John_Brown

OG | Crypto trader & speculator | Pro-local, pro-global, anti-national | Long education & freedom | Short hierarchy & dictation

Where does price correlation come from?

Bitcoin is supposed to be uncorrelated or even negatively correlated to traditional assets and thus an important addition to any diversified portfolio. But especially since the crash of March 12th Bitcoin more and more often moves alongside traditional markets, especially equities. Where does this change originate from? As a safe haven asset, shouldn’t Bitcoin be uncorrelated or even negatively correlated? And why is correlation often non-existent just to suddenly spikes up out of nowhere to then fade out again (see chart, kudos to [https://twitter.com/cryptounfolded](https://twitter.com/cryptounfolded))? To answer these questions, we must first understand what drives correlation in the first place. Consider two stocks: both working in the same industry, say airline business. Ciovid-19 is a blow to the whole industry, so both stocks A and B decline in tandem: nearly perfect correlation. Then quarterly reports are due and company A presents surprisingly good results while company B shows surprisingly bad results. Stock price of A goes up while B goes down – negative correlation on that day. On average over the whole quarter correlation is still positive, although not perfectly 1:1 anymore. This makes perfect sense: stocks of both companies are mainly driven by industry exposure and the Covid-19 event, while the rest is idiosyncratic in relation to how well they manage the situation and their company in general. This is the standard explanation of correlation: two assets share a similar exposure and thus a similar price pattern. But can this view help to explain the changing correlation of Bitcoin with traditional equities? Yes, it can. To see why, let’s consider two case studies. **Case one: Crypto OG** Consider being an OG. You run some mining back in the days while Satoshi was still active on bitcointalk.org. You are a geek, a computer nerd, a fan of cryptography – you own a ton of Bitcoin but you have no clue about finance and do not own any stocks, bonds, commodities, funds or derivatives and might not even own a brokerage account. Over time and with every roller coaster of Bitcoin’s price you dig more into monetary economics and trading. You start to try to sell some of your precious coins when markets seem to be overheated: “These $7 are totally unreal, how can any person in his right mind pay so much for a Bitcoin when you could simply mine it on your laptop while sleeping? Sell!” (price went to $30 before it went down to $2 again). And you start to buy back when you think the price tanked already too much: “Price dropped now from $1,200 to $600 just because of Mt. Gox going belly up. This does not change any fundamentals – buy!” (price went to $220 before going back up again). You and your peers make up 90% of the crypto market and since no one is much interested in traditional markets, Bitcoin price action is completely uncorrelated. Although the best strategy in hindsight would have been to simply hold on to your coins, you outperformed all your peers who at some point sold all their coins waiting to buy back lower – just to realize they missed the train and buy back much higher. Then this crazy bull market in 2017 and January 2018 happens and your net worth explodes. You read about portfolio diversification and calculate your crypto exposure: 99.96% of your portfolio. By any means, that is unhealthy. You decide to “professionalize” and start by diversifying with the “conservative” rule to “only” hold 50% of your portfolio in crypto. You cash out 50% of your holdings, put the4se $50 million into stocks – some ETFs and, after about half an hour of research, you also toss in $1 million to some handpicked stocks in biomedicine and robotics. Every week you calculate your exposure to your assets and then rebalance. If Bitcoin went up compared to equities, you sell Bitcoin and buy stocks. If Bitcoin declined, you sell stocks and buy Bitcoin. Hello correlation: your diversification rule triggered the formerly uncorrelated assets to start becoming correlated – especially when prices move strongly. **Case two: Traditional fund manager** Now consider being a fund manager. You are well trained in finance and your clear focus on your career helped you to outperform your peers both university and the trading desks you worked for. Some of your old friends talk about “crypto” and the crazy gains that can be made there. But the focus on your work does not allow you to have any side interest and so you never read Satoshi’s white paper and in general remain unknowledgeable about crypto. Just like all your peers: no one in traditional finance is in crypto. Over the years you climb the career ladder and you grab a senior position at a large institutional investor. Your narrow focus widens. At the same time, crypto becomes more and more mainstream and with the bull run in 2017 you start paying attention to crypto. You immediately grasp the beauty of the concept and are well-trained to not bother about missed opportunities and do not listen to the voice in your head wining “I should have listened to my old friends back then”. Instead, you focus on the opportunities at hand and calculate how much the risk adjusted performance of the fund you are responsible would go up, if 10% were allocated to Bitcoin. In order to not sound too crazy you propose to allocate 5% of the fund to Bitcoin. While most board members think you are crazy, fortunately, your CEO is not originally trained in finance but has a broad background and a vast experience in spotting the rare occasions when someone presents a great idea. After only two meetings you convince your CEO and, in turn, the board to make the “bold and risky” move to allocate up to 1% of the fund to Bitcoin. It just needs to pass legal. The legal team feels safe but requires to cover their ass by first getting official approval from the regulator. About a year and a half later a one pager arrives stating that the regulator has no concern. Four weeks and a series of well-orchestrated and executed OTC trades $50 million were invested into Bitcoin. The internal requirement is to never have more than 1% exposure to Bitcoin and so the rule is made to rebalance Bitcoin and equity positions in real time when prices move. Hello correlation: this rule causes a correlation between traditional markets and Bitcoin. **What does this mean for Bitcoin?** While Bitcoin is not affected by the number of sales or quarterly earnings, these examples show how Bitcoin can still be correlated to traditional assets: by portfolio allocation. When one asset declines, the other needs to be sold to rebuy the declining asset – in effect the declining asset tanks less at the expense of the “unaffected” asset that now also declines. This is especially true for leveraged trading and when the market tanks and collateral needs to be sufficient to sustain positions. This exposure to portfolio rebalancing and need for collateral perfectly explains the drastic correlation spikes when traditional markets a) move strongly, and especially b) decline strongly. These two case studies also show how a shift in the strategies of the market participants (100% crypto vs. balanced portfolio) and a change of market participants in general (only crypto OGs vs. institutions entering) can change the link, that is correlation, between assets. The increasing correlation between Bitcoin and equity markets can thus be seen as a sign of market efficiency and “professionalism”, that is, existing market participants either become more sophisticated or leave the market, while new market entrants from traditional finance enter the space.

