Powerful CEOs and their impact on corporate performance

We argue in this paper that executives can only impact firm outcomes if they have influence over crucial decisions. Based on this idea we develop and test a hypothesis about how CEOs’ power to influence decisions will affect firm performance: since managers’ opinions may differ, firms whose CEOs have more decision-making power should experience more variability in firm performance. Thus performance depends on the interaction between executive characteristics and organizational variables. By focusing on this interaction we are able to use firm-level characteristics to test predictions that are related to unobservable managerial characteristics. Using such firmlevel characteristics of the Executive Office we develop a proxy for the CEO’s power to influence decisions and provide evidence consistent with our hypothesis. Firm performance (measured by Tobin’s Q, stock returns and ROA) is significantly more variable for firms with greater values of our proxy for CEO influence power. The results are robust across various tests designed to detect differences in variability.

We're Chained: an analysis of systemic risk in finance

This dissertation presents two papers on how to deal with simple systemic risk measures to assess portfolio risk characteristics. The first paper deals with the Granger-causation of systemic risk indicators based in correlation matrices in stock returns. Special focus is devoted to the Eigenvalue Entropy as some previous literature indicated strong re- sults, but not considering different macroeconomic scenarios; the Index Cohesion Force and the Absorption Ratio are also considered. Considering the S&P500, there is not ev- idence of Granger-causation from Eigenvalue Entropies and the Index Cohesion Force. The Absorption Ratio Granger-caused both the S&P500 and the VIX index, being the only simple measure that passed this test. The second paper develops this measure to capture the regimes underlying the American stock market. New indicators are built using filtering and random matrix theory. The returns of the S&P500 is modelled as a mixture of normal distributions. The activation of each normal distribution is governed by a Markov chain with the transition probabilities being a function of the indicators. The model shows that using a Herfindahl-Hirschman Index of the normalized eigenval- ues exhibits best fit to the returns from 1998-2013.

Dois ensaios em finanças

In the first chapter, we test some stochastic volatility models using options on the S&P 500 index. First, we demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility process using the empirical structure function, or variogram. This result is consistent with findings of previous studies. The main contribution of our paper is to estimate the two time-scales in the volatility process simultaneously by using nonlinear weighted least-squares technique. To test the statistical significance of the rates of mean-reversion, we bootstrap pairs of residuals using the circular block bootstrap of Politis and Romano (1992). We choose the block-length according to the automatic procedure of Politis and White (2004). After that, we calculate a first-order correction to the Black-Scholes prices using three different first-order corrections: (i) a fast time scale correction; (ii) a slow time scale correction; and (iii) a multiscale (fast and slow) correction. To test the ability of our model to price options, we simulate options prices using five different specifications for the rates or mean-reversion. We did not find any evidence that these asymptotic models perform better, in terms of RMSE, than the Black-Scholes model. In the second chapter, we use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month.

Do insiders get abnormal returns? : event studies on the trades of insiders of the firms with differentiated corporate governance of the São Paulo stock exchange

The subject insider trading is controversial. This paper presents series of event studies carried through on the trades with stocks of the firm carried by insiders with the objective to detect abnormal returns, based on the access to privileged information. The sample is composed by trades performed by insiders of the companies with stocks negotiated in the São Paulo Stock Exchange, that are classified as firms with differentiated corporate governance. Indication that trades performed by insiders resulted in abnormal returns compared to the statistically significant expected ones, as in the purchases of common shares; or for selling of preferred stocks.

Tests of conditional asset pricing models in the brazilian stock market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976-1992. We also test a conditional APT modeI by using the difference between the 3-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.

