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O abuso de informação privilegiada : enquadramento jurídico da negociação algorítmica de alta frequência (high frequency trading)
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A presente dissertação tem por objectivo uma breve análise do crime de abuso de informação privilegiada, seguida de um enquadramento no nosso ordenamento jurídico, do fenómeno de Negociação de Alta Frequência (High Frequency Trading), e da relação que se pode estabelecer entre ambos os institutos.
Iremos iniciar o tratamento do tema por uma visão geral do mercado de valores mobiliários, a evolução legislativa (Portuguesa e Europeia) no que respeita ao crime de abuso de informação privilegiada, o bem jurídico tutelado pela norma incriminadora, o papel fundamental que a informação desempenha no mercado enquanto pedra basilar do seu bom funcionamento, a problemática das assimetrias de informação e os pressupostos deste tipo de ilícito.
Serão ainda abordadas a regulação e a supervisão do mercado, enquanto mecanismos necessários para mitigar as falhas de mercado, bem como, a postura activa e preventiva que a Comissão de Valores Mobiliários deve exercer face a novos desafios regulatórios, resultantes de novas técnicas e estratégias de negociação influenciadas pelo advento das novas tecnologias.
Consideramos que o tema em questão, para além de complexo, é extremamente dinâmico, não se perdendo de forma alguma a sua actualidade, como foi possível constatar pelos escândalos de insider trading que têm vindo a verificar-se nos últimos anos. No nosso entender, os crimes de mercado são uma realidade em constante mutação que a legislação, regulação e supervisão devem acompanhar.
É nesse âmbito que partiremos para uma análise da negociação algorítmica, especialmente a Negociação Algorítmica de Alta Frequência, ou High Frequency Trading, percebendo no que consiste esta prática relativamente recente de comercialização de títulos no mercado bolsista, que tem ganho crescente relevância ao longo da última década.
Assim, tentaremos perceber se certas estratégias de negociação a ela associadas poderão ser ofensivas do bem jurídico tutelado pelo crime de abuso de informação privilegiada, e nesse sentido, se serão enquadráveis neste tipo legal de crime.
The purpose of this dissertation is to provide a brief analysis of insider trading, followed by its framework on our legal system, an examination of algorithmic trading, more precisely the High Frequency Trading, and the relationship that can be established between both institutes. We will approach the subject starting with an overview of the securities market, Portuguese and European legislative developments concerning insider trading, the foundation for this prohibition, the fundamental role that information plays in the market as a corner stone of its proper functioning, the information asymmetries problematic in the market and the structure of insider trading criminal norm. Market regulation and supervision will also be addressed as necessary mechanisms to mitigate market failures, as well as the active and preventive stance that Portuguese Securities and Exchange Commission must adopt facing new regulatory challenges, consequence of the emerging computerized negotiation strategies and techniques, influenced by the advent of new technologies. We consider this issue both complex and extremely dynamic, and over the years has not lost its relevance, as can be seen from the insider trading scandals occurring in the last two decades. By our viewpoint, market crimes, like insider trading, are an everchanging reality, which legislative, regulatory and supervisory bodies are required to monitor and keep up with. It is in this context that we will start analyzing the Algorithmic Negotiation, specially its High Frequency Trading subcategory, which has been attracting attentions and notoriety during the last decade, realizing what this relatively recent practice of securities negotiation means for the markets. Accordingly, we will try to understand if some strategies of negotiation associated with High Frequency Trading can be harmful and represent a threat to the markets, and finally, if they fit in the insider trading legal framework.
The purpose of this dissertation is to provide a brief analysis of insider trading, followed by its framework on our legal system, an examination of algorithmic trading, more precisely the High Frequency Trading, and the relationship that can be established between both institutes. We will approach the subject starting with an overview of the securities market, Portuguese and European legislative developments concerning insider trading, the foundation for this prohibition, the fundamental role that information plays in the market as a corner stone of its proper functioning, the information asymmetries problematic in the market and the structure of insider trading criminal norm. Market regulation and supervision will also be addressed as necessary mechanisms to mitigate market failures, as well as the active and preventive stance that Portuguese Securities and Exchange Commission must adopt facing new regulatory challenges, consequence of the emerging computerized negotiation strategies and techniques, influenced by the advent of new technologies. We consider this issue both complex and extremely dynamic, and over the years has not lost its relevance, as can be seen from the insider trading scandals occurring in the last two decades. By our viewpoint, market crimes, like insider trading, are an everchanging reality, which legislative, regulatory and supervisory bodies are required to monitor and keep up with. It is in this context that we will start analyzing the Algorithmic Negotiation, specially its High Frequency Trading subcategory, which has been attracting attentions and notoriety during the last decade, realizing what this relatively recent practice of securities negotiation means for the markets. Accordingly, we will try to understand if some strategies of negotiation associated with High Frequency Trading can be harmful and represent a threat to the markets, and finally, if they fit in the insider trading legal framework.
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Valores mobiliários Mercado financeiro Informação privilegiada Abuso de informação Negociação algorítmica Teses de mestrado - 2018