Implied volatility, option pricing, no-arbitrage conditions, volatility models

Abstract:
This paper studies strategic asset allocation and consumption choice in the presence of regime switching in asset returns. We find evidence that four separate regimes - characterized as crash, slow growth, bull and recovery states - are required to capture the joint distribution of stock and bond returns. Optimal asset allocations vary considerably across these states - both among bonds and stocks and among large and small stocks - and change over time as investors revise their estimates of the underlying state probabilities. In the crash state investors always allocate more of their portfolio to stocks the longer their investment horizon, while the optimal allocation to stocks declines as a function of the investment horizon in bull markets. The joint effects of learning about the underlying state probabilities and predictability of asset returns from the dividend yield give rise to a non-monotonic relationship between the investment horizon and the demand for stocks. Consumption-to-wealth ratios are found to depend on the underlying state and welfare costs from ignoring regime switching are substantial even after accounting for parameter uncertainty. Out-of-sample forecasting experiments confirm the economic importance of accounting for the presence of regimes in asset returns.

Asset allocation, regime wwitching, bull and bear, optimal consumption, portfolio choice

Abstract:
Prior studies have shown that investment banking affiliations place pressure on analysts to produce optimistic recommendations on the investment bank's stock-clients. Our analysis of a large sample of recommendations issued from 1995 through 2003 indicates that a mutual fund affiliation also affects analysts' research. That is, analysts are likely to look favorably at stocks held by the affiliated mutual funds. Controlling for a variety of factors including the investment banking affiliation, we find that the greater the portfolio weight of a stock for the affiliated mutual funds, the more optimistic the analyst rating becomes when compared to the consensus. Reputation partly restrains the optimism of analyst recommendations. In fact, the presence of other institutional investors as shareholders of the recommended stocks curbs analyst optimism. Nevertheless, from 1999 through 2001, star analysts report the most optimism when they recommend stocks in the portfolios of affiliated mutual funds.

analyst coverage, ratings, mutual funds

Abstract:
Prior studies have shown that the investment banking affiliation spawns pressure on analysts to produce optimistic recommendations on the investment bank's stock-clients. Our analysis of a large sample of recommendations issued from 1995 through 2003 indicates that the mutual fund affiliation as well significantly affects analysts' research. That is, analysts are likely not only to provide research but also to look favorably at stocks held by the affiliated mutual funds. Controlling for a variety of factors including the investment banking affiliation, we find that the greater the portfolio weight of a stock for the affiliated mutual fund family, the more optimistic the analyst rating becomes when compared to the consensus. All-star analysts report the most optimism when they recommend stocks in the portfolios of the affiliated mutual funds. However, the presence of other institutional investors as shareholders of the recommended stocks curbs analyst optimism.

analyst coverage, ratings, mutual funds

Abstract:
This paper models the joint distribution of stock and bond returns as a multivarate Markov switching process. We found evidence that four states are needed to capture the joint distribution of returns on these asset classes. This gives rise to rich patterns in the term structure of risk measures such as the Value at Risk and expected shortfall as a function of the state probabilities and investment horizon. Compared to a Gaussian IID and a multivariate GARCH specification, in general the regime switching model suggests higher tail losses and expected shortfall. We also study real-time measures of risk and out-of-sample forecasts generated by the proposed econometric specification.

Abstract:
This paper studies the relationship between civil war and the value of firms in a poor, resource abundant country using microeconomic data for Angola. We focus on diamond mining firms and conduct an event study on the sudden end of the conflict, marked by the death of the rebel movement leader in 2002. We find that the stock market perceived this event as "bad news" rather than "good news" for companies holding concessions in Angola, as their abnormal returns declined by 4 percentage points. The event had no effect on a control portfolio of otherwise similar diamond mining companies. This finding is corroborated by other events and by the adoption of alternative methodologies. We interpret our findings in the light of conflict-generated entry barriers, government bargaining power and transparency in the licensing process.

