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V 1 N 2 a 1 the Dynamic THE DYNAMIC RELATION BETWEEN RETURNS, TRADING VOLUME AND VOLATILITY IN BRAZILIAN STOCK-LISTED AGRIBUSINESS COMPANIES RELAÇÃO DINÂMICA ENTRE RETORNO, VOLUME DE NEGOCIAÇÕES E VOLATILIDADE DAS AÇÕES DAS EMPRESAS DE CAPITAL ABERTO DO AGRONEGÓCIO BRASILEIRO Valéria Gama Fully Bressan Doutora em Economia Aplicada Bolsista de Desenvolvimento Tecnológico Industrial do CNPq. Departamento de Economia Rural Universidade Federal de Viçosa [email protected] Aureliano Angel Bressam Doutor em Economia Aplicada Professor Adjunto da Faculdade de Ciências Econômicas Universidade Federal de Minas Gerais Pesquisador do CNPq. João Eustáquio de Lima PhD pela University of Florida Professor Titular do Departamento de Economia Rural Universidade Federal de Viçosa Pesquisador do CNPq. Marcelo José Braga PhD pela University of Califórnia at Davis Professor Adjunto do Departamento de Economia Rural Universidade Federal de Viçosa Pesquisador do CNPq. ABSTRACT - In order to verify similarities and/or differences on the behavior of returns and volatility on traded stocks of Brazilian agribusiness companies, this study examines the existence of leverage effects and tests the hypothesis that trading volume is a useful proxy for information innovations, for a sample of 25 stock-listed Brazilian agribusiness companies. Using daily data from July/1999 to January/2007, two specifications of EGARCH models are tested, with and without trading volume as an explanatory variable. The results confirm the existence of leverage effects for almost all of the analyzed companies, and some influence of trading volume in the explanation of the volatility dynamics, but without any remarkable differences between companies and/or their related sub-sectors. Keywords: Financial Returns, Trading Volume, Volatility, EGARCH, Agribusiness. RC&C – Rev. Cont. e Controladoria Curitiba v. 1 n. 2 p. 89-101 mai./ago. 2009 ISSN: 1984-6266 89 THE DYNAMIC RELATION BETWEEN Valéria Gama Fully Bressan RETURNS, TRADING VOLUME AND Aureliano Angel Bressam VOLATILITY IN BRAZILIAN STOCK-LISTED João Eustáquio de Lima AGRIBUSINESS COMPANIES Marcelo José Braga The investigation about the relation between stock returns and trading volume is an important issue in financial 1 INTRODUCTION research. Karpoff (1987) lists three main reasons for the importance of researches The purpose of this paper is to examine regarding this relation. First, the the dynamic relation between stock returns/trading volume relation provides returns, trading volume and volatility for important insights about the structure of 25 stock-listed Brazilian agribusiness- financial markets. Second, its importance related companies. Previous studies, such for event studies that use these relations as those conducted by Chen, Firth and to draw inferences about market Rui (2001) and Tabak and Guerra (2003), efficiency. Third, that relation is a critical evaluated such relation in stock markets issue in the investigation of the empirical of several countries, such as the United distribution of speculative prices. States, Japan, U. Kingdom, France, The returns/trading volume relation is Canada, Italy, Hong Kong and Brazil. In studied with different approaches among an alternative approach, this study intends researchers. For instance, Granger and to evaluate this relation for a specific Morgenstern (1963) used the relation economic sector, in order to identify between stock indexes and aggregated some specific features that could be transaction volume, while Crouch (1970) observed in Brazilian agribusiness worked with the absolute variation of companies. prices and trading volume. Westerfield Specifically, the purpose of this paper is (1977), Tauchen and Pitts (1983) and to evaluate if returns are conditioned by Rogalski (1978) analyzed the relation the arrival of new information that affect between price variations (returns) and trading volume. The 25 companies in the trading volume. Epss and Epps (1976) analyzed sample are characterized as examined the relation between the those which have stocks traded in the variance of returns and trading volume, Brazilian Stock Exchange (BOVESPA) while Harris (1986) and Clark (1973) until January 2007. These companies investigated the relation between the represent specific activities, such as square of price variations and trading fishery and agriculture, foods and volume. beverages, paper and pulp, textiles, Some recent results in the literature are of fertilizers, tobacco and industrial special interest to this study. Gallant, machinery, classified according to Rossi and Tauchen (1992), using daily Economática’s database. data from the New York Stock Exchange The analysis is based on an EGARCH between 1928 and 1987, investigated the model that is estimated in order to