25 resultados para Forecast-combination puzzle
em Repositório digital da Fundação Getúlio Vargas - FGV
Resumo:
In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.
Resumo:
In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.
Resumo:
In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.
Resumo:
The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.
Resumo:
The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.
Resumo:
Our focus is on information in expectation surveys that can now be built on thousands (or millions) of respondents on an almost continuous-time basis (big data) and in continuous macroeconomic surveys with a limited number of respondents. We show that, under standard microeconomic and econometric techniques, survey forecasts are an affine function of the conditional expectation of the target variable. This is true whether or not the survey respondent knows the data-generating process (DGP) of the target variable or the econometrician knows the respondents individual loss function. If the econometrician has a mean-squared-error risk function, we show that asymptotically efficient forecasts of the target variable can be built using Hansens (Econometrica, 1982) generalized method of moments in a panel-data context, when N and T diverge or when T diverges with N xed. Sequential asymptotic results are obtained using Phillips and Moon s (Econometrica, 1999) framework. Possible extensions are also discussed.
Resumo:
Industrial companies in developing countries are facing rapid growths, and this requires having in place the best organizational processes to cope with the market demand. Sales forecasting, as a tool aligned with the general strategy of the company, needs to be as much accurate as possible, in order to achieve the sales targets by making available the right information for purchasing, planning and control of production areas, and finally attending in time and form the demand generated. The present dissertation uses a single case study from the subsidiary of an international explosives company based in Brazil, Maxam, experiencing high growth in sales, and therefore facing the challenge to adequate its structure and processes properly for the rapid growth expected. Diverse sales forecast techniques have been analyzed to compare the actual monthly sales forecast, based on the sales force representatives’ market knowledge, with forecasts based on the analysis of historical sales data. The dissertation findings show how the combination of both qualitative and quantitative forecasts, by the creation of a combined forecast that considers both client´s demand knowledge from the sales workforce with time series analysis, leads to the improvement on the accuracy of the company´s sales forecast.
Resumo:
Using data from the United States, Japan, Germany , United Kingdom and France, Sims (1992) found that positive innovations to shortterm interest rates led to sharp, persistent increases in the price level. The result was conÖrmed by other authors and, as a consequence of its non-expectable nature, was given the name "price puzzle" by Eichenbaum (1992). In this paper I investigate the existence of a price puzzle in Brazil using the same type of estimation and benchmark identiÖcation scheme employed by Christiano et al. (2000). In a methodological improvement over these studies, I qualify the results with the construction of bias-corrected bootstrap conÖdence intervals. Even though the data does show the existence of a statistically signiÖcant price puzzle in Brazil, it lasts for only one quarter and is quantitatively immaterial
Resumo:
This paper uses 1992:1-2004:2 quarterly data and two di§erent methods (approximation under lognormality and calibration) to evaluate the existence of an equity-premium puzzle in Brazil. In contrast with some previous works in the Brazilian literature, I conclude that the model used by Mehra and Prescott (1985), either with additive or recursive preferences, is not able to satisfactorily rationalize the equity premium observed in the Brazilian data. The second contribution of the paper is calling the attention to the fact that the utility function may not exist if the data (as it is the case with Brazilian time series) implies the existence of states in which high negative rates of consumption growth are attained with relatively high probability.
Resumo:
Em 1985, Mehra e Prescott levantaram uma questão que até hoje não foi respondida de forma satisfatória: o prêmio de risco das ações americanas é muito maior do que poderia ser explicado pelo “paradigma neoclássico de finanças econômicas” (financial economics) representado pelo modelo C-CAPM. E, a partir de então, este problema não resolvido ficou conhecido como o “Equity Premium Puzzle” (EPP) ou o “Enigma do Prêmio (de risco) das Ações”. Este enigma estimulou a produção de uma série de artigos, dissertações e teses que tentaram ajustar os modelos intertemporais de utilidade esperada aos dados dos mercados financeiros. Dentro deste contexto, esta tese busca (i) revisar a evolução histórica da teoria dos modelos de maximização da utilidade intertemporal dos agentes, (ii) analisar os pressupostos e conceitos chaves desses modelos, (iii) propor um novo modelo que seja capaz de solucionar o EPP, (iv) aplicar este modelo proposto aos dados históricos anuais entre 1929 e 2004 e (v) validar a lógica deste modelo através das metodologias Mehra-Prescott e Hansen-Jagannathan. Esta tese faz uma crítica de que os estudos até aqui desenvolvidos tentaram explicar a dinâmica de um mercado financeiro altamente sofisticado, através de um modelo de economia não-monetária e de subsistência. Assim, a sua contribuição consiste na alteração desse pressuposto de uma economia de subsistência, considerando que a renda disponível do setor privado não seja integralmente consumida, mas que também possa ser poupada. Assumindo que as pessoas obtêm satisfação (utilidade) tanto pelo consumo atual como pela poupança atual (que será o consumo futuro), será deduzido que a utilidade marginal de consumir é igual à de poupar, em todo e qualquer período. Com base nisso, a utilidade marginal a consumir é substituída pela utilidade marginal de poupar dentro do modelo básico do C-CAPM. Para reforçar a idéia de que o modelo desta tese usa dados de poupança em vez de consumo, ao longo do trabalho ele será chamado de Sanving-CAPM, ou S-CAPM. Este novo modelo mostrou-se capaz de solucionar o EPP quando submetidas às abordagens Mehra-Prescott e Hansen-Jagannathan.