Civil war, event studies, rent-seeking, Angola

Abstract:
This paper studies the relationship between civil war and the value of firms in a poor, resource abundant country using microeconomic data for Angola. We focus on diamond mining firms and conduct an event study on the sudden end of the conflict, marked by the death of the rebel movement leader in 2002. We find that the stock market perceived this event as "bad news" rather than "good news" for companies holding concessions in Angola, as their abnormal returns declined by 4 percentage points. The event had no effect on a control portfolio of otherwise similar diamond mining companies. This finding is corroborated by other events and by the adoption of alternative methodologies. We interpret our findings in the light of conflict-generated entry barriers, government bargaining power and transparency in the licensing process.

Angola, civil war, rent seeking, event studies

Abstract:
We analyze the pricing and informational efficiency of the Italian market for options written on the most important stock index, the MIB30. We find several indications inconsistent with the hypothesis that the Italian MIBO is an efficient market. We report that a striking percentage of the data consists of option prices violating basic no-arbitrage conditions. This percentage declines but never becomes negligible when we relax the no-arbitrage restrictions to accommodate for the presence of bid/ask spreads and other frictions. The result holds in general for all levels of moneyness and time to maturity. We also investigate the informational efficiency of the MIBO and conclude that option prices are poor predictors of the volatility of MIB30 returns. This conclusion is robust to a number of statistical and sampling methods.

Option pricing, arbitrage, informational efficiency, MIB30 index

Abstract:
This paper develops a flexible approach to combine forecasts of future spot rates with forecasts from time-series models or macroeconomic variables. We find empirical evidence that accounting for both regimes in interest rate dynamics and combining forecasts from different models helps improve the out-of-sample forecasting performance for US short-term rates. Imposing restrictions from the expectations hypothesis on the forecasting model are found to help at long forecasting horizons.

Forecast combinations, regime switches, short term interest rates, expectations hypothesis.

Abstract:
This paper develops a flexible approach to combine forecasts of future spot rates with forecasts from time-series models or macroeconomic variables. We find empirical evidence that accounting for both regimes in interest rate dynamics and combining forecasts from different models helps improve the out-of-sample forecasting performance for US short-term rates. Imposing restrictions from the expectations hypothesis on the forecasting model are found to help at long forecasting horizons.

forecast combinations, regime switching, interest rates

Abstract:
This paper considers a variety of econometric models for the joint distribution of US stock and bond returns in the presence of regime switching dynamics. While simple two- or three-state models capture the univariate dynamics in bond and stock returns, a more complicated four state model with regimes characterized as crash, slow growth, bull and recovery states is required to capture their joint distribution. The transition probability matrix of this model has a very particular form. Exits from the crash state are almost always to the recovery state and occur with close to 50 percent chance suggesting a bounce-back effect from the crash to the recovery state.

Regime switching, stock and bond return predictability, nonlinear modeling

Abstract:
This paper considers a variety of econometric models for the joint distribution of US stock and bond returns in the presence of regime switching dynamics. While simple two- or three-state models capture the univariate dynamics in bond and stock returns, a more complicated four state model with regimes characterized as crash, slow growth, bull and recovery states is required to capture their joint distribution. The transition probability matrix of this model has a very particular form. Exits from the crash state are almost always to the recovery state and occur with close to 50 percent chance suggesting a bounce-back effect from the crash to the recovery state.

Regime switching, stock and bond return predictability, nonlinear modeling

Abstract:
We calculate optimal portfolio choices for a long-horizon, risk-averse investor who diversifies among European stocks, bonds, real estate, and cash, when excess asset returns are predictable. Simulations are performed for scenarios involving different risk aversion levels, horizons, and statistical models capturing predictability in risk premia. Importantly, under one of the scenarios, the investor takes into account the parameter uncertainty implied by the use of estimated coefficients to characterize predictability. We find that real estate ought to play a significant role in optimal portfolio choices, with weights between 12 and 44 percent. Under plausible assumptions, the welfare costs of either ignoring predictability or restricting portfolio choices to traditional financial assets only are found to be in the order of 150-300 basis points per year. These results are robust to changes in the benchmarks and in the statistical framework.

