982 resultados para he Johansen Co-integration


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The aim of this study is to examine the level of stock market co-movement in the BRICS countries and three major industrialized countries (Japan, UK and USA). While analyzing the interdependence and integration of markets, two subsets are examined: before (2000 – 2007) and during the global financial crisis (2007-2011). Generally, interdependence across markets is likely to increase during a highly volatile period. This is problematic because if it were true, the main benefit of international diversification would be reduced at times when it is most needed. The results reveal the dominant role of the US financial markets over the examined time period. Empirical studies of this research paper indicate that cross-market linkages have become slightly stronger during the ongoing subprime crisis than before crisis. However, results also show that an investor may obtain some international diversification benefits by investing especially in the BRICS countries despite the fact of unstable economic condition and growing globalization.

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The purpose of this study is to investigate whether there exists any kind of relationship between the spot and future prices of the different commodities or not. Commodities like cocoa, coffee, crude oil, gold, natural gas and silver are considered from January 3, 2000 to December 31, 2012. For this purpose, ADF test and KPSS test are used in testing the stationarity whereas Johansen Cointegration test is used in testing the long-run relationship. Johansen co-integration test exhibits that there at least 5 co-integrating pairs out of 6 except crude oil. Moreover, the result of Granger Causality supports the fact that if two or more than two time series tend to be co-integrated there exists either uni-directional or bi-directional relationship. However, our results reveled that although there exists the co-integration between the variable, one might not granger causes another .VAR model is also used to measure the proportion of effects. These findings will help the derivative market and arbitragers in developing the strategies to gain the maximum profit in the financial market.

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Futures trading in Commodities has three specific economic functions viz. price discovery, hedging and reduction in volatility. Natural rubber possesses all the specifications required for futures trading. Commodity futures trading in India attained momentum after the starting of national level commodity exchanges in 2003. The success of futures trading depends upon effective price risk management, price discovery and reduced volatility which in turn depends upon the volume of trading. In the case of rubber futures market, the volume of trading depends upon the extent of participation by market players like growers, dealers, manufacturers, rubber marketing co-operative societies and Rubber Producer’s Societies (RPS). The extent of participation by market players has a direct bearing on their awareness level and their perception about futures trading. In the light of the above facts and the review of literature available on rubber futures market, it is felt that a study on rubber futures market is necessary to fill the research gap, with specific focus on (1) the awareness and perception of rubber futures market participants viz. (i) rubber growers, (ii) dealers, (iii) rubber product manufacturers, (iv) rubber marketing co-operative societies and Rubber Producer’s Societies (RPS) about futures trading and (2) whether the rubber futures market is fulfilling the economic functions of futures market viz. hedging, reduction in volatility and price discovery or not. The study is confined to growers, dealers, rubber goods manufacturers, rubber marketing co-operative societies and RPS in Kerala. In order to achieve the stated objectives, the study utilized secondary data for the period from 2003 to 2013 from different published sources like bulletins, newsletters, circulars from NMCE, Reserve Bank of India (RBI), Warehousing Corporation and traders. The primary data required for this study were collected from rubber growers, rubber dealers, RPS & Rubber Marketing Co-operative Societies and rubber goods manufacturers in Kerala. Data pertaining to the awareness and perception of futures trading, participation in the futures trading, use of spot and futures prices and source of price information by dealers, farmers, manufacturers and cooperative societies also were collected. Statistical tools used for analysis include percentage, standard deviation, Chi-square test, Mann – Whitney U test, Kruskal Wallis test, Augmented Dickey – Fuller test statistic, t- statistic, Granger causality test, F- statistic, Johansen co – integration test, Trace statistic and Max –Eigen statistic. The study found that 71.5 per cent of the total hedges are effective and 28.5 per cent are ineffective for the period under study. It implies that futures market in rubber reduced the impact of price risks by approximately 71.5 per cent. Further, it is observed that, on 54.4 per cent occasions, the futures market exercised a stabilizing effect on the spot market, and on 45.6 per cent occasions futures trading exercised a destabilizing effect on the spot market. It implies that elasticity of expectation of futures market in rubber has a predominant stabilizing effect on spot prices. The market, as a whole, exhibits a bias in favour of long hedges. Spot price volatility of rubber during futures suspension period is more than that of the pre suspension period and post suspension period. There is a bi-directional association-ship or bi-directional causality or pair- wise causality between spot price and futures price of rubber. From the results of the hedging efficiency, spot price volatility, and price discovery, it can be concluded that rubber futures market fulfils all the economic functions expected from a commodity futures market. Thus in India, the future of rubber futures is Bright…!!!

