Screening For (Crypto) Diamonds in the Rough

With major coins now down an average of 52% off all time highs, we designed a simple screen to help identify coins that may have now fallen to attractive price points.  The results highlight privacy coins (ZCash, Dash & Monero) and NEO GAS as 4 of the most interesting at current levels. Sample: - We... Continue Reading →

“Bitcoins vs Sh*tcoins”: An Apples-to-Apples comparison

Given the sudden influx of new money that has been chasing "cheap Altcoins", to a new investor Bitcoin's ~$15,000 price tag may appear unaffordable compared to an Altcoin priced at ~$1. So the aim is to remove the "unit bias" of each Altcoin by repricing them using the same current Total Coin Supply as Bitcoin.  

A Monte Carlo simulation of Bitcoin price modeled as a fractional Brownian Motion.

Bitcoin (BTC/USD) price is modeled as a stochastic process following a fractional Brownian motion (fBm) demonstrated via a Hurst exponent (H) to try and measure the long term memory in the time series. Monte Carlo simulations were performed on this model to extend historical data and forecast Bitcoin price. Out of sample simulation results showed accuracy was to within ~10% of current prices.  The 180 day (6 month) most probable (median) forward looking Bitcoin price prediction is ~USD14,211 by May 2018 and implying upside risk of ~95%. In addition, within this time frame Quantile risk/loss estimates show that there is only a 5% tail-end risk of a drop back to the ~$2000 price level (or a ~70% price drop).

Up ↑