verify returns/trading volume relation, with the existing relations between returns, some interesting results: (i) positive trading volume and conditional volatility. correlation between conditional volatility The results are analyzed in a comparative and trading volume, (ii) large price manner, intending to verify possible movements are followed by high trading similarities and differences between volume, (iii) the conditioning on trading sectors and companies. volume reduces the leverage effect on volatility, and (iv) after conditioning on RC&C – Rev. Cont. e Controladoria Curitiba v. 1 n. 2 p. 89-101 mai./ago. 2009 ISSN: 1984-6266 90 THE ACCOUNTANCY OF THE POTENTIAL Valéria Gama Fully Bressan INCOME LOST DUE PREMATURE DEATH: Aureliano Angel Bressam DIFFERENCES DETERMINED BY GENDER João Eustáquio de Lima Marcelo José Braga lagged volume, there is a positive relation 2 THE DATA between risk and return. Andersen (1996) developed an empirical This paper analyzes all the companies model of trading volume and volatility listed in BOVESPA wich are classified in from a microstructure framework in one of three sub-sectors of Brazilian which informational asymmetries and agribusiness, namely: agricultural lack of liquidity motivates the negotiation production, economic inputs and derived from the arrival of new production factors and processing & information. Using a sequential distribution sector. information arrival hypothesis, the dynamic characteristics are driven by the The daily price and trading volume data information flow and modeled as an of these stocks were extracted from ARCH process. The results indicate that Economatica® database from July/1994 the model can be useful for the analysis to January/2007. Initially the sample was of economic factors that are behind the composed by 35 companies. However, observed volatility clusters. those which have their register cancelled during that period were excluded from Chordia and Swaminathan (2000) the sample, resulting in a final sample of examined the interaction between trading 25 companies: Alpargatas, Ambev, volume and return predictability of daily Aracruz, Avipal, Buettner, Cacique, returns. The results indicated that returns Cambuci, Coteminas, Fertibras, Fosfertil, with high trading volume lead stock Guararapes, Klabin, Minupar, Perdigão, returns with low trading volume, a result Rasip Agro Pastoril, Sadia, Santista that was explained by the authors as a Têxtil, Souza Cruz, Suzano Papel, Teka, tendency of high volume stocks to Vicunha Têxtil, Vigor, Votorantim C P, respond promptly to new information. Weg and Yara Brasil. Kuo, Hsu and Chiang (2004) applied the same model of Chordia and Swaminathan The returns were calculated in the (2000) for the Taiwanese market, finding logarithmic form, resulting similar results along with some market Rt = log(Pt/P t-1), where Pt is current price inefficiencies. and Pt-1 is the 1-period lagged price. The volume is the product between the current Although these studies have some price and the number of traded stocks on implications for causal relations between the specific class (common or preferred trading volume and stock returns, neither stocks). Volatility is defined as the has analyzed a specific economic sector, square-root of the square of returns, in order to confirm or reject the results according to the zero-mean hypothesis of found in the literature. In this study, such expected returns, as described in Taylor empirical relations are examined for 25 (2005). stock-listed Brazilian agribusiness companies, in order to identify the existing relations between returns and trading volume. 3 THE MODEL Following Enders (2004), an important feature of stock prices is that “bad” news tends to have a higher effect on volatility RC&C – Rev. Cont. e Controladoria Curitiba v. 1 n. 2 p. 89-101 mai./ago. 2009 ISSN: 1984-6266 91 THE ACCOUNTANCY OF THE POTENTIAL Valéria Gama Fully Bressan INCOME LOST DUE PREMATURE DEATH: Aureliano Angel Bressam DIFFERENCES DETERMINED BY GENDER João Eustáquio de Lima Marcelo José Braga then “good” news of the same magnitude, data with persistence in volatility, a stylized fact known in the literature as presenting conditional lognormal “leverage effect”. variance in continuous time. As a Another special feature is that financial consequence, as the time interval returns tend to exhibit fat tails in their becomes shorter, the innovations distributions and for that reason GARCH- distribution is a mixture of normal and based models are widely applied in lognormal distributions. In this sense, financial literature, once that these Hiemstra and Jones (1994) argue that the models can incorporate not only the EGARCH model is better suited to verify leptokurtosis of squared returns, but also causal relations between
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