The Lightning Network Reference Rate & Bitcoins Derivative Pricing

Authors: Maximilian Boelstler (Research Assistant), Lewin Boehnke PhD (Head of Research), Patrick Heusser (Senior Trader)

Download The Lightning Network Reference Rate (LNRR) & Bitcoins Derivative Pricing Research Report PDF


“People far too often associate derivative markets with mere speculation, but there are very legitimate businesses that need derivatives to protect themselves against risk.”

         – Fred Ehrsam, Co-Founder of Coinbase


Bitcoin derivatives are relatively new, especially when compared to traditional derivative products. While doing research for our last paper on Bitcoin’s Lightning Network, we detected that there is a possibility of earning interest without counterparty risk. We put our heads together to ponder this interesting idea, which raised the question of how derivatives on Bitcoin are actually priced since no base rate is available. We conducted a quantitative analysis by calculating the implied interest rates of Bitcoin futures with different maturities. The results revealed that there are some similarities with the borrowing and lending rates that are used in the digital asset ecosystem. An additional thought experiment about the pricing of Bitcoin futures using the Lightning Network Reference Rate showed that this rate might serve as Bitcoin’s base rate and thus increase transparency in the pricing process.

As already pointed out above in the quote by Fred Ehrsam, the co-founder of the digital currency exchange company Coinbase, derivatives do not only serve a speculative purpose. A derivative is a contract, which derives its value from the performance of an underlying. In traditional banking, this kind of product is widely used for hedging purposes, resulting in a situation where the market capitalisation of derivatives is around 8 times greater than the equity market capitalisation, and around 2 times greater than the debt market capitalisation.

Forward and futures contracts represent a subset of these financial instruments, allowing market participants to offset or assume the risk of a price change of an asset over time. On December 10, 2017, the Cboe Futures Exchange, LLC (CFE) launched the first regulated Bitcoin Futures under the ticker symbol “XBT”. According to their factsheet, “XBT futures are U.S. dollar-denominated, cash-settled futures contracts that are based on the auction price of bitcoin on the Gemini Exchange”.

In the meantime, several futures for Bitcoin and even Ethereum are available. Cboe and the CME Group predominantly offer futures contracts for institutional investors, whereas Deribit, BitMEX, and Crypto Facilities (CF) also provide a selection for private investors. Interestingly, all platforms determine futures prices that are quite similar, despite the fact that no risk-free interest rate or base rate for Bitcoin is available. If we classify Bitcoin as a commodity, such as the US Commodity Futures Trading Commission does – they have also declared virtual currencies as commodities – the question arises as what implied interest rate curves are being used for the pricing?

Taking into consideration that the Lightning Network[1] is continuously growing and becoming more stable, the possibility of earning risk-free interest on Bitcoin deposits might be addressed in the wake of Bitcoin’s derivative pricing. For analysing this idea and its potential impact, this paper is structured as follows: first, we will address the analogies between the interest rates in traditional markets and the Lightning Network Reference Rate (LNRR) in the digital asset market in order to establish a general understanding. We will then look at the current pricing of Bitcoin Futures to provide both an overview and a comparison of the implied interest rates used. Finally, we will conduct a thought experiment to determine the impact on the Bitcoin Futures using the LNRR – carried out under specific assumptions.

The Lightning Network Reference Rate  and Traditional Interest Rates

In traditional banking, we believe in interest rates determined by the treasury curve, the LIBOR curve, and the OIS curve – whereas the last one is commonly used for determining the fair market value of a collateralised investment or the pricing of derivatives. A visualisation of the OIS curves of the USD and the EUR (EONIA[2]), retrieved from Bloomberg on February 8, 2019, can be found in Fig. 1. As can be observed in Fig. 1, rates may differ significantly from one country or economic area to another. Overall, the determination approach is based on a closed and non-transparent network of participants

Figure 1: Comparison of USD OIS Curve and EUR OIS Curve
Source: Bloomberg (February 8, 2019)

An interest rate is generally defined as “the amount charged, expressed as a percentage of principal, by a lender to a borrower for the use of assets. Interest rates are typically noted on an annual basis, known as the annual percentage rate (APR)”. Central banks use interest rates also as a control instrument of their monetary policy. For instance, the decreasing of the interest rate could increase the demand for loans, thus increasing the purchases, and, ultimately, stimulating the associated economic growth. Because an interest rate might be such a powerful instrument, a central institution takes charge of its determination. E.g., the ECB in Europe and the FED in the US.

In wake of the Lightning Network, the idea emerged of the “technological” determination of interest rates – a peer-to-peer based interest rate for Bitcoin. As mentioned in our last report, one property of the Lightning Network is the “free choice” of the transaction path. Since every default setting of a Lightning application generally selects the cheapest path due to the routing algorithm employed, the channels, which are not in line with the fees of the great majority, will never be actively used. The market chases efficiency.

Even though the LNRR might not be used as a control instrument to accelerate/decelerate economic growth, a participant-based interest rate does allow the determination to be based on demand and supply in a more transparent manner. This rate also allows investors to measure their opportunity cost of Bitcoin. Thinking one step further, the risk-free LNRR might have an impact on the price determination of Bitcoin derivatives as the opportunity cost of Bitcoin becomes measurable.

Within this context, most readers will now start thinking about the risk-return relationship of traditional assets, and what is more, the question of why we actually consider the LNRR as “risk-free”.

Here’s a counter question: have you ever thought about the risk-return relationship of digital assets?

The Risk-Return Relationship of Digital Assets

In traditional markets, financial risk is defined as the variance or standard deviation of an asset’s returns. Debt instruments such as government or corporate bonds serve rather as low interest and secure investment vehicles compared to equity investments, e.g. the shares of a stock. Leveraged investments in non-established or almost bankrupt companies are associated with even more risk and therefore considered as high-risk investments, e.g. venture capital or private equity (funds), c.f. Fig. 2.

It is possible to determine many sub-classifications within each investment category leading to some products perhaps overlapping within the risk-return relationship. For example, junk bonds are characterised by higher risks as there is a higher probability of a payment default; in exchange, they usually bear higher interest rates than common corporate bonds.

Figure 2: Risk-Return Relationship (TM)
Source: Own Illustration

The general rule states: the higher the risk, the higher the expected return.

The concept of risk and return could even be applied to the digital asset ecosystem (c.f. Fig. 3). Let us consider the Lightning Network as risk-free because there is no related counterparty risk. An analogy could be drawn by investing in a US Government Bond or a US Government Bill – we will have a more detailed discussion about the term “risk-free” in the following section.

Several exchanges offer collateralised and uncollateralised borrowing and lending of cryptocurrencies. For instance, retail customers of Bitfinex may borrow and lend (without any collateral) either FIAT or cryptocurrencies in exchange for an interest rate that is between 8.5% and 9.5% p.a., depending on the term (by the beginning of January). There are also collateralised, institutional solutions as offered by the open exchange platform Lendingblock. The company provides a platform for the instant matching of borrowers and lenders allowing them to exchange digital assets in the double-digit millions for 12% p.a. (also state of the beginning of January).

Figure 3: Risk-Return Relationship (DAE)
Source: Own Illustration

Then, there are the initial coin offerings (ICOs),[3] which played a crucial role during the last years. According to, funds in the amount of approximately USD 14bn were raised by ICOs in 2017 and 2018. On average, this new funding approach has a by far larger variance than lending and borrowing – at least according to our most recent experiences. With the implementation of security token offerings (STOs), a more defined investment vehicle within the digital ecosystem should follow. We are therefore including them in the overview of the digital asset ecosystem.

From a risk-return perspective, the concept of a STO can be compared with a (regulated) IPO in the traditional financial world. In general, we would classify a STO between the uncollateralised lending and investing in ICOs within the ecosystem, measured by the expected risk and return. However, this is just an assumption that needs to be validated, as there is no representative data available.

But can the LNRR really be considered risk-free?

Doing an investment and receiving a positive return is commonly associated with risks. In wake of the financial crisis in 2008, particularly the counterparty risk (of derivatives) played a significant role. As a short reminder, counterparty risk describes the risk to each party of a contract that the counterparty will not live up to its contractual obligations.

In the report “Getting to grips with counterparty risk”, the consulting firm McKinsey created an overview of risks that might arise by doing an investment, matching the general risk categories of an investment with the corresponding capital market products offered. The matching has the advantage that not only the risks of a specific investment vehicle but also the deal type will be considered, i.e. how the product is traded (exchange traded, OTC, etc.). Depending on the trade type, risks may vary.

However, for our purposes, we adapted the initial overview, which exhibits the following four general risks: credit, market, operational, and liquidity risk. In order to conduct a proper analysis of the term “risk-free”, and why Lightning does not bear the common risks of a financial product, we applied these categories and compared an uncollateralised debt product (e.g. a traditional government bond with ten years to maturity), a collateralised debt product (e.g. a mortgage) and an investment in the Lightning Network. This enables us to compare traditional investment vehicles that are likely considered to be risk-free with the LNRR by applying the framework proposed by McKinsey (see Fig. 4).

The most discussed threat in regards to the risk-return relationship is the credit risk that could be sub-classified within the issuer and counterparty risk. In terms of a government bond (uncollateralised debt), there is every credit risk associated, since the bond is issued by a bank, and, moreover, a counterparty is involved – in this specific case a state. The situation is quite similar for a mortgage (collateralised debt), however, the debt is at least secured if the counterparty defaults. Additionally, both investments bear a settlement risk.

