共查询到20条相似文献，搜索用时 15 毫秒
1.
Levent Bulut 《Journal of forecasting》2018,37(3):303-315
In this paper, we use Google Trends data for exchange rate forecasting in the context of a broad literature review that ties the exchange rate movements with macroeconomic fundamentals. The sample covers 11 OECD countries’ exchange rates for the period from January 2004 to June 2014. In out‐of‐sample forecasting of monthly returns on exchange rates, our findings indicate that the Google Trends search query data do a better job than the structural models in predicting the true direction of changes in nominal exchange rates. We also observed that Google Trends‐based forecasts are better at picking up the direction of the changes in the monthly nominal exchange rates after the Great Recession era (2008–2009). Based on the Clark and West inference procedure of equal predictive accuracy testing, we found that the relative performance of Google Trends‐based exchange rate predictions against the null of a random walk model is no worse than the purchasing power parity model. On the other hand, although the monetary model fundamentals could beat the random walk null only in one out of 11 currency pairs, with Google Trends predictors we found evidence of better performance for five currency pairs. We believe that these findings necessitate further research in this area to investigate the extravalue one can get from Google search query data. 相似文献
2.
Paul Smith 《Journal of forecasting》2016,35(3):263-284
Internet search data could be a useful source of information for policymakers when formulating decisions based on their understanding of the current economic environment. This paper builds on earlier literature via a structured value assessment of the data provided by Google Trends. This is done through two empirical exercises related to the forecasting of changes in UK unemployment. Firstly, economic intuition provides the basis for search term selection, with a resulting Google indicator tested alongside survey‐based variables in a traditional forecasting environment. Secondly, this environment is expanded into a pseudo‐time nowcasting framework which provides the backdrop for assessing the timing advantage that Google data have over surveys. The framework is underpinned by a MIDAS regression which allows, for the first time, the easy incorporation of Internet search data at its true sampling rate into a nowcast model for predicting unemployment. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
3.
In this paper an investigation is made of the properties and use of two aggregate measures of forecast bias and accuracy. These are metrics used in business to calculate aggregate forecasting performance for a family (group) of products. We find that the aggregate measures are not particularly informative if some of the one‐step‐ahead forecasts are biased. This is likely to be the case in practice if frequently employed forecasting methods are used to generate a large number of individual forecasts. In the paper, examples are constructed to illustrate some potential problems in the use of the metrics. We propose a simple graphical display of forecast bias and accuracy to supplement the information yielded by the accuracy measures. This support includes relevant boxplots of measures of individual forecasting success. This tool is simple but helpful as the graphic display has the potential to indicate forecast deterioration that can be masked by one or both of the aggregate metrics. The procedures are illustrated with data representing sales of food items. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
4.
This paper examines the predictive relationship of consumption‐related and news‐related Google Trends data to changes in private consumption in the USA. The results suggest that (1) Google Trends‐augmented models provide additional information about consumption over and above survey‐based consumer sentiment indicators, (2) consumption‐related Google Trends data provide information about pre‐consumption research trends, (3) news‐related Google Trends data provide information about changes in durable goods consumption, and (4) the combination of news and consumption‐related data significantly improves forecasting models. We demonstrate that applying these insights improves forecasts of private consumption growth over forecasts that do not utilize Google Trends data and over forecasts that use Google Trends data, but do not take into account the specific ways in which it informs forecasts. 相似文献
5.
In this study we introduce a new indicator for private consumption based on search query time series provided by Google Trends. The indicator is based on factors extracted from consumption‐related search categories of the Google Trends application Insights for Search. The forecasting performance of the new indicator is assessed relative to the two most common survey‐based indicators: the University of Michigan Consumer Sentiment Index and the Conference Board Consumer Confidence Index. The results show that in almost all conducted in‐sample and out‐of‐sample forecasting experiments the Google indicator outperforms the survey‐based indicators. This suggests that incorporating information from Google Trends may offer significant benefits to forecasters of private consumption. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
6.
Suleyman Gokcan 《Journal of forecasting》2000,19(6):499-504
ARCH and GARCH models are substantially used for modelling volatility of time series data. It is proven by many studies that if variables are significantly skewed, linear versions of these models are not sufficient for both explaining the past volatility and forecasting the future volatility. In this paper, we compare the linear(GARCH(1,1)) and non‐linear(EGARCH) versions of GARCH model by using the monthly stock market returns of seven emerging countries from February 1988 to December 1996. We find that for emerging stock markets GARCH(1,1) model performs better than EGARCH model, even if stock market return series display skewed distributions. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
7.
