Solving non-linear stochastic models by parameterizing expectations: An application to asset pricing with production

A new algorithm called the parameterized expectations approach(PEA) for solving dynamic stochastic models under rational expectationsis developed and its advantages and disadvantages are discussed. Thisalgorithm can, in principle, approximate the true equilibrium arbitrarilywell. Also, this algorithm works from the Euler equations, so that theequilibrium does not have to be cast in the form of a planner's problem.Monte--Carlo integration and the absence of grids on the state variables,cause the computation costs not to go up exponentially when the numberof state variables or the exogenous shocks in the economy increase. \\As an application we analyze an asset pricing model with endogenousproduction. We analyze its implications for time dependence of volatilityof stock returns and the term structure of interest rates. We argue thatthis model can generate hump--shaped term structures.

Asset pricing implications of benchmarking: A two-factor CAPM

In this paper we consider the equilibrium effects of an institutionalinvestor whose performance is benchmarked to an index. In a partialequilibrium setting, the objective of the institutional investor is modeledas the maximization of expected utility (an increasing and concave function,in order to accommodate risk aversion) of final wealth minus a benchmark.In equilibrium this optimal strategy gives rise to the two-beta CAPM inBrennan (1993): together with the market beta a new risk-factor (that wecall active management risk) is brought into the analysis. This new betais deffined as the normalized (to the benchmark's variance) covariancebetween the asset excess return and the excess return of the market overthe benchmark index. Different to Brennan, the empirical test supports themodel's predictions. The cross-section return on the active management riskis positive and signifficant especially after 1990, when institutionalinvestors have become the representative agent of the market.

A unifying approach to the empirical evaluation of asset pricing models

Two main approaches are commonly used to empirically evaluate linear factor pricingmodels: regression and SDF methods, with centred and uncentred versions of the latter.We show that unlike standard two-step or iterated GMM procedures, single-step estimatorssuch as continuously updated GMM yield numerically identical values for prices of risk,pricing errors, Jensen s alphas and overidentifying restrictions tests irrespective of the modelvalidity. Therefore, there is arguably a single approach regardless of the factors being tradedor not, or the use of excess or gross returns. We illustrate our results by revisiting Lustigand Verdelhan s (2007) empirical analysis of currency returns.

Keeping up with the Joneses: An international asset pricing model

We derive an international asset pricing model that assumes local investorshave preferences of the type "keeping up with the Joneses." In aninternational setting investors compare their current wealth with that oftheir peers who live in the same country. In the process of inferring thecountry's average wealth, investors incorporate information from the domesticmarket portfolio. In equilibrium, this gives rise to a multifactor CAPMwhere, together with the world market price of risk, there existscountry-speciffic prices of risk associated with deviations from thecountry's average wealth level. The model performs signifficantly better, interms of explaining cross-section of returns, than the international CAPM.Moreover, the results are robust, both for conditional and unconditionaltests, to the inclusion of currency risk, macroeconomic sources of risk andthe Fama and French HML factor.

Asset pricing with idiosyncratic risk and overlapping generations

A number of existing studies have concluded that risk sharing allocations supported by competitive, incomplete markets equilibria are quantitatively close to first-best. Equilibrium asset prices in these models have been difficult to distinguish from those associated with a complete markets model, the counterfactual features of which have been widely documented. This paper asks if life cycle considerations, in conjunction with persistent idiosyncratic shocks which become more volatile during aggregate downturns, can reconcile the quantitative properties of the competitive asset pricing framework with those of observed asset returns. We begin by arguing that data from the Panel Study on Income Dynamics support the plausibility of such a shock process. Our estimates suggest a high degree of persistence as well as a substantial increase in idiosyncratic conditional volatility coincident with periods of low growth in U.S. GNP. When these factors are incorporated in a stationary overlapping generations framework, the implications for the returns on risky assets are substantial. Plausible parameterizations of our economy are able to generate Sharpe ratios which match those observed in U.S. data. Our economy cannot, however, account for the level of variability of stock returns, owing in large part to the specification of its production technology.

