On Comparing the Influences of Exogenous Information on Bitcoin Prices and Stock Index Values

Luis Montesdeoca () and Mahesan Niranjan ()
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Luis Montesdeoca: University of Southampton
Mahesan Niranjan: University of Southampton

A chapter in Mathematical Research for Blockchain Economy, 2020, pp 93-100 from Springer

Abstract: Abstract We consider time series analysis on cryptocurrencies such as Bitcoin. The traded values of any financial instrument could be seen as being influenced by market forces as well as underlying fundamentals relating to the performance of the asset. Bitcoin is somewhat different in this respect because there isn’t an underlying asset upon which its value may depend on. Here, by constructing a simple linear time series model, and by attempting to explain the variation in the residual signal by means of macroeconomic and currency exchange variables, we illustrate that the influencing variables are vastly different for cryptocurrencies from a stock indices (S&P 500) in both timescales analysed (daily and monthly values). We use a sequential estimation scheme (Kalman filter) to estimate the autoregressive model and a sparsity inducing linear regression with lags (LagLasso) to select relevant subsets of influencing variables to compare.

Keywords: Bitcoin; Kalman filter; LagLasso (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-37110-4_7

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DOI: 10.1007/978-3-030-37110-4_7

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