862 resultados para Error correction model
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We look through both the demand and supply side information to understand dynamics of price determination in the real estate market and examine how accurately investors’ attitudes predict the market returns and thereby flagging off extent of any demand-supply mismatch. Our hypothesis is based on the possibility that investors’ call for action in terms of their buy/sell decision and adjustment in reservation/offer prices may indicate impending demand-supply imbalances in the market. In the process, we study several real estate sectors to inform our analysis. The timeframe of our analysis (1995-2010) allows us to observe market dynamics over several economic cycles and in various stages of those cycles. Additionally, we also seek to understand how investors’ attitude or the sentiment affects the market activity over the cycles through asymmetric responses. We test our hypothesis variously using a number of measures of market activity and attitude indicators within several model specifications. The empirical models are estimated using Vector Error Correction framework. Our analysis suggests that investors’ attitude exert strong and statistically significant feedback effects in price determination. Moreover, these effects do reveal heterogeneous responses across the real estate sectors. Interestingly, our results indicate the asymmetric responses during boom, normal and recessionary periods. These results are consistent with the theoretical underpinnings.
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This paper examines the lead–lag relationship between the FTSE 100 index and index futures price employing a number of time series models. Using 10-min observations from June 1996–1997, it is found that lagged changes in the futures price can help to predict changes in the spot price. The best forecasting model is of the error correction type, allowing for the theoretical difference between spot and futures prices according to the cost of carry relationship. This predictive ability is in turn utilised to derive a trading strategy which is tested under real-world conditions to search for systematic profitable trading opportunities. It is revealed that although the model forecasts produce significantly higher returns than a passive benchmark, the model was unable to outperform the benchmark after allowing for transaction costs.
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Low-power medium access control (MAC) protocols used for communication of energy constraint wireless embedded devices do not cope well with situations where transmission channels are highly erroneous. Existing MAC protocols discard corrupted messages which lead to costly retransmissions. To improve transmission performance, it is possible to include an error correction scheme and transmit/receive diversity. It is possible to add redundant information to transmitted packets in order to recover data from corrupted packets. It is also possible to make use of transmit/receive diversity via multiple antennas to improve error resiliency of transmissions. Both schemes may be used in conjunction to further improve the performance. In this study, the authors show how an error correction scheme and transmit/receive diversity can be integrated in low-power MAC protocols. Furthermore, the authors investigate the achievable performance gains of both methods. This is important as both methods have associated costs (processing requirements; additional antennas and power) and for a given communication situation it must be decided which methods should be employed. The authors’ results show that, in many practical situations, error control coding outperforms transmission diversity; however, if very high reliability is required, it is useful to employ both schemes together.
The effect of teacher correction and student revision on university A-level student written accuracy
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This dissertation proposes a bivariate markov switching dynamic conditional correlation model for estimating the optimal hedge ratio between spot and futures contracts. It considers the cointegration between series and allows to capture the leverage efect in return equation. The model is applied using daily data of future and spot prices of Bovespa Index and R$/US$ exchange rate. The results in terms of variance reduction and utility show that the bivariate markov switching model outperforms the strategies based ordinary least squares and error correction models.
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The paper aims to investigate on empirical and theoretical grounds the Brazilian exchange rate dynamics under floating exchange rates. The empirical analysis examines the short and long term behavior of the exchange rate, interest rate (domestic and foreign) and country risk using econometric techniques such as variance decomposition, Granger causality, cointegration tests, error correction models, and a GARCH model to estimate the exchange rate volatility. The empirical findings suggest that one can argue in favor of a certain degree of endogeneity of the exchange rate and that flexible rates have not been able to insulate the Brazilian economy in the same patterns predicted by literature due to its own specificities (managed floating with the use of international reserves and domestic interest rates set according to inflation target) and to externally determined variables such as the country risk. Another important outcome is the lack of a closer association of domestic and foreign interest rates since the new exchange regime has been adopted. That is, from January 1999 to May 2004, the US monetary policy has no significant impact on the Brazilian exchange rate dynamics, which has been essentially endogenous primarily when we consider the fiscal dominance expressed by the probability of default.
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This paper investigates whether there is evidence of structural change in the Brazilian term structure of interest rates. Multivariate cointegration techniques are used to verify this evidence. Two econometrics models are estimated. The rst one is a Vector Autoregressive Model with Error Correction Mechanism (VECM) with smooth transition in the deterministic coe¢ cients (Ripatti and Saikkonen [25]). The second one is a VECM with abrupt structural change formulated by Hansen [13]. Two datasets were analysed. The rst one contains a nominal interest rate with maturity up to three years. The second data set focuses on maturity up to one year. The rst data set focuses on a sample period from 1995 to 2010 and the second from 1998 to 2010. The frequency is monthly. The estimated models suggest the existence of structural change in the Brazilian term structure. It was possible to document the existence of multiple regimes using both techniques for both databases. The risk premium for di¤erent spreads varied considerably during the earliest period of both samples and seemed to converge to stable and lower values at the end of the sample period. Long-term risk premiums seemed to converge to inter-national standards, although the Brazilian term structure is still subject to liquidity problems for longer maturities.
