Nicola Santoni
Jul 29, 2019 · 15 min read

A clear visible trend in the crypto space is the proliferation of designing Proof-of-Stake networks. Some have recently launched, others are in their fine-tuning phase (testnet) and many more are in the making. The fact that Ethereum is vigorously heading in this direction is a boost for the entire ecosystem. The Proof-of-Stake (PoS) trend seems indisputable.

While much has been written about the various implications of PoS, such as security and cryptoeconomics, in this post I will focus on one specific aspect of PoS: namely the multitude of potentially tradable products that those cryptonetworks could originate.

After a general review of the economics behind staking and a brief description of traditional financial derivatives, I will then dive into an ambitious classification of products providing a rationale and at least one plausible example for each segment.

In other words, we will take a tour of what the future realm of cryptoderivatives and staking derivatives could look like.

Primary assets vs Staking rewards

Before moving on, one non-trivial distinction to be made is the difference between the primary assets and the staking rewards that are created through “inflation”:

  • Primary assets are the primary, native assets that capitalize, incentivize and coordinate PoS networks (XTZ, ATOM)
  • Staking rewards instead, simplistically called “yields”, can be thought of as actual shares of the rewards doled out by the network to its validators

The whole primary assets and staking rewards dichotomy is additionally nuanced by the fact that often staking rewards are distributed and denominated in primary assets. However, this is not necessarily the case. In Cosmos Hub for example, staking rewards from inflation are in ATOMs but rewards from transaction fees on Cosmos will likely be in the asset being transacted.

In this post I will divide the two, considering staking rewards as a new, de-facto asset class.

Staking as an asset class

Having that distinction in mind, it is now easier to proceed with the following separation:

  • Cryptoderivatives: products linked directly to primary assets i.e. call option on ATOM price
  • Staking derivatives: products linked to the amount of staking rewards distributed by the protocol to network validators or participants

An introduction to derivatives

Now, let’s step back for a moment from PoS and cryptonetworks to take a quick overview of derivatives in traditional finance.

So, what are those derivatives and why were they introduced to the world in the first place?

Borrowing the definition from Investopedia for simplicity, a derivative is a financial security with a value that is reliant upon, or derived from, an underlying asset or group of assets. The derivative itself is a contract between two or more parties, and its price is determined by fluctuations in the underlying asset. There are derivatives on almost anything tradable that you can think of. From derivatives on stocks to interest rates, moving to pork belly, freight and movies (the last one being banned by the Dodd-Frank Bill).

At the very beginning, derivatives were primarily devised to protect (hedge) one specific position over an underlying asset. We can also think of them as a form of insurance (we will come back to that later on).

Since their inception, more and more players have joined the derivatives party from multiple angles satisfying many, often nascent, different needs resulting in a total global value worth in the hundreds of trillions.

The economics behind staking

First of all let’s quickly discuss consensus mechanisms in relation to PoS networks.

Reaching consensus across a distributed network of nodes is possibly one of the most researched, debated and fascinating aspect across the whole industry. However, for this post I will just scratch the surface of the topic when discussing staking derivatives with reference to security.

Broadly speaking a PoS protocol entitles its token holders to be rewarded a certain amount of primary asset (share of staking rewards) upon providing a service to the network itself. These services are typically represented by (1) validating transactions, (2) proposing new blocks and also (3) storing, gossiping and making data available to be verified. Embracing the generalized mining narrative, the set of actors performing these services are called miners (or validators) and the rewards are paid proportionally to each of them, based on their token holdings (stakes).

Economically speaking, this translates into a “fairly predictable” return. The semantics behind said “yield” are very interesting, yet rarely understood as described in this article written by Lorien Gabel from Figment Networks.

I am anticipating that a growing range of products will focus on the predictability of said rewards.

However, an important consideration needs to be made: what are the main factors affecting the economics of staking?

Looking at the most prominent live PoS protocols, the most meaningful “economics” seem to be: (please note that the list is by no means comprehensive):

  • Validation and block propagation economics (commonly branded “inflation rate”)
  • Deposit / Withdraw economics (liquidity)
  • Slashing economics (penalties)
  • Transaction economics

There is one basic relationship that characterizes our economy that needs to be highlighted: in most cases, a non risk-free return asset, embeds an unavoidable uncertainty which leads the holder to seek some sort of protection (hedging).

To fully understand the ethos of this post, it is useful to follow the different paths that buyers/sellers of cryptoderivatives and staking derivatives would undertake.

Both, (1) primary asset holders (green dot) and (2) network participants (blue dot) initially engage with the network: (1) buy primary assets and (2) participate in the validation process (e.g. staking). Now, they both have an economic exposure and could incur in losses. They both choose to seek protection and to hedge their exposures with (1) cryptoderivatives and (2) staking derivatives (both in the upper band on the chart).