BTCDOM: An underappreciated gem of an index

Six weeks ago, on 6th of May, The Bitcoin Dominance Index was launched on Bitfinex. It trackes the relative price movement of Bitcoin vs. seven altcoins. More precisely, it measures the relative price movements of these equally weighted pairs: · ETH/BTC · EOS/BTC · LTC/BTC · XRP/BTC · BCH/BTC · BSV/BTC · XTZ/BTC · XLM/BTC Bitcoin increases against these seven tokens, the index goes up, otherwise it goes down. To ease measurement, the starting price was set to $100. Hence, if you are bullish on alts you short the index, and if you are either bearish on alts or more bullish on Bitcoin than on alts, then you long the index. So far the index never fell below $100 and peaked at around $115 on May 14th. What is remarkable that there is extremely low volume on the pair. Still, there have been no price wicks (the one on May 12th only looks like a wick, but prices went crazy that day and the index kept track smoothly), since the order book seems rather liquid compared to the low volume. This liquidity can also be seen on June 9th, that showed quite some volume but without any price effect. One characteristic that cannot easily be spotted on a graph is the correlation to the Bitcoin price in USD. One would expect that a Bitcoin Dominance Index has a positive correlation with BTC/USD, after all, it should track Bitcoin’s success. But that is actually wrong. I took minute price data of the BTCDOM mark price and BTC/USD to find out that there is no statistically significant correlation between both price feeds (neither significant, not strong)! That effectively means that the correlation between Bitcoin and the seven altcoins of the index is so strong that the absolute movement in USD terms does not have any effect on BTCDOM. This independence of the BTC/USD price makes BTCDOM an even greater product to trade. It does not only let you bet on the relative performance of Bitcoin vs altcoins, but also allows you to do so without getting any exposure to BTC/USD that you would need to hedge. This makes it a nice and pure bet. Apart from this, BTCDOM can also be a great hedge for larger and thus illiquid or locked altcoin holdings. For example, consider you have a portfolio of $100 and would like to allocate $50 to Bitcoin, $30 to cash and $20 to altcoins, but have $50 locked in altcoins, $30 in cash and an underexposure of only $20 in Bitcoin. Then you simply buy $30 of BTCDOM to reach your target exposure.

