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Dissection of Bitcoin's multiscale bubble history : from January 2012 to February 2018
Gerlach, Jan-Christian; Demos, Guilherme; Sornette, Didier - 2018
We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of uninterrupted market growth (drawups) and regimes of uninterrupted market...
Persistent link: https://www.econbiz.de/10011899669
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Local adaptive multiplicative error models for high-frequency forecasts
Härdle, Wolfgang; Hautsch, Nikolaus; Mihoci, Andrija - 2012
We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....
Persistent link: https://www.econbiz.de/10009526607
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Comfort: a common market factor non-Gaussian returns model
Paolella, Marc S.; Polak, Pawel - 2013
A new multivariate time series model with various attractive properties is motivated and studied. By extending the CCC model in several ways, it allows for all the primary stylized facts of financial asset returns, including volatility clustering, non-normality (excess kurtosis and asymmetry),...
Persistent link: https://www.econbiz.de/10010256409
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Reexamining Financial and Economic Predictability with New Estimators of Realized Variance and Variance Risk Premium
Casas, Isabel - 2018
This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from...
Persistent link: https://www.econbiz.de/10012925879
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The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility
Hizmeri, Rodrigo - 2019
, 60, and 300 seconds), forecast horizons (1, 5, 22, and 66 days) and the use of standard and robust-to-noise volatility … measures at the 300-second frequency generate the smallest real-time mean squared forecast errors. Finally, the forecasts from …
Persistent link: https://www.econbiz.de/10012889687
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Retail Investors’ Trading Activity and the Predictability of Stock Return Correlations
Ballinari, Daniele - 2021
Considerable theoretical and empirical evidence links price comovements with the behavior of retail investors. Nevertheless, when predicting stock return correlations, research has focused on the leverage effect. We propose a new model of realized covariances that allows exogenous predictors to...
Persistent link: https://www.econbiz.de/10013214872
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Local Adaptive Multiplicative Error Models for High- Frequency Forecasts
Härdle, Wolfgang K. - 2013
We propose a local adaptive multiplicative error model (MEM) accommodating time-varying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....
Persistent link: https://www.econbiz.de/10013077176
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Stock price forecast accuracy and recommendation profitability of financial magazines
Tiberius, Victor; Lisiecki, Laura - In: International Journal of Financial Studies : open … 7 (2019) 4/58, pp. 1-8
In this study, we analyze the forecast accuracy and profitability of buy recommendations published in five major German … financial magazines for private households based on fundamental analysis. The results show a high average forecast accuracy but … with a very high standard deviation, which indicates poor forecast accuracy with regard to individual stocks. The …
Persistent link: https://www.econbiz.de/10012150526
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Can Security Analyst Forecasts Predict Gold Returns?
Mihaylov, George - 2017
via its impact on stock return synchronicity.We then examine if the difference between forecast and observed earnings for …
Persistent link: https://www.econbiz.de/10012967299
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Forecasting leveraged loan market volatility using GARCH models
Keßler, Andreas - 2021
This paper compares different GARCH models in terms of their out-of-sample predictive ability of leveraged loan market volatility. The study investigates whether the asymmetric effects of good and bad news on volatility is present and how distributional assumptions affect the selection of GARCH...
Persistent link: https://www.econbiz.de/10013220294