Figure 4: Risk Evaluation of Different Investment Vehicles – What is really “risk-free”? Source: Own Illustration according to McKinsey (2010, p.2)

Funds, which are locked in the Lightning Network, are not faced with any credit risk in general because the network is “using the Bitcoin scripting op-codes to enable the transfer of funds without risk of counterparty theft, especially with long-term miner risk mitigations.” This means that no counterparty could default or any issues might arise in relation with the settlement process.

However, market and operational risks are still included in all investment vehicles:

– Uncollateralised debt, e.g. government bond (state default, operational failure possible)

– Collateralised debt, e.g. mortgage (depreciation of collateral, operational failure possible)

– LNRR (flash crash risk and protocol risk, operational failure possible)

In terms of the liquidity risk, a government bond would definitely be the most liquid choice – especially in comparison to a mortgage. By comparing the LNRR, we have a kind of liquidity risk due to the timelock of the smart contract (generally, we are talking about 144 blocks being equal to one day). According to the original Lightning Whitepaper by Dryja and Poon, “it is [therefore] preferable to use a small payment per HTLC” since “if the payment does not reach its destination and one of the participants along the path is uncooperative, it is possible that the sender must wait until the expiry before receiving a refund.” Otherwise, this can be also seen as “the time-value of fees pays for consuming time (e.g. 3 days) and is conceptually equivalent to a gold lease rate without custodial risk; it is the time-value for using up the access to money for a very short duration.”

However, in every respect we could determine that the term risk-free is definitely misleading. Even the investment vehicles that in traditional terms are recognised as risk-free, bear several risks. The Lightning Network, controversially, and the resulting LNRR is associated with less risks if the necessary knowledge is available to deal with the operational risks. Nevertheless, it is surely not wrong to consider the LNRR as risk-free if your unit of account is Bitcoin.

Current Pricing of Bitcoin Futures

There are two types of Bitcoin Futures offered by several exchanges: futures contracts and perpetual swaps. In both cases, we traditionally have a currency’s base rate for its price determination. As there is no base rate in the cryptocurrency market, there is also no yield curve or any kind of interest rate for Bitcoin. However, if you take a closer look on the pricing of Bitcoin Futures, you could observe that an interest rate is applied. Because perpetual swaps are mainly spot driven contracts (the price cannot really deviate from the spot price as the derivatives market is outperforming the cash market), this analysis will focus on the futures contracts.

According to the CME Group, a futures contract needs to be “distinct from a forward contract in two important ways: first, a futures contract is a legally binding agreement to buy or sell a standardised asset on a specific date or during a specific month. Second, this transaction is facilitated through a futures exchange. The exchange also guarantees that the contract will be honoured, eliminating counterparty risk. Every exchange-traded futures contract is centrally cleared. This means that when a futures contract is bought or sold, the exchange becomes the buyer to every seller and the seller to every buyer. This greatly reduces the credit risk associated with the default of a single buyer or seller. The exchange thereby eliminates counterparty risk and, unlike a forward contract market, provides anonymity to futures market participants.”

However, the guarantee is only offered by regulated exchanges such as Cboe or CME. Even though Bitmex uses the so-called auto deleveraging, social losses are theoretical possible. The same applies to Deribit. To sum up, there is no guarantee that the counterparty risk is eliminated.

Figure 5: Futures Contracts on Bitcoin with various Maturities, dated on January 10, 2019

The overview (Fig. 5) on the previous page shows the futures contract prices from five exchange platforms offering Bitcoin Futures with various maturities, dated on January 10, 2019. Just as a reminder: whereas the more regulated exchanges, CME and Cboe, are solely offering services for institutional investors, the platforms Deribit, CF, and Bitmex also offer futures for retail investors. Moreover, LedgerX provides options that will be not subject to our analysis.

On first glance, it becomes obvious that the futures prices decline with the contract length. The moment we took this snapshot, the Bitcoin spot price was around USD 4,019. A futures contract that expires around 170 days later (June 25, 2019) was traded at around USD 3,915. Therefore, we made our first hypothesis: the implied interest rate curve or forward curve of Bitcoin, respectively, should be in backwardation.

Taking a further look at the futures prices around four weeks later, dated on February 11, 2019, another image is reflected. Although prices decline, one might recognise quickly that they do not decline as strongly as four weeks prior. Depending on the exchange, the term futures are almost flat (c.f. Fig. 6).

Figure 6: Futures Contracts on Bitcoin with various Maturities, dated on February 11, 2019

In order to get a better overview of how prices developed during this time please find attached a snapshot, extracted from Tradingview. Here you can see how the Bitcoin price developed (red) and how the XBT March 2019 futures price moved during these four weeks (see Fig.7). You can see a real shift concerning the relation between the spot and the futures price: the gap between the spot price and the March futures prices became even smaller; for a short time, the futures contract was actually trading higher than the spot. The blue line reflects this relationship more precisely, and the difference is expressed in USD (secondary y-axis).

Figure 7: Bitcoin Price Development from January 10, 2019 – February 11, 2019
Source: Tradingview

It is for this reason that our second hypothesis is that the implied interest rates also decreased.

Calculation of Implied Interest Rates

In order to support that hypothesis, we calculated the funding rates or the implied interest rates, respectively, for the several contract lengths – and for both dates we took the data. For the calculation, the following future price formula was employed:

FBTC, the futures contract’s price with time to maturity ( ) and as  the corresponding Bitcoin spot rate were extracted from the platform’s homepage on January 10, 2019. For  the USD Libor rate with the corresponding (and adapted[4]) time to maturity was used. An overview of the results can be found in Fig. 8.

This data shows that the implied interest rates vary between 3.6% and 3.9% for the futures contracts expiring the next month, and between 5.4% and 5.6% for the contracts expiring in a half year. This equals a yield of around 9.5% – 14%, if there would be a futures product available with a term period of one year[5]. A visualisation of the corresponding implied interest rate curves from January 10, 2019 can be also found in Fig. 8. Moreover, the USD Libor curve was inserted for comparison purposes.


Figure 8: Implied Interest Rates (January 10, 2019)

Please take now a second look on Fig. 9 below that shows the implied interest rate from February 11, 2019.

Figure 9: Implied Interest Rates (February 11, 2019)

The numbers show that the implied rates decrease around 2.4% and 2.7% for the futures contract expiring the next month, and between 3.4% and 3.8% for the contract with a period of a half year. This equals a yield of around 4.8% – 6.2% if there would be a futures product available with a term period of one year [6]. To sum up, the yields of the futures dropped around 5% p.a. within these four weeks, resulting in an interest rate curve that is considerably flatter than the one by the beginning of January.

If we compare these rates with borrowing and lending rates offered in the cryptocurrency space, we see a strong correlation. However, the unknown component is still the skew in this context. Nevertheless, it seems that these rates are mainly driven by supply and demand as there is no reference rate available. This should definitely not mean that futures in traditional markets are not driven by supply and demand, however, not in this scope.

Moreover, our sanity check verified that there was no arbitrage opportunity, at least not by the beginning of January, if:

1. Someone borrows money at a 2.5% p.a. interest rate and goes long on BTCs;

2. Or borrows the BTCs for 10%, and,

3. Simultaneously shorts BTC Futures (with an implied rate of approx. 12.5% p.a.)

Figure 10: Arbitrage Triangle

In conclusion, the assumption might be made that borrowing and lending rates are employed for the pricing of Bitcoin derivatives. By taking into consideration the borrowing and lending rates of February 11, this assumption could be strengthened. Nevertheless, we will conduct a more detailed quantitative analysis to finally verify this observations in a subsequent report, which will be based on the historic data available.

The Impact of the LNRR on Bitcoin’s Derivative Pricing

There is not so much transparency available in the recent pricing of Bitcoin Futures. Within a few weeks, the prices of Bitcoin Futures and the corresponding implied interest rates could change considerably. Accordingly, the prices of the traded futures become affected in the opposite direction. Nevertheless, the analysis has revealed that there might be a strong correlation between the borrowing and lending rates and the implied interest rates employed in Bitcoin’s derivative pricing.

By taking into account that the base rate of a currency also does not change as quickly as the implied rates employed in the recent pricing of Bitcoin Futures, we considered to introduce a potential base rate for Bitcoin: the LNRR. Therefore, here is another short thought experiment: What would happen if the LNRR could be used for Bitcoin’s derivative pricing?

In order to evaluate the potential impact of the LNRR on Bitcoin’s derivative pricing, we need to begin by making a few assumptions:

– It is possible to receive a LNRR of 0.4% p.a. with a rising trend, a second estimation is already around 1.5% p.a. (probably these are the most impressive rates that you can currently find and earn with the Lightning Network. However, there is definitely the possibility of earning interest for providing the liquidity)

– The LNRR is considered a risk-free rate for Bitcoin as concluded in the previous section

– Bitcoin is considered as a commodity

Firstly, the LNRR is lower than the LIBOR, the collateralised and the uncollateralised lending rates of BTCs. Taking into account that the LNRR could be considered risk-free, these numbers make sense from a risk-return perspective.

