Testing the Markov property with ultra high frequency financial data

This paper develops a framework to test whether discrete-valued irregularly-spaced financial transactions data follow a subordinated Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates not only the irregular spacing of transactions data, but also price discreteness. Further, it turns out that, under such an observation rule, the current price duration is independent of previous price durations given the current price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Finally, we investigate whether or not bid-ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid-ask spread. The results are mixed in the sense that the Markov assumption is rejected for three out of the five stocks we have analyzed.

Forecasting daily volatility using high frequency financial data

Aiming at empirical findings, this work focuses on applying the HEAVY model for daily volatility with financial data from the Brazilian market. Quite similar to GARCH, this model seeks to harness high frequency data in order to achieve its objectives. Four variations of it were then implemented and their fit compared to GARCH equivalents, using metrics present in the literature. Results suggest that, in such a market, HEAVY does seem to specify daily volatility better, but not necessarily produces better predictions for it, what is, normally, the ultimate goal. The dataset used in this work consists of intraday trades of U.S. Dollar and Ibovespa future contracts from BM&FBovespa.

Industry analysis of the high frequency trading industry : an assessment of the industry boundaries, environment and strategic options

O Mercado Acionário Americano evoluiu rapidamente na última década. Este tornou-se uma arquitetura aberta em que participantes com tecnologia inovadora podem competir de forma eficaz. Várias mudanças regulatórias e inovações tecnológicas permitiram mudanças profundas na estrutura do mercado. Essas mudanças, junto com o desenvolvimento tecnológico de redes de alta velocidade, agiu como um catalisador, dando origem a uma nova forma de negociação, denominada Negociação em Alta Frequência (HFT). As empresas de HFT surgiram e se apropriaram em larga escala do negócio de formação de mercado, no fornecimento de liquidez. Embora HFT tem crescido massivamente, ao longo dos últimos quatro anos, HFT perdeu rentabilidade significativamente, uma vez que mais empresas aderiram ao setor reduzindo as margens. Portanto, diante deste contexto, esta tese buscou apresentar uma breve revisão sobre a atividade de HFT, seguida de uma análise dos limites deste setor, bem como, das características do macroambiente do HFT. Para tanto, a tese realizou uma extensa revisão do histórico literário, documentos públicos qualitativos, tais como, jornais, atas de reunião e relatórios oficiais. A tese empregou um ferramental de análise, Barreiras de Entrada e Mobilidade (Porter, 1980); Modelos de Evolução Setorial (McGahan, 2004); Estrutura do Setor de Informação Intensiva (Sampler, 1998), para analisar os limites do setor de HFT. Adicionalmente, empregou as ferramentas de análise, Modelos de Evolução Setorial (McGahan, 2004) e PESTEL (JOHNSON, SCHOLES, and WHITTINGTON, 2011), para analisar o setor e o contexto que envolve o negócio de HFT. A análise concluiu que as empresas que empregam HFT para atuar e competir no mercado acionário, compoem um setor independente.

The effects of adult literacy on earnings and employment

This paper provides evidence of the effects of adult literacy on individuals’ income and employability in Brazil based on information obtained from the monthly employment survey (PME). The OLS results indicate that after controlling for observable characteristics, there is a 21.25% increase in wages for individuals who become literate; however, there is no significant impact on employability. Moreover, the findings show an 8.1% increase in the probability of being employed in the formal sector. We also explore the longitudinal structure of the dataset to control for unobservable fixed characteristics of individuals. The fixed-effects estimators show smaller effects compared to the OLS estimators. We find that literacy has a 4.4% effect on wages and a 4.3% impact on the probability of being formally employed. The effects are significantly different from zero.

Information asymmetry and competition in credit markets: the pricing of overdraft loans in Brazil

This paper evaluates how information asymmetry affects the strength of competition in credit markets. A theory is presented in which adverse selection softens competition by decreasing the incentives creditors have for competing in the interest rate dimension. In equilibirum, although creditors compete, the outcome is similar to collusion. Three empirical implications arise. First, interest rate should respond asymmetrically to changes in the cost of funds: increases in cost of funds should, on average, have a larger effect on interest rates than decreases. Second, aggressiveness in pricing should be associated with a worseing in the bank level default rates. Third, bank level default rates should be endogenous. We then verify the validity of these three empirical implications using Brazilian data on consumer overdraft loans. The results in this paper rationalize seemingly abnormallly high interest rates in unsecured loans.

Growth, increasing returns, and public infrastructure : time series evidence

Initial endogenous growth models emphasized the importance of external effects and increasing retums in explaining growth. Empirically, this hypothesis can be confumed if the coefficient of physical capital per hour is unity in the aggregate production function. Previous estimates using time series data rejected this hypothesis, although cross-country estimates did nol The problem lies with the techniques employed, which are unable to capture low-frequency movements of high-frequency data. Using cointegration, new time series evidence confum the theory and conform to cross-country evidence. The implied Solow residual, which takes into account externaI effects to aggregate capital, has its behavior analyzed. The hypothesis that it is explained by government expenditures on infrasttucture is confIrmed. This suggests a supply-side role for government affecting productivity.

