941 resultados para Long-Short


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This paper contributes to the debate on the effects of the financialization of commodity futures markets by studying the conditional volatility of long–short commodity portfolios and their conditional correlations with traditional assets (stocks and bonds). Using several groups of trading strategies that hedge fund managers are known to implement, we show that long–short speculators do not cause changes in the volatilities of the portfolios they hold or changes in the conditional correlations between these portfolios and traditional assets. Thus calls for increased regulation of commodity money managers are, at this stage, premature. Additionally, long–short speculators can take comfort in knowing that their trades do not alter the risk and diversification properties of their portfolios.

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O objetivo do trabalho é realizar uma análise da estratégia long-short feita pelos fundos de investimentos, no mercado acionário, e testar a neutralidade dos fundos long-short brasileiros ao principal índice de mercado, o Ibovespa, utilizando os testes de neutralidade de Patton (2006) como referência. As explicações da estratégia long-short se divide em duas partes: a estratégia de pairs trading pela arbitragem estatística, e a estratégia de pairs trading pela arbitragem de risco. O resultado encontrado mostra que quase a totalidade dos fundos analisados (85%) falha no teste de neutralidade em relação ao mercado acionário, mais especificamente ao Ibovespa.

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Diversos estudos sobre investimentos em Ações e Fundos de Investimentos no Brasil, mais especificamente sobre Fundos Multimercados Long-Short, focam em sua neutralidade em relação ao Ibovespa bem como na performance de seus gestores e de suas respectivas estratégias, como Penna (2007) e Gomes e Cresto (2010). Com ênfase na comparação entre a liquidez da posição comprada e a da posição vendida em ações, foi verificado o comportamento de fundos long-short em situações normais e de crise, do período que vai de 2007 a 2009. Foram encontrados fortes indícios de que houve perda maior em momentos de estresse por parte de fundos que carregavam ações menos líquidas em suas carteiras na posição comprada em relação a posição vendida, apesar do número reduzido de fundos estudados e também de ter sido utilizado periodicidade mensal. Encontrou-se um retorno médio em 2008 de 11,1% para uma carteira formada por fundos com ações mais líquidas na posição comprada do que na posição vendida e 5,4% para uma carteira com posição inversa. Uma análise de risco-retorno feita com o Índice de Sharpe (IS) corrobora o estudo, pois a carteira composta por fundos com posição mais líquida na posição vendida apresentou IS de -1,5368, bem inferior ao IS de -0,3374 da carteira de posição inversa (mais líquida na posição comprada). Foi também utilizado o Modelo Índice, como em Bodie, Kane e Marcus (2005), para verificar se esses fundos, separados em carteiras divididas entre mais líquidos na posição comprada do que na posição vendida e vice-versa, tinham desempenho melhor que o mercado (IBOVESPA) de maneira sistemática (alpha=α) e a exposição dessas carteiras ao risco de mercado (Beta = β), além do Modelo de Fatores. As regressões realizadas para os modelos citados encontram coeficientes e respectivas inferências estatísticas que respaldam a hipótese acima, apesar de baixo número de observações utilizado.

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Alavancagem em hedge funds tem preocupado investidores e estudiosos nos últimos anos. Exemplos recentes de estratégias desse tipo se mostraram vantajosos em períodos de pouca incerteza na economia, porém desastrosos em épocas de crise. No campo das finanças quantitativas, tem-se procurado encontrar o nível de alavancagem que otimize o retorno de um investimento dado o risco que se corre. Na literatura, os estudos têm se mostrado mais qualitativos do que quantitativos e pouco se tem usado de métodos computacionais para encontrar uma solução. Uma forma de avaliar se alguma estratégia de alavancagem aufere ganhos superiores do que outra é definir uma função objetivo que relacione risco e retorno para cada estratégia, encontrar as restrições do problema e resolvê-lo numericamente por meio de simulações de Monte Carlo. A presente dissertação adotou esta abordagem para tratar o investimento em uma estratégia long-short em um fundo de investimento de ações em diferentes cenários: diferentes formas de alavancagem, dinâmicas de preço das ações e níveis de correlação entre esses preços. Foram feitas simulações da dinâmica do capital investido em função das mudanças dos preços das ações ao longo do tempo. Considerou-se alguns critérios de garantia de crédito, assim como a possibilidade de compra e venda de ações durante o período de investimento e o perfil de risco do investidor. Finalmente, estudou-se a distribuição do retorno do investimento para diferentes níveis de alavancagem e foi possível quantificar qual desses níveis é mais vantajoso para a estratégia de investimento dadas as restrições de risco.

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This paper deals with the role of the higher-order evanescent modes generated at the area discontinuities in the acoustic attenuation characteristics of an elliptical end-chamber muffler with an end-offset inlet and end-centered outlet. It has been observed that with an increase in length, the muffler undergoes a transition from being acoustically short to acoustically long. Short end chambers and long end chambers are characterized by transverse plane waves and axial plane waves, respectively, in the low-frequency range. The nondimensional frequency limit k(0)(D-1/2) or k(0)R(0) as well as the chamber length to inlet/outlet pipe diameter ratio, i.e., L/d(0), up to which the muffler behaves like a short chamber and the corresponding limit beyond which the muffler is acoustically long are determined. The limits between which neither the transverse plane-wave model nor the conventional axial plane-wave model gives a satisfactory prediction have also been determined, the region being called the intermediate range. The end-correction expression for this muffler configuration in the acoustically long limit has been obtained using 3-D FEA carried on commercial software, covering most of the dimension range used in the design exercise. Development of a method of combining the transverse plane wave model with the axial plane wave model using the impedance Z] matrix is another noteworthy contribution of this work.