Secondly, we have determined that recently the futures are not priced on a base rate, but instead mainly driven by demand and supply through the mechanism of the trading platforms – to be validated in our upcoming report. This will definitely not change in the near future, which in turn is also due to the fact that there is still the option to leverage the future positions. However, with more trading volume and liquidity in the Lightning Network, the LNRR might become more attractive and, therefore, a specific yield curve for Bitcoin might be established. This should not lead to the situation where there is only one correct yield (measured by LNRR). However, it might help establish a kind of yield curve basis for Bitcoin. Keep in mind that in traditional markets, we also have various yield curves.

Thirdly, the LNRR as a kind of base rate could establish more transparency in the entire derivatives market and the associated pricing. Through the establishment of a further “yield curve” that can be used for comparative purposes, the resulting pricing would become more fundamental and reasonable. In the long term, the market might therefore become more efficient. Moreover, a new business model for OTC desks and brokers could emerge – risk-free lending of Bitcoin in exchange for the LNRR, a “Lightning Bank”?

Limitations of Employing the LNRR

Even though we have seen a considerable increase in the number of Lightning nodes, the number of payment channels, and the network’s capacity during the last months, one has to keep in mind that we are still in the early development stage. This means that the price-finding process for routing fees is not yet completed. Additionally, there are several open issues in wake of the centralisation of the network, liquidity balances, state of available routes, and live nodes.

The initial Lightning paper also addresses the following risk factors that might arise in the context of Lightning:

– Improper Timelocks

– Forced Expiration Spam

– Coin Theft via Cracking

– Data Loss

– Forgetting to Broadcast the Transaction in Time

– Colluding Miner Attacks

The person or company providing the node, however, might mitigate most of these risks. Therefore, we would classify almost all of them as “operational” risks – with the exception of miner collusion. After talking to our systems engineering, we estimate an annual fix costs of approximately CHF 320 for running one Lightning node including a bitcoind Full Node in an appropriate manner. On top of that, monitoring costs of around CHF 5,000 should be considered (rough estimation), but might be spread over the amount of active nodes; the more nodes are run the less monitoring costs. In any case, channel monitoring is inevitable.

Considering these costs, it is not surprising that Lightning nodes are currently mainly provided because of experimental and ideological reasons.


After dealing with some analogies between traditional financial markets and the digital ecosystem, the analysis has shown that the LNRR could be considered justifiably as risk-free. The current pricing exhibits that there is an implied interest rate used which has a strong correlation with the borrowing and lending rates. Since the rates could increase or decrease in a relative short timeframe, the hypothesis was made that the rates and therefore the futures prices are mainly driven by supply and demand. This will be tested in a more quantitative analysis based on historical data in a subsequent report.

In terms of using the LNRR as a base rate for Bitcoin, we were able to demonstrate that the usage of the LNRR would make sense from a risk-return perspective. In addition to that, more transparency concerning the pricing of Bitcoin derivatives could be established and the market efficiency might be increased.

Nevertheless, it is highly important to note that this thought experiment was conducted under several assumptions. As long as the Lightning Network is still in its early development stage, meaning that the network is not yet stable, the exhibited LNRRs are definitely not really representative and thus unusable for definitive pricing.

Download The Lightning Reference Rate (LNRR) & Bitcoins Derivative Pricing Research Report PDF


[1] In our last research paper about Bitcoin’s Lightning Network, we discussed the basics of the Lightning Network and the related emergence of innovative business models. We described the establishing of a peer-to-peer based, risk-free interest rate for a single-asset Lightning Network and proposed the opportunity to earn money by routing lightning payments.

[2] EONIA is the effective overnight reference rate for the euro, computed as a weighted average of all overnight-unsecured lending transactions in the interbank market from a panel of 28 banks. The OIS for the USD is similarly determined.

[3] For more information concerning ICOs, please take a closer look on our latest research report “ERC20 Token Swaps – the Redemption”.

[4] Using the term structure from 7 to 180 days, sourced by Bloomberg, and adapted for the corresponding time frame.

[5] Calculated by using the extrapolation method based on the average confidence interval of 95%

[6] Calculated by using the extrapolation method based on the average confidence interval of 95%

Bitcoin’s Lightning Network & Innovative Business Models

Disruptive Technologies Drive the Emergence of Innovative Business Models:
a Peer
to-Peer Based Interest Rate and Savings Account Without Counterparty Risk

As blockchain technology matures, the market becomes more professional and measures are taken to eliminate its weaknesses. Bitcoin, as the most famous cryptocurrency, is often criticised for its scalability problem, i.e. the fact that only a limited amount of transactions can be done per second. A traditional payment solution provider such as VISA is able to process up to 56,000 transactions per second (around 2,000 on average), whereas bitcoin is only able to process between three to around ten transactions per second (depending on transaction type).

It is well known that necessity is the mother of invention. Consequently, an idea emerged where transactions are conducted off-chain but retain the security standard of on-chain transactions. This is the Bitcoin Lightning Network. This second layer protocol, run on the bitcoin blockchain, enables fast transactions through a network of bidirectional payment channels. The network makes it possible to process millions of transactions per second (using bitcoin as a payment method) via its second layer protocol called Lightning. Transaction settlement can be done instantly due to the off-chain architecture.

Does this mean that bitcoin will soon be usable as a currency?

Excepting the volatility risk, we would argue “Yes”. The Lightning Network offers incredible progress toward the use of bitcoin as a medium of (instant) exchange. However, this is not the subject of this article. Instead, we would like to focus on the interesting topic of the time value of bitcoin and the Lightning Network Reference Rate (LNRR), introduced by Nik Bhatia, and the idea of establishing a savings account without any counterparty risk and peer-to-peer based interest rate.

We will start by giving you a general overview of the Lightning Network, its payment channel structure, and the concept of routing. After that, we will go into more depth about these two business models and address the associated limitations. Lastly, we will then take things one step further in our next research report. Since the possibility of determining a risk-free interest rate of bitcoin would affect the price determination of bitcoin derivatives, we will analyse the resulting differences concerning the recent (and the potential future pricing) of bitcoin derivatives considering the Lightning Network Rate (LNNR).

About the Lightning Network and its Payment Channels Structure

As already mentioned, bitcoin is often criticised for its scalability problem. The root cause for this is also one of its highly appreciated core characteristics – the recording of every transaction on bitcoin’s main chain. Joseph Poon and Thaddeus Dryja proposed a solution with the implementation of the Lightning Network in early 2016, summarised in their whitepaper “The Bitcoin Lightning Network: Scalable Off-Chain Instant Payments”.

The Lightning Network is based on a second layer protocol run by the bitcoin blockchain. The three companies Blockstream, Acinq, and Lightning Lab are involved to the extent that they develop and provide the lightning protocol and the associated ecosystem, e.g. with c-lightning, eClair, and lnd. In order to solve the scalability problem, transactions are processed off-chain instead of on-chain, meaning that transactions can be conducted without actually transferring the custody of funds. This can be achieved by using an interchannel rebalancing mechanism, which makes the processing of several thousands of transactions per second possible in an instant and nearly commission free.

In Fig. 1 below, you will see an illustration of the relation between bitcoin and the second layer protocol Lightning.

Figure 1: Relation between bitcoin’s main chain and the Lightning Network

From Fig. 1, it can be derived that the Lightning Network is on the one hand independent of bitcoin’s blockchain, but, on the other hand, it is still interacting with bitcoin’s main chain. At any time when a payment channel is opened or closed, communication with the main chain will occur. The Lightning Network itself consists of nodes. If payment channels are opened properly, these nodes process and are able to route lightning transactions. The connection between two nodes is called a payment channel, or to be more specific, a bidirectional payment channel with a hashed timelock contract.

As soon as two parties have funded a payment channel, the funds become locked via a multi-sig contract between the corresponding parties. From an application-oriented perspective, this can be compared with the storing of funds within a safe “off-chain”. Every channel is limited to its funding amount, meaning that transactions routed by a channel can only be processed up to the initial funding amount (more details on this below in “The Concept of Routing”). Additionally, multi-sig implies that the safe can only be opened if both parties sign a transaction. As long as the funds remain in this safe, they can be transferred instantly between the corresponding participants. After any transaction, the two parties then update the recent state amongst themselves like an ever-shifting balance sheet. This is somewhat akin to the decentralised concept of real time gross settlement (RTGS) and CLS (continuous linked settlement) found in traditional banking with the significant difference of being trustless.

When one party submits the state back to the blockchain, the payment channel will be closed and the latest transaction balance will be broadcasted to the blockchain – but potentially, the timelock will need to be expired. Finally, the funds are available again on bitcoin’s main chain. Since there is no possibility of receiving and sending more money than initially funded and locked, the entire concept results in a zero-sum game.

The participation in or the usage of the Lightning Network is possible by either running a full lightning node (internal node) or by using a lightweight wallet (SPV) software application to send transactions (external node or leaf). The terms internal and external nodes stem from data structure theory. Whereby an internal node describes a node with at least one child, a leaf is characterised by no children. Currently, the receiving of transactions is only possible by running an internal node; however, an increasing interest in Lightning has fostered several initiatives to develop a lightweight wallet, which will allow for the participation in Lightning without the need for a full node.

In the wake of the Lightning Network, both node forms differ also in transaction liquidity: whereby the usage of a leaf is limited to the conducting of transactions (restricted using of the liquidity), an internal node may function as a routing provider (liquidity provider). Due to the nature of our research, this report focuses on the running of a full lightning node (internal node), and the possibility of earning an interest rate for providing funds to the network.