Gke Soydemir 《Journal of forecasting》2000,19(3):149-176
This paper investigates the transmission patterns of stock market movements between developed and emerging market economies by estimating a four‐variable VAR model. The underlying economic fundamentals and trade links are considered as possible determinants of differences in transmission patterns. The results of the impulse response functions and variance decompositions indicate that significant links exist between the stock markets of the USA and Mexico and weaker links between the markets of the USA, Argentina, and Brazil. Differences in the patterns of stock market responses are consistent with differences in trade flows. The response of emerging markets to a shock to the US market lasts longer than that of a developed market such as the UK. While no single emerging market can affect the US stock market, the combined effect of emerging markets on the US stock market is found to be statistically significant. These findings can be linked to differences in the speed of information processing and to the institutional structure governing the market. Overall the findings suggest that the transmission of stock market movements is in accord with underlying economic fundamentals rather than irrational contagion effects. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
8.
Masahiro Ashiya 《Journal of forecasting》2010,29(5):435-441
This paper investigates whether some forecasters consistently outperform others using Japanese CPI forecast data of 42 forecasters over the past 18 quarters. It finds that the accuracy rankings of 0, 1, 2, and 5‐month forecasts are significantly different from those that might be expected when all forecasters had equal forecasting ability. Moreover, their rankings of the relative forecast levels are also significantly different from a random one. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
9.
We consider tests for the equality of prediction mean squared errors and for forecast encompassing. It is shown that, if forecast errors exhibit ARCH, size distortions are induced in the usual tests. Adjusted test statistics are suggested to alleviate this problem. Copyright © 1999 John Wiley & Sons, Ltd. 相似文献
10.
Benedikt Maas 《Journal of forecasting》2020,39(3):394-411
This paper aims to assess whether Google search data are useful when predicting the US unemployment rate among other more traditional predictor variables. A weekly Google index is derived from the keyword “unemployment” and is used in diffusion index variants along with the weekly number of initial claims and monthly estimated latent factors. The unemployment rate forecasts are generated using MIDAS regression models that take into account the actual frequencies of the predictor variables. The forecasts are made in real time, and the forecasts of the best forecasting models exceed, for the most part, the root mean squared forecast error of two benchmarks. However, as the forecasting horizon increases, the forecasting performance of the best diffusion index variants decreases over time, which suggests that the forecasting methods proposed in this paper are most useful in the short term. 相似文献
11.
In this paper, we forecast local currency debt of five major emerging market countries (Brazil, Indonesia, Mexico, South Africa, and Turkey) over the period January 2010 to January 2019 (with an in-sample period: March 2005 to December 2009). We exploit information from a large set of economic and financial time series to assess the importance not only of “own-country” factors (derived from principal component and partial least squares approaches), but also create “global” predictors by combining the country-specific variables across the five emerging economies. We find that, while information on own-country factors can outperform the historical average model, global factors tend to produce not only greater statistical and economic gains, but also enhance market timing ability of investors, especially when we use the target variable (bond premium) approach under the partial least squares method to extract our factors. Our results have important implications not only for fund managers but also for policymakers. 相似文献
12.
Econometric prediction accuracy for personal income forecasts is examined for a region of the United States. Previously published regional structural equation model (RSEM) forecasts exist ex ante for the state of New Mexico and its three largest metropolitan statistical areas: Albuquerque, Las Cruces and Santa Fe. Quarterly data between 1983 and 2000 are utilized at the state level. For Albuquerque, annual data from 1983 through 1999 are used. For Las Cruces and Santa Fe, annual data from 1990 through 1999 are employed. Univariate time series, vector autoregressions and random walks are used as the comparison criteria against structural equation simulations. Results indicate that ex ante RSEM forecasts achieved higher accuracy than those simulations associated with univariate ARIMA and random walk benchmarks for the state of New Mexico. The track records of the structural econometric models for Albuquerque, Las Cruces and Santa Fe are less impressive. In some cases, VAR benchmarks prove more reliable than RSEM income forecasts. In other cases, the RSEM forecasts are less accurate than random walk alternatives. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
13.
For analysts there is a tradeoff between the accuracy and the timeliness of their forecasts. Prior literature heavily investigates analyst forecast accuracy. Few papers investigate the importance of timeliness. To our best knowledge, there are no empirical papers to date to investigate the dynamic interplay between these key characteristics. We show that if analysts experience a period of high accuracy relative to their peers, they subsequently focus more on the timeliness of their forecasts in the subsequent period and thus issue their forecasts earlier than they did in the prior period. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
14.
Shiu‐Sheng Chen 《Journal of forecasting》2005,24(6):453-464
This paper studies in‐sample and out‐of‐sample tests for Granger causality using Monte Carlo simulation. The results show that the out‐of‐sample tests may be more powerful than the in‐sample tests when discrete structural breaks appear in time series data. Further, an empirical example investigating Taiwan's investment–saving relationship shows that Taiwan's domestic savings may be helpful in predicting domestic investments. It further illustrates that a possible Granger causal relationship is detected by out‐of‐sample tests while the in‐sample test fails to reject the null of non‐causality. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
15.
