Improving mutual fund market timing measures: a markov switching approach

Market timing performance of mutual funds is usually evaluated with linear models with dummy variables which allow for the beta coefficient of CAPM to vary across two regimes: bullish and bearish market excess returns. Managers, however, use their predictions of the state of nature to deÞne whether to carry low or high beta portfolios instead of the observed ones. Our approach here is to take this into account and model market timing as a switching regime in a way similar to Hamilton s Markov-switching GNP model. We then build a measure of market timing success and apply it to simulated and real world data.

Timing de fundos no Brasil

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Análise empírica da presença de "Market timing" no mercado acionário brasileiro

Este trabalho objetiva verificar a existência de “Market Timing” no mercado acionário brasileiro. Os nossos estudos foram divididos em três análises distintas. Primeiro verificamos a presença de “market-timing” nos IPOs e posteriormente expandimos para as ofertas subseqüentes de ações (OSAs). Por último verificamos a persistência dos efeitos do “Market Timing” sobre a estrutura de capital das empresas. Os resultados dos nossos estudos mostram que as empresas brasileiras tendem a emitir mais capital quando o mercado está aquecido. Essas emissões acontecem através de IPOs e de OSAs e alteram a estrutura de capital dessas empresas. Com o passar do tempo essa alteração na estrutura de capital tende a diminuir.

The effects of uncertainty about the timing of deals on consumer behavior

I examine the effects of uncertainty about the timing of de aIs (i.e. temporary price cuts or sales) on consumer behavior in a dynamic inventory model of consumer choice. I derive implications for purchase behavior and test them empirically, using two years of scanner data for soft drinks. I fmd that loyal consumers' decisions, both about the allocation of their purchases over time and the quantity to be purchased in a particular deal, are affected by the uncertainty about the timing of the deal for the product. Loyal consumers buy a higher fraction of their overall purchases during de ais as the uncertainty decreases. This effect increases with an increase in the product' s share of a given consumer' s purchase in the same category or if the consumer stockpiles (i.e., is a shopper). During a particular deal, loyal shoppers increase the quantity they purchase the more time that has passed since the previous de aI, and the higher the uncertainty about the deals' timing. For the non-Ioyal consumers these effects are not significant. These results hold for products that are frequently purchased, like soft-drinks and yogurt, but do not hold for less frequentIy purchased products, such as laundry detergents. The fmdings suggest that manufacturers and retailers should incorporate the effects of deals' timing on consumers' purchase' decisions when deriving optimal pricing strategies.

Market timing as a motive for IPOs: evidence from IPOs of Japanese keiretsu firms

This paper examines the relevance of market timing as a motive for initial public offerings (IPOs) by comparing IPOs of firms that are members of Japanese keiretsu industrial groups with IPOs of independent Japanese firms. We argue that Japanese keiretsu-linked IPOs form a favorable sample to find evidence of the market timing motive. Instead, the data provide strong evidence for a restructuring motive and little evidence for market timing. We find that long run returns to keiretsu and independent IPOs are not negative, contrary to U.S. evidence, and are indistinguishable from each other; initial returns to keiretsu-linked IPOs are significantly higher than to independent firms; and a significant number of keiretsu IPO firms adjust their linkages with the group following the IPO, with both increases and decreases.

Earnings dynamics and inequality in Venezuela: 1995-1997

In this paper, we decompose the variance of logarithmic monthly earnings of prime age males into its permanent and transitory components, using a five-wave rotating panel from the Venezuelan “Encuesta de Hogares por Muestreo” from 1995 to 1997. As far as we know, this is the first time a variance components model is estimated for a developing country. We test several specifications and find that an error component model with individual random effects and first order serially correlated errors fits the data well. In the simplest model, around 22% of earnings variance is explained by the variance of permanent component, 77% by purely stochastic variation and the remaining 1% by serial correlation. These results contrast with studies from industrial countries where the permanent component is predominant. The permanent component is usually interpreted as the results of productivity characteristics of individuals whereas the transitory component is due to stochastic perturbations such as job and/or price instability, among others. Our findings may be due to the timing of the panel when occurred precisely during macroeconomic turmoil resulting from a severe financial crisis. The findings suggest that earnings instability is an important source of inequality in a region characterized by high inequality and macroeconomic instability.

Demand expectations and the timing of stimulus policies

This paper proposes a simple macroeconomic model with staggered investment decisions. The model captures the dynamic coordination problem arising from demand externalities and fixed costs of investment. In times of low economic activity, a firm faces low demand and hence has less incentives for investing, which reinforces firms’ expectations of low demand. In the unique equilibrium of the model, demand expectations are pinned down by fundamentals and history. Owing to the beliefs that arise in equilibrium, there is no special reason for stimulus at times of low economic activity.

Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors

This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.