The Concept of Routing

Apart from the payment channel structure, the Lightning Network is characterised by its routing systematic. In order to send transactions through the entire network and not only to any direct peer using already established payment channels, nodes with enough liquidity into the right “funding direction” might act as a kind of bridge. These nodes are referred to as “routing-nodes”.

Let me explain this functionality with an example: Cornelius would like to make a Lightning transaction with Florence to settle his debts resulting from yesterday’s dinner. Unfortunately, the two friends have not yet opened a direct payment channel between them. They then realise that they have an “indirect” channel via Daisy and Eric. And since there already is a payment channel between Cornelius and Daisy, who also has a channel with Eric, who in turn has a Lightning channel with Florence, an indirect payment channel is found. In Fig. 2 below, you can see an overview of this rather complicated constellation.

Figure 2: Concept of Routing: Initial Positions

Apart from the fact that there is a payment channel connection in general, there is no information as to “how” the single channels are currently being funded. The channel funding and the associated channel allocation has a significant impact on the routing capability and the resulting possibility of forwarding the transaction. In order to give an overview of some extrema, please take a second glance at Fig. 2 above and the three different initial positions exhibited.

A payment channel can be compared with slide control. Aviv Zohar, Associate Professor at the School of Engineering and Computer Science at The Hebrew University and The Chief Scientist at QED-it, states that “you can think of it as if we are in a state space between 0 and 10. If we are just transacting in single units of bitcoin, we are just moving around there”. Therefore, we tried to integrate the “funding direction” in the overview. So, let us explain this statement more in depth and let us assume the following channel allocations (c.f. Fig. 2):

Channel Allocation 1:
– Cornelius fully funded a channel with Daisy in the amount of 200 satoshis
– Daisy fully funded a channel with Eric in the amount of 50 satoshis
– Eric fully funded a channel with Florence in the amount of 100 satoshis

Channel Allocation 2:
– Cornelius partially funded a channel with Daisy, both in the amount of 100 satoshis
– Daisy partially funded a channel with Eric, both in the amount of 25 satoshis
– Eric partially funded a channel with Florence, both in the amount of 50 satoshis

Channel Allocation 3:
– Daisy fully funded a channel with Cornelius in the amount of 200 satoshis
– Eric fully funded a channel with Daisy in the amount of 50 satoshis
– Florence fully funded a channel with Eric in the amount of 100 satoshis

As already mentioned, if there is an indirect payment channel from Cornelius to Florence, he has the possibility to transfer his funds using the concept of routing. Moreover, he does not face the necessity to open (and thus fund) a new, direct payment channel because, in general, the opening of the payment channel is associated with a transaction fee because of the associated on-chain transaction. Coming back to the channel allocation opportunities, we can derive two extrema: one-sided, fully funded payment channels (c.f. Channel Allocation 1 and 3), and perfect equally funded channels, as can be seen in Channel Allocation 2. In practice, every slide control position is possible.

Depending on the current state of these routing channels and the corresponding slide control position, the following transactions (maximum gross channel amount) between them are possible:

Figure 3: Concept of Routing – Case Scenario: maximum transaction amount

At first glance, one might quickly recognise that in the case of Channel Allocation 3 exhibited in Fig. 3, no transaction from Cornelius to Florence is possible. Since the channels are funded “in the wrong direction”, only transactions from Florence to Cornelius could be routed. The same situation can be actually observed in Channel Allocation 1, but with the significant difference that a transaction is possible due to the “perfect” funding allocation for this transaction – but let us play this routing game step by step:

1. Cornelius might transfer up to 200 satoshis
2. BUT Daisy ONLY has a routing capacity of up to 50 satoshis
3. Finally, Eric would be able to forward 100 satoshis

Therefore, we can draw the conclusion that a routing path cannot forward more than the smallest channel capacity within the corresponding path. In this case, no more than 50 satoshis can be transferred. Other paths through the network might be able to route larger payments between Cornelius and Florence.

By considering Channel Allocation 2, one might observe the same issue with the difference that the situation is even worse. Due to the payment channel equivalence between Daisy and Eric, she is now only able to forward 25 satoshis.

To sum up, not only the funding amount of a payment channel, but also the channel allocation has a considerable influence on a node’s routing abilities.

We have neglected to mention the previously described “routing fees” so far. In exchange for routing the payments, the payment sender, who is in this case Cornelius, must pay a fee to the routing nodes. For the net calculation of our dinner scenario, please take a closer look at Fig. 4 below.

Figure 4: Concept of Routing – Case Scenario: maximum transaction amount, incl. routing fees

It is necessary to clarify that every node provider has the opportunity to determine its own routing fees within its node settings. These fees are composed of a base fee rate and a proportional fee rate (to the transaction amount). In our case scenario in Fig. 4 above, we used a base fee of 1000msat (= 1 satoshi) and a proportional fee rate of 100ppm (parts per million) = 0.01%, meaning that the sender must pay 100 satoshis for every 1,000,000 satoshis transferred. Even though a dinner between 50 or 200 satoshis is not feasible, these are realistic fee rates, which have been recently applied in the Lightning Network.

As soon as we take into account that Daisy and Eric charge the fees mentioned above, the maximum transaction amount of the corresponding channel decreases by one satoshi due to the smallest channel capacity of 50 satoshis between Eric and Daisy. Even if Cornelius transfers 52 satoshis, the remaining two satoshis would be stuck in the channel with Daisy.

The Lightning Network Rate (LNNR) – a Peerto-Peer based Interest Rate for Bitcoin

After having now described how the Lightning Network works, the one or other reader might already have an idea of the possibility concerning the “technological” determination of interest rates. Nevertheless, most readers will ask themselves how an interest rate might be determined if every node provider could set its own fee rates. To be honest, that makes no sense, does it?

The answer is a peer-to-peer based interest rate. One property of the Lightning Network is the “free choice” of the transaction path. Nevertheless, every default setting of a Lightning application generally selects the cheapest path due to the routing algorithm employed. This seems quite reasonable from an economical point of view due to the general rule that a market chases efficiency. Therefore, the channels, which are not in line with the fees of the great majority, will never be actively used.

The routing algorithm employed also considers influencing factors, e.g. the payment channel volume, the possible connections, but also (as previously mentioned), the associated transaction fees. In order to analyse which transaction paths are possible, the Light Pathfinder tool, provided by, could be used (see Fig. 5). Such tools rely on public information of the network, where the current allocation of funds in a channel is private information between the two involved parties. While qualitatively accurate, the precise numbers might be off.

Figure 5: Visualisation of Transaction Paths

Using this example, we tried to conduct a transaction from our Crypto Finance Research Node (“CRAG”), in Fig. 6, called “Source”, to a BitMEX Research Node called “Destination”. As you can see, there are several routing paths available for this transaction. The paths differ in transaction fees and the number of nodes involved. In this particular case, there is either the possibility to route via one node to four nodes.

According to the whitepaper by Poon and Dryja, the general rule states “smaller transfers with more intermediaries imply a higher percentage paid as Lightning Network fees to the intermediaries.” In practise, however, every node has its own routing fee settings. Taking a second look at Fig. 5, you might recognise the corresponding channel fees exhibited by the arrows between the channels. The number in brackets below indicates the maximum routing amount for this corresponding channel. In our example, a maximum of 5 million satoshis (~ USD 177) could be transferred between CRAG and the BitMex Research Node for a fee of 1000 satoshis (~ USD 0.035). This equals a percentage fee of approximately 0.02%. An overview of the correlation between the transaction amount and the corresponding transaction fees for our sample transaction can be found in Fig. 6.

Figure 6: Transaction fees in proportion to the Transaction Amount

As you can see, the fee chart is shaped by terraces whereby each stagger represents a different transaction path. The different paths are marked in gold in the path visualisation above the terraces. Since the base fee is commonly one satoshi or 1000msat, respectively, the transaction fee is mainly due to the proportional fees of the different paths.

Using this example, one might recognise that transactions up to 1,700,000 satoshis are almost commission free. Suddenly, the first [second] terrace emerges implying that a different channel needs to be used for a transaction in the amount between 1,700,000 [3,000,000] satoshis to 3,000,000 [4,500,000] satoshis, whereby a higher proportional fee rate is applied. The maximum payment amount between these two nodes is limited to 5,000,001 satoshis. Generally, the maximum payment channel amount is limited to 16,777,215 satoshis, as defined by the current Lightning protocol restrictions. Additionally, the chart supports the described proportional relation between transaction amount and transaction fee.

Especially from an economical point of view, questions might be raised concerning the incentives of providing a Lightning node. In recent times, routing fees that might be earned by providing a node have varied significantly. Nik Bhatia referred in one of his articles to a Twitter post made by Alex Bosworth sharing their node statistics (c.f. Fig. 7). The data reveals that Alex earns a 0.4% interest rate on his principal amount provided, which, in turn, is “material income” in recent times by taking into account the interest rates offered by banks. Controversially, Andreas made less even though he provided a larger principal amount. This might be due to his node settings and positioning. While technologically sound in itself, the infrastructure around lightning is very much still evolving. How should a node choose its peers to position itself well as a route, and, subsequently, receive relevant fees? When should a channel be closed based on the changed global situation and reposition? Fully automated approaches, so called autopilots, are very much underperforming human experience these days. Successful heuristics are proprietary information.