However, since cryptoderivatives and staking derivatives are openly tradable assets, they will most likely be buyers and sellers of said assets who do not necessarily hold the underlying assets. In other words, you do not need to hold ETH to buy or sell a put option on ETH and you do not necessarily need to stake ATOMs to buy or sell an off-chain a “staking reward swap” on ATOMs.

Comparison between asset holder vs. network participant

It goes without saying that for each product to be exchanged, there needs to be a buyer and a seller. Looking at the above chart we will have four kinds of players:

  1. Buyers of risk mitigation (seeking economic protection)
  2. Sellers of risk mitigation (providing liquidity, seeking economic speculation)
  3. Buyers of risk exposure (seeking economic speculation)
  4. Sellers of risk exposure (providing liquidity, seeking economic speculation)

I will give a more detailed overview about the ecosystem players in another article.

The staking derivatives realm

Here is a general classification of cryptoderivatives and staking derivatives:

  1. Staking derivatives by product
  2. Staking derivatives by domain
  3. Staking derivatives by nativeness.

Let’s dive into it.

Staking derivatives by product

Let’s start with the simplest partition across the space.

  • Legacy products
  • Staking crypto primitives

Legacy products are all those products that are borrowed from the financial market. Swaps, futures, options, repo, etc, would fit into this category.

Staking crypto primitives are a variety of products that are created to hedge (or gain exposure to) a certain “risk” embedded in a PoS protocol. They would ideally be trustless and on-chain. In my opinion, more interesting to design and explore.

Plausible example:

  • An off-chain call option on the staking reward rate for validating Tezos (legacy product)
  • An on-chain DAO-issued insurance product for downtime slashing on Cosmos (staking crypto primitive)

Staking derivatives by domain

The economic risk associated with staking has a multi-dimensional form. Depending on the particular interaction with the cryptonetwork, the stakeholder could incur different losses.

The following is a list of instruments in relation to each domain:

  • Security and Operability: instruments protecting from attacks and from losses due to network malfunctioning
  • Economics: instruments preventing pure economic losses
  • Governance: instruments preventing losses from cryptonetwork mismanagement
  • Network peculiarities: instrument protecting different kinds of losses, such as the right to perform a work for the network or to vote or participate in any kind of activity, peculiar to a network

Let’s now dive in each segment.

Staking derivatives by domain

Security and Operability

In a PoS cryptonetwork, security is possibly the most important property to achieve in order for the protocol to survive. This segment can be split into:

Liveness: Derivative products protecting token holders from a failure of the network, acting as an insurance for an attack to the blockchain. One could think of them as a life insurance for your tokens.

We refer to liveness as:

  • Availability
  • Consistency

Two important points to mention:

  1. The distinction between liveness at network level and at individual node validator level. The latter being relatively insignificant in the context of network performance
  2. In terms of network design, there is often a decision on what to prioritize in case of network partition (availability vs consistency). Insurance products would therefore be one-sided as the network pre-determines how it will behave in adversarial situations

Operability: Emergency products issued by foundations to attract new validators when live nodes drop below a predefined threshold.

This would act as an additional stimulus to the dynamic inflation mechanism currently enforced by cryptonetworks like Cosmos or Ethereum 2.0.

These products could be a quicker, more effective tool in comparison to a change in the incentive structure (i.e. inflation). This is especially true since many of those decisions are currently made through elaborate off-chain governance processes.

A suitable and helpful parallel with traditional finance would be a quantitative easing policy.

For example, a government executing quantitative easing would translate into an on-chain crypto derivative issued by a foundation or by an emergency DAO.

This newly issued derivative would be more effective than a structural policy aimed to stimulate the economy from the ground up. In fact, the latter would produce tangible results only after years, if not decades. Alternatively, our instrument would produce immediate effects.

In conclusion, the line between security and operability is extremely thin and blurred. If a cryptonetwork security is threatened, its operability would be indistinguishably compromised.

Let’s revisit the parallels between a cryptonetwork and a city or state. A breach in its high-level security (e.g. a coup d’Etat or an enemy invasion) would also affect its operability (e.g. the public transportation would stop working). But on the other hand there is also a non-zero chance that the subway system in a city stops working without the state being attacked. Back to our PoS derivatives realm, the family of “operability derivatives” would address the single risk of operational failure. Either in a form of insurance (binary options) or in the form of futures or swaps, where the value of the product increases (or decreases) based on the likelihood of the failure occurrence.