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O objetivo do presente trabalho é utilizar modelos econométricos de séries de tempo para previsão do comportamento da inadimplência agregada utilizando um conjunto amplo de informação, através dos métodos FAVAR (Factor-Augmented Vector Autoregressive) de Bernanke, Boivin e Eliasz (2005) e FAVECM (Factor-augmented Error Correction Models) de Baneerjee e Marcellino (2008). A partir disso, foram construídas previsões fora da amostra de modo a comparar a eficácia de projeção dos modelos contra modelos univariados mais simples - ARIMA - modelo auto-regressivo integrado de média móvel e SARIMA - modelo sazonal auto-regressivo integrado de média móvel. Para avaliação da eficácia preditiva foi utilizada a metodologia MCS (Model Confidence Set) de Hansen, Lunde e James (2011) Essa metodologia permite comparar a superioridade de modelos temporais vis-à-vis a outros modelos.
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Esta tese é composta de três artigos que analisam a estrutura a termo das taxas de juros usando diferentes bases de dados e modelos. O capítulo 1 propõe um modelo paramétrico de taxas de juros que permite a segmentação e choques locais na estrutura a termo. Adotando dados do tesouro americano, duas versões desse modelo segmentado são implementadas. Baseado em uma sequência de 142 experimentos de previsão, os modelos propostos são comparados à benchmarks e concluí-se que eles performam melhor nos resultados das previsões fora da amostra, especialmente para as maturidades curtas e para o horizonte de previsão de 12 meses. O capítulo 2 acrescenta restrições de não arbitragem ao estimar um modelo polinomial gaussiano dinâmico de estrutura a termo para o mercado de taxas de juros brasileiro. Esse artigo propõe uma importante aproximação para a série temporal dos fatores de risco da estrutura a termo, que permite a extração do prêmio de risco das taxas de juros sem a necessidade de otimização de um modelo dinâmico completo. Essa metodologia tem a vantagem de ser facilmente implementada e obtém uma boa aproximação para o prêmio de risco da estrutura a termo, que pode ser usada em diferentes aplicações. O capítulo 3 modela a dinâmica conjunta das taxas nominais e reais usando um modelo afim de não arbitagem com variáveis macroeconômicas para a estrutura a termo, afim de decompor a diferença entre as taxas nominais e reais em prêmio de risco de inflação e expectativa de inflação no mercado americano. Uma versão sem variáveis macroeconômicas e uma versão com essas variáveis são implementadas e os prêmios de risco de inflação obtidos são pequenos e estáveis no período analisado, porém possuem diferenças na comparação dos dois modelos analisados.
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This research aims to investigate the Hedge Efficiency and Optimal Hedge Ratio for the future market of cattle, coffee, ethanol, corn and soybean. This paper uses the Optimal Hedge Ratio and Hedge Effectiveness through multivariate GARCH models with error correction, attempting to the possible phenomenon of Optimal Hedge Ratio differential during the crop and intercrop period. The Optimal Hedge Ratio must be bigger in the intercrop period due to the uncertainty related to a possible supply shock (LAZZARINI, 2010). Among the future contracts studied in this research, the coffee, ethanol and soybean contracts were not object of this phenomenon investigation, yet. Furthermore, the corn and ethanol contracts were not object of researches which deal with Dynamic Hedging Strategy. This paper distinguishes itself for including the GARCH model with error correction, which it was never considered when the possible Optimal Hedge Ratio differential during the crop and intercrop period were investigated. The commodities quotation were used as future price in the market future of BM&FBOVESPA and as spot market, the CEPEA index, in the period from May 2010 to June 2013 to cattle, coffee, ethanol and corn, and to August 2012 to soybean, with daily frequency. Similar results were achieved for all the commodities. There is a long term relationship among the spot market and future market, bicausality and the spot market and future market of cattle, coffee, ethanol and corn, and unicausality of the future price of soybean on spot price. The Optimal Hedge Ratio was estimated from three different strategies: linear regression by MQO, BEKK-GARCH diagonal model, and BEKK-GARCH diagonal with intercrop dummy. The MQO regression model, pointed out the Hedge inefficiency, taking into consideration that the Optimal Hedge presented was too low. The second model represents the strategy of dynamic hedge, which collected time variations in the Optimal Hedge. The last Hedge strategy did not detect Optimal Hedge Ratio differential between the crop and intercrop period, therefore, unlikely what they expected, the investor do not need increase his/her investment in the future market during the intercrop
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As condições de ambiente térmico e aéreo, no interior de instalações para animais, alteram-se durante o dia, devido à influência do ambiente externo. Para que análises estatísticas e geoestatísticas sejam representativas, uma grande quantidade de pontos distribuídos espacialmente na área da instalação deve ser monitorada. Este trabalho propõe que a variação no tempo das variáveis ambientais de interesse para a produção animal, monitoradas no interior de instalações para animais, pode ser modelada com precisão a partir de registros discretos no tempo. O objetivo deste trabalho foi desenvolver um método numérico para corrigir as variações temporais dessas variáveis ambientais, transformando os dados para que tais observações independam do tempo gasto durante a aferição. O método proposto aproximou os valores registrados com retardos de tempo aos esperados no exato momento de interesse, caso os dados fossem medidos simultaneamente neste momento em todos os pontos distribuídos espacialmente. O modelo de correção numérica para variáveis ambientais foi validado para o parâmetro ambiental temperatura do ar, sendo que os valores corrigidos pelo método não diferiram pelo teste Tukey, a 5% de probabilidade dos valores reais registrados por meio de dataloggers.