Figure 7: Node Statistics
Source: Medium Post by Nik Bhatia

In this context, we have to mention explicitly that these stats are not representative. However, they do hint toward the general possibility of earning an interest by providing liquidity to the Lightning Network. This approach allows investors to measure their opportunity cost of bitcoin. The larger the Lightning Network becomes, the more representative data will be available. Of late, the network is based neither on rationality nor on efficiency. There are several people acting as Lightning enthusiasts and thus providing liquidity for free, implying that they are running a node without any economic incentive.

Ben Woosley, a developer of the Lightning wallet app Zap, stated, „As the network grows and a smaller portion are using it for ideological reasons, fees will move toward a more economic outcome.“ Factors such as node positioning, the number of channels, and their funding amount might have a significant influence on the economic performance of a node.

From an economical perspective, the concept of routing fulfils two tasks akin to a centralised, traditional commercial bank and the central bank: providing liquidity and determining an interest rate. The difference is that the Lightning Network takes charge of this task in a decentralised manner. An interesting approach emerges to determine interest rates on a peer-to-peer basis and not the centralised determination by one or several central banks.

A Savings Account without Counterparty Risk

A savings account is an interest-bearing deposit account held at a bank or other financial institution that provides a modest interest rate. In every traditional, interest-bearing financial product offered, the involvement of a counterparty such as banks, insurances, or other third-party companies is required. Even with the so-called risk-free treasuries, a counterparty risk is associated in form of state bankruptcy.

Besides the fact that Lightning offers a risk-free interest rate for providing liquidity in form of bitcoins to the Lightning Network, a further interesting property arises: there is no counterparty involved. In this context, Poon and Dryja compare the concept “to a gold lease rate without custodial risk”.

Counterparty risk is the risk to each party of contract that the counterparty will not live up to its contractual obligations. In Lightning, the funds are locked via a multi-sig contract due to hashed timelock contracts (HTLCs). When this timelock is due, the latest balance will be submitted. Therefore, the contract is enforced either when counterparties cooperatively close the payment channel or when the timelock is due. Thus, the counterparty risk is replaced by a protocol risk due to issues associated with the cryptographic pegging.

Starting from the Bottom, now we have around 13,000 Channels

The Lightning Network was launched in mid-January 2018. On December 10, there were around 4,000 nodes. Its current network capacity contains around 160BTCs in the amount of USD 1,700,000. According to Jonas Schnelli, one of bitcoin’s main developers, “channel amounts will slowly increase as confidence rises.” A recent snapshot of the Lightning Network, meaning a visualisation of the 4,000 nodes and its 13,093 payment channels, can be found in Fig. 8 below.

Figure 8: Visualisation of the Lightning Network
Source: Recksplorer (10.12.18)

Therein, the single nodes are shown as labels by their “nicknames”. Some inter-esting examples are “SWIFT.connect”, ”***ROUTE 66***”, “VISA Killer” or “RebelDinosaur [LND]”. The colourful lines between them represent the opened payment channels. On closer inspection, one might also identify a structure as to how they are linked to each other, resulting in a kind of hub and spoke system. Some nodes have many payment channels and thus act like a hub. According to Poon and Dryja “eventually, with optimisations, the network will look a lot like the correspondent banking network, or Tier-1 ISPs.”

This assumption is supported by a recent network trend: since mid-November, the network capacity has increased by around 320%. This development is mainly due to a provider of the so-called “ [lnd-xx]” nodes whereby “xx” represents a placeholder ranging from 01 to 42. In short, an unknown party provides at least 20 nodes with channel capacities ranging from 15BTCs to 26.7BTCs (~ USD 53,204 – USD 94,655 on December 10, 2018), with an ongoing upward trend in evidence. Unfortunately, we cannot make any specific statements about their transaction and routing volume, since the information is private.

Limitations of the Lightning Network

Although the concept of Lightning proposes a considerable approach concerning the scalability problem and other bottlenecks associated with bitcoin, the second layer protocol still has some limitations.

The major issues are due to the early development state of the network and the surrounding ecosystem. Since full participation (sending and receiving of transactions) is only possibly by running an internal node, access is more or less restricted to people having the necessary expertise to set up and run a node. This leads to a limited number of participants and liquidity within the network.

Additionally, the Lightning Network can easily be dominated in the current state, c.f. the entrance of LNBIG. Thus, the decentralised establishment of an interest rate is not possible and the network might be easily centralised. Moreover, the routing systematic is not completely matured. In consideration of Lightning’s upper limit on channel funding amounts, larger payments are most likely to fail since they cannot be successfully routed. This leads to the fact that Lighting is currently (only) suitable for smaller transactions.

However, optimisation measures have already been taken with the implementation of the so-called multi-path routing for payments. This mechanism allows the splitting up of a payment in multiple partial payments, which will be routed by all channels available that together make up the total amount. Therefore, it becomes possible to overcome limitations of a single funding channel amount.

In conclusion, we can state that Lightning represents an effective approach to solving the scalability problem of bitcoin. Furthermore, some interesting business models have emerged in this context. When the network grows, it becomes more stable, and thus a representative LNNR might be established, which influences the derivatives pricing of crypto assets. In our next research report, we will be conducting a thought experiment, where we analyse how this interest rate could influence the pricing of bitcoin futures.

Download Lightning Research Paper as PDF

Bart Simpson Pattern – Inefficiencies in Crypto Trading

How has Bart Simpson managed to weasel his way into cryptocurrency analysis? What possibly could the connection between cryptocurrency pricing and a fictional yellow character from the American TV series The Simpsons be? Talking with the trading experts at Crypto Broker AG, who analyse bitcoin charts, and with our further research in the area of trading patterns and trend analysis, we suggest a different significance behind this price chart pattern – all jokes aside.

Thanks to a little ingenuity and some inspiration from highly reliable, albeit satirical media sources, a recognisable chart pattern, known as the Bart Simpson Pattern, can be used to explain the recent inefficiencies in cryptocurrency trading.

So, what is happening?

The Bart Simpson Pattern occurs when an unexpected spike (or a drop) in prices is followed by a sideways movement, and subsequently by a sudden drop (or a spike) in prices. The chart pattern takes on the shape of Bart Simpson’s head.

Bart Simpson Pattern on Price Chart
Figure 1 – Bart Simpson Pattern on Price Chart

And why is it worth taking a closer look at the Bart Simpson chart pattern?

One enticing thought is that even though the cryptocurrency markets are becoming more professionalised, the possibility of price and market influences still exist. They manifest in the Bart Simpson Pattern. Inexperienced market participants are causing a great deal of these inefficiencies, which could easily be mitigated, e.g. by the use of appropriate brokerage services.

Allow me to explain by going more in depth.

The Bitfinex chart above (Fig.1) shows a BTC/USD price development. Several common market fluctuations are visible without any apparent abnormalities. Generally, a massive green (or red) candle will introduce the typical (or inverse) Bart Simpson Pattern. Upon closer inspection, at least two Bart Simpson Patterns can be made out in Fig.1: an inverse Bart starts on September 8th, with the end of the formation already beginning to form the second Bart Pattern. Images of Bart Simpson’s head have been inserted into the corresponding periods.

Ever since the beginning of 2018, both the variety and frequency of Bart Patterns have increased. When asked about price patterns in general, American financial market analyst John J. Murphy explained: “Price patterns are pictures or formations, which appear on price charts of stocks or commodities, that can be classified into different categories, and that have a predictive value”.

Despite the fact that cryptocurrencies and crypto assets came after his time, it also goes without saying that this research paper in no way constitutes financial investment advice nor will it offer any predictive value.

Returning now to Murphy’s definition, research has shown that the Bart Pattern may vary in its volatility, duration, and frequency. The formation usually occurs over a period of a few hours, apparent on intraday charts with a scale of 15-minute intervals. In Fig.2, which shows a close-up of the same two patterns depicted in Fig.1, the inverse Bart Pattern is visible in the significant increase in trading volume and significant decrease in price. In total, the price drops here for a period of approximately two hours. Subsequently, there is a kind of consolidation phase characterised by prices moving very little over a 15 hour period (the so-called accumulation area), after which an unexpected price increase takes place. The typical Bart Pattern that follows after that could be described in the reverse.

Zoom-In Bart Simpson Pattern
Figure 2: Zoom-In Bart Simpson Pattern [1]
As shown in Fig.2, a price cycle will generally contain the following phases: accumulation, markup, distribution, and markdown. However, a common price cycle is not characterised by an extremely steep markup and markdown curve as seen in a Bart Pattern. Moreover, a complete price cycle may last for a few hours, days, or months. A theoretical price cycle according to renowned stock market authority Richard Wyckoff is depicted in Fig.3.

Wyckoff Price Cycle
Figure 3 – Wyckoff Price Cycle

Here, the accumulation area is characterised by a sideways movement with the price moving relatively slowly. This phase is also referred to as market consolidation. During the late stages of a bear market, in particular, many investors try to trade during the accumulation phase in order to catch the bottom of the trend. Nevertheless, it is also possible for the bears to win, and a further downward trend will follow. Once the resistance level of the accumulation phase is exceeded, the markup phase will then begin. In this context, new highs will be set, or in the case of the Bart Pattern, an exceptional new high will be set in a relatively short period of time. Usually, the markup will last longer than the accumulation phase. At this point, investors of all kinds are attracted to invest, in the hopes of making profits during the upward trend.