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Using US data for the period 1967:5-2002:4, this paper empirically investigates the performance of a Fed’s reaction function (FRF) that (i) allows for the presence of switching regimes, (ii) considers the long-short term spread in addition to the typical variables, (iii) uses an alternative monthly indicator of general economic activity suggested by Stock and Watson (1999), and (iv) considers interest rate smoothing. The estimation results show the existence of three switching regimes, two characterized by low volatility and the remaining regime by high volatility. Moreover, the scale of the responses of the Federal funds rate to movements in the rate of inflation and the economic activity index depends on the regime. The estimation results also show robust empirical evidence that the importance of the term spread in the FRF has increased over the sample period and the FRF has been more stable during the term of office of Chairman Greenspan than in the pre-Greenspan period.

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This paper considers the basic present value model of interest rates under rational expectations with two additional features. First, following McCallum (1994), the model assumes a policy reaction function where changes in the short-term interest rate are determined by the long-short spread. Second, the short-term interest rate and the risk premium processes are characterized by a Markov regime-switching model. Using US post-war interest rate data, this paper finds evidence that a two-regime switching model fits the data better than the basic model. The estimation results also show the presence of two alternative states displaying quite different features.

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Using US data for the period 1967:5-2002:4, this paper empirically investigates the performance of an augmented version of the Taylor rule (ATR) that (i) allows for the presence of switching regimes, (ii) considers the long-short term spread in addition to the typical variables, (iii) uses an alternative monthly indicator of general economic activity suggested by Stock and Watson (1999), and (iv) considers interest rate smoothing. The estimation results show the existence of switching regimes, one characterized by low volatility and the other by high volatility. Moreover, the scale of the responses of the Federal funds rate to movements in the term spread, inflation and the economic activity index depend on the regime. The estimation results also show robust empirical evidence that the ATR has been more stable during the term of office of Chairman Greenspan than in the pre-Greenspan period. However, a closer look at the Greenspan period shows the existence of two alternative regimes and that the response of the Fed funds rate to inflation has not been significant during this period once the term spread is considered.

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The nonlinear dynamics of longitudinal dust lattice waves propagating in a dusty plasma bi-crystal is investigated. A “diatomic”-like one-dimensional dust lattice configuration is considered, consisting of two distinct dust grain species with different charges and masses. Two different frequency dispersion modes are obtained in the linear limit, namely, an optical and an acoustic wave dispersion branch. Nonlinear solitary wave solutions are shown to exist in both branches, by considering the continuum limit for lattice excitations in different nonlinear potential regimes. For this purpose, a generalized Boussinesq and an extended Korteweg de Vries equation is derived, for the acoustic mode excitations, and their exact soliton solutions are provided and compared. For the optic mode, a nonlinear Schrödinger-type equation is obtained, which is shown to possess bright- (dark-) type envelope soliton solutions in the long (short, respectively) wavelength range. Optic-type longitudinal wavepackets are shown to be generally unstable in the continuum limit, though this is shown not to be the rule in the general (discrete) case.

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For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based on turnwise processing. We present a novel approach to on-line emotion recognition from speech using Long Short-Term Memory Recurrent Neural Networks. Emotion is recognised frame-wise in a two-dimensional valence-activation continuum. In contrast to current state-of-the-art approaches, recognition is performed on low-level signal frames, similar to those used for speech recognition. No statistical functionals are applied to low-level feature contours. Framing at a higher level is therefore unnecessary and regression outputs can be produced in real-time for every low-level input frame. We also investigate the benefits of including linguistic features on the signal frame level obtained by a keyword spotter.

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In this paper, we employ a unique dataset of actual US dollar (USD) forward positions against a number of currencies taken by so-called Commodity Trading Advisors (CTAs). We investigate to what extent these positions exhibit a pattern of USD carry trading or other patterns of currency trading over the recent period of the ultra-loose US monetary policy. Our analysis indeed shows that USD positions against emerging market currencies are characterised by a pattern of carry trading. That is, the USD, as the lower yielding currency, is associated with short positions. The payoff distributions of these positions, moreover, are found to have positive Sharpe ratios, negative skewness and high kurtosis. On the other hand, we find that USD positions against other advanced country currencies have a pattern completely opposite to carry trading which is in line with uncovered interest parity trading; that is, the lower (higher) yielding currency is associated with long (short) positions.

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In recent years, Deep Learning (DL) techniques have gained much at-tention from Artificial Intelligence (AI) and Natural Language Processing (NLP) research communities because these approaches can often learn features from data without the need for human design or engineering interventions. In addition, DL approaches have achieved some remarkable results. In this paper, we have surveyed major recent contributions that use DL techniques for NLP tasks. All these reviewed topics have been limited to show contributions to text understand-ing, such as sentence modelling, sentiment classification, semantic role labelling, question answering, etc. We provide an overview of deep learning architectures based on Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Recursive Neural Networks (RNNs).