Introducing the Fishiness Indicator for Derivative Trading Volume

Perpetual and Futures are an integral part of today’s crypto markets and most serious spot exchanges by now offer these products as well. Just like with spot markets, traders tend to look at 24h volumes as a proxy for liquidity. While the claimed trading volumes for derivatives seem to be more honest than claimed spot volumes, the reason might simply be that complete fake exchanges still mostly focus on spot. On a second look, claimed derivative volumes seem quite odd, too. I hereby introduce the **Fishiness Indicator**for derivative trading volume as a metric to measure if claimed 24h trading volumes look reasonable or odd and define it as the **claimed 24h trading volume divided by the open interest**. The rationale behind this is that while it is quite easy to fake trading volume, open interest is harder to fake (although far from impossible). Not surprisingly, the Fishiness Indicators of claimed volume to open interest differ strongly between exchanges from 0.19 for Bitfinex to 8.19 for Binance (see figure). There are **three legitimate reasons** for why such ratio might differ between exchanges: 1) **Fees**: The lower the fees, the higher the trading volume. The less it costs to trade, the more is traded, since traders can chase smaller edges. The best example for this when “back in the days” trading on Chinese exchanges was charged 0% both for maker and for taker trades. CNY trading volume was then reported to be 98% to 99% of global BTC trading volume (exchanges made their money by lending fees for margin trading). Some derivative exchanges have lower fees than others; this potentially explains a part of the difference in ratios. 2) **Presence of gamblers**: Gambling traders trade with a higher leverage, get liquidated more often, and more often switch between positions. This causes, on average, more trading volume per open interest than professionals, who just open one position to hedge and then hold it until expiry or drastic changes in market conditions. 3) **Volatility of premiums and funding rates**: The more volatile premiums on futures and on funding rates are, the higher the incentive to switch positions back and forth to react to these changes. Since the volatility of premiums and funding rates differs across exchanges (something to look at in more detail in a future pulse) this can likely explain part of the observed difference. While the difference in the ratio can certainly be explained in part by these legitimate reasons, I strongly believe that other, “fishy”, reasons also explain part of the differences. These relate to either faked or manipulated trading volume. Let’s first look at **naked volume faking**. The most basic way to fake volume is to simply report more volume than is reported in the trade history. A little bit more elaborate, and much more common, is to print false trades between the spread. This can be done in a stupid way (steady over time, identical trade sizes or identical trade size distribution) or clever (mimicking actual trading volume in regards to time and order sizes). Basic and stupid volume faking can easily be observed by watching the order books and trade flow. Spotting clever volume faking is harder, but can be detected by looking more closely and using some tools (e.g. [https://github.com/Whalepool/Bitcoin-Volume-Validator](https://github.com/Whalepool/Bitcoin-Volume-Validator)). I thus believe that naked volume faking does not play much of a role anymore (except for pure fake exchanges). More likely seems to be **manipulation of trading volume. **This is actual trading volume but conducted** **via **Internal Trading Desks** (ITC) that pay zero fees (either directly or indirectly by being owned by the exchange). These desks create a liquid market with many executed trades and much liquidity in the order books. While this looks and sounds good it is actually quite bad for traders and much worse than naked volume faking? To see why, let’s break such volume down into two categories: a) trades between internal trading desks and b) trades between an internal trading desk and a customer. Trades of category a) might look similar to naked fake volume, but are worse: they take liquidity from a regular trader that now either cannot execute his trade or only at a worse price. Such volume thus does not only create the false impression of liquidity in the trade history but also in the order books. Trades of category b) actually look positive on the surface: Traders get executed at potentially better prices than what other regular traders would accept (since ITCs effectively pay 0% fee on their trades and can thus offer better quotes). Traders should be happy about ITCs – after all, they give them liquidity, no? No. ITCs do not exist to lose money to traders. Instead, they are armed with the best tools and best traders available and trade at the lowest latency. They will only execute trades that have a positive expected value – which means that the other side has a negative expected value for his trade. Thus, if a trader gets executed against an internal trading desk, he can expect it to be a losing trade. But such desks do not only execute the losing orders of regular traders but also prevent their winning orders from being executed: since ITCs pay zero fees, a trader can expect such desks to snap any profitable trading opportunity before him. Think of ITCs as the odds maker in sports betting: you might win against them in the short term, but will always end up **losing against the house in the long run**. I want to explicitly exclude any exchange activity that is not aimed at profitable trading by exploiting their customers but simply at channeling or mirroring liquidity across books. This cannot, by definition, exploit traders to make extra money, but is instead designed to return zero profits. Manipulation by ITCs cannot be spotted by observing order books or the trade history. Instead, other metrics are needed. One idea would be to track external indicators like website traffic. While this approach is promising, it comes with some limitations and a lot of workload. I thus propose the Fishiness Indicator as a shortcut to identify potentially manipulative exchanges where traders should be cautious. Knowing that such an indicator is not precise science I suggest to be cautious, when an exchange has a Fishiness Indicator value of 3 or larger and be at the lookout at a value between 2 and 3. The limitation of the Fishiness Indicator is that it assumes that volume can be easily faked but open interest not. This is a strong assumption, since open interest can also be faked, either directly by reporting a wrong figure or by having internal trading desks build positions that offset each other. Hence, a low value of the indicator does not imply that there is no volume manipulation. Actually, with so such an indicator becoming public knowledge, I predict that we will see much lower values in the future, when manipulative exchanges decrease it by increasing their reported open interest. This logic could actually be turned upside down: If, such the Fishiness Indicator of an exchange is high today but low in, say 6 months, without the reported volume having changed, it is a good sign that the exchange is manipulating the trading volume. One thought on the very low FI of Bitfinex: It is quite possible that their derivative products are mostly used by professionals that want to hedge positions but do not change these once built. The very low volatility of the funding rate (usually it is 0%) supports this view since these traders aim to keep their hedging costs close to zero. ​

