Research Papers on Bitcoin Pricing part 1
- The Price and Cost of Bitcoin(arXiv)
Abstract : Explaining changes in bitcoin’s price and predicting its future have been the foci of many research studies. In contrast, far less attention has been paid to the relationship between bitcoin’s mining costs and its price. One popular notion is the cost of bitcoin creation provides a support level below which this cryptocurrency’s price should never fall because if it did, mining would become unprofitable and threaten the maintenance of bitcoin’s public ledger. Other research has used mining costs to explain or forecast bitcoin’s price movements. Competing econometric analyses have debunked this idea, showing that changes in mining costs follow changes in bitcoin’s price rather than preceding them, but the reason for this behavior remains unexplained in these analyses. This research aims to employ economic theory to explain why econometric studies have failed to predict bitcoin prices and why mining costs follow movements in bitcoin prices rather than precede them. We do so by explaining the chain of causality connecting a bitcoin’s price to its mining costs
2. Bitcoin Price Predictive Modeling Using Expert Correction(arXiv)
Author : Bohdan M. Pavlyshenko
Abstract : The paper studies the linear model for Bitcoin price which includes regression features based on Bitcoin currency statistics, mining processes, Google search trends, Wikipedia pages visits. The pattern of deviation of regression model prediction from real prices is simpler comparing to price time series. It is assumed that this pattern can be predicted by an experienced expert. In such a way, using the combination of the regression model and expert correction, one can receive better results than with either regression model or expert opinion only. It is shown that Bayesian approach makes it possible to utilize the probabilistic approach using distributions with fat tails and take into account the outliers in Bitcoin price time series.
3.Bitcoin option pricing: A market attention approach (arXiv)
Abstract : A model is proposed that models Bitcoin prices by taking into account market attention. Assuming that market attention follows a mean-reverting Cox-Ingersoll-Ross process and allowing it to influence Bitcoin returns (after some delay) leads to a tractable affine model with semi-closed formulae for European put and call prices. A maximum likelihood estimation procedure is proposed for this model. The accuracy of its call and put prices outperforms a number of standard models when tested on real data.
4. Recent scaling properties of Bitcoin price returns(arXiv)
Author : Tetsuya Takaishi
Abstract : While relevant stylized facts are observed for Bitcoin markets, we find a distinct property for the scaling behavior of the cumulative return distribution. For various assets, the tail index μ of the cumulative return distribution exhibits μ≈3, which is referred to as “the inverse cubic law.” On the other hand, that of the Bitcoin return is claimed to be μ≈2, which is known as “the inverse square law.” We investigate the scaling properties using recent Bitcoin data and find that the tail index changes to μ≈3, which is consistent with the inverse cubic law. This suggests that some properties of the Bitcoin market could vary over time. We also investigate the autocorrelation of absolute returns and find that it is described by a power-law with two scaling exponents. By analyzing the absolute returns standardized by the realized volatility, we verify that the Bitcoin return time series is consistent with normal random variables with time-varying volatility.