Exploring the determinants of Bitcoins price: an application of Bayesian Structural Time Series

Reading time: 4 minute
...

📝 Original Info

  • Title: Exploring the determinants of Bitcoins price: an application of Bayesian Structural Time Series
  • ArXiv ID: 1706.01437
  • Date: 2017-06-06
  • Authors: Researchers from original ArXiv paper

📝 Abstract

Currently, there is no consensus on the real properties of Bitcoin. The discussion comprises its use as a speculative or safe haven assets, while other authors argue that the augmented attractiveness could end accomplishing money's functions that economic theory demands. This paper explores the association between Bitcoin's market price and a set of internal and external factors using Bayesian Structural Time Series Approach. I aim to contribute to the discussion by differentiating among several attractiveness sources and employing a method that provides a more flexible analytic framework that decompose each of the components of the time series, apply variable selection, include information on previous studies, and dynamically examine the behavior of the explanatory variables, all in a transparent and tractable setting. The results show that the Bitcoin price is negatively associated with a neutral investor's sentiment, gold's price and Yuan to USD exchange rate, while positively related to stock market index, USD to Euro exchange rate and variated signs among the different countries' search trends. Hence, I find that Bitcoin has mixed properties since still seems to act as a speculative, safe haven and a potential a capital flights instrument.

💡 Deep Analysis

Deep Dive into Exploring the determinants of Bitcoins price: an application of Bayesian Structural Time Series.

Currently, there is no consensus on the real properties of Bitcoin. The discussion comprises its use as a speculative or safe haven assets, while other authors argue that the augmented attractiveness could end accomplishing money’s functions that economic theory demands. This paper explores the association between Bitcoin’s market price and a set of internal and external factors using Bayesian Structural Time Series Approach. I aim to contribute to the discussion by differentiating among several attractiveness sources and employing a method that provides a more flexible analytic framework that decompose each of the components of the time series, apply variable selection, include information on previous studies, and dynamically examine the behavior of the explanatory variables, all in a transparent and tractable setting. The results show that the Bitcoin price is negatively associated with a neutral investor’s sentiment, gold’s price and Yuan to USD exchange rate, while positively relat

📄 Full Content

0

Exploring the determinants of Bitcoin’s price: an application of Bayesian Structural Time Series
Student: Obryan Poyser Supervisor: Jordi Perdiguero June 2017

1

Abstract Currently, there is no consensus on the real properties of Bitcoin. The discussion comprises its use as a speculative or safe haven assets, while other authors argue that the augmented attractiveness could end accomplishing money’s functions that economic theory demands. This paper explores the association between Bitcoin’s market price and a set of internal and external factors using Bayesian Structural Time Series Approach. I aim to contribute to the discussion by differentiating among several attractiveness sources and employing a method that provides a more flexible analytic framework that decompose each of the components of the time series, apply variable selection, include information on previous studies, and dynamically examine the behavior of the explanatory variables, all in a transparent and tractable setting. The results show that the Bitcoin price is negatively associated with a neutral investor’s sentiment, gold’s price and Yuan to USD exchange rate, while positively related to stock market index, USD to Euro exchange rate and variated signs among the different countries’ search trends. Hence, I find that Bitcoin has mixed properties since still seems to act as a speculative, safe haven and a potential a capital flights instrument. Short Currently, there is no consensus on the real properties of Bitcoin. The discussion comprises its use as a speculative or safe haven assets, while other authors argue that the augmented attractiveness could end accomplishing money’s functions that economic theory demands. This paper explores the association between Bitcoin’s market price and a set of internal and external factors using Bayesian Structural Time Series Approach. The results show that Bitcoin has mixed properties since seems to currently act as a speculative, safe haven asset and a potential a capital flights instrument.

2

Abstract …………………………………………………………………………………………………………………………… 1 I. Introduction…………………………………………………………………………………………………………….. 4 II. Background ………………………………………………………………………………………………………….. 6 III. Related works ………………………………………………………………………………………………………. 7 1. Price drivers …………………………………………………………………………………………………………. 10 Internal factors …………………………………………………………………………………………………………. 10 External factors ………………………………………………………………………………………………………… 11 IV. Data …………………………………………………………………………………………………………………….. 12 V. Methodology ………………………………………………………………………………………………………….. 16 1. Structural time series models ………………………………………………………………………………… 16 Posterior inference and forecasting …………………………………………………………………………….. 17 2. Bayesian variable selection ……………………………………………………………………………………. 19 Spike and slab priors’ specification …………………………………………………………………………….. 21 3. Model specification ………………………………………………………………………………………………… 21 4. Standardized variables ………………………………………………………………………………………….. 22 5. Assessing seasonality ……………………………………………………………………………………………. 23 VI. Forecasting results ……………………………………………………………………………………………. 24 VII. Posterior estimates results ……………………………………………………………………………….. 27 1. Hyperparameters and priors calibration …………………………………………………………………. 27 2. Marginal posterior regression estimates …………………………………………………………………. 29 Results on internal determinants ……………………………………………………………………………

…(Full text truncated)…

Reference

This content is AI-processed based on ArXiv data.

Start searching

Enter keywords to search articles

↑↓
ESC
⌘K Shortcut