A note on the fundamental value of $LEO

In my recent pulse ([https://www.bitfinex.com/pulse/post/a75e17d9-8a36-4d2c-b183-59ebd46fe594](https://www.bitfinex.com/pulse/post/a75e17d9-8a36-4d2c-b183-59ebd46fe594)) I developed a link between the prices of RRT and LEO and concluded that the chance to recover the stolen BTC from the 2016 hack explains around $0.075 of the LEO price. At the current price of $1.22 this leaves $1.145 unexplained. This post aims at closing the gap. An important aspect of LEO value is its buyback characteristic: 27% of all revenues of Bitfinex are used to constantly buy LEO on the open market. To estimate how much this is worth per token, we can compare it to the price of Bitfinex shares, which are currently traded at around $3.50 on Bnktothefuture (last trade at $3.13, second to last trade at $3.75, highest bid at $3.25, lowest ask at $4.5). With around 175 million shares outstanding, this amounts to a valuation of the company of 612.5 million, which reflects the value of 73% of its revenue minus the costs of operation. If we assume costs to be $20 million per year and use a multiplier of x10 (equaling a discounting factor of 0.1), this yields a valuation of $812.5 million for 73% of the revenues. The remaining 27% devoted to LEO holders are then worth $300.5 million (and 100% of the revenue stream being worth $1.113 billion). With 978.9 million LEO token outstanding, this translates into $0.333 per token. Taken together with the $0.075 of the hack recovery value this explains $0.408 or 33.4% of the LEO price. LEO Tokens also provide some benefits to its holders, especially a reduction in fees. This feature is very idiosyncratic in its value to LEO holders: It is very valuable to high frequency traders with lots of trading volume but makes not much of a difference to someone with a buy&hold strategy. So let us assume that it only brings value to those with large trading volumes – and at the same time assume that these customers make up for 80% of the total fees paid. If they, on average, save 20% in fees, that would man that the utility aspect of lowered fees is worth 16% of the fee income/revenue stream. This translates into a value of $178 million for LEO holders and thus explains $0.182 of the LEO token price. Together with the other aspects we now explain $0.59 or 48.3% of the LEO price leaving open $0.63 or 51.7%. If LEO is priced correctly, the remaining gap must be explained by the expected value of the use of 80% (net of costs) of recovered frozen funds held via Crypto Capital for buying back LEO tokens within a period of 18 months. Following the same logic as with the effect of a recovery of funds from the 2016 hack (see my last post linked above) we can value such an event at $3 per LEO token (meaning that the recovery causes the price to go up by $3). With only $0.63 of the token price left to explain, this means that the market gives an implicit probability of the recovery of such funds of 21% ($0.63/$3). Twisting this logic, we could say that someone estimating the probability of recovery at 50% (=$1.50) should value LEO at $2.09, rendering LEO a clear buy. Obviously, these numbers depend on a couple of assumptions, mainly: - A recovery of either hacked funds or CC funds each leading to a boost of LEO of +$3 (this number comes somewhat out of thin air and also the funds at Crypto Capital are worth less than the value of the stolen BTC) - Recovery is analyzed as a binary event (yes/no) and neglects partial recoveries - Bitfinex equity is fairly priced at $3.50, although the market is very illiquid - The fee rebate value of LEO is worth 16% of the revenue stream This post is much more about the thought process than about the actual result. The reader is thus encouraged to change these assumptions based on his own estimates to come up with different results.