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The study examines the short-run and long-run causality running from real economic growth to real foreign direct investment inflows (RFDI). Other variables such as education (involving combination of primary, secondary and tertiary enrolment as a proxy to education), real development finance, unskilled labour, to real RFDI inflows are included in the study. The time series data covering the period of 1983 -2013 are examined. First, I applied Augmented Dicky-Fuller (ADF) technique to test for unit root in variables. Findings shows all variables integrated of order one [I(1)]. Thereafter, Johansen Co-integration Test (JCT) was conducted to establish the relationship among variables. Both trace and maximum Eigen value at 5% level of significance indicate 3 co-integrated equations. Vector error correction method (VECM) was applied to capture short and long-run causality running from education, economic growth, real development finance, and unskilled labour to real foreign direct investment inflows in the Republic of Rwanda. Findings shows no short-run causality running from education, real development finance, real GDP and unskilled labour to real FDI inflows, however there were existence of long-run causality. This can be interpreted that, in the short-run; education, development finance, finance and economic growth does not influence inflows of foreign direct investment in Rwanda; but it does in long-run. From the policy perspective, the Republic of Rwanda should focus more on long term goal of investing in education to improve human capital, undertake policy reforms that promotes economic growth, in addition to promoting good governance to attract development finance – especially from Nordics countries (particularly Norway and Denmark).

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This research investigates the spatial market integration of the Chilean wheat market in relation with its most representative international markets by using a vector error correction model (VECM) and how a price support policy, as a price band, affect it. The international market was characterized by two relevant wheat prices: PAN from Argentina and Hard Red Winter from the United States. The spatial market integration level, expressed in the error correction term (ECT), allowed concluding that there is a high integration degree among these markets with a variable influence of the price band mechanism mainly related with its estimation methodology. Moreover, this paper showed that Chile can be seen as price taker as long as the speed of its adjustment to international shocks, being these reactions faster than in the United States and Argentina. Finally, the results validated the "Law of the One Price", which assumes price equalization across all local markets in the long run.

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Résumé : Le transistor monoélectronique (SET) est un dispositif nanoélectronique très attractif à cause de son ultra-basse consommation d’énergie et sa forte densité d’intégration, mais il n’a pas les capacités suffisantes pour pouvoir remplacer complètement la technologie CMOS. Cependant, la combinaison de la technologie SET avec celle du CMOS est une voie intéressante puisqu’elle permet de profiter des forces de chacune, afin d’obtenir des circuits avec des fonctionnalités additionnelles et uniques. Cette thèse porte sur l’intégration 3D monolithique de nanodispositifs dans le back-end-of-line (BEOL) d’une puce CMOS. Cette approche permet d’obtenir des circuits hybrides et de donner une valeur ajoutée aux puces CMOS actuelles sans altérer le procédé de fabrication du niveau des transistors MOS. L’étude se base sur le procédé nanodamascène classique développé à l’UdeS qui a permis la fabrication de dispositifs nanoélectroniques sur un substrat de SiO2. Ce document présente les travaux réalisés sur l’optimisation du procédé de fabrication nanodamascène, afin de le rendre compatible avec le BEOL de circuits CMOS. Des procédés de gravure plasma adaptés à la fabrication de nanostructures métalliques et diélectriques sont ainsi développés. Le nouveau procédé nanodamascène inverse a permis de fabriquer des jonctions MIM et des SET métalliques sur une couche de SiO2. Les caractérisations électriques de MIM et de SET formés avec des jonctions TiN/Al2O3 ont permis de démontrer la présence de pièges dans les jonctions et la fonctionnalité d’un SET à basse température (1,5 K). Le transfert de ce procédé sur CMOS et le procédé d’interconnexions verticales sont aussi développés par la suite. Finalement, un circuit 3D composé d’un nanofil de titane connecté verticalement à un transistor MOS est réalisé et caractérisé avec succès. Les résultats obtenus lors de cette thèse permettent de valider la possibilité de co-intégrer verticalement des dispositifs nanoélectroniques avec une technologie CMOS, en utilisant un procédé de fabrication compatible.