Resumo:
O objetivo dessa dissertação é analisar as variáveis importantes da inflação para a decisão de política econômica do Banco Central. Considerando a importância de reações forward looking das autoridades monetárias num regime de metas de inflação, estudam-se alguns modelos de projeção de inflação de curto prazo para verificar qual modelo possui maior capacidade de previsão. Com o objetivo de entender a dinâmica inflacionária brasileira ao longo desses anos desde a implementação do sistema de metas de inflação, procura-se analisar a dinâmica da inércia inflacionária e do repasse cambial.
Resumo:
We build a pricing kernel using only US domestic assets data and check whether it accounts for foreign markets stylized facts that escape consumption based models. By interpreting our stochastic discount factor as the projection of a pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets. We address predictability issues associated with the forward premium puzzle by: i) using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations, and; ii) by pricing Lustig and Verdelhan (2007)'s foreign currency portfolios. Our results indicate that the relevant state variables that explain foreign-currency market asset prices are also the driving forces behind U.S. domestic assets behavior.
Resumo:
Using information on US domestic financial data only, we build a stochastic discount factor—SDF— and check whether it accounts for foreign markets stylized facts that escape consumption based models. By interpreting our SDF as the projection of a pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets prices. We address predictability issues associated with the forward premium puzzle by: i) using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations, and; ii) by pricing Lustig and Verdelhan (2007)’s foreign currency portfolios. Our results indicate that the relevant state variables that explain foreign-currency market asset prices are also the driving forces behind U.S. domestic assets behavior.
Resumo:
Using information on US domestic financial data only, we build a stochastic discount factor—SDF— and check whether it accounts for foreign markets stylized facts that escape consumption based models. By interpreting our SDF as the projection of a pricing kernel from a fully specified model in the space of returns, our results indicate that a model that accounts for the behavior of domestic assets goes a long way toward accounting for the behavior of foreign assets prices. We address predictability issues associated with the forward premium puzzle by: i) using instruments that are known to forecast excess returns in the moments restrictions associated with Euler equations, and; ii) by comparing this out-of-sample results with the one obtained performing an in-sample exercise, where the return-based SDF captures sources of risk of a representative set of developed and emerging economies government bonds. Our results indicate that the relevant state variables that explain foreign-currency market asset prices are also the driving forces behind U.S. domestic assets behavior.
Resumo:
A inconsistência entre a teoria e o comportamento empírico dos agentes no que tange ao mercado privado de pensões tem se mostrado um dos mais resistentes puzzles presentes na literatura econômica. Em modelos de otimização intertemporal de consumo e poupança sob incerteza em relação ao tempo de vida dos agentes, anuidades são ativos dominantes, anulando ou restringindo fortemente a demanda por ativos cujos retornos não estão relacionados à probabilidade de sobrevivência. Na prática, entretanto, consumidores são extremamente céticos em relação às anuidades. Em oposição ao seguro contra longevidade oferecido pelas anuidades, direitos sobre esses ativos - essencialmente ilíquidos - cessam no caso de morte do titular. Nesse sentido, choques não seguráveis de liquidez e a presença de bequest motives foram consideravelmente explorados como possíveis determinantes da baixa demanda verificada. Apesar dos esforços, o puzzle persiste. Este trabalho amplia a dominância teórica das anuidades sobre ativos não contingentes em mercados incompletos; total na ausência de bequest motives, e parcial, quando os agentes se preocupam com possíveis herdeiros. Em linha com a literatura, simulações numéricas atestam que uma parcela considerável do portfolio ótimo dos agentes seria constituída de anuidades mesmo diante de choques de liquidez, bequest motives, e preços não atuarialmente justos. Em relação a um aspecto relativamente negligenciado pela academia, mostramos que o tempo ótimo de conversão de poupança em anuidades está diretamente relacionado à curva salarial dos agentes. Finalmente, indicamos que, caso as preferências dos agentes sejam tais que o nível de consumo ótimo decaia com a idade, a demanda por anuidades torna-se bastante sensível ao sobrepreço (em relação àquele atuarialmente justo) praticado pela indústria, chegando a níveis bem mais compatíveis com a realidade empírica.