The work on frontrunning (manipulating order of transaction on a decentralized exchanges) by Phil Daian is extremely inspirational. Frontrunning is an operability risk that could incur in losses. However, it would be very challenging today to create a product protecting these kinds of risks. Even more challenging would probably be collecting the data and prove that a certain behaviour has actually occurred and caused (you) economic losses.

Plausible example: A derivative product on Polkadot, issued by an emergency-DAO, offering X times higher validation staking returns (for a short, limited period) until the restoration of a minimum set of validators is completed (liveness).


Similarly to PoW mechanisms, PoS protocols are designed to incentivize miners (validators) to provide valuable resources to the network (such as security, block validation, storage) in exchange of staking rewards coming from newly minted tokens.

Staking rewards are doled out to validators in proportion to the amount of tokens staked in the network. Since PoS leads to some predictability of rewards, the affiliation with a traditional cash flow bearing instrument then becomes extremely intuitive.

Naturally, this is the area where one could foresee the vast majority of staking derivatives flourish.

A non-comprehensive list of those instruments includes:

  • Reward linked products: this is possibly the most popular. Those instruments would track exposures to staking rewards rate, fees, commission rates and validators uptime. We are not far away from having products hedging against a validator’s commission rate change in Cosmos, for example. A comprehensive list of risk/reward factors in the Cosmos network can be found here.
  • Risk linked products: those instruments would offer insurance against economic losses resulting from slashing, unbonding or downtime. Taking Cosmos again as an example, one can imagine a derivative product providing protection against a validator being “jailed” or against a revision of its “minimum self-delegation”. However, during early conversations some doubts arose: this kind of protection could result in a net negative for network security. Validators could insure themselves against slashing and therefore be less incentivized to spend additional resources on securing themselves.
  • Liquidity linked products: those instruments would facilitate liquidity for token holders who are obligated by the protocol to lock their tokens for a certain amount of time. In Cosmos, for example, the maximum threshold for slashing is currently set at 5%. That means that 95% of the tokens can not incur in any kind of slashing. One can envision a proliferation of derivatives products representing rights over a portion of locked, but secure, tokens. They would be basically used as collateral. In addition, for Layer 2, there is a whole uncovered field about renting liquidity to L2 hubs, like a lightning network or state channels network. The whole locking mechanism makes funds unusable, yet a hub earns some fees. One could consider this as a hub providing both liquidity and L2 payments routing. Akin to delegation in PoS networks, one could provide liquidity to an L2 hub in exchange for shared earnings. While in the PoS realm one casually sees yield, in lightning the rate of return is called Lightning Network Reference Rate. Consequently, one could wrap this into a derivative.
  • DeFi linked products: This range of products, ideally swaps, would provide the holder a protection (exposure) to one or more “competition” protocols for the deployment of the same, locked asset. Taking ETH now as an example, imagine an asset representing a portion of your locked ETH in validation. Let’s call this new asset DETH. 1 DETH = 1/X ETH, with X dynamically set between 1,05 and 10 depending on risk parameters. A staking derivative product would algorithmically pick the most profitable decentralized protocol to autonomously deploy DETH (i.e. Maker vs Dharma vs Compound). The above example would only work if Maker, Dharma and Compound would accept DETH as a collateral asset.

Plausible examples:

  • Put option on Tezos staking rewards (Reward linked)
  • A Cosmos on-chain insurance-DAO derivative covering downtime slashing (Risk linked)
  • A staking provider or CEX backed liquidity certificate on locked ATOMs (Liquidity linked)
  • Off-chain interest rate swap on ETH locked in Compound vs Maker (DeFi linked)


This is possibly the most “futuristic” and exciting domain to explore. Governance, or a lack of it, has tremendous implications in a cryptonetwork, whether on or off-chain. However, the specs of the debate go far beyond the scope of this article.

What we are really interested in are the economic impacts of those implications. They will be more or less measurable and more or less “hedgeable”.

To this day, it is practically inconceivable to be able to measure the impact that a governance outcome would have on its primitive asset price. The ecosystem developing around decentralized predictions markets though, is evidence of this trend.

A “cryptogovernance” derivative sounds very far from the state-of-the-art blockchain ecosystem. Its abstractivity could feel overwhelming. However, Jesse Walden had previously compared cryptonetworks to cities while Joel Monegro associated governance to capital. The gap is narrowing and this trend will not likely stop.

Cryptonetworks like Tezos and Polkadot are creating mechanisms for a fair and open governance to insure a sound evolution of the cryptonetwork. The more decisions that are made on-chain, the more rational actors will have the opportunity to evaluate outcomes and assess risks. Governance processes will make decisions on fees, rates, upgrades and much more. As I stated before, risks bring uncertainty which leads to seeking protection.