Optimal asset allocation, Real estate, Predictability, Parameter uncertainty

Abstract:
We show that when in Lucas model the process for dividends is described by a lattice tree subject to infrequent but observable structural breaks, in equilibrium recursive rational learning may inflate the equity risk premium and reduce the risk-free interest rate for low levels of risk aversion. The key condition for these results to obtain is the presence of sufficient initial pessimism. The relevance of these findings is magnified by the fact that under full information our artificial economy cannot generate asset returns matching the empirical evidence for any positive relative risk aversion.

Rational learning, equilibrium asset returns, structural breaks

Abstract:
We systematically examine the comparative predictive performance of a number of linear and non-linear models for stock and bond returns in the G7 countries. Besides Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STAR) regime switching models, we also estimate univariate models in which conditional heteroskedasticity is captured by a GARCH and in which predicted volatilities appear in the conditional mean function. Although we fail to find a consistent winner/out performer across all countries and markets, it turns out that capturing non-linear effects may be key to improve forecasting. U.S. and U.K. asset return data are "special" in the sense that good predictive performance seems to require that non-linear dynamics be modeled, especially using a Markov switching framework. Although occasionally stock and bond return forecasts for other G7 countries also appear to benefit from non-linear modeling (especially of TAR and STAR type), data from France, Germany, and Italy imply that the best predictive model is often one of the simple benchmarks, such as the random walk and univariate auto-regressions. U.S. and U.K. markets also provide the only data for which we find statistically significant differences between forecasting models. Results appear to be remarkably stable over time, robust to changes in the loss function used in statistical evaluations as well as to the methodology employed to perform pairwise comparisons.

Non-linearities, regime switching, threshold predictive regressions, forecasting, predictability in financial returns

Abstract:
This paper characterizes equilibrium asset prices under adaptive, rational and Bayesian learning schemes in a model where dividends evolve on a binomial lattice. The properties of equilibrium stock and bond prices under learning are shown to differ significantly. Learning causes the discount factor and risk-neutral probability measure to become path-dependent and introduces serial correlation and volatility clustering in stock returns. We also derive conditions under which the expected value and volatility of stock prices will be higher under learning than under full information. Finally, we investigate restrictions on prior beliefs under which Bayesian and rational learning lead to identical prices and show how the results can be generalized to more complex settings where dividends follow either multi-state i.i.d. distributions or multi-state Markov chains.

Rational learning, adaptive learning, Bayesian updating, lattice models, asset prices

Abstract:
This paper characterizes equilibrium asset prices under adaptive, rational and Bayesian learning schemes in a model where dividends evolve on a binomial lattice. The properties of equilibrium stock and bond prices under learning are shown to differ significantly. Learning causes the discount factor and risk-neutral probability measure to become path-dependent and introduces serial correlation and volatility clustering in stock returns. We also derive conditions under which the expected value and volatility of stock prices will be higher under learning than under full information. Finally, we investigate restrictions on prior beliefs under which Bayesian and rational learning lead to identical prices and show how the results can be generalized to more complex settings where dividends follow either multi-state i.i.d. distributions or multi-state Markov chains.

Rational learning, adaptive learning, Bayesian updating, lattice models, asset prices.

Abstract:
Despite its important role in monetary policy and finance, the expectations hypothesis (EH) of the term structure of interest rates has received virtually no empirical support. The empirical failure of the EH was attributed to a variety of econometric biases associated with the single-equation models used to test it; however, none account for it. Moreover, Sarno, Valente, and Thornton (2006) find that the EH is readily rejected using more powerful multi-equation Lagrange Multiplier test developed by Bekaert and Hodrick (2001). The ubiquitous rejection of the EH raise the possibility that its failure is fundamental rather than econometric. This paper analyzes the EH by focusing on its fundamental tenet— - the predictability of the short-term rate. This is done by comparing h-month ahead forecasts for the 1-month Treasury yield implied by the EH with the forecasts from random-walk, Diebold and Lei (2003), and Duffee (2002) models. The evidence suggests that the failure of the EH is likely a consequence of market participants' inability to predict the short-term rate.

