At each point information from neighbouring data is used. As the time series considered are finite, the areas at the start and end of the data (especially at higher period bands) will not have all the data required. One solution to make computation possible, chosen here, is to pad the time series with zeros where required. However, the zero padding will impact the reliability of the results. It is standard to use a cone of influence to represent this difference in reliability of results. Pale colours represent those areas outside the cone of influence with less reliable results (as seen on Fig 3). Higher period bands require more data for computation resulting in the cone shape.
Cryptocurrencies have seen an explosion in popularity since they rose to prominence in 2009 and there are now over two thousand in existence. Some of the ‘major’ cryptocurrencies include Bitcoin, Ethereum and Litecoin. These are among the most traded cryptocurrencies worldwide, with the largest market caps.

We also consider two additional factors that account for the finding that in some periods prices drift away from fundamentals. The first factor is the return of Bitcoin. We argue that Bitcoin, being the largest and most traded cryptocurrency, is the most perceptible to sentiment and speculative trading by investors. Thus, as a factor, it can capture periods when trading forces unrelated to fundamentals are the strongest. The second factor is a cryptocurrency price momentum factor that we construct following the seminal work of Jegadeesh and Titman (1993). Momentum effects have been linked to investor psychology (e.g. Barberis et al. 1998).
Cryptocurrencies do not exist as a stack of notes or coins. Instead, they live only on the internet. Consider them virtual tokens, the value of which is decided by market forces created by those seeking to purchase or sell them.