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Current On-Chain Derivatives Landscape

Addressing the Liquidity-Conundrum

A long-standing challenge in decentralized trading has been liquidity. The market is currently stuck in a causality dilemma (chicken and egg problem):
Traders go to the most liquid markets, and liquidity goes to the markets with the most traders.
The most liquid markets are currently centralized exchanges. Traders who face lower liquidity, higher slippage, and higher fees on-chain will rationally remain on centralized exchanges until these conditions change. And while traders remain on centralized exchanges, they will continue to be the most productive place for liquidity to flow.
So how do DEXs attract liquidity without traders, and traders without liquidity?
This is a review of what the current on-chain derivatives market looks like and IntentX's unique role in it:
The prominent solutions in the DeFi market can be classified into (1) Order Book, (2) AMM-based, and (3) Oracle-based vAMM.
IntentX, with its unique intent-based architecture, stands out with a novel approach to the liquidity dilemma.

On-Chain Order books:

Orderbooks are the most widely used method for crypto exchange as they enable peer-to-peer (P2P) trading with granular control of liquidity. They offer market transparency, high efficiency from a fee & liquidity perspective and a great degree of internal price discovery. This allows for reliable listing and exchange of a wide range of assets.
Order book exchanges are optimal for liquid markets and internal price discovery, however, when built on-chain, order book exchanges face several unique challenges:

1. Limited Throughput (speed):

Because order books require high-frequency updates of orders, they are highly reliant on throughput to operate. Every millisecond counts as evidenced by traditional finance market makers optimizing for speed at the cost of billions of dollars annually.
Most secure/decentralized blockchains do not provide sufficient throughput to operate an entirely on-chain orderbook. Leading projects are attempting to solve this by building their own layer 1 blockchain; however, this introduces concerns over validator centralization.
This is part of the blockchain trilemma” introduced by Vitalik Buterin, the idea that blockchains inherently have to trade off between decentralization, security, and scalability.

2. Centralization:

Firstly, because of the limits of the blockchain throughput, on-chain order books typically have off-chain matching engines. This is a centralization risk because the economic incentive to front-run order flow is exceptional. The payment for order flow (PFOF) market size in traditional finance is over $4B annually.
Secondly, as their own layer 1 blockchain, fully on-chain order books still require a permissioned set of trusted validators to structure order flow.
Both of these solutions compromise on the “Decentralized” corner of the blockchain dilemma:

3. Market-Making and Liquidity:

From a market-making perspective, maintaining order books is a complex operation that requires considerable capital commitments (maker orders are committed capital). As a result, trading volume and liquidity tend to centralize on existing incumbents.
On-chain order book exchanges have struggled to build deep liquidity with the on-chain markets being so fragmented (many competing blockchains and exchanges). Every new orderbook exchange must necessarily fragment/capture liquidity from existing ones. This is simply because maker orders in an order book are committed capital; this contrasts to how IntentX approaches market-making with just-in-time liquidity.
The result of this fragmentation is a liquidity crunch, with trading volume typically gravitating towards exchanges with the highest liquidity. This brings us back to the causality dilemma between liquidity and trade volumes.
While decentralized order books will continue to advance in technology and liquidity to compete with CEXs over time, the technology and trade experience is not currently there.

Automatic Market Maker (AMM) Models:

While AMMs are not directly perpetual futures contracts, they can allow traders to have Delta = 1 exposure to underlying assets with leverage via borrowing funds (price move in underlying asset is reflected identically in the price of the derivative).
These exchanges operate primarily by offering traders leverage via borrowing, and utilize spot-AMM liquidity and markets to match buy and sell orders, which allow for internal price discovery.
These are some pros to the model:
  • Utilization of existing spot-AMM liquidity for orders (composability)
  • LPs are not direct counterparties to traders (like in a vAMM model)
  • Because it is AMM-based, potentially any long-tail assets can be traded.
However, there are reasons this model has not found product market fit:
  • Leverage is limited by lender capital, which has to be heavily incentivized. This means leverage is largely limited (2–5x) and extremely expensive for traders and the protocol.
  • Lenders face credit risks because traders are at risk of insolvency.
There is no easy way to work around the capital-intensive liquidity challenges of this model, and because of the capital inefficiencies presented, this model has not found wide-scale adoption.
Power perpetuals introduced by Paradigm in 2021 are a new approach to AMM-based futures, with a few notable projects currently building new products that promise improvements to what we have seen. However, these will always be constrained by costly and scarce liquidity.

Oracle Based Virtual Automatic Market Maker (vAMM) Models:

The vAMM model, popularized by platforms like GMX, has been an innovative market response to current challenges in on-chain order book shortcomings. This model has gained traction with considerable daily volume and now many iterations of forks.
vAMM exchanges allow for guaranteed order execution, high leverage, and predictable trade slippage.
This model hinges on a counterparty liquidity pool (LP), which serves as the de facto counterparty for trader positions. However, this approach is fraught with inefficiencies:
  1. 1.
    Capital Inefficiency
  • Liquidity is idle and awaiting utilization (under-utilization).
  • The LP counter-trades all positions and open interest (OI) must be restricted to only what the protocol could pay out in total loss situations.
  • Risk cannot be properly priced without price discovery, so OI has to be restricted, particularly on long-tail volatile assets, to protect the LP depositors.
2. High Costs
  • With no price discovery mechanisms (oracle-based), the protocol cannot price risks adequately. This is inherently a market operation.
  • Because the LP counter-trades all positions, the platform fees must offset the risk of any losses taken by the LP.
  • The fees for execution, borrowing, and funding are considerably higher than centralized exchanges.
  • Because the LP has to be compensated for the risk, the vast majority (up to 70%) of the platform revenues go to LPs rather than the project stakeholders.
3. Limited Asset Range
  • Listing long-tail and volatile assets is troublesome because of the risk for losses to LPs.
  • OI is severely restricted if listed, and fees + slippage are high to offset the risk.
4. Oracle Dependency (manipulation risk)
  • The vAMM model requires external oracles to inform the price of assets. This opens the protocol to the risk of price and oracle manipulation.
  • According to blockthreat.io, Price Oracle Manipulation is currently the #1 DeFi attack vector:
5. Fragmented Liquidity
  • Because a large liquidity pool is required to execute trades, vAMMs suffer from fragmented liquidity.
  • Every new fork and iteration that launches must pull liquidity away from existing protocols and this results in worse overall liquidity conditions for traders due to fragmentation.
  • Further, this limits multi-chain deployments, for every new chain deployed requires its own distinct liquidity to be built up.
  • Incentivizing liquidity is costly to protocols and is usually done through inflationary rewards at the expense of stakeholder value.
The market is saturated with marginally tweaked forks that while finding some adoption; cannot escape the inherently inefficient aspects of the vAMM model.

While it is clear that there’s been a product market fit and demand for on-chain perpetuals, the existing solutions have failed to provide competitive trading experiences and pull trade volume from CEXs as the comparable spot market has.
IntentX's solution to these problems via its unique architecture and approach to liquidity is outlined in IntentX Solution & Architecture Overview.