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Exploiting News Analytics for Volatility Forecasting
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-10-22 DOI: 10.1002/jae.3095
Simon Tranberg Bodilsen, Asger Lunde
{"title":"Exploiting News Analytics for Volatility Forecasting","authors":"Simon Tranberg Bodilsen,&nbsp;Asger Lunde","doi":"10.1002/jae.3095","DOIUrl":"https://doi.org/10.1002/jae.3095","url":null,"abstract":"<p>This study investigates the potential of news sentiment in predicting stock market volatility. We augment traditional time series models of realized volatility with the sentiment of macroeconomic and firm-specific news. Our results demonstrate that incorporating the sentiment of domestic macroeconomic news significantly improves volatility predictions for individual stocks and the S&amp;P 500 Index. Notably, we find substantial enhancements in long-horizon volatility predictions when including the sentiment of macroeconomic news in the regression models. In contrast, firm-specific news sentiment shows only modest predictive power in the general framework. However, expanding the set of predictors to include the news count of firm-specific news occurring overnight between two consecutive trading periods significantly improves one-period-ahead volatility forecasts.</p><p><b>JEL Classification:</b> C53, C55, C58, G14, G17</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"40 1","pages":"18-36"},"PeriodicalIF":2.3,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3095","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Quantile-Based Test for Heterogeneous Treatment Effects 基于量纲的异质性治疗效果检验
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-10-16 DOI: 10.1002/jae.3093
EunYi Chung, Mauricio Olivares
{"title":"Quantile-Based Test for Heterogeneous Treatment Effects","authors":"EunYi Chung,&nbsp;Mauricio Olivares","doi":"10.1002/jae.3093","DOIUrl":"https://doi.org/10.1002/jae.3093","url":null,"abstract":"<p>We introduce a permutation test for heterogeneous treatment effects based on the quantile process. However, tests based on the quantile process often suffer from estimated nuisance parameters that jeopardize their validity, even in large samples. To overcome this problem, we use Khmaladze's martingale transformation. We show that the permutation test based on the transformed statistic controls size asymptotically. Numerical evidence asserts the good size and power performance of our test procedure compared to other popular quantile-based tests. We discuss a fast implementation algorithm and illustrate our method using experimental data from a welfare reform.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"40 1","pages":"3-17"},"PeriodicalIF":2.3,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Optimal multi-action treatment allocation: A two-phase field experiment to boost immigrant naturalization 优化多重行动治疗分配：促进移民入籍的两阶段实地实验
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-09-05 DOI: 10.1002/jae.3092
Achim Ahrens, Alessandra Stampi-Bombelli, Selina Kurer, Dominik Hangartner
{"title":"Optimal multi-action treatment allocation: A two-phase field experiment to boost immigrant naturalization","authors":"Achim Ahrens,&nbsp;Alessandra Stampi-Bombelli,&nbsp;Selina Kurer,&nbsp;Dominik Hangartner","doi":"10.1002/jae.3092","DOIUrl":"10.1002/jae.3092","url":null,"abstract":"<p>Research underscores the role of naturalization in enhancing immigrants' socio-economic integration, yet application rates remain low. We estimate a policy rule for a letter-based information campaign encouraging newly eligible immigrants in Zurich, Switzerland, to naturalize. The policy rule assigns one out of three treatment letters to each individual, based on their observed characteristics. We field the policy rule to one-half of 1717 immigrants, while sending random treatment letters to the other half. Despite only moderate treatment effect heterogeneity, the policy tree yields a larger, albeit insignificant, increase in application rates compared with assigning the same letter to everyone.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 7","pages":"1379-1395"},"PeriodicalIF":2.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Heterogeneous autoregressions in short T panel data models 短 T 面板数据模型中的异质自回归
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-08-09 DOI: 10.1002/jae.3085
M. Hashem Pesaran, Liying Yang
{"title":"Heterogeneous autoregressions in short \u0000\u0000 \u0000 T\u0000 panel data models","authors":"M. Hashem Pesaran,&nbsp;Liying Yang","doi":"10.1002/jae.3085","DOIUrl":"10.1002/jae.3085","url":null,"abstract":"<p>This paper considers a first-order autoregressive (AR) panel data model with individual-specific effects and heterogeneous AR coefficients defined on the interval \u0000<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>(</mo>\u0000 <mo>−</mo>\u0000 <mn>1,1</mn>\u0000 <mo>]</mo>\u0000 </mrow>\u0000 <annotation>$$ left(-1,1right] $$</annotation>\u0000 </semantics></math>, thus allowing for some of the individual processes to have unit roots. It proposes estimators for the moments of the cross-sectional distribution of the AR coefficients, assuming a