Expectations theory, Random walk hypothesis, Time-varying risk premium

Abstract:
This paper characterizes the term structure of risk measures such as Value at Risk (VaR) and expected shortfall under different econometric approaches including multivariate regime switching, GARCH-in-mean models with student-t errors, two-component GARCH models and a non-parametric bootstrap. We show how to derive the risk measures for each of these models and document large variations in term structures across econometric specifications. An out-of-sample forecasting experiment applied to stock, bond and cash portfolios suggests that the best model is asset - and horizon specific but that the bootstrap and regime switching model are best overall for VaR levels of 5% and 1%, respectively.

Term structure of risk, nonlinear econometric models, simulation methods

Abstract:
This Paper characterizes the term structure of risk measures such as Value at Risk (VaR) and expected shortfall under different econometric approaches including multivariate regime switching, GARCH-in-mean models with student-t errors, two-component GARCH models and a non-parametric bootstrap. We show how to derive the risk measures for each of these models and document large variations in term structures across econometric specifications. An out-of-sample forecasting experiment applied to stock, bond and cash portfolios suggests that the best model is asset and horizon specific but that the bootstrap and regime switching model are best overall for VaR levels of 5% and 1%, respectively.

Term structure of risk, nonlinear econometric models, simulation models

Abstract:
This paper characterizes the term structure of risk measures such as Value at Risk (VaR) and expected shortfall under different econometric approaches including multivariate regime switching, GARCH-in-mean models with student-t errors, two-component GARCH models and a non-parametric bootstrap. We show how to derive the risk measures for each of these models and document large variations in term structures across econometric specifications. An out-of-sample forecasting experiment applied to stock, bond and cash portfolios suggests that the best model is asset - and horizon specific but that the bootstrap and regime switching model are best overall for VaR levels of 5% and 1%, respectively.

Term structure of risk, nonlinear econometric models, simulation methods

Abstract:
This paper develops a two-country OLG model under the assumption that investors are on a Bayesian learning path. While investors from both countries receive identical information flows, domestic investors start off with less precise prior beliefs concerning foreign fundamentals. On a learning path, differences in beliefs and estimation risk generate portfolio biases similar to those observed empirically: home bias in equity portfolios and trend-chasing in international flows. In addition, due to the higher volatility of the estimates of foreign state variables, our model produces excessive turnover in foreign securities as reported by Tesar and Werner (1995). We use real GDP data for the US and Europe to calibrate the model and produce simulations that show that under the assumption of a financial liberalization during the 1970s, substantial home bias and excess turnover should have been observed in the subsequent years.

Home country bias, International Asset Allocation, Bayesian learning

Abstract:
We estimate a number of multivariate regime switching VAR models on a long monthly U.S. data set for eight variables that include excess stock and bond returns, the real T-bill yield, predictors used in the finance literature (default spread and the dividend yield), and three macroeconomic variables (inflation, industrial production growth, and a measure of real money growth). Heteroskedasticity may be accounted for by making the covariance matrix a function of the regime. We find evidence of four regimes and of time-varying covariances. We show that the best in-sample fit is provided by a four state model in which the VAR(1) component fails to be regime-dependent. We interpret this as evidence that the dynamic linkages between financial markets and the macroeconomy have been stable over time. The four-state model can be helpful in forecasting applications and provides one-step ahead predicted Sharpe ratios.