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This study aims to investigate the influence of the balance of payments constrained on economic growth in Brazil from 1991 to 2010. With this order, are shown some of the Keynesian balance of payments constrained growth models, inspired by Thirlwall (1979) and Kaldor (1970), which are supported by important points in common, such as adherence to the principle of effective demand. Given that within this theoretical perspective, there is no consensus about the best model to explain the growth rate allowed by the balance of payments constraint, the results are presented by the representative of the empirical literature that addresses the topic, which are necessary for understand the Brazilian case. From the estimation of the income elasticity of imports (0.85) via autoregressive vectors with error correction (VEC), it was calculated five growth rates of income, as predicted by the models of Thirlwall (1979), Thirlwall and Hussain (1982), Moreno-Brid (1998, 2003) and Lourenço et al. (2011) and compared with the actual growth rate. The empirical analysis has shown that: it can not reject the presence of external constraint in the Brazilian economy, there is a strong similarity in growth rates provided by different modeling suggest that growth with external constraint. In addition, when using data in quarterly for the period after 1990 there are no factors that could cause instability in the parameters of the import function (income elasticity and price elasticity of imports) within the period, which indicates that the structural break widely associated with the year 1994 was not confirmed by this study
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Nowadays, with the implantation of GNSS (Global Navigation Satellite System) reference station networks, several positioning techniques have been developed and/or improved. Using such kind of network data it is possible to model the GNSS distance dependent errors and to compute correction terms for the network region. Several methods have been developed to formulate the corrections terms from network stations data. A method that has been received a great attention is the Virtual Reference Station (VRS). The idea is that the VRS data resemble as much as possible a real receiver data placed in the same local. Therefore, the user has the possibility of using the VRS as if it were a real reference station in your proximities, and to accomplish the relative positioning with a single frequency receiver. In this paper it is described a different methodology applied to implement the VRS concept, using atmospheric models developed by Brazilian researchers. Besides, experiments for evaluating the quality of generated VRS are presented, showing the efficiency of the proposed method.
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Este trabalho apresenta um estudo sobre transmissões de vídeo em sistemas sem fio. O objetivo da metodologia aplicada é comprovar a existência de uma relação direta entre a BER e a perda de qualidade (Perda de PSNR) nas transmissões de vídeo em sistemas OFDM (Orthogonal Frequency Division Multiplexing). Os resultados foram obtidos a partir de simulações, desenvolvidas no ambiente computacional Matlab®, e, aferições em cenários reais, realizadas no campus universitário e dentro do laboratório de estudos, em ambiente controlado. A partir da comparação entre dados simulados e aferidos, foi comprovada a relação entre BER e Perda de PSNR, resultando na formulação de um modelo empírico Cross-Layer com característica exponencial. A modelagem obteve erro RMS e desvio padrão próximos de 1,65 dB quando comparada com as simulações. Além disso, sua validação foi realizada a partir dos dados obtidos de cenários reais, que não foram usados para ajustar os parâmetros da equação obtida. O modelo obtido não necessita da especificação do tipo de canal ou codificação utilizada no FEC (Forward Error Correction), possibilitando uma futura integração com softwares de planejamento de redes, em versões comerciais ou open-sources.
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Corresponding to $C_{0}[n,n-r]$, a binary cyclic code generated by a primitive irreducible polynomial $p(X)\in \mathbb{F}_{2}[X]$ of degree $r=2b$, where $b\in \mathbb{Z}^{+}$, we can constitute a binary cyclic code $C[(n+1)^{3^{k}}-1,(n+1)^{3^{k}}-1-3^{k}r]$, which is generated by primitive irreducible generalized polynomial $p(X^{\frac{1}{3^{k}}})\in \mathbb{F}_{2}[X;\frac{1}{3^{k}}\mathbb{Z}_{0}]$ with degree $3^{k}r$, where $k\in \mathbb{Z}^{+}$. This new code $C$ improves the code rate and has error corrections capability higher than $C_{0}$. The purpose of this study is to establish a decoding procedure for $C_{0}$ by using $C$ in such a way that one can obtain an improved code rate and error-correcting capabilities for $C_{0}$.