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In this work we compare the hydrothermal stability performance of a Templated Molecular Sieve Silica (TMSS) membrane against a standard, non-templated Molecular Sieve Silica (MSS) membrane. The tests were carried under dry and wet (steam) conditions for single gas (He, H2, CO and CO2) at 1-2 atm membrane pressure drop at 200oC. Single gas TMSS membrane H2, permeance and H2/CO permselectivity was found to be 2.05 x 10-8 mols.m-2.s-1.Pa-1 and 15, respectively. The MSS membrane showed similar selectivity, but increased overall flux. He permeance through membranes decayed at a rate of 4-5 x 10-10 mols.m-2.s-1.Pa-1 per day regardless of membrane ambience (dry or wet). Although H2/CO permselectivity of the TMSS membrane slightly improved from 15 to 18 after steam testing, the MSS membrane resulted in significant reduction from 16 to 8.3. In addition, membrane regeneration after more than 50 days resulted in the TMSS membrane reverting to its original permeation levels while no significant improvements were observed for the MSS membra ne. Results showed that the TMSS membrane had enhanced hydrothermal stability and regeneration ability.

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Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

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The aim of this thesis is to examine stock returns as predictive indicators to macroeconomic variables in BRIC-countries, Japan, USA and euro area. We picked to represent macroeconomic variables interest rate, inflation, currency, gross domestic product and industrial production. For the beginning we examined previous studies and theory about the subject. Hypothesis of this thesis were derived from the previous studies. To conduct the results we used tests such augmented Dickey-Fuller, Engle-Granger co-integration, Granger causality and lagged distribution model. According to results stock returns do predictive macroeconomic variables and specifically changes of GDP and industrial production. There were few evidences of stock returns predictive power of inflation.

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Abstract Big data nowadays is a fashionable topic, independently of what people mean when they use this term. But being big is just a matter of volume, although there is no clear agreement in the size threshold. On the other hand, it is easy to capture large amounts of data using a brute force approach. So the real goal should not be big data but to ask ourselves, for a given problem, what is the right data and how much of it is needed. For some problems this would imply big data, but for the majority of the problems much less data will and is needed. In this talk we explore the trade-offs involved and the main problems that come with big data using the Web as case study: scalability, redundancy, bias, noise, spam, and privacy. Speaker Biography Ricardo Baeza-Yates Ricardo Baeza-Yates is VP of Research for Yahoo Labs leading teams in United States, Europe and Latin America since 2006 and based in Sunnyvale, California, since August 2014. During this time he has lead the labs in Barcelona and Santiago de Chile. Between 2008 and 2012 he also oversaw the Haifa lab. He is also part time Professor at the Dept. of Information and Communication Technologies of the Universitat Pompeu Fabra, in Barcelona, Spain. During 2005 he was an ICREA research professor at the same university. Until 2004 he was Professor and before founder and Director of the Center for Web Research at the Dept. of Computing Science of the University of Chile (in leave of absence until today). He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989. Before he obtained two masters (M.Sc. CS & M.Eng. EE) and the electronics engineer degree from the University of Chile in Santiago. He is co-author of the best-seller Modern Information Retrieval textbook, published in 1999 by Addison-Wesley with a second enlarged edition in 2011, that won the ASIST 2012 Book of the Year award. He is also co-author of the 2nd edition of the Handbook of Algorithms and Data Structures, Addison-Wesley, 1991; and co-editor of Information Retrieval: Algorithms and Data Structures, Prentice-Hall, 1992, among more than 500 other publications. From 2002 to 2004 he was elected to the board of governors of the IEEE Computer Society and in 2012 he was elected for the ACM Council. He has received the Organization of American States award for young researchers in exact sciences (1993), the Graham Medal for innovation in computing given by the University of Waterloo to distinguished ex-alumni (2007), the CLEI Latin American distinction for contributions to CS in the region (2009), and the National Award of the Chilean Association of Engineers (2010), among other distinctions. In 2003 he was the first computer scientist to be elected to the Chilean Academy of Sciences and since 2010 is a founding member of the Chilean Academy of Engineering. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow.