Predictability, Multivariate Regime Switching, Predictive Density Tests, Sharpe Ratios

Abstract:
We use multivariate regime switching vector autoregressive models to characterize the time-varying linkages among the Irish stock market, one of the top world performers of the 1990s, and the US and UK stock markets. We find that two regimes, characterized as bear and bull states, are required to characterize the dynamics of excess equity returns both at the univariate and multivariate level. This implies that the regimes driving the small open economy stock market are largely synchronous with those typical of the major markets. However, despite the existence of a persistent bull state in which the correlations among Irish and UK and US excess returns are low, we find that state comovements involving the three markets are so relevant to reduce the optimal mean-variance weight carried by ISEQ stocks to at most one-quarter of the overall equity portfolio. We compute time-varying Sharpe ratios and recursive mean-variance portfolio weights and document that a regime switching framework produces out-of-sample portfolio performance that outperforms simpler models that ignore regimes. These results appear robust to endogenizing the effects of dynamics in spot exchange rates on excess stock returns.

international portfolio diversification, multivariate regime switching, national stock markets comovements, Sharpe ratios

Abstract:
We address one interesting case - the predictability of excess US asset returns from macroeconomic factors within a flexible regime switching VAR framework - in which the presence of regimes may lead to superior forecasting performance from forecast combinations. After having documented that forecast combinations provide gains in prediction accuracy and these gains are statistically significant, we show that combinations may substantially improve portfolio selection. We find that the best performing forecast combinations are those that either avoid estimating the pooling weights or that minimize the need for estimation. In practice, we report that the best performing combination schemes are based on the principle of relative, past forecasting performance. The economic gains from combining forecasts in portfolio management applications appear to be large.

Forecast Combination, Predictability, Multivariate Regime Switching, Portfolio Performance

Abstract:
We calculate optimal portfolio choices for a long-horizon, risk-averse investor who diversifies among European stocks, bonds, real estate, and cash, when excess asset returns are predictable. Simulations are performed for scenarios involving different risk aversion levels, horizons, and statistical models capturing predictability in risk premia. Importantly, under one of the scenarios, the investor takes into account the parameter uncertainty implied by the use of estimated coefficients to characterize predictability. We find that real estate ought to play a significant role in optimal portfolio choices, with weights between 12 and 44 percent. Under plausible assumptions, the welfare costs of either ignoring predictability or restricting portfolio choices to traditional financial assets only are found to be in the order of 150-300 basis points per year. These results are robust to changes in the benchmarks and in the statistical framework.

optimal asset allocation, real estate, predictability, parameter uncertainty

Abstract:
We calculate optimal portfolio choices for a long-horizon, risk-averse investor who diversifies among European stocks, bonds, real estate, and cash, when excess asset returns are predictable. Simulations are performed for scenarios involving different risk aversion levels, horizons, and statistical models capturing predictability in risk premia. Importantly, under one of the scenarios, the investor takes into account the parameter uncertainty implied by the use of estimated coefficients to characterize predictability. We find that real estate ought to play a significant role in optimal portfolio choices, with weights between 12 and 44 percent. Under plausible assumptions, the welfare costs of either ignoring predictability or restricting portfolio choices to traditional financial assets only are found to be in the order of 150-300 basis points per year. These results are robust to changes in the benchmarks and in the statistical framework.

optimal asset allocation, real estate, predictability, parameter uncertainty

Abstract:
Research has documented that the first report an investment bank affiliated analyst issues on a newly listed stock tends to be favorable. Our analysis of 16,824 relationships between analyst teams and established listed companies during 1995-2003 indicates that analyst coverage decisions of seasoned stocks are influenced by their affiliations with investment banks and mutual funds. Controlling for market returns, stock characteristics, and a variety of performance indicators, we find analysts are more likely to issue favorable reports when the stock is held by affiliated mutual funds. The more invested by affiliated mutual funds, the more optimistic the analyst rating compared to the consensus.

Universal banks, analyst coverage, ratings, analyst coverage, analyst ratings, mutual funds

Abstract:
This paper studies the effects of conflict onset on asset markets applying the event study methodology. We consider a sample of 112 conflicts during the period 1974-2004 and find that a sizeable fraction of them had a significant impact on stock market indices and on major commodity prices. Furthermore, our results suggest that we are more likely to see investor reactions in response to conflicts that occur in highly polarized settings, possibly because the expected duration and intensity of the conflict is higher.

