$BTCUSD SOPR, BFX Longs and Shorts, Greed, Liquidations.
This is one of the multi-chart evolving dashboards I use daily for crypto trading. This dashboard attempts to distill a broad scope of data and sentiment into glance value charts. The goal with such dashboards is to seek to stack probabilities to be on the right side of the percentages in every trade.
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The top panel chart shows the SOPR (Spent Output Profit Ratio, (grey line, using the symbol $BTC_SOPR) overlay vs $BTCUSDT (Binance, in blue). The SOPR is a very simple indicator. It is the spent outputs expressed as a ratio and shown as an oscillator on the chart. The Bitcoin SOPR is the realised dollar value divided by the dollar value at creation of the output. Or simply: price sold divided by price paid.
SOPR showing under value 1 means that the on chain data has recorded a net realised loss for "spent" Bitcoin. SOPR showing over value 1 means net profit. Renato Shirakashi appears to be the inventor of SOPR for BTC, and he writes about SOPR: "In this analysis two important psychological turning points that significantly change the supply of bitcoin are going to be described by introducing a new oscillating indicator that signals when these major supply changes occur, using blockchain data." I interpret this reference to the psychology of "weak hands" getting flushed out of the market by selling at a loss as shown when SOPR sits below 1 for extended periods of time (bear), and when all the weak hands have left the market, we find a bottom.
Because I am an impatient learner, I needed further examples to understand fully. If someone sells you 1 Bitcoin at $50,000USD, that transaction is recorded on the blockchain. If you then sell it for $25,000USD, that is now a spent output which is obviously a negative 0.5 ratio, and would contribute to a SOPR lower than the value 1. Interestingly the SOPR tends to be very close to the value 1 nearly always. Which means that the aggregated data of all spent outputs is nowhere near as extreme as the example I gave (although I'm sure there are plenty of retail traders who bought the high and sold the bottom at a 50% loss).
If we rewind to extended periods of low points in the SOPR ratio, extended negative ratio periods coincide with low points. In the past 5 years the lowest ratio was around 0.88, which was December 2018, when the price of Bitcoin was heading lower than $4k USD. That particularly brutal bear market lasted 18 months and you can see that the SOPR was below value 1 for nearly the entire time, indicating that there was a long tail of weak hands realising losses the entire time.
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Also present on the top chart is a brilliant little free indicator called Liq.Levels , wtf is all I can say, this a masterpiece of long/short liquidation data based on market maker behaviour in this case Binance's perpetual BTC/USDT leveraged futures (one of the most active retail leverage platforms). On this layout I have hidden all but the 25x liquidation points both short and long as it captures the widest spread and for the simplest visual as this is a glance-dashboard, on a single panel layout you can view the 50x and 100x which are tighter spreads. Liq.Levels also filters for a minimum of one million USD, so this is real value the market makers are getting out of bed for, essentially these levels are where the market maker really wants to push the price to. If you're new to leverage (don't do it! just buy at spot!), the reason they do this is to hunt the longs and the shorts and cause maximum liquidations (are you still trading with leverage?!).
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The second panel is the famous Bitfinex Longs (green) and Shorts (red) . You can see currently the longs, since around the $39000 level went parabolic. The shorts are just tiny in comparison. The data from Bitfinex seems less erratic than those from other exchanges, so if you find looking at longs and shorts ratios useful, I'd suggest also looking at other websites to see the other major exchange long and short activity, liquidations, and ratios.
This info is used to monitor large moves by leveraged traders. While Bitfinex is not the best measure here (ideally you would want all major exchanges aggregated longs vs shorts, but I have not found such indicators on TV, only Bitfinex), you can check the data by comparing it to another exchange, for example Binance you can see that parabolic move the Longs made from the 11th of July to around the 14th of July (while the BTC price fell off a cliff from $30k to $20k), where the ratio of Longs vs Shorts on Binance also skewed heavily to the Long side.
This is another way to stack a probability. As the Longs level off and get flushed out (usually by mass liquidation!), this is another variable to find support or resistance. For example you can see the levelling off around 12 May 2022, Bitcoin's price found a short term bottom at $29k. Similarly and most recently you can see as the Longs levelled off from a hectic run up in the mid June 2022 selloff, the price found a short term bottom around $20k. You could say that recently or commonly this is a contrarian indicator, assuming that smart money is seeking to liquidate the maximum possible leveraged positions, so we can assume that generally these leveraged retail traders will largely make incorrect bets most of the time, hence historically as soon as Shorts leave the market, the price spikes up, and vice versa. So, another thing to watch.