Speculation, risk premia and expectations in the yield curve

An affine asset pricing model in which traders have rational but heterogeneous expectations aboutfuture asset prices is developed. We use the framework to analyze the term structure of interestrates and to perform a novel three-way decomposition of bond yields into (i) average expectationsabout short rates (ii) common risk premia and (iii) a speculative component due to heterogeneousexpectations about the resale value of a bond. The speculative term is orthogonal to public informationin real time and therefore statistically distinct from common risk premia. Empirically wefind that the speculative component is quantitatively important accounting for up to a percentagepoint of yields, even in the low yield environment of the last decade. Furthermore, allowing for aspeculative component in bond yields results in estimates of historical risk premia that are morevolatile than suggested by standard Affine Gaussian term structure models which our frameworknests.

Dynamic higher order expectations

In models where privately informed agents interact, agents may need to formhigher order expectations, i.e. expectations of other agents' expectations. This paper develops a tractable framework for solving and analyzing linear dynamic rational expectationsmodels in which privately informed agents form higher order expectations. The frameworkis used to demonstrate that the well-known problem of the infinite regress of expectationsidentified by Townsend (1983) can be approximated to an arbitrary accuracy with a finitedimensional representation under quite general conditions. The paper is constructive andpresents a fixed point algorithm for finding an accurate solution and provides weak conditions that ensure that a fixed point exists. To help intuition, Singleton's (1987) asset pricingmodel with disparately informed traders is used as a vehicle for the paper.

Giffen goods and market making

This paper shows that information effects per se are not responsible forthe Giffen goods anomaly affecting competitive traders demands in multi-asset, noisy rational expectations equilibrium models. The role thatinformation plays in traders strategies also matters. In a market withrisk averse, uninformed traders, informed agents havea dual motive for trading: speculation and market making. Whilespeculation entails using prices to assess the effect of private signalerror terms, market making requires employing them to disentangle noisetraders effects in traders aggregate orders. In a correlated environment,this complicates a trader s signal-extraction problem and maygenerate upward-sloping demand curves. Assuming either (i) that competitive,risk neutral market makers price the assets, or that (ii) the risktolerance coefficient of uninformed traders grows without bound, removesthe market making component from informed traders demands, rendering themwell behaved in prices.

Stock market volatility and learning

Introducing bounded rationality in a standard consumption-based asset pricing model with time separable preferences strongly improves empirical performance. Learning causes momentum and mean reversion of returns and thereby excess volatility, persistence of price-dividend ratios, long-horizon return predictability and a risk premium, as in the habit model of Campbell and Cochrane (1999), but for lower risk aversion. This is obtained, even though our learning scheme introduces just one free parameter and we only consider learning schemes that imply small deviations from full rationality. The findings are robust to the learning rule used and other model features. What is key is that agents forecast future stock prices using past information on prices.

Applications of stochastic analysis in finance and statistical inference

First: A continuous-time version of Kyle's model (Kyle 1985), known as the Back's model (Back 1992), of asset pricing with asymmetric information, is studied. A larger class of price processes and of noise traders' processes are studied. The price process, as in Kyle's model, is allowed to depend on the path of the market order. The process of the noise traders' is an inhomogeneous Lévy process. Solutions are found by the Hamilton-Jacobi-Bellman equations. With the insider being risk-neutral, the price pressure is constant, and there is no equilibirium in the presence of jumps. If the insider is risk-averse, there is no equilibirium in the presence of either jumps or drifts. Also, it is analised when the release time is unknown. A general relation is established between the problem of finding an equilibrium and of enlargement of filtrations. Random announcement time is random is also considered. In such a case the market is not fully efficient and there exists equilibrium if the sensitivity of prices with respect to the global demand is time decreasing according with the distribution of the random time. Second: Power variations. it is considered, the asymptotic behavior of the power variation of processes of the form _integral_0^t u(s-)dS(s), where S_ is an alpha-stable process with index of stability 0&alpha&2 and the integral is an Itô integral. Stable convergence of corresponding fluctuations is established. These results provide statistical tools to infer the process u from discrete observations. Third: A bond market is studied where short rates r(t) evolve as an integral of g(t-s)sigma(s) with respect to W(ds), where g and sigma are deterministic and W is the stochastic Wiener measure. Processes of this type are particular cases of ambit processes. These processes are in general not of the semimartingale kind.