Plausible example: Digital option on rental fees triggered by the positive or negative outcome of a Polkadot governance decision relative to an upgrade of validator’s dilution-fee.

Network peculiarities, hybrids and miscellaneous

In this segment I will include risks initiated by peculiar actions implemented within a cryptonetwork.

The above-mentioned risks do not necessarily need to incur in economic losses. On the contrary, they could relate more qualitatively to risk. A non-exhaustive list includes:

  • Right to operate: this range of products was inspired by the talk of Gavin Wood from Polkadot about its parachain auction mechanism. Polkadot will have a certain initially pre-defined number of slots available for its parachains. I found the model extremely interesting and I am confident this kind of mechanism will be a source of inspiration for designing staking derivatives.
Polkadot Parachain deployment —
Polkadot Parachain auction schedule —

One could see derivatives hedging the risk of losing the right to carry out work for the network.

  • Inter-protocol products: One can envision a multitude of specialized actors creating products and providing liquidity for them in a fully decentralized fashion. They would create new “markets” exploring opportunities across cryptonetworks. Teams are already creating infrastructures facilitating this. I also envision those products being collateralized by different cryptoassets. Consequently they will demand different requirements based on the collateralized asset volatility and liquidity parameters. However, they would be extremely hard to implement in a completely decentralized way. Therefore, centralized inter-protocol products will be much easier to create.
  • Structured products (offering combination of payoffs)
  • Regulatory insurance

Plausible examples:

  • An interest rate swap on Cosmos vs Polkadot validation (Inter-protocol product)
  • On-chain structure product long ETH staking rewards + a basket of call options on staking rewards for interoperability protocols (Structured product)
  • Off-chain OTC futures on a Polkadot parachain slot.

Many of those products could belong to two or more categories at the same time. A product tackling downtime, for example, could be seen with multiple lenses: purely economic, operational or for security.

The chart below summarizes interconnections across products and domains.

Interconnections across products and domains

Staking derivatives by “nativeness”

Finally, I introduce the concept of “nativeness” to better understand the origin of the risk in relation to the cryptonetwork.

I propose three main categories:

  • Ad-hoc risk / Ad-hoc network: possibly the most intuitive and the easiest products to create and adopt. They protect one single event in one single cyptonetwork.
  • Cross risks / Ad-hoc network: these derivatives protect or give exposure to multiple economic risks in one specific network. For example, a product composed by the combination of cash flow from staking rewards plus a call option on participation. Both related to the same cryptonetwork.
  • Cross risks / Cross networks: this range of products represents the highest level of sophistication and complexity. Pushing the boundaries forward, one can imagine a derivative hedging a staking reward in cryptonetwork A while selling the right to perform a job in the cryptonetwork B.

Plausible examples:

  • An ETH on-chain futures on gas return (Ad-hoc risk / Ad-hoc network)
  • A structured product composed by a long position in staking rewards DOT and a short position in a parachain lot future (Cross risks / Ad-hoc network)
  • A structured product “buying” unbonding time on Cosmos and shorting staking rewards yield on Tezos (Cross risks / Cross networks)
Staking derivatives comparison chart (click to enlarge)

All of this seems very futuristic. However, it’s worth noting that the vast majority of players and liquidity providers in the legacy financial markets are individuals or institutions who do not necessarily hold the underlying asset. Many of them may not have any direct exposure to it all. This is the well known concept of paper vs physical.

As of today, thinking about these sorts of products borders on pure fantasy. However, we can not neglect (1) the power of innovation, especially when talking about software, and (2) the flourishing ecosystem populated by highly skilled staking providers who are going to take notes on returns, risks, downtime, historical performances, and much more. Data will be elaborated on and used to devise products that will help mitigate existing risks and opening new ones.

Conclusion and further research

Most of the PoS cryptonetworks are still social experiments at massive scale which embed unavoidable risks. Risks lead to losses. Losses lead to lessons. Lessons lead to protection.

Actors will take notes and learn from their losses. Economic incentives and profits from trading will attract a wide range of rational agents and intermediaries contributing liquidity, infrastructures and products design.

As I just scratched the surface of the staking derivatives realm, many subjects require further research and further elaboration in future posts. These include:

  1. Relationships and dynamics between individual risks
  2. Governance risks and its measurability in economic terms
  3. Players
  4. Security staking derivatives: liveness and consistency

Much of my thinking has been inspired by conversations and guidance from my colleagues at Lemniscap, which I very much appreciate. Thank you to Sergey Ukustov, Lorien Gabel and Andrea Bracciali for their generous feedback and for sparking this reflection.


advisory and investment in the blockchain space

Nicola Santoni

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