This paper assesses the international efficiency of the European football betting market by examining the forecastability of match outcomes on the basis of the information contained in different sets of online and fixed odds quoted by six major bookmakers. The paper also investigates the profitability of strategies based on: combined betting, simple heuristic rules, regression models and prediction encompassing. The empirical results show that combined betting across different bookmakers can lead to limited but highly profitable arbitrage opportunities. Simple trading rules and betting strategies based on forecast encompassing are found capable of also producing significant positive returns. Despite the deregulation, globalization and increased competition in the betting industry over recent years, the predictabilities and profits reported in this paper are not fully consistent with weak-form market efficiency. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
16.
There is ample empirical evidence that expert‐adjusted model forecasts can be improved. One way to potential improvement concerns providing various forms of feedback to the sales forecasters. It is also often recognized that the experts (forecasters) might not constitute a homogeneous group. This paper provides a data‐based methodology to discern latent clusters of forecasters, and applies it to a fully new large database with data on expert‐adjusted forecasts, model forecasts and realizations. For the data at hand, two clusters can clearly be identified. Next, the consequences of having clusters are discussed. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
17.
In this paper, we assess the predictive content of latent economic policy uncertainty and data surprise factors for forecasting and nowcasting gross domestic product (GDP) using factor-type econometric models. Our analysis focuses on five emerging market economies: Brazil, Indonesia, Mexico, South Africa, and Turkey; and we carry out a forecasting horse race in which predictions from various different models are compared. These models may (or may not) contain latent uncertainty and surprise factors constructed using both local and global economic datasets. The set of models that we examine in our experiments includes both simple benchmark linear econometric models as well as dynamic factor models that are estimated using a variety of frequentist and Bayesian data shrinkage methods based on the least absolute shrinkage operator (LASSO). We find that the inclusion of our new uncertainty and surprise factors leads to superior predictions of GDP growth, particularly when these latent factors are constructed using Bayesian variants of the LASSO. Overall, our findings point to the importance of spillover effects from global uncertainty and data surprises, when predicting GDP growth in emerging market economies. 相似文献
18.
This paper introduces a methodology for estimating the likelihood of private information usage amongst earnings analysts. This is achieved by assuming that one group of analysts generate forecasts based on the underlying dynamics of earnings, while all other analysts are assumed to issue forecasts based on the prevailing consensus forecast. Given this behavioural dichotomy, we are able to derive (and estimate) a structural econometric model of forecast behaviour, which has implications regarding the determinants of analysts' private information endowments and forecast accuracy over the forecast horizon. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
19.
Frederik Kunze 《Journal of forecasting》2020,39(2):313-333
By linking measures of forecast accuracy as well as testing procedures with regard to forecast rationality this paper investigates aggregated survey forecasts with forecast horizons of 3, 12, and 24 months for the exchange rates of the Chinese yuan, the Hong Kong dollar, the Japanese yen, and the Singapore dollar vis-à-vis the US dollar and, hence, for four different currency regimes. The rationality of the exchange rate predictions is initially assessed utilizing tests for unbiasedness and efficiency which indicate that the investigated forecasts are irrational in the sense that the predictions are biased. As one major contribution of this paper, it is subsequently shown that these results are not consistent with an alternative, less restrictive, measure of rationality. Investigating the order of integration of the time series as well as cointegrating relationships, this empirical evidence supports the conclusion that the majority of forecasts are in fact rational. Regarding forerunning properties of the predictions, the results are rather mediocre, with shorter term forecasts for the tightly managed USD/CNY FX regime being one exception. As one additional important and novel evaluation result, it can be concluded, that the currency regime matters for the quality of exchange rate forecasts. 相似文献
20.
Livio Fenga 《Journal of forecasting》2020,39(2):281-295
Google Trends data is a dataset increasingly employed for many statistical investigations. However, care should be placed in handling this tool, especially when applied for quantitative prediction purposes. Being by design Internet user dependent, estimators based on Google Trends data embody many sources of uncertainty and instability. They are related, for example, to technical (e.g., cross-regional disparities in the degree of computer alphabetization, time dependency of Internet users), psychological (e.g., emotionally driven spikes and other form of data perturbations), linguistic (e.g., noise generated by double-meaning words). Despite the stimulating literature available today on how to use Google Trends data as a forecasting tool, surprisingly, to the best of the author's knowledge, it appears that to date no articles specifically devoted to the prediction of these data have been published. In this paper, a novel forecasting method, based on a denoiser of the wavelet type employed in conjunction with a forecasting model of the class SARIMA (seasonal autoregressive integrated moving average), is presented. The wavelet filter is iteratively calibrated according to a bounded search algorithm, until a minimum of a suitable loss function is reached. Finally, empirical evidence is presented to support the validity of the proposed method. 相似文献