📊Current On-Chain Derivatives Landscape
Addressing the Liquidity-Conundrum
In decentralized trading, an enduring challenge has been liquidity. The market finds itself entangled in a longstanding causality dilemma, akin to a chicken-and-egg problem:
Traders go to the most liquid markets, and liquidity goes to the markets with the most traders.
Presently, centralized exchanges boast the highest liquidity in the markets. Traders, experiencing lower liquidity, increased slippage, and higher fees on decentralized platforms, logically opt to stay on centralized exchanges until these conditions undergo a shift. As long as traders persist in centralized exchanges, these platforms will remain the most effective conduits for liquidity.
So how do DEXs attract liquidity without traders, and traders without liquidity?
Let's delve into the current state of the on-chain derivatives market and understand GemaX's distinct position within it: In the DeFi landscape, the prevailing solutions fall into three main categories: (1) Order Book, (2) AMM-based, and (3) Oracle-based vAMM.
GemaX distinguishes itself by tackling the liquidity challenge with an innovative intent-based architecture.
On-Chain Order books:
Order books are extensively employed in crypto exchanges, providing a peer-to-peer (P2P) trading mechanism with precise control over liquidity. They bring about market transparency, operational efficiency in terms of fees and liquidity, and a considerable level of internal price discovery.
This setup facilitates the dependable listing and exchange of diverse assets. While order book exchanges are ideal for liquid markets and internal price discovery, challenges emerge when these exchanges are implemented on-chain:
1. Limited Throughput (speed):
Order books, needing frequent order updates, heavily depend on throughput for functionality. The importance of every millisecond is evident in traditional finance, where market makers prioritize speed, spending billions annually.
However, many secure and decentralized blockchains lack the necessary throughput for a fully on-chain order book. Some major projects aim to address this by creating their own layer 1 blockchain, but this raises worries about centralization among validators.
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:
To start, due to blockchain throughput limitations, on-chain order books usually incorporate off-chain matching engines. This introduces a risk of centralization, given the significant economic incentive for front-running order flow—an aspect illustrated by the over $4 billion annual market size of payment for order flow (PFOF) in traditional finance.
Additionally, even with their own layer 1 blockchain, fully on-chain order books still need a permissioned group of trusted validators to organize order flow. Both of these approaches compromise the "Decentralized" aspect of the blockchain dilemma:
3. Market-Making and Liquidity:
From a market-making standpoint, managing order books is a intricate task that demands significant capital commitments, as maker orders involve committed capital. Consequently, trading volume and liquidity often concentrate on established players in the market.
On-chain order book exchanges face challenges in developing substantial liquidity, given the fragmentation of on-chain markets across various blockchains and exchanges. Every new order book exchange must attract liquidity from existing ones, as maker orders in an order book entail committed capital. This contrasts with GemaX's market-making approach, which adopts a just-in-time liquidity model.
The outcome of this fragmentation is a liquidity crunch, leading trading volume to gravitate towards exchanges with the highest liquidity. This brings us back to the inherent challenge of the causality dilemma between liquidity and trade volumes. While decentralized order books are expected to progress in technology and liquidity to compete with centralized exchanges over time, the current technology and trade experience are not yet up to par.
Automatic Market Maker (AMM) Models:
While Automated Market Makers (AMMs) don't directly deal in perpetual futures contracts, they enable traders to attain Delta = 1 exposure to underlying assets with leverage by borrowing funds (reflecting price movements in the underlying asset identically in the derivative's price).
These exchanges primarily function by providing traders with leverage through borrowing, utilizing spot-AMM liquidity and markets to match buy and sell orders, allowing for internal price discovery. Some advantages of this model include the use of existing spot-AMM liquidity for orders (composability), LPs not serving as direct counterparts to traders (unlike in a vAMM model), and the potential trading of various long-tail assets due to its AMM-based nature.
However, certain reasons hinder the widespread adoption of this model:
Leverage is restricted by lender capital, requiring significant incentivization. This results in limited leverage (2–5x), making it exceedingly expensive for both traders and the protocol.
Lenders face credit risks due to the potential insolvency of traders.
There is no straightforward way to overcome the capital-intensive liquidity challenges of this model. The inefficiencies in capital usage have hindered its broad-scale adoption.
Paradigm introduced Power Perpetuals in 2021, offering a fresh perspective on AMM-based futures. Presently, several noteworthy projects are working on developing new products that pledge enhancements to the existing models. Nevertheless, these innovations will inevitably face limitations due to the expensive and limited availability of liquidity.
Oracle Based Virtual Automatic Market Maker (vAMM) Models:
The vAMM model, championed by platforms such as GMX, stands as a creative market solution to address the existing shortcomings of on-chain order books. It has garnered popularity, boasting significant daily volume and witnessing multiple iterations in the form of forks.
vAMM exchanges offer assured order execution, substantial leverage, and predictable trade slippage. This model relies on a counterparty liquidity pool (LP) acting as the default counterpart for trader positions. However, this approach comes with inherent inefficiencies:
Capital Inefficiency
The available liquidity remains inactive, indicating underutilization.
The liquidity provider (LP) counter-trades all positions, and the open interest (OI) is constrained to what the protocol could cover in total loss scenarios.
Properly assessing risk is challenging without sufficient price discovery, necessitating limitations on open interest, especially for volatile long-tail assets, to safeguard the LP depositors.
2. High Costs
Absence of price discovery mechanisms (oracle-based) prevents the protocol from accurately assessing risks, making it inherently a market operation.
As the liquidity provider (LP) counter-trades all positions, the platform fees must account for the risk of any losses incurred by the LP.
Fees for execution, borrowing, and funding are notably higher compared to centralized exchanges.
Due to the necessity of compensating the LP for the risk, a substantial portion (up to 70%) of the platform revenues is allocated to LPs rather than the project stakeholders.
3. Limited Asset Range
Including long-tail and volatile assets poses challenges due to the potential for losses to liquidity providers (LPs).
If listed, open interest (OI) faces significant limitations, and fees along with slippage are set high to counterbalance the associated risk.
4. Oracle Dependency (manipulation risk)
The vAMM model relies on external oracles to determine asset prices, exposing the protocol to the risk of manipulation, both in terms of prices and oracles.
According to blockthreat.io, Price Oracle Manipulation is currently the #1 DeFi attack vector:
5. Fragmented Liquidity
Fragmented liquidity is a challenge for vAMMs as a substantial pool is needed for trade execution.
With each new fork or iteration, liquidity is drawn away from existing protocols, leading to worsened overall liquidity conditions for traders due to fragmentation.
Moreover, this limitation hinders multi-chain deployments, as each new chain deployment necessitates the establishment of its unique liquidity.
Incentivizing liquidity proves expensive for protocols and is typically achieved through inflationary rewards, often at the expense of stakeholder value.
The market is filled with slightly modified forks that, despite gaining some adoption, cannot avoid the inherently inefficient aspects of the vAMM model.
Although there is evident product-market fit and demand for on-chain perpetuals, the current solutions have fallen short in delivering competitive trading experiences and attracting trade volume from centralized exchanges (CEXs) as effectively as the comparable spot market. GemaX addresses these challenges through its distinctive architecture and innovative approach to liquidity.
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