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Testing for bubbles in cryptocurrencies with time-varying volatility
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Cited by:
- Jean-Louis Bago & Koffi Akakpo & Imad Rherrad & Ernest Ouédraogo, 2021.
"Volatility Spillover and International Contagion of Housing Bubbles,"
JRFM, MDPI, vol. 14(7), pages 1-14, June.
- Bago, Jean-Louis & Akakpo, Koffi & Rherrad, Imad & Ouédraogo, Ernest, 2020. "Volatility Spillover and International Contagion of Housing Bubbles," MPRA Paper 100098, University Library of Munich, Germany.
- Cathy Yi-Hsuan Chen & Christian M. Hafner, 2019.
"Sentiment-Induced Bubbles in the Cryptocurrency Market,"
JRFM, MDPI, vol. 12(2), pages 1-12, April.
- Chen, Cathy Yi-Hsuan & Hafner, Christian, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," LIDAM Reprints ISBA 2019053, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Yang Hu, 2023. "A review of Phillips‐type right‐tailed unit root bubble detection tests," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 141-158, February.
- Packham, Natalie, 2018. "Optimal contracts under competition when uncertainty from adverse selection and moral hazard are present," IRTG 1792 Discussion Papers 2018-033, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Qingliang Fan & Wei Zhong, 2018.
"Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(3), pages 388-399, July.
- Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- De Pace, Pierangelo & Rao, Jayant, 2023.
"Comovement and instability in cryptocurrency markets,"
International Review of Economics & Finance, Elsevier, vol. 83(C), pages 173-200.
- De Pace, Pierangelo & Rao, Jayant, 2020. "Comovement and Instability in Cryptocurrency Markets," Economics Department, Working Paper Series 1012, Economics Department, Pomona College, revised 14 Jan 2020.
- Stefan Richter & Weining Wang & Wei Biao Wu, 2018.
"A supreme test for periodic explosive GARCH,"
Papers
1812.03475, arXiv.org.
- Richter, Stefan & Wang, Weining & Wu, Wei Biao, 2020. "A supreme test for periodic explosive GARCH," IRTG 1792 Discussion Papers 2020-018, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Victor Chernozhukov & Wolfgang K. Hardle & Chen Huang & Weining Wang, 2018.
"LASSO-Driven Inference in Time and Space,"
Papers
1806.05081, arXiv.org, revised May 2020.
- Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019. "LASSO-Driven Inference in Time and Space," CeMMAP working papers CWP20/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2018. "LASSO-driven inference in time and space," CeMMAP working papers CWP36/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Chernozhukov, V. & Härdle, W.K. & Huang, C. & Wang, W., 2018. "LASSO-Driven Inference in Time and Space," Working Papers 18/04, Department of Economics, City University London.
- Pavel Baboshkin & Alexey Mikhaylov & Zaffar Ahmed Shaikh, 2022. "Sustainable Cryptocurrency Growth Impossible? Impact of Network Power Demand on Bitcoin Price," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 3, pages 116-130, June.
- Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
- Stefan Richter & Weining Wang & Wei Biao Wu, 2023. "Testing for parameter change epochs in GARCH time series," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 467-491.
- Christian M. Hafner & Sabrine Majeri, 2022.
"Analysis of cryptocurrency connectedness based on network to transaction volume ratios,"
Digital Finance, Springer, vol. 4(2), pages 187-216, September.
- Hafner, Christian M. & Majeri , Sabrine, 2022. "Analysis of cryptocurrency connectedness based on network to transaction volume ratios," LIDAM Reprints ISBA 2022033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Chuffart, Thomas, 2022. "Interest in cryptocurrencies predicts conditional correlation dynamics," Finance Research Letters, Elsevier, vol. 46(PA).
- Maarten R.C. van Oordt, 2024. "On Bubbles in Cryptocurrency Prices," Tinbergen Institute Discussion Papers 24-050/IV, Tinbergen Institute.
- Chen, Cathy Yi-Hsuan & Després, Roméo & Guo, Li & Renault, Thomas, 2019. "What makes cryptocurrencies special? Investor sentiment and return predictability during the bubble," IRTG 1792 Discussion Papers 2019-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Wang, Honglin & Yu, Fan & Zhou, Yinggang, 2018. "Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach," IRTG 1792 Discussion Papers 2018-051, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Alessandra Cretarola & Gianna Figà-Talamanca & Cyril Grunspan, 2021. "Blockchain and cryptocurrencies: economic and financial research," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 781-787, December.
- Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Zhong, Wei & Liu, Xi & Ma, Shuangge, 2018. "Variable selection and direction estimation for single-index models via DC-TGDR method," IRTG 1792 Discussion Papers 2018-050, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Xinwen Ni & Wolfgang Karl Hardle & Taojun Xie, 2020. "A Machine Learning Based Regulatory Risk Index for Cryptocurrencies," Papers 2009.12121, arXiv.org, revised Aug 2021.
