International Journal of Forecasting最新文献_第8页

Skew–Brownian processes for estimating the volatility of crude oil Brent 用于估算布伦特原油波动率的偏斜-布朗过程

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-07-20 DOI: 10.1016/j.ijforecast.2024.06.009

Michele Bufalo , Brunero Liseo , Giuseppe Orlando

引用次数: 0

Does economic uncertainty predict real activity in real time? 经济的不确定性能实时预测实际活动吗？

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-07-20 DOI: 10.1016/j.ijforecast.2024.06.008

Bart Keijsers , Dick van Dijk

{"title":"Does economic uncertainty predict real activity in real time?","authors":"Bart Keijsers , Dick van Dijk","doi":"10.1016/j.ijforecast.2024.06.008","DOIUrl":"10.1016/j.ijforecast.2024.06.008","url":null,"abstract":"<div><div>We assess the predictive ability of 15 economic uncertainty measures in a real-time out-of-sample forecasting exercise for The Conference Board’s coincident economic index and its components (industrial production, employment, personal income, and manufacturing and trade sales). The results show that the measures hold (real-time) predictive power for quantiles in the left tail. Because uncertainty measures are all proxies of an unobserved entity, we combine their information using principal component analysis. A large fraction of the variance of the uncertainty measures can be explained by two factors: a general economic uncertainty factor with a slight tilt toward financial conditions, and a consumer/media confidence index which remains elevated after recessions. Using a predictive regression model with the factors from the set of uncertainty measures yields more consistent gains compared to a model with an individual uncertainty measure. Further, although accurate forecasts are obtained using the National Financial Conditions Index (NFCI), the uncertainty factor models are better when forecasting employment, and in general, the uncertainty factors have predictive content that is complementary to the NFCI.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 748-762"},"PeriodicalIF":6.9,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptively aggregated forecast for exponential family panel model 指数族面板模型的自适应汇总预测

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-07-19 DOI: 10.1016/j.ijforecast.2024.06.005

Dalei Yu , Nian-Sheng Tang , Yang Shi

{"title":"Adaptively aggregated forecast for exponential family panel model","authors":"Dalei Yu , Nian-Sheng Tang , Yang Shi","doi":"10.1016/j.ijforecast.2024.06.005","DOIUrl":"10.1016/j.ijforecast.2024.06.005","url":null,"abstract":"<div><div>Aggregation strategies play an important role akin to that of model selection and have been extensively studied in different statistical models to improve forecasting accuracy. However, traditional aggregated forecast strategies for panel data are mainly developed under the assumption that response variables are continuously distributed (or normally distributed). Replacing this assumption by a more general family of distributions, i.e., exponential family distributions, this paper proposes a computationally efficient way to construct the cumulative risk function and to explicitly accommodate the correlation structure of within-subject observations, develops two novel adaptively aggregated forecasting strategies via exponential reweighting and quadratic reweighting, and rigorously establishes the corresponding tight oracle inequalities. The proposed exponential reweighting-based strategy enjoys promising Kullback–Leibler risk-bound adaptation. Moreover, under the quadratic risk, a promising adaptation property can be achieved by the quadratic reweighting-based strategy. The risk-bound properties of the two proposed procedures in the presence of pre-screening are established under mild conditions. The calibration properties of the proposed methods are also analyzed. Simulation studies, together with an example in analyzing television viewers’ binary decision sequence of watching drama episodes, verify the superiority of our methods over existing model selection and aggregation methods.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 733-747"},"PeriodicalIF":6.9,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141848769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Probabilistic forecasting of cross-sectional returns: A Bayesian dynamic factor model with heteroskedasticity 横截面回报的概率预测：具有异方差性的贝叶斯动态因子模型

IF 7.1 2区经济学

International Journal of Forecasting Pub Date : 2024-07-12 DOI: 10.1016/j.ijforecast.2024.06.007

Dan Weitzenfeld

引用次数: 0

Predicting and optimizing the fair allocation of donations in hunger relief supply chains 预测和优化饥饿救济供应链中捐款的公平分配

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-07-10 DOI: 10.1016/j.ijforecast.2024.06.004

Nowshin Sharmile , Isaac A. Nuamah , Lauren Davis , Funda Samanlioglu , Steven Jiang , Carter Crain

引用次数: 0

Emotions and the status quo: The anti-incumbency bias in political prediction markets 情绪与现状：政治预测市场中的反在位偏见

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-06-28 DOI: 10.1016/j.ijforecast.2024.06.003