Cash flow and discount rate risk decomposition and ICAPM for the US and brazilian stock markets

Esse trabalho é uma aplicação do modelo intertemporal de apreçamento de ativos desenvolvido por Campbell (1993) e Campbell e Vuolteenaho (2004) para as carteiras de Fama-French 2x3 brasileiras no period de janeiro de 2003 a abril de 2012 e para as carteiras de Fama-French 5x5 americanas em diferentes períodos. As varíaveis sugeridas por Campbell e Vuolteenaho (2004) para prever os excessos de retorno do mercado acionário americano no period de 1929 a 2001 mostraram-se também bons preditores de excesso de retorno para o mercado brasileiro no período recente, com exceção da inclinação da estrutura a termo das taxas de juros. Entretanto, mostramos que um aumento no small stock value spread indica maior excesso de retorno no futuro, comportamento que não é coerente com a explicação para o prêmio de valor sugerida pelo modelo intertemporal. Ainda, utilizando os resíduos do VAR preditivo para definir o risco de choques de fluxo de caixa e de choques nas taxas de desconto das carteiras de teste, verificamos que o modelo intertemporal resultante não explica adequadamente os retornos observados. Para o mercado norte-americano, concluímos que a abilidade das variáveis propostas para explicar os excessos de retorno do mercado varia no tempo. O sucesso de Campbell e Vuolteenaho (2004) em explicar o prêmio de valor para o mercado norte-americano na amostra de 1963 a 2001 é resultado da especificação do VAR na amostra completa, pois mostramos que nenhuma das varíaveis é um preditor de retorno estatisticamente significante nessa sub-amostra.

Predictable dividends and returns

The conventional wisdom is that the aggregate stock price is predictable by the lagged pricedividend ratio, and that aggregate dividends follow approximately a random-walk. Contrary to this belief, this paper finds that variation in the aggregate dividends and price-dividend ratio is related to changes in expected dividend growth. The inclusion of labor income in a cointegrated vector autoregression with prices and dividends allows the identification of predictable variation in dividends. Most of the variation in the price-dividend ratio is due to changes in expected returns, but this paper shows that part of variation is related to transitory dividend growth shocks. Moreover, most of the variation in dividend growth can be attributed to these temporary changes in dividends. I also show that the price-dividend ratio (or dividend yield) can be constructed as the sum of two distinct, but correlated, variables that separately predict dividend growth and returns. One of these components, which could be called the expected return state variable, predicts returns better than the price-dividend ratio does.

Brazil’s 2014 presidential elections: the interconnection between election news and stock market behavior

This study researches whether there has been abnormal stock market behaviour in Brazil as a consequence of election news (observed via opinion polls), regarding the last Brazilian presidential election, held in October 2014. Via applying event study methodology, the research on the Ibovespa and Petrobras suggests that events in which Rousseff was gaining in share have been subject to negative abnormal returns, and events where Rousseff was loosing in share have led to positive abnormal returns. Moreover, volatility has been significantly elevated during the election period and volume has been found to have slightly increased.

Are returns on Foreign Direct Investment (FDI), FDI determinants?

Foreign Direct Investments (FDI) acquired an important role in the development process of the global economy. FDI inward stock was equivalent to an average of 32% of GDP for OECD countries in 2013. However, FDI affects a country’s Balance of Payments (BoP) in two ways: FDI flows are recorded in the BoP financial account while returns on FDI affect the BoP current account. Therefore, part of the positive contribution of inward FDI to a country on its financial account could be potentially offset by a negative contribution of FDI returns on the current account. The intent of this work is to complement the research on FDI determinants by introducing FDI returns as a variable in a gravity model where bilateral FDI outflows are the dependent variable. Moreover, using outward FDI flows as the dependent variable, the work allows looking at the behavior of Multinational Corporations (MNC) investing abroad. The results show that MNCs repatriate returns generating from the investments they make abroad. This is particularly true when high-income countries are involved: MNCs from high-income countries repatriate returns to their home countries from FDI made anywhere, while MNCs from middle-income countries repatriate returns from FDI in high-income countries. Repatriated returns are a relevant variable determining the value of FDI that a country makes in another country. The information on FDI returns is starting to become available to the public. This allows MNCs to sharpen their investment location decision models and national IPAs to better assess the two-fold BoP effects of promoting FDI.

Volatility of returns, variations in prices and volume traded: evidence from the main stocks in Brazil

We study the relationship between the volatility and the price of stocks and the impact that variables such as past volatility, financial gearing, interest rates, stock return and turnover have on the present volatility of these securities. The results show the persistent behavior of volatility and the relationship between interest rate and volatility. The results also showed that a reduction in stock prices are associated with an increase in volatility. Finally we found a greater trading volume tends to increase the volatility.