by Jamie Holmes
In a recent paper by Polish scientist Mariusz Tarnopolski, the physics model based on fractal Brownian motion is utilized to predict the price of bitcoin. The results show that BTC-USD will reach $6,358.32 during the beginning of 2018.
Price predictions for bitcoin are ever more frequent as the ecosystem grows and new players join the scene. Many experts have predicted a price of $6,000 based on fundamental factors by the end of 2017, including Gatecoin’s Thomas Glucksmann and early Bitcoin proponent Max Keiser. Unsurprisingly, looking through r/bitcoin, there is even stronger bullish sentiment with some calling for $10,000 or more. Bitcoin critics will undoubtedly predict a price closer to zero.
As noted in our trading guide inspired by Bill Williams, 90 percent of everything you hear is a lie (even if not intended to mislead); financial commentators have different life experiences and perspectives on the world, you could even say that everyone lives somewhat in their own reality. Every individual needs to learn to judge the markets for themselves if they want to be successful, simultaneously being aware of their own personal biases, emotions and unconscious mind.
But let’s drop some science.
Physicists are the envy of economists. They can make accurate, pinpoint predictions about the state of nature. Formulas named after scientists such as Planck, Newton, and Hooke can help you to accurately determine what will happen in real life. Economics, on the other hand, is clumsy when it comes to giving a precise or quantitative answer and there are no ‘hard’ rules, such as the Planck constant in Physics.
Increasingly, economics is turning to physics to attain a similar status as a ‘hard science’ and more and more scientific breakthroughs are seeping into the field. With the bitcoin price, we can usually look at fundamental analysis, but that usually gives us a direction not a precise price. Furthermore, we could use fractals analysis, which draws on psychology and mathematics. Taking it one step further, a recent paper uses the concept of a fractal Brownian motion to predict BTC-USD.
Fractal Brownian motion is also known as the ‘random walk process.’ Imagine a man who has consumed a lot of alcohol and he is walking his dog. The dog is the current price of bitcoin. The drunk man is the future price of bitcoin. In other words, the increments in such a motion are dependent, so that if there were increasing pattern in previous ‘steps,’ then it is likely that the current ‘step’ will be increasing as well.
Given bitcoin’s persistent upward climb and, like many other financial time series data, the price in the next month or so will be mostly determined by the price in the current month, this is exploited to predict the future price in Tarnopolski’s paper. A Monte Carlo simulation is used with a sample of 10,000 geometric fractal Brownian motions as the random process governing BTC-USD.
A large time span is used in the investigation, dating back to December 2011 up until June 2017. By generating a large number of fractal Brownian Motion realizations, parameters can be attained and plugged into a formula which is then solved to attain the probability of the mean, median, mode and other charateristics of the price level at the end of a 180-day period.
The paper first looks at the data set until the end of 2016, with the results showing that the price was predicted to have just a 5.3 percent chance of going below $955.73, the price of bitcoin on 31 December, 2016. The result also showed that exceeding the mode of $1714.29 has a 72.1 percent chance of occurring. For a threshold of $5,000 or more, the prediction was 9.3 percent. Precise predictions of the price were given by the median values obtained and for this subset of data, this was found to be $2,357.07, around 10 percent lower than the actual price 180 days into 2017. Given the accuracy of these results, this motivated the author to conduct a prediction for the future.
The tredictions made for 180 days ahead of June 7, 2017 use the same method. The price at the start of the period was $2575.90 and the model employed by Tarnopolski suggested that there is a 11.4 percent chance of falling below this level.
Furthermore, the results show that there is a 27.5 percent chance that BTC-USD will reach $10,000 or higher in early 2018, giving some support to those bullish on the cryptocurrency. The mean in these simulations came out at $8,410.34 with a corresponding probability of 35.5 percent. Finally, the median price prediction is $6,358.32, suggesting that the bitcoin price will reach this level after we welcome the new year.
While the model is quite accurate for the limited data we have at hand, it will be a monumentous task to realistically capture the markets as the natural sciences capture the physical world. The author points to extreme events in the finance such as the Black Monday Crash in 1987 as an illustrative example. Tarnopolski suggests several improvements to his modelling, including adding bearish and bullish parameters to account for huge swings, which is deserving of further study.