Asset pricing with index investing

We provide a novel theoretical analysis of how index investing affects capital market equilibrium. We consider a dynamic exchange economy with heterogeneous investors and two Lucas trees and find that indexing can either increase or decrease the correlation between stock returns and in general increases (decreases) volatilities and betas of stocks with larger (smaller) market capitalizations. Indexing also decreases market volatility and interest rates, although those effects are weak. The impact of index investing is particularly strong when stocks have heterogeneous fundamentals. Our results highlight that indexing changes not only how investors can trade but also their incentives to trade

Essays on predictability of stock returns

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2007.Includes bibliographical references.This thesis consists of three chapters exploring predictability of stock returns. In the first chapter, I suggest a new approach to analysis of stock return predictability. Instead of relying on predictive regressions, I employ a state space framework. Acknowledging that expected returns and expected dividends are unobservable, I use the Kalman filter technique to extract them from the observed history of realized dividends and returns. The suggested approach explicitly accounts for the possibility that dividend growth can be predictable. Moreover, it appears to be more robust to structural breaks in the long-run relation between prices and dividends than the conventional OLS regression. I show that for aggregate stock returns the constructed forecasting variable provides statistically and economically significant predictions both in and out of sample. The likelihood ratio test based on a simulated finite sample distribution of the test statistic rejects the hypothesis of constant expected returns at the 1% level. In the second chapter, I analyze predictability of returns on value and growth portfolios and examine time variation of the value premium. As a major tool, I use the filtering technique developed in the first chapter. I construct novel predictors for returns and dividend growth on the value and growth portfolios and find that returns on growth stocks are much more predictable than returns on value stocks. Applying the appropriately modified state space approach to the HML portfolio, I build a novel forecaster for the value premium. Consistent with rational theories of the value premium, the expected value premium is time-varying and countercyclical. In the third chapter, based on the joint work with Igor Makarov, I develop a dynamic asset pricing model with heterogeneously informed agents.(cont.) I focus on the general case in which differential information leads to the problem of "forecasting the forecasts of others" and to non-trivial dynamics of higher order expectations. I prove that the model does not admit a finite number of state variables. Using numerical analysis, I compare equilibria characterized by identical fundamentals but different information structures and show that the distribution of information has substantial impact on equilibrium prices and returns. In particular, asymmetric information might generate predictability in returns and high trading volume.by Oleg Rytchkov.Ph.D

Asset pricing with index investing

We theoretically analyze how index investing affects financial markets using a dynamic exchange economy with heterogeneous investors and two Lucas trees. We identify two ef- fects of indexing: lockstep trading of stocks increases market volatility and stock return correlations but reduction in risk sharing decreases them. Overall, indexing decreases market volatility but has an ambiguous effect on the correlations. Also, index invest- ing decreases an investor’s welfare, but indexing by other investors partially offsets the loss. When the introduction of index trading opens financial markets for new investors, the improved risk sharing makes market returns more volatile and stock returns more correlated

Regional Reallocation of Russian Industry in Transition

In this paper we suggest to use a 'new economic geography' paradigm for explanation of regional reallocation of industrial employment in Russia in 1985-1999. We construct a new economic geography" type model adjusted to specific features of Russian economy. This model gives a counterfactual distribution of industry across regions and allows us to construct a theoretical factor NEGF which is supposed to predict real changes in allocation of industrial employment. Our analysis of empirical data shows that NEGF indeed has a predictive power and this result is valid for a sufficiently wide range of model specifications.Russia, new economic geography, industry allocation

Aggregation of Information About the Cross Section of Stock Returns: A Latent Variable Approach

We propose a new approach for estimating expected returns on individual stocks from a large number of firm characteristics. We treat expected returns as latent variables and apply the partial least squares (PLS) estimator that filters them out from the characteristics under an assumption that the characteristics are linked to expected returns through one or few common latent factors. The estimates of expected returns constructed by our approach from 26 firm characteristics generate a wide cross-sectional dispersion of realized returns and outperform estimates obtained by alternative techniques. Our results also provide evidence of commonality in asset pricing anomalies