Are price limits on futures markets that cool?: evidence from the Brazilian Mercantile and Futures Exchange

This paper investigates the impact of price limits on the Brazilian futures markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the SËœao Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. The results indicate that the conditional mean features a floor cool-off effect, whereas the conditional variance significantly increases as the price approaches the upper limit. We then build a trading strategy that accounts for the cool-off effect in the conditional mean so as to demonstrate that the latter has not only statistical, but also economic significance. The in-sample Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider, whereas out-of-sample results evince similar performances.

Marketing performance measurement : overview of approaches and practices for high technology firms

Um levantamento de 320 executivos de marketing feito pelo Conselho CMO e divulgado em junho de 2004 indicou que poucas companhias de alta tecnologia (menos de 20% das empresas entrevistadas) têm desenvolvido medidas e métricas úteis e expressivas para as suas organizações de marketing. Porém a pesquisa também revelou que companhias que estabeleceram medidas formais e compreensivas atingiram resultados financeiros superiores e tiveram mais confiança do CEO na função de marketing. Esta dissertação provê uma visão geral da informação precisa para executivos de marketing entenderem e implementarem processos para medição de performance de marketing (MPM) em suas organizações. Ela levanta questões para gerentes de marketing na industria de alta tecnologia com respeito às demandas para maior responsabilidade final, valor de medição para o melhoramento dos processos de marketing, iniciativas para determinar a lucratividade dos investimentos em marketing, e a importância das atividades de marketing nos relatórios corporativos. Esta dissertação defende a implementação de MPM, mapeando seus benefícios de medição para ambos gerentes de marketing e as suas empresas. o trabalho logo explora alguns conceitos gerais de medição de marketing e investiga algumas abordagens a MPM propostas pela industria, pela comunidade acadêmica, e pelos analistas. Finalmente, a dissertação descreve algumas práticas que todo gerente de marketing na industria de alta tecnologia deve considerar quando adotando MPM. As sugestões são gerais, mas devem familiarizar o leitor com as informações precisas para habilitar processos e rigor na sua organização com respeito a MPM.

Conditional alphas and realized betas

This paper proposes a two-step procedure to back out the conditional alpha of a given stock using high-frequency data. We rst estimate the realized factor loadings of the stocks, and then retrieve their conditional alphas by estimating the conditional expectation of their risk-adjusted returns. We start with the underlying continuous-time stochastic process that governs the dynamics of every stock price and then derive the conditions under which we may consistently estimate the daily factor loadings and the resulting conditional alphas. We also contribute empiri-cally to the conditional CAPM literature by examining the main drivers of the conditional alphas of the S&P 100 index constituents from January 2001 to December 2008. In addition, to con rm whether these conditional alphas indeed relate to pricing errors, we assess the performance of both cross-sectional and time-series momentum strategies based on the conditional alpha estimates. The ndings are very promising in that these strategies not only seem to perform pretty well both in absolute and relative terms, but also exhibit virtually no systematic exposure to the usual risk factors (namely, market, size, value and momentum portfolios).

The effects of the minimum wage on earnings and employment in Brazil

This paper analyzes the effects of the mlmmum wage on both, eammgs and employment, using a Brazilian rotating panel data (Pesquisa Mensal do Emprego - PME) which has a similar design to the US Current Population Survey (CPS). First an intuitive description of the data is done by graphical analysis. In particular, Kemel densities are used to show that an increase in the minimum wage compresses the eamings distribution. This graphical analysis is then forrnalized by descriptive models. This is followed by a discussion on identification and endogeneity that leads to the respecification of the model. Second, models for employment are estimated, using an interesting decomposition that makes it possible to separate out the effects of an increase in the minimum wage on number of hours and on posts of jobs. The main result is that an increase in the minimum wage was found to compress the eamings distribution, with a moderately small effect on the leveI of employment, contributing to alleviate inequality.

Price discovery using a regime-sensitive cointegration approach

This work proposes a method to examine variations in the cointegration relation between preferred and common stocks in the Brazilian stock market via Markovian regime switches. It aims on contributing for future works in "pairs trading" and, more specifically, to price discovery, given that, conditional on the state, the system is assumed stationary. This implies there exists a (conditional) moving average representation from which measures of "information share" (IS) could be extracted. For identification purposes, the Markov error correction model is estimated within a Bayesian MCMC framework. Inference and capability of detecting regime changes are shown using a Montecarlo experiment. I also highlight the necessity of modeling financial effects of high frequency data for reliable inference.