Conflict onset, Event study, Asset markets, Polarization

Abstract:
In the presence of infrequent but observable structural breaks, we show that a model in which the representative agent is on a rational learning path concerning the real consumption growth process can generate high equity premia and low risk-free interest rates. In fact, when the model is calibrated to U.S. consumption growth data, average risk premia and bond yields similar to those displayed by post-depression (1938-1999) U.S. historical experience are generated for low levels of risk aversion. Even ruling out pessimistic beliefs, recursive learning inflates the equity premium without requiring a strong curvature of the utility function. Simulations reveal that other moments of equilibrium asset returns are easily matched, chiefly excess volatility and the presence of ARCH effects. These findings are robust to a number of details of the simulation experiments, such as the number and dating of the breaks.

Equity premium, rational learning, structural breaks, pessimism

Abstract:
We use multivariate regime switching vector autoregressive models to characterize the time-varying linkages among short-term interest rates (monetary policy) and stock returns in the Irish, the US and UK markets. We find that two regimes, characterized as bear and bull states, are required to characterize the dynamics of returns and short-term rates. This implies that we cannot reject the hypothesis that the regimes driving the markets in the small open economy are largely synchronous with those typical of the major markets. We compute time-varying Sharpe ratios and recursive mean-variance portfolio weights and document that a regime switching framework produces out-of-sample portfolio performance that outperforms simpler models that ignore regimes. Interestingly, the portfolio shares derived under regime switching dynamics implies a fairly low committment to the Irish market, in spite of its brilliant unconditional risk-return trade-off.

multivariate regime switching; Sharpe ratio; time-varying predictability

Abstract:
In the context of an international portfolio diversification problem, we find that small capitalization equity portfolios become riskier in bear markets, i.e. display negative co-skewness with other stock indices and high co-kurtosis. Because of this feature, a power utility investor ought to hold a well-diversified portfolio, despite the high risk premium and Sharpe ratios offered by small capitalization stocks. On the contrary small caps command large optimal weights when the investor ignores variance risk, by incorrectly assuming joint normality of returns. The dominant factor in inducing such shifts in optimal weights is represented by the co-skewness, the predictable, time-varying covariance between returns and volatilities. We calculate that if an investor were to ignore co-skewness and co-kurtosis risk, he would suffer a certainty-equivalent reduction in utility equal to 300 basis points per year under the steady-state distribution for returns. Our results are qualitatively robust when both European and North American small caps are introduced in the analysis. Therefore this paper offers robust evidence that predictable covariances between means and variances of stock returns may have a first order effect on portfolio composition.

intertemporal portfolio choice, return predictability, co-skewness and co-kurtosis, international portfolio diversification

Abstract:
Welfare gains to long-horizon investors may derive from time diversification that exploits non-zero intertemporal return correlations associated with predictable returns. Real estate may thus become more desirable if its returns are negatively serially correlated. While it could be important for long horizon investors, time diversification has been mostly investigated in asset menus without real estate and focusing on in-sample experiments. This paper evaluates ex post, out-of-sample gains from diversification when E-REITs belong to the investment opportunity set. We find that diversification into REITs increases both the Sharpe ratio and the certainty equivalent of wealth for all investment horizons and for both Classical and Bayesian (who account for parameter uncertainty) investors. The increases in Sharpe ratios are often statistically significant. However, the out-of sample average Sharpe ratio and realized expected utility of long-horizon portfolios are frequently lower than that of a one-period portfolio, which casts doubts on the value of time diversification.

real time asset allocation, real estate, ex post performance, predictability, parameter uncertainty

Abstract:
We calculate the ex-post, realized portfolio performance for an investor who diversifies among U.S. stocks, bonds, real estate indirect investment vehicles (E-REITS), and cash. Simulations are performed for two alternative asset allocation frameworks - classical and Bayesian - and for scenarios involving two different samples and six different investment horizons. Interestingly, the ex-post welfare cost of restricting portfolio choice to traditional financial assets (i.e., stocks, bonds, and cash) only is found to be positive in all scenarios for a Bayesian investor. On the contrary, substitution of E-REITS for stocks in optimal portfolios turns out to reduce ex-post portfolio performance over the nineties and for a Classical investor who ignores parameter estimation uncertainty.