- Hans Rawhouser & Silvio Vismara & Nir Kshetri, 2024. "Blockchain and vulnerable entrepreneurial ecosystems," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 36(1-2), pages 10-35, January.
- Kalkbrener, Michael & Packham, Natalie, 2018. "Correlation Under Stress In Normal Variance Mixture Models," IRTG 1792 Discussion Papers 2018-035, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Caravello, Tomas E. & Psaradakis, Zacharias & Sola, Martin, 2023.
"Rational bubbles: Too many to be true?,"
Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
- Tomás Caravello & Zacharias Psaradakis & Martín Sola, 2021. "Rational Bubbles: Too Many to be True?," Department of Economics Working Papers 2021_06, Universidad Torcuato Di Tella.
- Martin Sola, 2023. "Rational Bubbles: Too Many to be True?," Working Papers 240, Red Nacional de Investigadores en Economía (RedNIE).
- Chiara Oldani & Giovanni S. F. Bruno & Marcello Signorelli, 2024. "Economic policy uncertainty and cryptocurrencies," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 14(3), pages 709-728, September.
- Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021.
"VCRIX — A volatility index for crypto-currencies,"
International Review of Financial Analysis, Elsevier, vol. 78(C).
- Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
- Hayet Ben Haj Hamida & Francesco Scalera, 2019. "Threshold Mean Reversion and Regime Changes of Cryptocurrencies using SETAR-MSGARCH Models," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 9(3), pages 221-229, July.
- Bellón, Carlos & Figuerola-Ferretti, Isabel, 2022. "Bubbles in Ethereum," Finance Research Letters, Elsevier, vol. 46(PB).
- Gradojevic, Nikola & Tsiakas, Ilias, 2021. "Volatility cascades in cryptocurrency trading," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 252-265.
- Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
- Panayiotis Theodossiou & Polina Ellina & Christos S. Savva, 2022. "Stochastic properties and pricing of bitcoin using a GJR-GARCH model with conditional skewness and kurtosis components," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 695-716, August.
- Junjie Hu & Wolfgang Karl Hardle & Weiyu Kuo, 2019.
"Risk of Bitcoin Market: Volatility, Jumps, and Forecasts,"
Papers
1912.05228, arXiv.org, revised Dec 2021.
- Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Darko Vukovic & Moinak Maiti & Zoran Grubisic & Elena M. Grigorieva & Michael Frömmel, 2021. "COVID-19 Pandemic: Is the Crypto Market a Safe Haven? The Impact of the First Wave," Sustainability, MDPI, vol. 13(15), pages 1-17, July.
- Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
- Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
- Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
- Pierre J. Venter & Eben Maré, 2020. "GARCH Generated Volatility Indices of Bitcoin and CRIX," JRFM, MDPI, vol. 13(6), pages 1-15, June.
- Wolfgang Karl Hardle & Campbell R. Harvey & Raphael C. G. Reule, 2020. "Editorial: Understanding Cryptocurrencies," Papers 2007.14702, arXiv.org.
- Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
- Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Chen, Bin-xia & Sun, Yan-lin, 2024. "Risk characteristics and connectedness in cryptocurrency markets: New evidence from a non-linear framework," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
- Bouteska, Ahmed & Mefteh-Wali, Salma & Dang, Trung, 2022. "Predictive power of investor sentiment for Bitcoin returns: Evidence from COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
- Eiji Kurozumi & Anton Skrobotov & Alexey Tsarev, 2020. "Time-Transformed Test for the Explosive Bubbles under Non-stationary Volatility," Papers 2012.13937, arXiv.org, revised Nov 2021.
- Andrada-Félix, Julián & Fernandez-Perez, Adrian & Sosvilla-Rivero, Simón, 2020.
"Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
- Julián Andrada-Félix & Adrian Fernandez-Perez & Simón Sosvilla-Rivero, 2019. "“Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities”," IREA Working Papers 201912, University of Barcelona, Research Institute of Applied Economics, revised Jul 2019.
- Aslanidis, Nektarios & Fernández Bariviera, Aurelio & Savva, Christos S., 2020. "Weekly dynamic conditional correlations among cryptocurrencies and traditional assets," Working Papers 2072/417680, Universitat Rovira i Virgili, Department of Economics.
- Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
- George Tzagkarakis & Frantz Maurer, 2023. "Horizon-Adaptive Extreme Risk Quantification for Cryptocurrency Assets," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1251-1286, October.
- Adam Hayes, 2018. "Bitcoin price and its marginal cost of production: support for a fundamental value," Papers 1805.07610, arXiv.org.
- Guo, Shaojun & Li, Dong & Li, Muyi, 2018. "Strict Stationarity Testing and GLAD Estimation of Double Autoregressive Models," IRTG 1792 Discussion Papers 2018-049, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos, 2023. "Forecasting realized volatility of Bitcoin: The informative role of price duration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1909-1929, November.