Vahid Karimi Motahhar , Thomas S. Gruca , Mohammad Hosein Tavakoli

{"title":"Emotions and the status quo: The anti-incumbency bias in political prediction markets","authors":"Vahid Karimi Motahhar , Thomas S. Gruca , Mohammad Hosein Tavakoli","doi":"10.1016/j.ijforecast.2024.06.003","DOIUrl":"10.1016/j.ijforecast.2024.06.003","url":null,"abstract":"<div><div>Emotions are often associated with politics, with new research confirming this connection. There is a link between negative emotions and political actions that oppose an incumbent candidate or party. We examine whether this “anti-incumbency” bias extends to political prediction markets, where such emotions can conflict with economic rationality. We analyze unique data from <em>Media Predict</em>, a commercial prediction market. Before a trade is executed, participants are asked to write a justification for their actions. Using text analysis, we measure the emotional sentiment of the justifications of traders buying contracts predicting a change in the incumbent candidate or party. Consistent with anti-incumbency bias, the justifications of buyers of a challenger contract had significantly more negative emotional sentiment scores. We document this finding in prediction markets associated with the 2012 US Presidential Election and the 2015 UK General Election. We conclude that, despite incentives to the contrary, traders’ actions in political stock markets are associated with strong emotions tied to incumbency status.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 2","pages":"Pages 571-579"},"PeriodicalIF":6.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An adaptive volatility method for probabilistic forecasting and its application to the M6 financial forecasting competition 概率预测的自适应波动率方法及其在M6金融预测竞赛中的应用

IF 7.1 2区经济学

International Journal of Forecasting Pub Date : 2024-06-22 DOI: 10.1016/j.ijforecast.2024.06.001

Joseph de Vilmarest , Nicklas Werge

{"title":"An adaptive volatility method for probabilistic forecasting and its application to the M6 financial forecasting competition","authors":"Joseph de Vilmarest , Nicklas Werge","doi":"10.1016/j.ijforecast.2024.06.001","DOIUrl":"10.1016/j.ijforecast.2024.06.001","url":null,"abstract":"<div><div>In this paper, we address the problem of probabilistic forecasting using an adaptive volatility method rooted in classical time-varying volatility models and leveraging online stochastic optimization algorithms. These principles were successfully applied in the M6 forecasting competition under the team named <em>AdaGaussMC</em>. Our approach takes a unique path by embracing the Efficient Market Hypothesis (EMH) instead of trying to beat the market directly. We focus on evaluating the efficient market and emphasize the importance of online forecasting in adapting to the dynamic nature of financial markets. The three key points of our approach are: (a) apply the univariate time-varying volatility model AdaVol, (b) obtain probabilistic forecasts of future returns, and (c) optimize the competition metrics using stochastic gradient-based algorithms. We contend that the simplicity of our approach contributes to its robustness and consistency. Our performance in the M6 competition resulted in an overall 7<sup>th</sup> place, with a 5<sup>th</sup> place in the forecasting task. Considering our approach’s perceived simplicity, this achievement underscores the efficacy of our adaptive volatility method in probabilistic forecasting.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 4","pages":"Pages 1514-1520"},"PeriodicalIF":7.1,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A modified VAR-deGARCH model for asynchronous multivariate financial time series via variational Bayesian inference 通过变异贝叶斯推理建立异步多变量金融时间序列的修正 VAR-deGARCH 模型

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-06-21 DOI: 10.1016/j.ijforecast.2024.06.002

Wei-Ting Lai , Ray-Bing Chen , Shih-Feng Huang

引用次数: 0

ABC-based forecasting in misspecified state space models 基于ABC的失范状态空间模型预测

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-06-19 DOI: 10.1016/j.ijforecast.2024.05.005

Chaya Weerasinghe, Rubén Loaiza-Maya, Gael M. Martin, David T. Frazier

{"title":"ABC-based forecasting in misspecified state space models","authors":"Chaya Weerasinghe, Rubén Loaiza-Maya, Gael M. Martin, David T. Frazier","doi":"10.1016/j.ijforecast.2024.05.005","DOIUrl":"10.1016/j.ijforecast.2024.05.005","url":null,"abstract":"<div><div>Approximate Bayesian Computation (ABC) has gained popularity as a method for conducting inference and forecasting in complex models, most notably those which are intractable in some sense. In this paper, we use ABC to produce probabilistic forecasts in state space models (SSMs). Whilst ABC-based forecasting in correctly-specified SSMs has been studied, the misspecified case has not been investigated. It is this case that we emphasize. We invoke recent principles of ‘focused’ Bayesian prediction, whereby Bayesian updates are driven by a scoring rule that rewards predictive accuracy; the aim being to produce predictives that perform well in that rule, despite misspecification. Two methods are investigated for producing the focused predictions. In a simulation setting, ‘coherent’ predictions are in evidence for both methods. That is, the predictive constructed using a particular scoring rule often predicts best according to that rule. Importantly, both focused methods typically produce more accurate forecasts than an exact but misspecified predictive, in particular when the degree of misspecification is marked. An empirical application to a truly intractable SSM completes the paper.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 1","pages":"Pages 270-289"},"PeriodicalIF":6.9,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting the equity premium around the globe: Comprehensive evidence from a large sample 预测全球股票溢价：来自大样本的综合证据

IF 6.9 2区经济学

International Journal of Forecasting Pub Date : 2024-06-08 DOI: 10.1016/j.ijforecast.2024.05.002

Fabian Hollstein , Marcel Prokopczuk , Björn Tharann , Chardin Wese Simen

引用次数: 0