On the price relation of RRT and LEO

In case of a recovery of the 119,756 BTC stolen in the 2016 hack, Bitfinex has committed to use 80% of the recovered net funds to buy back LEO over the course of 18 months. At $9,500/BTC the current value of the stolen BTC is around $1.13 billion, but before any recovered funds could be used to buy back LEO, all holders of RRT need to be paid first. Each Recovery Right Token makes his holder eligible to a payment of $1 per token. While the exact amount of RRT outstanding is unknown, the LEO whitepaper mentions 30 million token to be circulating ([https://www.bitfinex.com/wp-2019-05.pdf](https://www.bitfinex.com/wp-2019-05.pdf)). This would leave the maximum net buyback of LEO tokens to be $1.1 billion \* 0.8 = $880 million. Other factors reducing this amount in a case of a recovery would be that only a partial amount of the token can be recovered, there are legal costs attached to the recovery, or that there is a deal with the hacker(s) leaving them a part of the funds. A factor increasing the buyback funds would be an increase in the BTC price. While it is pure speculation how much funds would actually be used for LEO buybacks in the event of a material recovery, it would certainly be in the hundreds of millions. With LEO holders knowing that a couple of hundred million Dollars will be used for buybacks over the course of 18 months, ask orders will quickly vanish from the books while regular buybacks plus recovery buybacks need to be executed. In such an event we would see a strong positive demand shock being met by a negative supply shock causing the LEO price to skyrocket. An increase of the LEO price by $3 to – at current prices $4.15 – is everything but unlikely and to be assumed for further analysis. Well, but how likely is such a funds recovery? With so many elements driving the LEO price, it would be hard to quantify any effect of a new information on a funds recovery by looking at the LEO price. However, the design of the Recovery Right Token makes it easy to translate its price into how likely the market deems a recovery of those funds. With the only value of the token being the eligibility to a payment of $1 per token and one RRT currently trading at $0.025, this translates into a 2.5% chance that the funds will get recovered (not accounting for any time value of money). Now comes the core of the argument, which is the link between the RRT market price and the LEO market price: If we assume as above that a recovery would cause the LEO price to skyrocket by $3, the funds recovery are priced in with $0.075 – or around 6.5% of LEOs current market value. If RRT were to increase from $0.025 to $0.05 this would mean that the market sees the likelihood of a recovery being increased by 2.5 percentage points, which should, in theory, cause the LEO price to increase by $0.075. Having established this link between RRT and LEO theory, let’s see how it behaved in practice and look at recent price spikes of RRT and see if RRT and LEO moved in accordance. In February 2019 the price spiked to $0.065 after an announcement that 27.66 BTC were recovered from the hack ([https://medium.com/bitfinex/bitcoins-returned-to-bitfinex-by-u-s-government-51fe84e8bb12](https://medium.com/bitfinex/bitcoins-returned-to-bitfinex-by-u-s-government-51fe84e8bb12)). LEO did not exist back then, but it shows how the RRT market reacts to new information. A few months later on 7th of June more coins of the hack moved and the price of RRT rallied from $0.043 to nearly $0.08 on 24th June 2019. This translates into the market seeing a 3.7% higher likelihood of a funds recovery and should have induced a LEO price change of around $0.11. And indeed, during that time the price of LEO realised from $1.50 to nearly $2. Was this an overreaction or was the LEO price action blurred by other factors like the general bull sentiment at the time and a LEO hype? Certainly the latter plays a role, but given that LEO moved from $1.50 to $1.64 only on June 6th – the day the coins moved – I think that there was a mismatch between LEO and RRT markets pricing in the new information at the time. This mismatch could have been exploited by selling LEO and buying RRT. The next time coins from the hack moved was 12th of August 2019 but neither the RRT nor the LEO price moved. A few days ago (22nd of May) some coins moved yet again and this time the RRT market reacted with a price move of $0.018 to $0.03 (actually happening a day later on 23rd of May). If we apply the above logic, this translates into an increase of the chances of funds recovery of 1.2 percentage points we should have seen a price move of around $0.036 in LEO. However, while LEO is on a consistent move upwards the last weeks, it barely moved on that day. Hence, we saw a mismatch of the prices, although this time the other way around and the exploitation would have been to sell RRT and buy LEO. Let’s be honest here: the RRT market is not liquid enough to give precise signals on the likelihood of a recovery of the stolen funds: even a small buy or sell order could move the market. I would thus refrain to move on any RRT-LEO trades on the above logic, while the mismatch is only small and only act, if there is a large mismatch (think of RRT moving close to $1 without LEO keeping track). The main point here is to unveil the link between RRT and LEO, which is likely unknown to most traders.