- Assaf, Ata & Demir, Ender & Ersan, Oguz, 2024. "Detecting and date-stamping bubbles in fan tokens," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 98-113.
- Xiaojia Bao & Qingliang Fan, 2020.
"The impact of temperature on gaming productivity: evidence from online games,"
Empirical Economics, Springer, vol. 58(2), pages 835-867, February.
- Bao, Xiaojia & Fan, Qingliang, 2018. "The impact of temperature on gaming productivity: evidence from online games," IRTG 1792 Discussion Papers 2018-053, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
- Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Gil-Alana, Luis Alberiko & Abakah, Emmanuel Joel Aikins & Rojo, María Fátima Romero, 2020. "Cryptocurrencies and stock market indices. Are they related?," Research in International Business and Finance, Elsevier, vol. 51(C).
- Rebekka Buse & Konstantin Gorgen & Melanie Schienle, 2022. "Predicting Value at Risk for Cryptocurrencies With Generalized Random Forests," Papers 2203.08224, arXiv.org, revised Oct 2024.
- Andrew Phiri, 2022. "Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 373-386, September.
- Jalan, Akanksha & Matkovskyy, Roman & Urquhart, Andrew & Yarovaya, Larisa, 2023.
"The role of interpersonal trust in cryptocurrency adoption,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
- Akanksha Jalan & Roman Matkovskyy & Andrew Urquhart & Larisa Yarovaya, 2023. "The role of interpersonal trust in cryptocurrency adoption," Post-Print hal-03946536, HAL.
- Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
- Nicole Branger & Mark Trede & Bernd Wilfling, 2024. "Extracting stock-market bubbles from dividend futures," CQE Working Papers 10724, Center for Quantitative Economics (CQE), University of Muenster.
- Ni, Xinwen & Härdle, Wolfgang Karl & Xie, Taojun, 2020. "A Machine Learning Based Regulatory Risk Index for Cryptocurrencies," IRTG 1792 Discussion Papers 2020-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Wang, Nianling & Lou, Zhusheng, 2023. "Sequential Bayesian analysis for semiparametric stochastic volatility model with applications," Economic Modelling, Elsevier, vol. 123(C).
- Wu, Chuanzhen, 2021. "Window effect with Markov-switching GARCH model in cryptocurrency market," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
- Christian M. Hafner, 2020. "Alternative Assets and Cryptocurrencies," JRFM, MDPI, vol. 13(1), pages 1-3, January.
- Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
- Kuczmaszewska, Anna & Yan, Ji Gao, 2018. "On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables," IRTG 1792 Discussion Papers 2018-041, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021. "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 179-201.
- Riccardo De Blasis, 2023. "Weighted-indexed semi-Markov model: calibration and application to financial modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
- Koziuk, Andzhey & Spokoiny, Vladimir, 2018. "Toolbox: Gaussian comparison on Eucledian balls," IRTG 1792 Discussion Papers 2018-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Steven Y. K. Wong & Jennifer S. K. Chan & Lamiae Azizi, 2024. "Quantifying neural network uncertainty under volatility clustering," Papers 2402.14476, arXiv.org, revised Sep 2024.
- Anyfantaki, Sofia & Arvanitis, Stelios & Topaloglou, Nikolas, 2021. "Diversification benefits in the cryptocurrency market under mild explosivity," European Journal of Operational Research, Elsevier, vol. 295(1), pages 378-393.
- Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Troster, Victor & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Macedo, Demian Nicolás, 2019. "Bitcoin returns and risk: A general GARCH and GAS analysis," Finance Research Letters, Elsevier, vol. 30(C), pages 187-193.
- Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
- Ben Osman, Myriam & Galariotis, Emilios & Guesmi, Khaled & Hamdi, Haykel & Naoui, Kamel, 2024. "Are markets sentiment driving the price bubbles in the virtual?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 272-285.
- Lee, Seungho & Meslmani, Nabil El & Switzer, Lorne N., 2020. "Pricing Efficiency and Arbitrage in the Bitcoin Spot and Futures Markets," Research in International Business and Finance, Elsevier, vol. 53(C).
- Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Jimmy E. Hilliard & Julie T. D. Ngo, 2022. "Bitcoin: jumps, convenience yields, and option prices," Quantitative Finance, Taylor & Francis Journals, vol. 22(11), pages 2079-2091, November.
- Sabah, Nasim, 2020. "Cryptocurrency accepting venues, investor attention, and volatility," Finance Research Letters, Elsevier, vol. 36(C).
- Bernd Süssmuth, 2022. "The mutual predictability of Bitcoin and web search dynamics," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 435-454, April.
- Chen, Cathy Yi-hsuan & Okhrin, Yarema & Wang, Tengyao, 2022. "Monitoring network changes in social media," LSE Research Online Documents on Economics 113742, London School of Economics and Political Science, LSE Library.
- Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".