Inter-exchanges spread is an interesting volatility indicator
After observing how much price could be different between exchanges especially during times of high volatility and emotion, I wondered whether I could reliably aggreggate and display concisely this information to improve my trading without having to frenetically check a dozen tickers of the same symbol across a dozen different exchanges, as most traders do, myself included. This led me to create two indicators based on this idea.
Here is the first indicator, which summarizes the inter-exchanges spread by calculating the deviation (standard deviation or median absolute deviation, the latter being more robust against outliers - exchanges that saw scamwicks due to low liquidity or an unusually large whale doing an exceptional transaction):
And here is the second one, which instead displays clouds of min-max values overlaid on the price data, so that we preserve the price data, which can be directly used to define stop losses or entries:
The subject of this idea is what I highlighted by a red arrow in the chart above, from the second indicator applied to BTCUSD in the first half of March 2023, post SVB bank collapse. BTCUSD saw an unexpected face-ripping rally. No indicator I know of could predict it, and no price action was indicative, except from experience knowing that we were in the lows of the range and that it was a potential time for a rally up, but I could not predict the proportions. I knew that because of SVB being a black swan event, the pump could be big, but I had no indication it could be bigger than the post FTX rally.
However, the second indicator linked above provided a convincing evidence of a much bigger volatility in the highs (green cloud) than in the lows (red cloud), which suggested that, in addition to an overall high volatility and hence emotions and hence likelihood of a big move potentially happening soon, the bigger green cloud suggested a bigger interest in longs than in sales (red cloud). Hence, it seems the second indicator's green and red clouds can also be seen as representative of buying-selling pressure in some ways that even buying and selling pressure indicators can't show (see also my other indicator which is a merge of several buying-selling pressure indicators):
This is a very interesting observation that I don't think I saw before. I will keep investigating inter-exchanges metrics, as this may provide a new way to detect early market inefficiencies.
Here is the first indicator, which summarizes the inter-exchanges spread by calculating the deviation (standard deviation or median absolute deviation, the latter being more robust against outliers - exchanges that saw scamwicks due to low liquidity or an unusually large whale doing an exceptional transaction):
And here is the second one, which instead displays clouds of min-max values overlaid on the price data, so that we preserve the price data, which can be directly used to define stop losses or entries:
The subject of this idea is what I highlighted by a red arrow in the chart above, from the second indicator applied to BTCUSD in the first half of March 2023, post SVB bank collapse. BTCUSD saw an unexpected face-ripping rally. No indicator I know of could predict it, and no price action was indicative, except from experience knowing that we were in the lows of the range and that it was a potential time for a rally up, but I could not predict the proportions. I knew that because of SVB being a black swan event, the pump could be big, but I had no indication it could be bigger than the post FTX rally.
However, the second indicator linked above provided a convincing evidence of a much bigger volatility in the highs (green cloud) than in the lows (red cloud), which suggested that, in addition to an overall high volatility and hence emotions and hence likelihood of a big move potentially happening soon, the bigger green cloud suggested a bigger interest in longs than in sales (red cloud). Hence, it seems the second indicator's green and red clouds can also be seen as representative of buying-selling pressure in some ways that even buying and selling pressure indicators can't show (see also my other indicator which is a merge of several buying-selling pressure indicators):
This is a very interesting observation that I don't think I saw before. I will keep investigating inter-exchanges metrics, as this may provide a new way to detect early market inefficiencies.