As soon as there is resistance and the market faces a correction or pullback, the distribution area will start. As in the accumulation phase, the bulls and bears will battle against the upcoming movement. This means that the distribution area does not necessarily allude to a price drop. If selling volumes increase regardless and buying volumes decrease, it is only a question of time before the resistance level is exceeded and the price will drop in the markdown phase until the next accumulation phase is reached.

Richard Wyckoff, who founded The Magazine of Wall Street, was a pioneer in technical stock market analysis. He based his trading strategy on three laws, with the intent of identifying the best markets to trade and the potential future directional bias for prices. According to his “Three Wyckoff Laws”, the price chart can be affected by:

– Supply and demand
– Trading volume and the corresponding price change
– Duration of accumulation and distribution period

Is There a Reason for a Bart Simpson Chart Pattern in Crypto Markets?

Research has shown that the conditions under which the Bart Simpson Pattern seems to appear is if price movements were not apparent before the formation started, although trade volumes increased. This assumption may be in line with one of Richard Wyckoff’s trading theory laws. Talking with the trading experts at Crypto Broker AG, analysing bitcoin charts, and conducting further research in the area of trading patterns and trend analysis, I concluded that the Bart Pattern is due mainly to liquidity issues.

To create an overview of the relationship between market liquidity and the corresponding price developments, I attempted an historical reappraisal of an inverse Bart Pattern (cf. Appendix A). It is possible to divide its development into the following six steps

1. Trade Initiation (Sell Order)

Firstly, a larger [2] selling (market) order needs to be issued to initiate a corresponding and considerable price movement. For instance, the bitcoin price may already have moved by 2% with a market order of 500 bitcoin on a smaller exchange. Due to the possibility of initiating a relatively large selling (market) order for bitcoin – for whatever reason – the market may be faced with a liquidity problem.

From an economical point of view, the market supply of bitcoin exceeds the current demand and consequently the supply has exerted downward pressure on the bitcoin price due to the surplus.

2. Trade Execution

If the market (S0) does not have enough supply or liquidity and one relatively large order is placed that cannot be easily satisfied by the corresponding exchange platform, the order books will be completely stripped out. When an exchange is faced with an oversized price shift, every single buy position below the current trading price will be accepted without any restrictions, particularly with a market order.

As a result, the trading price is pushed down instantly until the trade is fully executed (D1). The left side of an inverse Bart Pattern is now visible. When the bottom is reached, the market starts to consolidate and so the sideways movement begins.

3. Accumulation Phase

Now, we enter the accumulation phase. Here, the market has reached its new equilibrium, meaning that the open orders were satisfied and the market will consolidate until S1 = D0. There is now also a new price (P1).

4. Trade Initiation (Buy Order)

As soon as a larger buy order is issued, leading to a breach of a higher resistance level, the probability increases that the bitcoin whales[3] will re-enter the market. By using their relatively large trading volume – in this case to execute a long position – the whales’ direct impact is reflected in the chart in an unexpected spike; and the second part of Bart’s head begins to appear. However, there is no shift in supply, only an unusual shift in demand (D0 –>D1).

5. Trade Execution

Because of the resulting demand surplus, the price is pushed even higher because there are not sufficient bitcoins available for the price offered. Similar to the previous trade executions for sell orders, every single sell position above the current trading price will be accepted without restrictions. Thus, the trading price is pushed even higher until the trade is fully executed (D1).

6. Distribution Phase

Subsequently, the distribution phase starts. As described in the accumulation phase, the market has reached its new equilibrium. The difference now, however, is that the balance is found at S1 = D1 with the new price (P2).This price could even be the price P0 from the beginning of the Bart Pattern.

The description above would be the same for a (non-inverse) Bart Simpson Pattern if steps one through three were to be changed to four through six, and vice versa.

Market Liquidity plays an Integral Role in the Markets

As a general rule, if there is sufficient market liquidity, most goods and services can be traded without there being any unexpected impact on their prices. Conversely, this implies that a lack of market liquidity could affect the prices of the traded goods, as shown in the example of the (inverse) Bart Simpson Pattern.

Both the upward and the downward move could be caused by a lack of liquidity. For the downward move, the lack of liquidity stems from too large of a supply that cannot be absorbed by the market. For the upward move, the lack of liquidity can be due to an increase in demand that also cannot be met by the market.

In the bitcoin market, two parties could be bitcoin whales and therefore capable of entering a relatively large order. On the one hand, there are institutional investors with the financial means to take influence on the market. On the other hand, there are many retail (private) investors who have an unusually large amount of cryptocurrencies, e.g. due to early participation in the crypto markets. In either case, one of them may represent a whale and thus be able to initiate such a trading pattern from the buy or sell side.

What is the intent of such an order beyond it simply being large and inadvertently burning money?

There are two explanations: either this is a retail investor without the necessary trading knowledge to execute a smart and smooth trading order; or the trade has been submitted intentionally by someone with a professional background. Speaking rationally, however, a large market order is completely inefficient because of the resulting financial loss. Both situations are therefore unusual in liquid traditional markets.

There is no proof that liquidity problems are entirely responsible for any Bart Simpson Pattern. There are, of course, examples where a Bart-like downward move was followed by a second downward move, forming a stair rather than a Bart Pattern. Yet, the great majority of Bart Patterns may be caused, and moreover explained, by liquidity issues.

Do Bart Simpson Patterns Also Appear in Traditional Markets?  

Yes and no. Since the beginning of 2018, the cryptocurrency market has faced a downward slide. In January 2018, its market capitalisation exhibited an all-time peak at approximately USD 800 billion. Through the following months, a steady decline in the market capitalisation became apparent. On October 23, 2018, 54% of the market capitalisation of approximately USD 209 billion was attributed to bitcoin. This is comparable to the market capitalisation of a single larger listed company such as McDonalds, IBM, or SAP. In short, it is difficult to compare a traditional market to the cryptocurrency market currently – not only because of its market capitalisation, but due to the market participants and emerging regulation.

A market that enables its participants to initiate relatively large orders also provides the greater possibility of prices being influenced. In the case of bitcoin, retail investors can enter these orders in the absence of regulation (be that through brokers or on exchanges). Whales are not just a factor in the bitcoin market. They also dominate the equity market, but there they are more likely to be institutional whales in a regulated environment. Thresholds to entry and related infrastructure in cryptocurrency markets vary significantly when compared to traditional markets. The execution of trades are carried out in an appropriate and more rational manner in traditional markets. Also, in traditional markets, so-called circuit breakers and other security mechanisms are implemented, as is apparent in the S&P 500 Index. As soon as a market or a single stock drops a predefined percentage within a predefined timeframe, a circuit breaker temporarily stops all trading on that exchange.

Crypto Finance AG, through its subsidiary Crypto Broker AG, is a financial intermediary available to qualified and institutional investors. This team of experienced investment bank traders draws on the liquidity of the world’s top exchanges to offer optimised order execution, without affecting prices, thus avoiding Bart Simpson Patterns.

Download the Bart Simpson Trading Pattern Research Article as a PDF


[1] Figure 2 includes the price development charts of Coinbase (red) and Binance (orange). It clearly shows that not only one exchange is faced with a considerable price drop and spike.

[2] Measured relative to the common trading volume during the last 24 hours

[3] Bitcoin whales – holders of large amounts of bitcoin


ERC20 Token Swaps – the Redemption

ICOs, Mainnet Launches & Token Swaps – the Redemption of ERC20 Tokens

During the last year, an increasing amount of companies have launched an initial coin offering (“ICO”) to finance their business. The Swiss Financial Market Supervisory Authority (“FINMA”) states in their recently published ICO Guidelines that “in an ICO, investors transfer funds, usually in the form of cryptocurrencies, to the ICO organiser. In return they receive a quantity of blockchain-based coins or tokens which are created and stored in a decentralised form either on a blockchain specifically created for the ICO or through a smart contract on a pre-existing blockchain”. According to a research report by PwC Strategy&, more funding was raised with ICOs within the first five months of 2018 than the total of the previous five years before.

An ICO is usually structured so that the company issues their own tokens using smart contracts that are executed on an existing blockchain. The establishment of a propriety and stable blockchain usually requires a substantial amount of development work and the associated investment in software. Startups developing their own blockchain do not have the necessary financial means at their disposal in the early stages. As these companies cannot immediately develop a blockchain solution from scratch, instead they use an existing blockchain with the ability to host an ICO token. Blockchains that allow this functionality must have “the ability to create a second layer on top of their own native token”.

Ethereum is the most popular blockchain used to issue ICO tokens, using the “ERC20” common technical standard for Ethereum tokens. For companies aiming to build their own blockchain, the issued ERC20 tokens act as a placeholder for the future “native” tokes. From an economic point of view, an ERC20 token exhibits similar characteristics to a convertible note, if the prospective native token meets the requirements of an asset token according to its definition by the FINMA. Whereby in case of a convertible note the initial loans will be converted to equity at a specific milestone, the ERC20 tokens are converted to native tokens at a specific milestone. There is also the option to use a Simple Agreement for Future Tokens (“SAFT”) in order to raise funding – as in the case of the Telegram ICO.

