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Forecasting the variability of stock index returns with the multifractal random walk model for realized volatilities
Sattarhoff, Cristina; Lux, Thomas - 2021
We adapt the multifractal random walk model by Bacry et al. (2001) to realized volatilities (denoted RV-MRW) and take stock of recent theoretical insights on this model in Duchon et al. (2012) to derive forecasts of financial volatility. Moreover, we propose a new extension of the binomial...
Persistent link: https://www.econbiz.de/10012672178
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Expected lifetime range ratio to find mean reversion : evidence from Indian stock market
Shaik, Muneer; Maheswaran, S. - In: Cogent economics & finance 6 (2018) 1, pp. 1-23
We use the expected lifetime range (ELR) ratio based on the extreme values of asset prices to detect the presence of mean reversion in stock returns. We find that the actual cross-sectional average of the ELR ratio is significantly less than its bootstrap means, thereby indicating a considerable...
Persistent link: https://www.econbiz.de/10011905649
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The modeling of earnings per share of Polish companies for the post-financial crisis period using random walk and ARIMA models
Kuryłek, Wojciech - In: Journal of banking and financial economics 19 (2023) 1, pp. 26-43
The proper forecasting of listed companies' earnings is crucial for their appropriate pricing. This paper compares forecast errors of different univariate time-series models applied for the earnings per share (EPS) data for Polish companies from the period between the last financial crisis of...
Persistent link: https://www.econbiz.de/10014285928
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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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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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Time-Disaggregated Dividend-Price Ratio and Dividend Growth Predictability in Large Equity Markets
Asimakopoulos, Panagiotis - 2016
Even in large equity markets, the dividend-price ratio is significantly related with the growth of future dividends. In … with within-year seasonality. We reduce the effect of price volatility on the dividend-price ratio by applying a simple … smoothing technique, and we identify the component of the smoothed dividend-price ratio that offers predictive power. An …
Persistent link: https://www.econbiz.de/10013006710
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That Is Not My Dog : Why Doesn't the Log Dividend-Price Ratio Seem to Predict Future Log Returns or Log Dividend Growths?
Dybvig, Philip H.; Zhang, Huacheng - 2021
Campbell and Shiller’s “accounting identity” implies that the log dividend-price ratio (LDPR) predicts either returns … or dividend growths, but neither is significantly predictable, a well-known puzzle. Existence of the long-term mean LDPR … therefore the long-term mean does not exist. However, the identity works well in our sample. The dividend growths (but not …
Persistent link: https://www.econbiz.de/10013223114
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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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Forecasting Stock Returns with Model Uncertainty and Parameter Instability
Zhang, Hongwei - 2019
We compare several representative sophisticated model averaging and variable selection techniques of forecasting stock returns. When estimated traditionally, our results confirm that the simple combination of individual predictors is superior. However, sophisticated models improve dramatically...
Persistent link: https://www.econbiz.de/10012901029