Optimal asset allocation, Real estate, Parameter uncertainty, Out-of-sample performance

Abstract:
The 2007-2008 financial crises has made it painfully obvious that markets may quickly turn illiquid. Moreover, recent experience has taught us that distress and lack of active trading can jump “around” between seemingly unconnected parts of the financial system contributing to transforming isolated shocks into systemic panic attacks. We develop a simple two-period model populated by both standard expected utility maximizers and by ambiguity-averse investors that trade in the market for a risky asset. We show that, provided there is a sufficient amount of ambiguity, market break-downs where large portions of traders withdraw from trading are endogeneous and may be triggered by modest re-assessments of the range of possible scenarios on the performance of individual securities. Risk premia (spreads) increase with the proportion of traders in the market who are averse to ambiguity. When we analyze the effect of policy actions, we find that when a market has fallen into a state of impaired liquidity, bringing the market back to orderly functioning through a reduction in the amount of perceived ambiguity may cause further reductions in equilibrium prices. Finally, our model provides stark indications against the idea that policy makers may be able to “inflate” their way out of a financial crisis.

ambiguity, ambiguity-aversion, participation, liquidity, asset pricing

Abstract:
This Paper studies the relationship between civil war and private investment in a poor, resource abundant country using microeconomic data for Angola. We focus on diamond mining firms and conduct an event study on the sudden end of the conflict, marked by the death of the rebel movement leader in 2002. We find that the stock market perceived this event as 'bad news' rather than 'good news' for companies holding concessions in Angola, as their abnormal returns declined by 4 percentage points. The event had no effect on a control portfolio of otherwise similar diamond mining companies. This finding is corroborated by other events and by the adoption of alternative methodologies. We also use nonparametric techniques with daily data on the intensity of conflict, and find that moderate levels of violence increased the abnormal returns of the 'Angolan' portfolio. We interpret our results in the light of the widespread rent seeking in the Angolan mineral industry.

Civil war, event studies, rent-seeking, Angola

Abstract:
Despite its important role in monetary policy and finance, the expectations hypothesis (EH) of the term structure of interest rates has received virtually no empirical support. The empirical failure of the EH was attributed to a variety of econometric biases associated with the single-equation models used to test it; however, none account for it. This paper analyzes the EH by focusing on its fundamental tenet - the predictability of the short-term rate. This is done by comparing h-month ahead forecasts for the 1- and 3-month Treasury yields implied by the EH with the forecasts from random-walk, Diebold and Lei (2006), and Duffee (2002) models. The evidence suggests that the failure of the EH is likely a consequence of market participants' inability to predict the short-term rate.

expectations theory, random walk, time-varying risk premium

Abstract:
This paper presents results from recursive modeling of nonlinear dynamics in UK stock returns. A specification search suggests a two-state model and we demonstrate the ability of this model to capture time-varying volatility, skew and kurtosis in UK stock returns. An out-of-sample forecasting experiment confirms the strong statistical evidence of nonlinearity and shows that accounting for regimes leads to improved forecasting performance.

Abstract:
This paper develops a two-country overlapping-generations (OLG) model under the assumption that investors are on a learning path. While investors from both countries receive identical information flows, domestic investors start off with less precise prior beliefs concerning foreign fundamentals. On a learning path, differences in beliefs and estimation risk generate portfolio biases that match the empirical evidence: home bias in equity portfolios and trend-chasing in international flows. In addition, due to the higher volatility of the estimates of foreign state variables, our model produces excessive turnover in foreign securities. We calibrate the model on the historical path of quarterly real GDP data for the US and Europe. Under the assumption of a financial liberalization in the 1970s, the model produces preference for domestic securities and turnover.