Security Tokens: The Megatrend of Crypto

I am following the space since nearly ten years now and witnessed quite some trends so far. The one that probably got me most excited was the concept of “colored coins” back then. While it was quite simple, it took some years until more and more tokens spread that are a representation of something else than the token, like a USD or Gold. This is just one example of a common characteristic I observed with all of the new trends, not matter how convincing or easy they seem to be: they take much longer than expected. With that experience in my bag I still love to observe and follow trends and get excited about them. The only difference is that I take some time before really getting excited and especially before I expect something material. There is one trend that I am keen on since two years but that I knew would take time to develop, not because it is technically complex, but because it is legally complex: security tokens. Having seen the first shy baby steps, I believe we will "soon" (=by the end of 2020) see the first larger and more serious approaches that will mark the beginning of a new era and will be dwarfed by what is about to come. I do not see crypto as something distinct from traditional financial markets that at some time might be adopted by its big brother in form of more and more institutions investing in Bitcoin. Rather, I think of crypto as a technology that will soak through more and more areas of our society. And with regards to securities, I believe that as soon as it becomes evident how superior token-based securities are compared to their paper-based securities, it will not take too long until paper-based securities will be a matter of the past. Such seismic shifts in societies and markets usually start very slowly and can get quite fast and brutal at their peaks. This is what I expect to see here as well: two more years of slow growth (slow compared to the size of legacy financial markets, this could still be large compared to crypto market caps) before a period of 3-5 years of mega-growth where the whole old system gets deconstructed and every stock, every fund, every bond, any kind of asset will get tokenized. Now is the time to get prepared for this megatrend.

BTCDOM outperforms BTC/USD

BTCDOM is up nearly 8% since its inception 6 days ago and outperformed BTC/USD. Remarkable is how stable it is when BTC dumps.

Benefits of LEO seem unknown

There are a couple of nice benefits of owning LEO and it seems to me that these are mostly unknown and not talked about. The most important benefit is to save on trading fees. Even owning one single LEO gives you already a nice discount of 15% on your taker fees. Additional LEO add to the fee advantage. You also save on lending fees. And then there is the psychological advantage: The longer you hold your LEO, the more you become a lion!

My Crypto Trading Background

- Started in 2011 with $500 - Largest trading volume month: $3.5billion - Traded on around four dozen exchanges - 50 out of the first 52 trading month were profitable - Lost focus and got sloppy after 2017/2018 bull run: 8 consecutive losing months in a row and 14/20 months were negative - Rebuilding since October 2019, mostly profitable - Never lost funds in an exchange hack/closure: o Got away early enough from Mt. Gox o Got reimbursed on Bitfinex o Fought off attacks by Hitbtc o Dodged Cryptsy early enough o Dodged Cryptopia early enough o Dodged QuadrigaCX early enough o Dodged more shit

Lending Rates Spiked

If you have some free BTC, USD or USDT to spare: consider putting them on the books to make a nice return.