Search

We apply the statistical sparse jump model, a recently developed, interpretable and robust regime-switching model, to infer key features that drive the return dynamics of the largest cryptocurrencies. The algorithm jointly performs feature selection, parameter estimation, and state classification. Our large set of candidate features are based on cryptocurrency, sentiment and financial market-based time series that have been identified in the emerging literature to affect cryptocurrency returns, while others are new. In our empirical work, we demonstrate that a three-state model best describes the dynamics of cryptocurrency returns. The states have natural market-based interpretations as they correspond to bull, neutral, and bear market regimes, respectively. Using the data-driven feature selection methodology, we are able to determine which features are important and which ones are not. In particular, out of the set of candidate features, we show that first moments of returns, features representing trends and reversal signals, market activity and public attention are key drivers of crypto market dynamics.

Tilltal (Tillgängligt kulturarv för forskning i tal, 'Accessible cultural heritage for speech research') is a multidisciplinary and methodological project undertaken by the Institute of Language and Folklore, KTH Royal Institute of Technology, and The Swedish National Archives in cooperation with the National Language Bank and SWE-CLARIN [1]. It aims to provide researchers better access to archival audio recordings using methods from language technology. The project comprises three case studies and one activity and usage study. In the case studies, actual research agendas from three different fields (ethnology, sociolinguistics and interaction analysis) serve as a basis for identifying procedures that may be simplified with the aid of digital tools. In the activity and usage study, we are applying an activity-theoretical approach with the aim of involving researchers and investigating how they use - and would like to be able to use - the archival resources at ISOF. Involving researchers in participatory design ensures that digital solutions are suggested and evaluated in relation to the requirements expressed by researchers engaged in specific research tasks [2]. In this paper we focus on one of the case studies, which investigates the process by which personal experience narratives are transformed into cultural heritage [3], and account for our results in exploring how different types of text material from the archives can be used to find relevant sections of the audio recordings. Finally, we discuss what lessons can be learned, and what conclusions can be drawn, from our experiences of interdisciplinary collaboration in the project., QC 20210322

QC 20200310