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on Forecasting |
| By: | Bokan, Nikola; Lenza, Michele; Araujo, Douglas; Comazzi, Fabio Alberto |
| Abstract: | Word embeddings are vectors of real numbers associated with words, designed to capture semantic and syntactic similarity between the words in a corpus of text. We estimate the word embeddings of the European Central Bank’s introductory statements at monetary policy press conferences by using a simple natural language processing model (Word2Vec), only based on the information and model parameters available as of each press conference. We show that a measure based on such embeddings contributes to improve core inflation forecasts multiple quarters ahead. Other common textual analysis techniques, such as dictionary-based metrics or sentiment metrics do not obtain the same results. The information contained in the embeddings remains valuable for out-of-sample forecasting even after controlling for the central bank inflation forecasts, which are an important input for the introductory statements. JEL Classification: E31, E37, E58 |
| Keywords: | central bank texts, embeddings, forecasting, inflation |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbwps:20253047 |
| By: | Jonas D. M. Fisher; Leonardo Melosi; Sebastian Rast |
| Abstract: | Professional forecasters’ long-run inflation expectations overreact to news and exhibit persistent, predictable biases in forecast errors. A model incorporating overconfidence in private information and a persistent expectations bias—which generates persistent forecast errors across most forecasters—accounts for these two features of the data, offering a valuable tool for studying long-run inflation expectations. Our analysis highlights substantial, time-varying heterogeneity in forecasters’ responses to public information, with sensitivity declining across all forecasters when monetary policy is constrained by the effective lower bound. The model provides a framework to evaluate whether policymakers’ communicated inflation paths are consistent with anchored long-run expectations. |
| Keywords: | Central bank communication; anchoring |
| JEL: | E31 D83 E52 E37 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedhwp:99677 |
| By: | triyawan, andi |
| Abstract: | To find out the price movement of JKII Stock prices in the future by using the Autoregressive Integrated Moving Average (ARIMA) method. The purpose of this research is to create a model and predict future prices of Jakarta Islamic Index Stock. The data used in this study is time series data in the form of bitcoin prices for 365 periods from 28 May 2022 to 26 May 2023 to predict JKII Stock prices for the next 10 periods from 29 May 2023 to 7 June 2023. The results of the study show that the JKII Stock prices for 365 periods does not meet the assumption of stationarity, so a differecing process is carried out so that the data becomes stationary. The resulting ARIMA model is ARIMA(1, 0, 0) and this model is suitable for predicting the price of JKII Stock. Also, The results of the analysis with ARIMA lead to the price of Stock for the next 10 periods increasing slowly. |
| Date: | 2023–06–12 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:z4m2s_v1 |
| By: | Yuying Sun (School of Economics and Management, University of Chinese Academy of Sciences and Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China); Shaoxin Hong (Center for Economic Research, Shandong University, Jinan, Shandong 250100, China); Zongwu Cai (Department of Economics, The University of Kansas, Lawrence, KS 66045, USA) |
| Abstract: | This paper proposes a novel state-varying model averaging prediction for varyingcoefficient models that accounts for parameter uncertainty and model misspecification. We develop a leave-h-out state-dependent forward-validation criterion to select state-varying combination weights. It is shown that the proposed averaging prediction is asymptotically optimal in the sense of achieving the lowest possible out-of-sample prediction risk in a class of model averaging estimators. This complements existing model averaging methods that primarily focus on minimizing the in-sample squared error loss. Besides, when the set of candidate models includes correctly specified models, the proposed approach asymptotically assigns full weight to these models. Furthermore, the proposed approach is flexible and encompasses special cases including ultra-high dimensional models as well as state-varying factor-augmented regression models. Simulation studies and empirical applications highlight the merits of the proposed averaging prediction relative to other existing model averaging and model selection methods. |
| Keywords: | Asymptotic optimality; Varying-coefficient models; Forward-validation; Model averaging; Weight convergence |
| JEL: | C2 C13 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:kan:wpaper:202507 |
| By: | Jonas D. M. Fisher, Jonas D. (FRB Chicag); Melosi, Leonardo (University of Warwick, European University Institute, De Nederlandsche Bank, and CEPR); Sebastian Rast, Sebastian (De Nederlandsche Bank) |
| Abstract: | Professional forecasters’ long-run inflation expectations overreact to news and exhibit persistent, predictable biases in forecast errors. A model incorporating overconfidence in private information and a persistent expectations bias—which generates persistent forecast errors across most forecasters—accounts for these two features of the data, offering a valuable tool for studying long-run inflation expectations. Our analysis highlights substantial, timevarying heterogeneity in forecasters’ responses to public information, with sensitivity declining across all forecasters when monetary policy is constrained by the effective lower bound. The model provides a framework to evaluate whether policymakers’ communicated inflation paths are consistent with anchored long-run expectations. |
| Keywords: | Panel survey data ; long-run inflation expectations ; rationality ; expectation bias ; overconfidence ; overreaction ; central bank communications ; anchoring JEL Codes: E31 ; D83 ; E52 ; E37 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1551 |
| By: | Granziera, Eleanora (Norges Bank); Larsen, Wegard H. (BI Norwegian Business School); Meggiorini, Greta (University of Auckland); Melosi, Leonardo (University of Warwick, European University Institute, DNB, and CEPR) |
| Abstract: | We investigate how speeches by Federal Open Market Committee (FOMC) members and regional Federal Reserve presidents influence private sector expectations. Speeches highlighting upcoming inflationary pressures lead both households and professional forecasters to raise their inflation expectations, suggesting the presence of Delphic effects. While professional forecasters adjust their expectations in response to Odyssean communications—i.e., statements about the central bank’s reaction to the announced inflationary pressures—households do not, leaving Delphic effects dominant. A novel general equilibrium model, in which agents differ in their ability to interpret Odyssean signals, accounts for these differential patterns. |
| Keywords: | Central bank communication ; Delphic, Odyssean ; inflation expectations ; textual analysis ; expectation formation |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1555 |