Abstract:
We analyse the pricing and informational efficiency of the Italian market for options written on the most important stock index, the MIB30. We report that a striking percentage of the data consists of option prices violating basic no-arbitrage conditions. This percentage declines when we relax the no-arbitrage restrictions to accommodate the presence of bid/ask spreads and other frictions but never becomes negligible. We also investigate the informational efficiency of the MIBO and conclude that option prices are poor predictors of the volatility of MIB30 returns. This conclusion is robust to a number of statistical and sampling methods.

Abstract:
This paper presents evidence of persistent 'bull' and 'bear' regimes in UK stock and bond returns and considers their economic implications from the perspective of an investor's portfolio allocation. We find that the perceived state probability has a large effect on the optimal asset allocation, particularly at short investment horizons. If ignored, the presence of such regimes gives rise to substantial welfare costs. Parameter estimation uncertainty, while clearly important, does not overturn the conclusion that predictability in the return distribution linked to the presence of bull and bear states has a significant effect on investors' strategic asset allocation.

Abstract:
Welfare gains to long-horizon investors may derive from time diversification that exploits nonzero intertemporal return correlations associated with predictable returns. Real estate may thus become more desirable if its returns are negatively serially correlated. While it could be important for long-horizon investors, time diversification has been mostly investigated in asset menus without real estate and focusing on in-sample experiments. This article evaluates, ex post, the out-of-sample gains from diversification when equity real estate investment trusts (REITs) belong to the investment opportunity set. We find that diversification into REITs increases both the Sharpe ratio and the certainty equivalent of wealth for all investment horizons and for both classical and Bayesian (who account for parameter uncertainty) investors. The increases in Sharpe ratios are often statistically significant. However, the out-of-sample average Sharpe ratio and realized expected utility of long-horizon portfolios are frequently lower than that of a one-period portfolio, which casts doubt on the value of time diversification.

Abstract:
This paper investigates the international asset allocation effects of time-variations in higher-order moments of stock returns such as skewness and kurtosis. In the context of a four-moment International Capital Asset Pricing Model (ICAPM) specification that relates stock returns in five regions to returns on a global market portfolio and allows for time-varying prices of covariance, co-skewness, and co-kurtosis risk, we find evidence of distinct bull and bear regimes. Ignoring such regimes, an unhedged US investor's optimal portfolio is strongly diversified internationally. The presence of regimes in the return distribution leads to a substantial increase in the investor's optimal holdings of US stocks, as does the introduction of skewness and kurtosis preferences.

G12, F30, C32

Abstract:
This paper develops a flexible approach to combine forecasts of future spot rates with forecasts from time-series models or macroeconomic variables. We find empirical evidence that accounting for both regimes in interest rate dynamics and combining forecasts from different models helps improve the out-of-sample forecasting performance for US short-term rates. Imposing restrictions from the expectations hypothesis on the forecasting model are found to help at long forecasting horizons.

Forecast combinations, term structure of interest rates

Abstract:
We calculate the ex-post, realized portfolio performance for an investor who diversifies among U.S. stocks, bonds, real estate indirect investment vehicles (E-REITS), and cash. Simulations are performed for two alternative asset allocation frameworks - classical and Bayesian - and for scenarios involving two different samples and six different investment horizons. Interestingly, the ex-post welfare cost of restricting portfolio choice to traditional financial assets (i.e., stocks, bonds, and cash) only is found to be positive in all scenarios for a Bayesian investor. On the contrary, substitution of E-REITS for stocks in optimal portfolios turns out to reduce ex-post portfolio performance over the nineties and for a Classical investor who ignores parameter estimation uncertainty.

Optimal asset allocation; Real estate; Parameter uncertainty; Out-of-sample performance

Abstract:
We show that in a Lucas endowment economy in which the process for dividends is described by a lattice tree subject to infrequent but observable structural breaks, in equilibrium recursive rational learning may inflate the equity risk premium and reduce the risk-free interest rate for low levels of risk aversion. The key condition for these results to obtain is the presence of sufficient initial pessimism. The relevance of these findings is magnified by the fact that under full information our artificial economy cannot generate asset returns matching the empirical evidence for any positive relative risk aversion.

Rational learning, equity premium, structural breaks