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Detecting and Forecasting Large Deviations and Bubbles in a Near-Explosive Random Coefficient Model
Banerjee, Anurag Narayan - 2013
the fundamental asset value and the recurrent presence of autonomous deviations or bubbles. Such a process can be … theory to analyze ordinary least-squares (OLS) estimation. One important theoretical observation is that the estimator … common procedure in the presence of localizing parameters. This methodology allows to detect the presence of bubbles and …
Persistent link: https://www.econbiz.de/10013076483
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Detecting and Forecasting Large Deviations and Bubbles in a Near-Explosive Random Coe fficient Model
Banerjee, Anurag Narayan - 2017
the fundamental asset value and the recurrent presence of autonomous deviations or bubbles. Such a process can be … theory to analyze ordinary least-squares (OLS) estimation. One important theoretical observation is that the estimator … common procedure in the presence of localizing parameters. This methodology allows to detect the presence of bubbles and …
Persistent link: https://www.econbiz.de/10012973901
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Multivariate variance ratio statistics
Hong, Seok Young; Linton, Oliver; Zhang, Hui Jun - 2014
We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the Efficient Market Hypothesis). We do not...
Persistent link: https://www.econbiz.de/10010365211
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LPPLS bubble indicators over two centuries of the S&P 500 index
Zhang, Qunzhi; Sornette, Didier; Balcilar, Mehmet; … - 2016
The aim of this paper is to present novel tests for the early causal diagnostic of positive and negative bubbles in the … LPPLS (log-periodic power law singularity) approach successfully diagnoses positive and negative bubbles, constructs … efficient End-of-Bubble signals for all of the well-documented bubbles, and obtains for the first time new statistical evidence …
Persistent link: https://www.econbiz.de/10011514490
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An investigation into multivariate variance ratio statistics and their application to stock market predictability
Hong, Seok Young; Linton, Oliver; Zhang, Hui Jun - 2015
We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the weak form Efficient Market Hypothesis). We do...
Persistent link: https://www.econbiz.de/10010496122
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The Log-Linear Return Approximation, Bubbles, and Predictability
Engsted, Tom - 2013
rational bubbles which have explosive conditional expectation, and we investigate the magnitude of the approximation error in … explosive bubbles. Only in very large samples do we find evidence that bubbles generate large approximation errors. Finally, we …
Persistent link: https://www.econbiz.de/10013094428
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Assessing Point Forecast Bias Across Multiple Time Series : Measures and Visual Tools
Davydenko, Andrey; Goodwin, Paul - 2021
Measuring bias is important as it helps identify flaws in quantitative forecasting methods or judgmental forecasts. It can, therefore, potentially help improve forecasts. Despite this, bias tends to be under represented in the literature: many studies focus solely on measuring accuracy. Methods...
Persistent link: https://www.econbiz.de/10013314570
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A Comparison of the Forecast Performance of Markov-Switching and Threshold Autoregressive Models of Us Gnp
Clements, Michael P.; Krolzig, Hans-Martin - 1999
While there has been a great deal of interest in the modelling of non-linearities in economic time series, there is no clear consensus regarding the forecasting abilities of non-linear time-series models. We evaluate the performance of two leading non-linear models in forecasting post-war US...
Persistent link: https://www.econbiz.de/10014197190
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Forecasting Half-Hourly Electricity Prices using a Mixed-Frequency Structural VAR Framework
Kapoor, Gaurav; Wichitaksorn, Nuttanan; Li, Mengheng; … - 2023
Electricity price forecasting has been a topic of significant interest since the deregulation of electricity markets worldwide. The New Zealand electricity market is run primarily on renewable fuels, and so weather metrics have a significant impact on electricity price and volatility. In this...
Persistent link: https://www.econbiz.de/10014354157
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Fin-GAN : Forecasting and Classifying Financial Time Series via Generative Adversarial Networks
Vuletić, Milena; Prenzel, Felix; Cucuringu, Mihai - 2023
We investigate the use of Generative Adversarial Networks (GANs) for probabilistic forecasting of financial time series. To this end, we introduce a novel economics-driven loss function for the generator. This newly designed loss function renders GANs more suitable for a classification task, and...
Persistent link: https://www.econbiz.de/10014258279