ERC20 Token Standard & Mainnet Launch

The term ERC20 describes a technical de-facto token standard for an Ethereum smart contract. ERC is the abbreviation for “Ethereum Request for Comment” which determines the necessary requirements for tokens to follow within the Ethereum ecosystem. The core ERC20 functions include:

– transfer(to, value)
– balanceOf(owner)
– approve(sender, value)
– allowance(owner, spender)
– transferFrom(from, to, value)
– totalSupply( )

Based on these commands, an ERC20 token is queried and modified. These commands and rules have to be met for a token to be accepted and to ensure that the tokens can interact with each other and the surrounding infrastructure on the Ethereum blockchain. Besides this “placeholder” function, this kind of token can be also used as a currency for dApps. Moreover, the smart contract may define additional features that hint towards the purpose of a token, for instance, the usage as a payment, utility or asset token.

By using an ERC20 token as a placeholder, issued on the Ethereum blockchain, their target purpose functionality might be limited. Once the final blockchain solution is developed, tested and successfully verified, the next step is the launch of this new, self-sufficient blockchain – the mainnet launch.

The mainnet, i.e. the new blockchain, may differ in basic characteristics such as the underlying security algorithm, cryptography, level of decentralization, level of efficiency, identity obfuscation strategy, network topology, block production policy, permissibility, scope of participants and grandeur of the vision. Many of these properties are highly related. The ERC20 tokens issued during the ICO might not be compatible with the new blockchain and its corresponding features and adaptions. Therefore, they need to be migrated onto the new blockchain. Normally, a project sets a date, or a time period, when the “old” tokens have to be swapped, otherwise they become frozen and thus unusable.

Past projects have approached this in several ways but commonly all ERC20 tokens that were not transferred from the Ethereum blockchain became frozen and thus useless at a pre-determined date. The tokens from the Ethereum blockchain must be moved to the new blockchain. This process is known as coin swap or token swaps. The most recent and best known token swaps were EOS (EOS), Tron (TRX) and VeChain (VEN). Figure 1 below shows a short overview of the most relevant ERC20 token swaps:

Figure 1: Overview of (upcoming) Token Swaps

Given the technical properties of cryptography and the underlying blockchain, the process of substituting two digital assets is not as complicated as it seems at first glance. To explain the whole process more understandably, we summarized two recent token swaps below.

Which are the necessary steps? Exhibited by the example of TRX & VEN

Tron (TRX)

The Tron ERC20 tokens had to be swapped into TRON20 standard tokens (the native coins for the Tron mainnet). All Tron tokens traded at this time were exchanged at a 1:1 ratio.

Figure 2: Visualization of the TRX token swap

To conduct the token swap, the token holders had to deposit their token on an exchange platform that supported the swap – there was no other way to swap these tokens. Around 60 exchanges supported the swap such as Bitfinex, Bittrex and Huobi. According to the official instructions published by the Tron foundation, the ERC20 Tron tokens had to be deposited onto the participating exchanges before June 24th 2018 to ensure a successful migration. Alternatively, the exchange platform Binance, have been offering an ongoing coin swap until the end of December 2018. The mainnet was already launched on May 31th 2018 using a “delegated Proof-of-Stake (POS) consensus algorithm and relies on 27 block validators – dubbed super representatives (SR) – to produce the blocks and verify transactions” – only a side remark for the more technical readers.

VeChain (VEN)

VeChain published a specific guide for their token swap. The company has described the whole procedure as a “smooth launch of VeChain’s mainnet”. In contrast to EOS where to tokens had to be swapped on a pre-determined date (and actually 1.2% of tokens failed to do so and are hence frozen), VeChain allows its token holders to swap their tokens during a defined time horizon beginning July 13th 2018. At the time of writing, no end-date for the swap has been announced and there will probably be no deadline (with the exception of a minority of specific token holders). Like Tron, the Vechain ERC20 tokens (VEN) are swapped into the native coins VeChainThor tokens (VET). However, in this case the tokens will be swapped at a 1:100 ratio – for every single VEN token transferred, the token holder will get 100 VET tokens.

Figure 3: Visualization of the VEN token swap

According to the VeChain guide, there are three different methods outlined how the VeChain tokens can be swapped. There is the possibility to swap via an exchange (like Tron), the VeChain wallet or the ledger nano hardware wallet. Using the exchange option, the VEN tokens had to be transferred to the exchange wallet before the second week of July 2018 when the token swap occurred. The swap was supported by seven exchanges, among them Lbank, Bithumb, Binance and Bitfinex. Similarly to TRX, an option to exchange after the announced time horizon passed has been possible using Lbank exchange. For the swap using the VeChainThor wallet, further detailed instructions can be found here. At the time of writing, there is unfortunately no guide released for token migration by using the hardware wallet nano ledger.

Is there a general approach for token swaps?

No. As outlined above, there is no blueprint to how a token swap is constructed. However, it is clear that for all token swaps the token holder must conduct research on the process. The token development teams typically provide instructions on the required steps of a token swap. These instructions are commonly published in the newsfeed of exchange platforms, via Twitter and Medium accounts or on their official homepage. Figure 4 summaries a framework on how a token holder should handle a token swap and which steps should be considered:

Figure 4: General assistance framework regarding token swaps

In the first step, an investor must determine if there is any fixed date when the token swap takes place or if there is any time horizon when the tokens should be swapped. In the case of EOS or Augur there was a pre-determined date on which the tokens had to be transferred. Alternatively, there is also the possibility of a time slot over a few months or more when the token swap can be conducted, such as in the case of Pundi X, Tron or VeChain. A different approach was implemented by Icon where both options were possible.

The second step addresses where the ERC20 tokens are currently stored. Depending on the storage option, a token swap might differ therefore varying actions steps are required.

In case of storing the coins on a wallet on an exchange platform, the investors have to check if the exchange supports the new token – based on announcements on the exchange platform or the website/ forum of the corresponding ERC20 token. In the past, the major exchanges have typically supported the native coin. As a side note, this process of initially issuing ERC20 tokens could represent a cheap and easy alternative of becoming listed on an exchange platform with a native token.

The specific way how the token will be swapped may also differ – there is either the possibility of an automatic exchange where tokens only have to be stored in the wallet on the exchange during a specific timeframe or, alternatively, some specific instructions will be announced. If the token migration is not supported, the token holder will have to transfer the ERC20 to a specific wallet that supports the token swap.

In case of storing the coins on any other kind of wallet, the investor has to analyze initially if their wallet supports the new token standard. For previous token swaps, this was usually not the case and the coins had to be transferred either to a specific supporting wallet or to any exchange platform supporting the exchange.

Are there any risks associated with a token swap?

The primary risk is missing the announced deadline – when it is likely that the ERC20 tokens can no longer be swapped. They will become frozen and thus worthless. Taking into consideration that this is a quite new process occurring in the decentralized cryptocurrency market where no central authority is available, such a “trustless” process itself represents a major problem. There is no legal recourse if anything goes wrong – unlike in a central (bank) system. Additionally, the token swap has to be conducted in a proper manner, like every blockchain based transaction because of their irreversibility. If, for instance, a wrong receiving address for the new wallet is used (which might be due to a mix up of private and public keys), then the coins could be lost.

In a nutshell

If an ICO issues ERC20 tokens as a placeholder, a token swap is an inevitable step that has to be completed by any token holder. The coin swap is necessary to gain access to the (native) token’s full functionality and to prevent freezing of the ERC20 tokens. How a token swap is conducted depends on several factors, however, our framework (see Figure 4) should assist with the swapping process. The key points to remember are to:

– check the official instructions
– be aware of a potential deadline
– follow the instructions in a proper manner

Considering that a significant number of ICOs have issued ERC20 placeholder tokens, there is an increasing amount of future tokens swaps expected – the most relevant ones are exhibited in Figure 1.

Download the ERC20 Token Swaps Research Report PDF

Bitcoin just had an “inflation bug” and no, it is not dying

A responsible disclosure is not fun. Especially if the stakes are high and the timeline tight.


On 17th of September a vulnerability was found that could, in the very worst case, have led to a real on-chain double spend. I will not go into the nature of the bug, how it was found and who resolved it (although that story is great and an amazing example of efficiency). Instead, I will focus on what it would take (or rather have taken) for an attacker to actually exploit the vulnerability and what he would stand to gain from it. There is a lot of misinformation about this in the media right now.

The attacker has to be a miner and he would have to create a block that includes a specially crafted transaction that spends the same input twice in the same transaction.  This transaction cannot be one that he picked up from the network, where such a transaction would not propagate. Think of it as handing over the same twenty Swiss Francs bill twice in one payment at the grocery store. The grocery store actually received forty Swiss Francs even though you only spent one twenty Swiss Francs bill. The total monetary supply just increased by twenty Swiss Francs. This is why the bug is often dubbed as an ‘inflation bug’. The bug originated in the bitcoin core node software – this is run by companies dealing with or accepting bitcoin as well as individuals or developers in order to independently verify the information that they get from the blockchain. Since version 0.15.0 (September 2017) it no longer recognized such transactions as invalid.

After the bug was found, only few hours passed before version 0.16.3 was released and as of now already 19% of publicly visible nodes run on that version[i].

