Discovering Bitcoin volatility patterns with INTRINSIC TIME
We know from our own personal experience in trading, that time does not pass uniformly.
We have periods when the markets are super active & prices are kicked around but also quiet periods when nothing is happening.
Price volatility can be triggered for many reasons: when a news story breaks and ‘all hell breaks loose’ or when brokers liquidate traders.
If we analyze traditional trading signals that use physical time (seconds, minutes, hours) the trading algo has to wait until a certain amount of calendar time has passed for data to be included in the algorithm, the algo response is too late, and results in losses for traders.
It’s clear that trading algorithms will fail if they are formulated in terms of physical calendar time.
Intrinsic time is one of the biggest discoveries in finance and can improve trading signals & algorithms.
Intrinsic time is “ticks” when there is market activity, hence can very fast capture real factors influencing the financial markets.
The famous Benoit Mandelbrot came up with the idea of modeling prices using a different time clock and proposed the use of transaction & volume-based clocks.
Central to the concept of Intrinsic Time are so-called “directional changes” and “overshoots”.
The “directional change” happens when the price does a trend reversal of a certain % and then the Intrinsic time ticks.
The directional change is then followed by the price “overshoot” until the next trend reversal (i.e. directional change) happens.
Intrinsic time enables us to discover the “scaling law” pattern, which tells us how the price will behave.
One of the patterns we can discover using Intrinsic time is the volatility seasonality of Bitcoin and FX prices!
The statistics we can use about Intrinsic Time to make market predictions is the number of directional changes.
By observing directional changes over a specific time period, we can discover daily, weekly & daily patterns in market volatility.
In the picture, we see that Bitcoin has a very specific volatility seasonality, which is different from FX volatility (EUR/USD)!
We can see Volatility seasonality reflects the opening and closing of markets, but also different market activity among geographical locations (US, Europe, Asia).
While for FX markets, European and US markets have the biggest impact on prices, for Bitcoin the most influential market is in Asia!
Richard Olsen, the founder of Lykke - a ZERO fee crypto exchange, has created a tool called ATTMO, where you can predict the crypto markets with the “scaling law” patterns from Intrinsic Time.
Head over to ATTMO's website (link in comments) and check out the patterns & test the trading signals!
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