Spanning tests in return and stochastic discount factor mean-variance frontiers: A unifying approach

We propose new spanning tests that assess if the initial and additional assets share theeconomically meaningful cost and mean representing portfolios. We prove their asymptoticequivalence to existing tests under local alternatives. We also show that unlike two-step oriterated procedures, single-step methods such as continuously updated GMM yield numericallyidentical overidentifyng restrictions tests, so there is arguably a single spanning test.To prove these results, we extend optimal GMM inference to deal with singularities in thelong run second moment matrix of the influence functions. Finally, we test for spanningusing size and book-to-market sorted US stock portfolios.

A comparison of stock market mechanisms

This paper studies the relationship between the amount of publicinformation that stock market prices incorporate and the equilibriumbehavior of market participants. The analysis is framed in a static, NREEsetup where traders exchange vectors of assets accessing multidimensionalinformation under two alternative market structures. In the first(the unrestricted system), both informed and uninformed speculators cancondition their demands for each traded asset on all equilibrium prices;in the second (the restricted system), they are restricted to conditiontheir demand on the price of the asset they want to trade. I show thatinformed traders incentives to exploit multidimensional privateinformation depend on the number of prices they can condition upon whensubmitting their demand schedules, and on the specific price formationprocess one considers. Building on this insight, I then give conditionsunder which the restricted system is more efficient than the unrestrictedsystem.

Understanding portfolio efficiency with conditioning information

We show that unconditionally efficient returns do not achieve the maximum unconditionalSharpe ratio, neither display zero unconditional Jensen s alphas, when returns arepredictable. Next, we define a new type of efficient returns that is characterized by thoseunconditional properties. We also study a different type of efficient returns that is rationalizedby standard mean-variance preferences and motivates new Sharpe ratios and Jensen salphas. We revisit the testable implications of asset pricing models from the perspective ofthe three sets of efficient returns. We also revisit the empirical evidence on the conditionalvariants of the CAPM and the Fama-French model from a portfolio perspective.

Flexible multivariate GARCH modeling with an application to international stock markets

The goal of this paper is to estimate time-varying covariance matrices.Since the covariance matrix of financial returns is known to changethrough time and is an essential ingredient in risk measurement, portfolioselection, and tests of asset pricing models, this is a very importantproblem in practice. Our model of choice is the Diagonal-Vech version ofthe Multivariate GARCH(1,1) model. The problem is that the estimation ofthe general Diagonal-Vech model model is numerically infeasible indimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contributionis to propose an alternative estimation method that is numerically feasible,produces positive semi-definite conditional covariance matrices, and doesnot impose unrealistic a priori restrictions. We provide an empiricalapplication in the context of international stock markets, comparing thenew estimator to a number of existing ones.

Betting on Hitler: The value of political connections in Nazi Germany

This paper examines the value of connections between German industry andthe Nazi movement in early 1933. Drawing on previously unused contemporarysources about management and supervisory board composition and stock returns,we find that one out of seven firms, and a large proportion of the biggest companies,had substantive links with the National Socialist German Workers Party. Firmssupporting the Nazi movement experienced unusually high returns, outperformingunconnected ones by 5% to 8% between January and March 1933. These resultsare not driven by sectoral composition and are robust to alternative estimatorsand definitions of affiliation.