random coefficient model for the AR coefficients without imposing any restrictions on the fixed effects. It is shown that the standard generalized method of moments estimators obtained under homogeneous slopes are biased. Small sample properties of the proposed estimators are investigated by Monte Carlo experiments and compared with a number of alternatives, both under homogeneous and heterogeneous slopes. It is found that a simple moment estimator of the mean of heterogeneous AR coefficients performs very well even for moderate sample sizes, but to reliably estimate the variance of AR coefficients, much larger samples are required. It is also required that the true value of this variance is not too close to zero. The utility of the heterogeneous approach is illustrated in the context of earnings dynamics.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 7","pages":"1359-1378"},"PeriodicalIF":2.3,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3085","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141922413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Panel treatment effects measurement: Factor or linear projection modelling? 小组治疗效果测量：因子模型还是线性预测模型？
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-08-09 DOI: 10.1002/jae.3081
Cheng Hsiao, Qiankun Zhou
{"title":"Panel treatment effects measurement: Factor or linear projection modelling?","authors":"Cheng Hsiao,&nbsp;Qiankun Zhou","doi":"10.1002/jae.3081","DOIUrl":"10.1002/jae.3081","url":null,"abstract":"<div>\u0000 \u0000 <p>We discuss methods of measuring the treatment effects of a unit through the use of other units in panel data by either the factor-based (FB) approach or the linear projection (LP) approach under different sample configurations of cross-sectional dimension \u0000<span></span><math>\u0000 <mi>N</mi></math> and time series dimension \u0000<span></span><math>\u0000 <mi>T</mi></math>. We show that the LP approach in general yields smaller mean square prediction error than the FB approach when either both \u0000<span></span><math>\u0000 <mi>N</mi></math> and \u0000<span></span><math>\u0000 <mi>T</mi></math> are large or \u0000<span></span><math>\u0000 <mi>N</mi></math> fixed and \u0000<span></span><math>\u0000 <mi>T</mi>\u0000 <mo>→</mo>\u0000 <mi>∞</mi></math> or \u0000<span></span><math>\u0000 <mi>T</mi></math> fixed and \u0000<span></span><math>\u0000 <mi>N</mi></math> large. The Monte Carlo simulation and empirical example are also conducted to consider their finite sample performances.</p>\u0000 </div>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 7","pages":"1332-1358"},"PeriodicalIF":2.3,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141922658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
The benefits of forecasting inflation with machine learning: New evidence 用机器学习预测通货膨胀的好处：新证据
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-08-08 DOI: 10.1002/jae.3088
Andrea A. Naghi, Eoghan O'Neill, Martina Danielova Zaharieva
{"title":"The benefits of forecasting inflation with machine learning: New evidence","authors":"Andrea A. Naghi,&nbsp;Eoghan O'Neill,&nbsp;Martina Danielova Zaharieva","doi":"10.1002/jae.3088","DOIUrl":"10.1002/jae.3088","url":null,"abstract":"<p>Medeiros et al. (2021) (Journal of Business &amp; Economic Statistics, 39:1, 98–119) find that random forest (RF) outperforms US inflation forecasting benchmarks. We replicate the main results in Medeiros et al. (2021) and (1) considerably expand the set of machine learning methods, (2) analyse the predictive ability of both the initial and extended sets of methods on Canadian and UK data, (3) add results on coverage rates and widths of prediction intervals and (4) extend the sample from January 2016 to October 2022. Our narrow replication confirms the main findings of the original paper. However, the wider replication results suggest that other methods are competitive with RF and often more accurate. In addition, RF produces disappointing results during the coronavirus pandemic and subsequent high inflation of 2020–2022, whereas a stochastic volatility model and some gradient boosting methods produce more accurate forecasts.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 7","pages":"1321-1331"},"PeriodicalIF":2.3,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Fast and order-invariant inference in Bayesian VARs with nonparametric shocks 具有非参数冲击的贝叶斯 VAR 中的快速有序不变推理
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-08-07 DOI: 10.1002/jae.3087
Florian Huber, Gary Koop