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Next we have a Crypto Fear & Greed Index , which as you can see nearly always oscillates in a tight rhythm with Bitcoin's price action. Above 75 (green dotted line) is extreme greed, below 25 (red dotted line) extreme fear. There are quite a few websites that attempt to measure crypto Fear & Greed, and even a variety of different indicators on TradingView, but this was the clearest visually I could find here. The inputs on this version according to the coder are stable coin flows (flight to safety), coin momentum (top 18 coin price relative to 30 day averages), and top 18 coin price high over the previous 90 days. So, it's interesting that despite this being at face value a rather complicated set of data with many inputs, that it just looks like a carbon copy of the Bitcoin chart. Bitcoin has a gravity that is inescapable for all things crypto right now.
The difference between looking at this indicator and simply looking at Bitcoin's chart is that it flattens out the action and has a set floor and a ceiling. You can see historically that the best buy times were when fear was at its "height" (where the yellow line is at its lowest). Another way to stack probabilities. At time of writing, is this a great time to buy? Fear appears to be leaving the market, we haven't had a commensurate price move up, so I'd be cautious. Like all these indicators, you can just overlay Bitcoin's price line and backtest the correlation in a few seconds. Buying when fear is at a maximum is usually easier said than done, though!
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Lastly we have Liquidations by Volume , as per the coder this "shows actual liquidations on a per-candle basis by using the difference in volume between spot and futures markets." Blue line is futures volumes, yellow are spot volumes. The code for this indicator shows that it is the same BTCUSDT Perpetual Future's contract from Binance that we have in the Liq.Levels indicator, perfect.
Worth noting is that the community of coders at TradingView is a trader's dream. These sorts of customisable dashboards you can build are high value. Having worked for the largest international institutions I find many of these indicators are institutional grade and they have just a few hundred users sometimes, pretty crazy how early in the adoption curve we are with this. If you haven't experienced the "other side" of trading, compared to regular equities forex futures etc the TradingView tools and the crypto data and exchanges are just lightyears ahead.
Back to why look at liquidations? As institutions come into the market, and retail wallets on exchanges like Binance and many others continue to use leverage, the action in the derivative (in this case $BTCUSDTPERP) can and often does drive the price of the underlying. Market makers hunt the maximum liquidations, always. The market context is highly relevant here. During volatile periods it is a swinging contrarian indicator. If there has been massive green bars showing short liquidations pushing the price up, then we could be forming/hitting resistance levels and can see reversal/selloffs, and vice versa if there are massive red bars showing long liquidations pushing the price down, this can be hammering out support levels and we look to bounce. The longs and the shorts really do seem to be taking turns getting liquidated right now.
Also of relevance is the price action relative to the liquidations. Obviously if an institutional candle pushes the price up or down, there will be mass liquidations. But another scenario that occurs is when are light volumes on the derivatives such as $BTCUSDTPERP we have under the microscope here, but we have large Bitcoin price movements, then the reasons for the move can be understood differently, and we can use this and other contexts to draw conclusions such as for example a scenario where price goes up with light liquidations and derivative action, which could be interpreted as much stronger hands holding coins rather than simply margin calls.
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Good luck!
Onchain
Combining wyckoff's theory with ONCHAIN data"This is a hypothesis that needs more testing to be more precise."
Wyckoff's theory t is one of the most influential theories of market expression, and the most important components of which are lateral movement areas and trends. This theory turns the graph into something like Dots and lines (stations and paths). But it is not as easy to use as written in books. After getting acquainted with Wyckoff's theory, I read several books on the subject, hoping that they could help me identify this area of lateral movement, the area of accumulation, or distribution. But there was a fundamental drawback. It is challenging to diagnose this issue. In fact, the rules discussed in these books are highly interpretive and subjective, and two different individual traders may come to exactly opposite conclusions based on their interpretation.
But as I became more familiar with the onchain analysis, an idea came to my mind that might be useful for more objectively recognizing charts based on Wyckoff's theory.
Composite Man: Wyckoff proposed a theory to help understand price movements in stocks. this is the “Composite Man” theory. (The same concept of whales or strong hands.)
he said: “…all the fluctuations in the market and in all the various stocks should be studied as if they were the result of one man’s operations. Let us call him the Composite Man, who, in theory, sits behind the scenes and manipulates the stocks to your disadvantage if you do not understand the game as he plays it; and to your great profit if you do understand it.” (The Richard D. Wyckoff Course in Stock Market Science and Technique, section 9, p. 1-2)
In fact, composite Man is a hypothetical man who has so much money and stocks that when he wants he can gradually increase the price by buying stocks and creating demand, and when the price goes high enough he selles his stock and lower the price. The composite man is the main player in the market. Wyckoff says that if you want to make a good profit from the market, figure out what a composite man game is.