A miner running such an attack however runs the risk that despite many nodes not noticing the creation of money, other players will. He runs the risk that the betrayal of the network rules is picked up by humans instead of nodes. If this happens quickly enough, the operators of nodes, especially of economically relevant ones at exchanges will manually override and ignore this block. All it takes for this is one input in the bitcoin core node terminal. All preparations for such a step are taken. This would subsequently lead to a split in the blockchain, where nodes with observant operators follow a different chain than those nodes that do not. However, there is still a risk that the attacker can get his unjustly gained coins to an exchange, sell them there and withdraw the proceeds in fiat or a different cryptocurrency before the exchange notices the split and freezes operation. Given the mentioned efficiency and careful observation of certain individuals, the risk of such an attack, especially in economically damaging amounts, is very low.

It all comes down to two things. Firstly, what does the attack cost the attacker and secondly, how fast is the network likely to notice the anomaly and work around the culprit before he can take his profit.

Since the attacker has to be a miner and put his inflating transaction into a block which would otherwise have been valid, he is losing out on the reward for the block, yet still has to cover the production cost of that block. If the attack is unsuccessful, he just lost 12.5 BTC (plus fees), or at current rates roughly CHF 80k. This represents his investment.

To the second point, for the likelihood of discovery, that very much depends on the level of automation. Above, I only mentioned the manual, human means of discovery, but this is certainly not all. Projects like Statoshi or Bitcoin Optech continually monitor all possible network parameters. Fork monitors run different node software to determine any deviations. Developers do that to notice deviations between their software to bitcoin core and actually any bitcoin node will notify its operator if it determines that it is running on a minority chain, i.e. if there is a chain that is at least six blocks longer, but the node determines that chain to be invalid.

There are mechanisms in place to monitor the network for inconsistencies. In that context, the fact that the commit that enabled this bug only happened last September is very good news. Older versions are therefore not affected.

As of right now, 64% of nodes are secure, only 31% are vulnerable and 5% of publicly visible nodes do not send a standard version identifier, which means that it is unknown if they are affected or not. Those numbers obviously come after 19% of nodes have already updated to 0.16.3, but even if we assume that all of those have previously been on an affected version 0.15.0 to 0.16.2, this means that in the worst case scenario, there are still 31% of nodes that have not been vulnerable at the time of disclosure.

This rather high number, together with tools that monitor anomalies in the network, make it very unlikely that an attacker would be able to successfully spend his unjustly gained coins before the community notices and self-adjusts.

As a corollary to this: We do know that this exploit has not been executed in the past. For the very simple reason that pre-vulnerability nodes, running lower versions are purposely still up, running and in sync with the vulnerable ones.

Above considerations are valid for BTC. Smaller networks skew the numbers significantly. If it is cheaper to create a block, or rather if the opportunity cost of missing out on one, is smaller, the investment for the attacker goes down. Moreover, if there are fewer nodes and fewer developers monitoring the network, the likelihood of success goes up massively.

[i] For this and the further number of nodes, I source the information from This gives an indication about the network. Getting exact numbers is impossible though, since many nodes do not publicly advertise their existence.

The BIS report – a rebuttal

Just a few years ago, every mentioning of cryptocurrencies in publications of the established financial systems was celebrated for the recognition that the young community received. These early days are clearly over. When the Bank for International Settlements (BIS) published a chapter about cryptocurrencies in their 2018 annual report, the community’s reaction was far from positive. The responses on twitter were of a form that we don’t intend to reproduce here. So this might generate some heat from the community as well: The report is actually fairly good. The technological valuation is sound, the economic critique is warranted. So where does this discrepancy originate? The BIS report fell short on only two aspects: It evaluated the technology for what it was a year ago and it criticizes cryptocurrencies for failing to be something that they do not aim for.

The technological criticism

Granted, it would not be prudent to take into the equation technology that does not exist yet. To trust that something will be around to save the day. Any prediction that something does not work is dangerous because some technological advancement might come along and render the counter-arguments invalid. But for the same reason a prediction that something does work can only rely on the current state of technology, not the hope for some breakthrough. The by far most famous example of such a misguided prediction is The Times newspaper’s prediction of 1894 that “In 50 years, every street in London will be buried under nine feet of manure”. Understandable at the time but obsoleted by the invention of the car. If an analogue prediction had been made in the
1920s, when the number of horses in London was even higher than in 1894, the prediction would seem negligent now instead of being a quirky anecdote of a time preceding the invention of the car. Analogously for the case of cryptocurrencies, when evaluating the scalability of the system, it is negligent to base this evaluation on the state of technology as of a year ago and discarding the technological breakthroughs that already happened. The BIS report does acknowledge the existence of proper scaling solutions, but hides this in a footnote, which does not acknowledge its relevance. So here it is:

Proposed solutions for the scaling problem include the Lightning Network, which essentially shifts small transactions off the main blockchain and into a separate pre-funded environment.

The Lightning Network is live and working. Indeed it still needs to increase adoption and for political reasons might fail to do so, but the technology is a settled thing. Instead of communicating every transfer to every participant of the network (if a cryptocurrency would reach global levels of adoption potentially billions of redundant copies of the same load of data), the Lightning Network communicates a transaction directly from the sender to the recipient or via up to 20 hops along the edges of the network. No permanent record is required beyond the closing of that particular channel, which might happen once every few months. Further improvements are also already in great progress, but since those are not live yet, it is fine to ignore them for the time being. Such a network topology does not “bring the internet to a halt”, as the BIS report put it. Even on today’s hardware and today’s global network infrastructure.

The second major infrastructure criticism is the ‘mining’ of cryptocurrencies. Here again, the BIS report is doing an exceptional job at analyzing the process. The description is among the most understandable and accessible that I’ve seen so far. It correctly identifies it as the “mathematical evidence that a certain amount of computational work has been done, in turn calling for costly equipment and electricity use”. This leads to the often made (and true) statements that “At the time of writing, the total electricity use of bitcoin mining equalled that of mid-sized economies such as Switzerland”.

What the report does not take into consideration however, as do most other criticisms, is how the electricity usage scales with the growth of the network. Not at all. Whether a block validates 1000 transactions or 2000 transactions or zero. The amount of electricity is the same. Arguments starting from the current electricity usage and extrapolating to a more widespread usage are invalid. The electricity consumption scales not with the use but with the desire for security in the system. Given an equilibrated system the electricity consumption will be close to the expected monetary reward. If that leads to fees that some use-cases of the system are not ready to pay because they do not require that level of security, then those use-cases will move to other systems, e.g. the still trustless Lightning Network. What remains on-chain is the desire for the native security. This mechanism is currently (at least in Bitcoin) still offset by the ‘block subsidy’ an extra reward of freshly mined coins that does not originate from fees that somebody pays for security. The desire for security might still increase, the block subsidy decreases. In net effect, the electricity consumption will probably rather decrease in the long run or stay roughly the same, even when faced with a much higher use.

The economic criticism

Cryptocurrencies do not aim to be easily adaptable to changing economic situations. They are not suitable as a replacement for the central bank money. On the contrary, they aspire to create stability by predictability. The future supply of most cryptocurrencies is predetermined (Ether is a notable exception of this). This is not to say that they do not have a place in the mission of a central bank.

The Swiss National Bank holds 1040 tonnes of gold. It does not do so because it thinks that gold would make a great payment system. To set it in context to the explicit goals and responsibilities of the Swiss National Bank, room for cryptocurrencies are not in the primary goal, the ‘price stability’, but rather in the ‘asset management’ task. In contrast to that, the BIS has been looking at cryptocurrencies only in the context of a form of ‘cash supply and distribution’, where it miserably fails, as the BIS correctly concluded. Precisely due to its highly predictable supply.


Figure 1: Source: BIS annual report 2018

The BIS coined the ‘money flower’ for characterizing forms of money based on discrete criteria. The central element of that, checking all boxes, is the ‘Central bank digital currencies (retail)’. In this taxonomy, the only difference between that and ‘Cryptocurrency (permissionless DLT)’, under which the BIS also counts Bitcoin and others, is the checkbox for ‘Central bank-issued’. If this is a benefit or drawback strongly depends on the use-case at hand.

(It is almost ironic at this point that – in this admittedly very simplified visualization of the already simplified reproduction of the original arguments – the only difference between ‘bank deposits’ and ‘virtual currencies’ is the wide accessibility. To make no mistake about the meaning, the prototypical example of a ‘virtual currency’ mentioned in the BIS report is World of Warcraft gold. While indeed more people currently use Bank deposits than WoW gold, the criteria for accessibility to the latter literally only requires internet access and a local shop selling a copy of World of Warcraft, while 31% of the adults do not have access to any financial services. So arguably, ‘bank deposits’ and ‘virtual currencies’ do not differ in this simplified characterization of the money flower.)

The mandate of a central bank is indeed incompatible with using a decentralized cryptocurrency. A central bank issued currency sources trust from its sound reaction to economic conditions, resulting in price stability in the day-to-day life of its users. Decentralized cryptocurrency without room for any political or monetary decisions sources trust from its non-reaction to economic conditions, resulting in value stability independent of day-to-day whims and fluctuations.

“Strong oversight and central bank accountability both help to support finality and hence trust” says the BIS report. This is probably the starkest difference between the view that the BIS holds on transactions and what the cryptocurrency community sees in that technological advancement: The BIS achieves trust through finality. Cryptocurrencies achieve finality through trust.