{"title":"Fast and order-invariant inference in Bayesian VARs with nonparametric shocks","authors":"Florian Huber,&nbsp;Gary Koop","doi":"10.1002/jae.3087","DOIUrl":"10.1002/jae.3087","url":null,"abstract":"<p>The shocks that hit macroeconomic models such as Vector Autoregressions (VARs) have the potential to be non-Gaussian, exhibiting asymmetries and fat tails. This consideration motivates the VAR developed in this paper that uses a Dirichlet process mixture (DPM) to model the reduced-form shocks. However, we do not follow the obvious strategy of simply modeling the VAR errors with a DPM as this would lead to computationally infeasible Bayesian inference in larger VARs and potentially a sensitivity to the way the variables are ordered in the VAR. Instead, we develop a particular additive error structure inspired by Bayesian nonparametric treatments of random effects in panel data models. We show that this leads to a model that allows for computationally fast and order-invariant inference in large VARs with nonparametric shocks. Our empirical results with nonparametric VARs of various dimensions show that nonparametric treatment of the VAR errors often improves forecast accuracy and can be used to analyze the changing transmission of US monetary policy.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 7","pages":"1301-1320"},"PeriodicalIF":2.3,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Structural breaks and GARCH models of exchange rate volatility: Re-examination and extension 汇率波动的结构性中断和 GARCH 模型：重新审视和扩展
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-08-06 DOI: 10.1002/jae.3091
Akram Shavkatovich Hasanov, Robert Brooks, Sirojiddin Abrorov, Aktam Usmanovich Burkhanov
{"title":"Structural breaks and GARCH models of exchange rate volatility: Re-examination and extension","authors":"Akram Shavkatovich Hasanov,&nbsp;Robert Brooks,&nbsp;Sirojiddin Abrorov,&nbsp;Aktam Usmanovich Burkhanov","doi":"10.1002/jae.3091","DOIUrl":"10.1002/jae.3091","url":null,"abstract":"<p>We examine the empirical significance of structural changes concerning generalized autoregressive conditional heteroskedasticity (GARCH) models of exchange rate volatility using out-of-sample tests by replicating and carrying out robustness checks on the volatility forecasting study by Rapach and Strauss (Journal of Applied Econometrics, 2008; 23, 65–90). We employ the same econometric models but incorporate recent US dollar daily exchange rates data while also using different software, a relatively recent forecast accuracy test and loss metrics. Our objective is to attain scientific replication in a broad sense. Our analysis verifies and broadly aligns with the results obtained in the original study. In particular, we find strong evidence that the models incorporating structural breaks demonstrate superior performance across all loss functions and forecast horizons compared with those models that ignore instabilities.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 7","pages":"1403-1407"},"PeriodicalIF":2.3,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Sudden stop: Supply and demand shocks in the German natural gas market 急刹车：德国天然气市场的供需冲击
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-07-31 DOI: 10.1002/jae.3089
Jochen Güntner, Magnus Reif, Maik Wolters
{"title":"Sudden stop: Supply and demand shocks in the German natural gas market","authors":"Jochen Güntner,&nbsp;Magnus Reif,&nbsp;Maik Wolters","doi":"10.1002/jae.3089","DOIUrl":"10.1002/jae.3089","url":null,"abstract":"<p>We use a structural vector autoregressive (SVAR) model to study the German natural gas market and investigate the impact of the 2022 Russian supply stop on the German economy. Combining conventional and narrative sign restrictions, we find that gas supply and demand shocks have large and persistent price effects, while output effects tend to be moderate. The 2022 natural gas price spike was driven by adverse supply shocks and positive storage demand shocks, as Germany filled its inventories before the winter. Counterfactual simulations of an embargo on natural gas imports from Russia indicate similar positive price and negative output effects compared with what we observe in the data.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 7","pages":"1282-1300"},"PeriodicalIF":2.3,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
The boosted Hodrick-Prescott filter is more general than you might think 增强型霍德里克-普雷斯科特滤波器比你想象的更通用
IF 2.3 3区 经济学
Journal of Applied Econometrics Pub Date : 2024-07-30 DOI: 10.1002/jae.3086
Ziwei Mei, Peter C. B. Phillips, Zhentao Shi
{"title":"The boosted Hodrick-Prescott filter is more general than you might think","authors":"Ziwei Mei,&nbsp;Peter C. B. Phillips,&nbsp;Zhentao Shi","doi":"10.1002/jae.3086","DOIUrl":"10.1002/jae.3086","url":null,"abstract":"<p>The global financial crisis and Covid-19 recession have renewed discussion concerning trend-cycle discovery in macroeconomic data, and boosting has recently upgraded the popular Hodrick-Prescott filter to a modern machine learning device suited to data-rich and rapid computational environments. This paper extends boosting's trend determination capability to higher order integrated processes and time series with roots that are local to unity. The theory is established by understanding the asymptotic effect of boosting on a simple exponential function. Given a universe of time series in FRED databases that exhibit various dynamic patterns, boosting timely captures downturns at crises and recoveries that follow.</p>","PeriodicalId":48363,"journal":{"name":"Journal of Applied Econometrics","volume":"39 7","pages":"1260-1281"},"PeriodicalIF":2.3,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jae.3086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
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