In fact, having a way of showing us where the Composite Man is in the market, can help us understand future trends
Who are the strong hands in the cryptocurrency market? (I use the strong hand word here instead of the composite man)
There are those who buy or sell more per capita than other market participants (retailers).
To understand this in the bitcoin market, I have used 3 charts and concepts:
1- Sending Addresses: The number of coins addresses making inflow transactions to the exchange.
Indicates the number of sellers' wallets (number of sellers)
2- buyers Addresses: The number of coins addresses making outflow transactions from the exchange.
Indicates the number of buyers' wallets (number of buyers)
3- Pay attention to this issue: the volume of transactions shows both the volume of sales and the buy (Volume of buy and sale is equal in the market)
Considering the above 3 issues, it can be concluded:
- If the number of Receiving Addresses is higher than the Sending Addresses (the number of people who bought compared to the number of those who sold), it indicates that more people bought and fewer people sold (given that the volume of sales and buys are the same) So the sellers were stronger hands. In such a situation, the composite man is on the sales side.
- If the number of Sending Addresses is higher than the Receiving Addresses (number of people who have sold more than the number of people who have bought), it indicates that more people have been sellers and fewer people have been buyers (given that the volume of sales and buys are the same) so the buyers were stronger hands. In such a situation, the Composite man is on the buying side.
To do this, the oscillator at the bottom of the chart divides the Number of Receiving Addresses by the Number of Sending Addresses. Numbers above 1.2 indicate that the Composite man is on the side of the sellers and should expect a price reduction in the future.
Values below 1 (or 1.2) indicate that the Composite man is on the buyers side. And we should expect price increases in the future.
NVM Ratio: Bitcoin is is overvalued"Please note that this post is not a recommendation to trade, it is just a review of an ONCHAIN index. "
One way to check the intrinsic value of bitcoin is the NVM Ratio, And it can be compared to the P/E index in the stock market This index is based on Metcalfe’s Law.
Metcalfe’s law states the effect of a telecommunications network is proportional to the square of the number of connected users of the system. In another world: the value of the network is proportional to the square of the number of active users.
Network Value to Metcalfe Ratio (NVM Ratio) is defined as the ratio of the log of market capitalization divided by the log of the square of daily active addresses.
The chart above shows the price of Bitcoin, MarketCap, and the number of active addresses.
We have compared these 3 values in the top 2021 compared to 2018. Although the number of active addresses has remained almost constant, the market cap has risen from 378 B to 1.22 T (It has increased almost 3.3 times). In fact, despite the fact that the number of active network addresses remains constant, its price has increased 3.3 times.
NVM ratio in the recent top was 1.32 and in the top of 2017 was 0.43. NVM Ratio is now close to its ATH. This could be a sign that the network is overvalued
the percent of circulating supply that has not moved 1 yearThis chart shows the percent of circulating supply that has not moved in at least 1 year. This data shows what percentage of long-term holders have kept their bitcoins.
This index has a negative correlation with price. When prices fall, holders are reluctant to sell and the index starts to rise. Once the price has risen enough, some of these holders will start selling their bitcoins, which causes supply to increase and prices to start falling.
The linear correlation in the correlation oscillator indicates the negative correlation with R = - 0.9. For a better understanding, a bitcoin chart is drawn next to it and the peak and trough points are marked.
BTC ON-CHAIN ANALYSIS: SOPR
ON-CHAIN analysis can be equated with fundamental analysis in the world of cryptocurrency. From now, I will try to do some of the analysis available in Trading View.
The SOPR index is one of the available on-chain data in Trading View. SOPR is an Abbreviation of The Spent Output Profit Ratio (SOPR). it is computed by dividing the realized value (in USD) divided by the value at creation (USD) of a spent output. Or simply: price sold / price paid. In fact, this index shows whether investors are in profit or in loss?
When SOPR> 1, it means that the owners of the BTC are in profit and when SOPR< 1, they are at a loss
during a bull market values of SOPR below 1 are rejected: In a bull market, when SOPR falls below 1, people would sell at a loss, and thus be reluctant to do so. This pushes the supply down significantly, which in turn puts upward pressure on the price, which increases.
during a bear market values of SOPR above 1 are rejected: In a bear market, everyone is selling or waiting for the break-even point to sell. When SOPR is close/greater than 1, people start to sell even more, as they reach break-even. With a higher supply, the price plunges.
This indicator can be used in another way - is the price relatively cheap or relatively expensive?
Based on historical data, I have drawn OVERBOUGHT and OVERSOLD areas. At low prices, investors tend to buy, which in turn will increase prices, and at high ratios, investors will tend to sell.
BITSTAMP:BTCUSD COINBASE:BTCUSD BINANCE:BTCUSD BINANCE:BTCUSDT BYBIT:BTCUSDT