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El presente documento se propone estimar y analizar la existencia de una relación de equilibrio de largo plazo entre la producción industrial y la importación de bienes de capital y materias primas para el período enero de 1993 - abril de 2005, que resulta útil para monitorear la dinámica industrial en el corto plazo y las complementariedades que pueden existir entre los factores productivos del mercado interno con el externo. Para tal efecto, se desarrolla un análisis econométrico de la metodología de cointegración con componentes estacionales aplicado a las variables índice de producción real (IPR), importación de bienes de capital e importación de materias primas de la industria colombiana. A partir de un modelo de cointegración estacional se evidencia empíricamente la existencia de una relación de equilibrio de largo plazo entre estas variables durante el período analizado. Adicionalmente, se utiliza el modelo estimado para realizar ejercicios de impulso-respuesta para analizar la trayectoria futura de las variables de interés cuando son afectadas por choques exógenos en el tiempo.

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O presente estudo apresenta um modelo de previsão do preço e do volume comercializado no mercado transoceânico de minério de ferro. Para tanto, foi desenvolvido um modelo VAR, utilizando, além das variáveis endógenas com um lag de diferença, o preço do petróleo Brent e um índice de produção industrial. Após testar raiz unitária das variáveis e constatar que nenhuma era estacionária, o teste de cointegração atestou que existia relação de longo prazo entre as mesmas que era estacionária, afastando a possibilidade de uma regressão espúria. Como resultado, a modelagem VAR apresentou um modelo consistente, com elevada aderência para a previsão do preço e do volume negociado de minério de ferro no mercado transoceânico, não obstante ele tenha apresentado alguma imprecisão no curto prazo.

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The design of a Gilbert Cell Mixer and a low noise amplifier (LNA), using GaAs PHEMT technology is presented. The compatibility is shown for co-integration of both block on the same chip, to form a high performance 1.9 GHz receiver front end. The designed LNA shows 9.23 dB gain and 2.01 dB noise figure (NF). The mixer is designed to operate at RF=1.9 GHz, LO=2.0 GHz and IF=100 MHz with a gain of 14.3 dB and single sideband noise figure (SSB NF) of 9.6 dB. The mixer presents a bandwith of 8 GHz.

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The design of a Gilbert Cell Mixer and a low noise amplifier (LNA), using GaAs PHEMT technology is presented. The compatibility is shown for co-integration of both block on the same chip, to form a high performance 1.9 GHz receiver front-end. The designed LNA shows 9.23 dB gain and 2.01 dB noise figure (NF). The mixer is designed to operate at RF=1.9 GHz, LO=2.0 GHz and IF=100 MHz with a gain of 14.3 dB and single sideband noise figure (SSB NF) of 9.6 dB. The mixer presents a bandwith of 8 GHz.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)