Stanislav Anatolyev

A Trading Approach to Testing for Predictability

We propose a market timing test for conditional mean independence of financial returns. The new excess predictability (EP) test statistic has an interpretation of a properly normalized return of a certain trading strategy. We discuss similarities of the EP test to the popular directional accuracy (DA) test of Pesaran and Timmermann. Power properties of the EP test are advantageous, and size properties are comparable to those of the DA test. We illustrate application of the test using weekly data on the S&P500 index.

Modeling Financial Return Dynamics via Decomposition

While the predictability of excess stock returns is detected by traditional predictive regressions as statistically small, the direction-of-change and volatility of returns exhibit a substantially larger degree of dependence over time. We capitalize on this observation and decompose the returns into a product of sign and absolute value components whose joint distribution is obtained by combining a multiplicative error model for absolute values, a dynamic binary choice model for signs, and a copula for their interaction. Our decomposition model is able to incorporate important nonlinearities in excess return dynamics that cannot be captured in the standard predictive regression setup. The empirical analysis of U.S. stock return data shows statistically and economically significant forecasting gains of the decomposition model over the conventional predictive regression.

SPECIFICATION TESTING IN MODELS WITH MANY INSTRUMENTS

This paper studies the asymptotic validity of the Anderson-Rubin (AR) test and the J test of overidentifying restrictions in linear models with many instruments. When the number of instruments increases at the same rate as the sample size, we establish that the conventional AR and J tests are asymptotically incorrect. Some versions of these tests, that are developed for situations with moderately many instruments, are also shown to be asymptotically invalid in this framework. We propose modifications of the AR and J tests that deliver asymptotically correct sizes. Importantly, the corrected tests are robust to the numerosity of the moment conditions in the sense that they are valid for both few and many instruments. The simulation results illustrate the excellent properties of the proposed tests.

A Ten-Year Retrospection of the Behavior of Russian Stock Returns

We study three aspects of the Russian stock market - factors influencing stock returns, integration of the stock market with world .financial markets, and market efficiency - from 1995 to present, putting emphasis on how these evolved over time.We .find many highly unstable relationships, and indeed, greater instability than that generated by financial crises alone.While most computed statistics exhibit constant ups and downs, there are recently clear tendencies in the development of the Russian stock market: a sharp rise in explainability of returns, an increased role of international financial markets, and a decrease in the profitability of trading. Key words: Russia, transition, stock returns, integration, efficiency. JEL codes: C22, F36, G14, G15

Nonparametric Retrospection and Monitoring of Predictability of Financial Returns

We develop and evaluate sequential testing tools for a class of nonparametric tests for predictability of financial returns that include, in particular, the directional accuracy and excess profitability tests. Our sequential methods consider in a unified framework both retrospection of a historical sample and monitoring newly arriving data. To this end, we focus on linear monitoring boundaries that are continuations of horizontal lines corresponding to retrospective critical values, elaborating on both two-sided and one-sided testing. We run a simulation study and illustrate the methodology by testing for directional and mean predictability of returns in young stock markets in Eastern Europe.

Trade intensity in the Russian stock market: dynamics, distribution and determinants

The distribution and evolution of intertrade durations for frequently traded stocks at the Moscow Interbank Currency Exchange are investigated. A flexible econometric model based on ARMA and GARCH is used which, when coupled with a certain class of distributions that allow for skewness and slim-tailedness, adequately captures the characteristics of conditional distribution of durations for Russian stocks, and is able to generate high quality density forecasts. What factors determine the dynamics of log-durations, and in which way, are also analyzed. The results in particular indicate that the Russian market is characterized by aggressive informed traders and timid liquidity traders, and that the participants react evenly to upward and downward short-run price trends.

AN ALTERNATIVE TO MAXIMUM LIKELIHOOD BASED ON SPACINGS

In the statistics literature, asymptotic properties of the Maximum Product of Spacings estimator are derived from first principles. We propose an alternative derivation based on the comparison between its objective function and that of the Maximum Likelihood estimator. 1. MOTIVATION Consider a scalar continuously distributed random variable x with probability density function (p.d.f.) f(x) f(x, 0) and corresponding cumulative distribution function (c.d.f.) F(x) F(x, 6) known up to a possibly multidimensional parameter 0 E ?. Denote the true value of the parameter by 00. Suppose that a random sample xl,..., x, is available. To estimate 00, one usually uses the maximum likelihood (ML) estimator

Instrumental variables estimation and inference in the presence of many exogenous regressors

We consider a standard instrumental variables model contaminated by the presence of a large number of exogenous regressors. In an asymptotic framework where this number is proportional to the sample size, we study the impact of their ratio on the validity of existing estimators and tests. When the instruments are few, the inference using the conventional 2SLS estimator and associated t and J statistics, as well as the Anderson–Rubin and Kleibergen tests, is still valid. When the instruments are many, the LIML estimator remains consistent, but the presence of many exogenous regressors changes its asymptotic variance. Moreover, the conventional bias correction of the 2SLS estimator is no longer appropriate, and the associated Hahn–Hausman test is not valid. We provide asymptotically correct versions of bias correction for the 2SLS estimator, derive its asymptotically correct variance estimator, extend the Hansen–Hausman–Newey LIML variance estimator to the case of many exogenous regressors, and propose asymptotically valid modi…cations of the Hahn–Hausman and J tests based on the LIML and bias corrected 2SLS estimators.

Multi-Market Direction-of-Change Modeling Using Dependence Ratios

We consider a multivariate dynamic model for the joint distribution of binary outcomes associated with directions-of-change for several markets or assets. The marginal distribution of each binary outcome follows a dynamic binary choice model, while the association structure is parameterized via possibly time varying dependence ratios. We illustrate the technique using daily stock index returns from three European markets, from three Baltic markets, and from two Chinese exchanges.

Inference About Predictive Ability When There are Many Predictors

We enhance the theory of asymptotic inference about predictive ability by considering the case when a set of variables used to construct predictions is sizable. To this end, we consider an alternative asymptotic framework where the number of predictors tends to in nity with the sample size, although more slowly. Depending on the situation the asymptotic normal distribution of an average prediction criterion either gains additional variance as in the few predictors case, or gains non-zero bias which has no analogs in the few predictors case. By properly modifying conventional test statistics it is possible to remove most size distortions when there are many predictors, and improve test sizes even when there are few of them.