Predicting intraday cryptocurrency returns - A sparse signals approach
Year of publication: |
2021
|
---|---|
Authors: | Lalwani, Vaibhav ; Meshram, Vedprakash |
Published in: |
The journal of prediction markets. - Buckingham : Univ. of Buckingham Press, ISSN 1750-6751, ZDB-ID 2388613-4. - Vol. 15.2021, 1, p. 3-9
|
Subject: | sparse signals | cryptocurrencies | LASSO | machine learning | intraday returns | financial markets | Virtuelle Währung | Virtual currency | Finanzmarkt | Financial market | Prognoseverfahren | Forecasting model | Kapitaleinkommen | Capital income | Signalling | Börsenkurs | Share price | Volatilität | Volatility |
-
Returns, volatility and the cryptocurrency bubble of 2017-18
Cross, Jamie, (2021)
-
Discovering the drivers of stock market volatility in a data-rich world
Chun, Dohyun, (2023)
-
Gupta, Rangan, (2023)
- More ...
-
The cross-section of Indian stock returns : evidence using machine learning
Lalwani, Vaibhav, (2022)
-
Accounting constructs and economic consequences of IFRS adoption in India
Meshram, Vedprakash, (2021)
-
Multi-factor asset pricing models in emerging and developed markets
Lalwani, Vaibhav, (2019)
- More ...