In order to offer perpetual future derivatives and provide the ability to long and short assets, and exchange needs to be willing to counter bet against the end user/trader. This means that similar to the business model of a casino, an exchange takes a loss whenever traders profit while the opposite interaction is true as well. This of course requires not only a large investment to bootstrap initial liquidity in the market from the party providing these financial instruments, but also incurs a non zero risk and liability on their behalf. That is to say, a large enough loss compromises the financial well being and even viability of the exchange to continue offering these services.
Traditional finance offsets this risk in stock exchange markets by letting users of the platform become the market makers themselves and bet against each other with Call/Put Options instruments. In this system, stock broker platforms simply become the middleman guaranteeing the execution of these transactions and settling the outcome of these trades. I believe the principles of this model can be easily encapsulated by smart contracts to work with decentralized exchanges and give them the ability to offer leveraged short and long trading to their users.
In the system I’m proposing, the market for an individual asset would consist of two interconnected but separate pools. One of which would be a pair of the stable coin collateralized debt position alongside the synthetic short token of the underlying asset, while the other pool would be the opposite long equivalent. The ratio of these two tokens in each pool would represent the amount of leverage chosen by the user, the percentage of which would also set a liquidation point, were the trade to play against the trader.
For example, if one were to enter the synthetic iBTC market at a price of $40,000 to open a 5x leverage short with a $2,000 collateralized debt position, 10,000 short tokens would be locked into the pool alongside the trader’s CDP with a liquidation point of $48,000. If the price of BTC were to move against the trader by raising in price and reaching liquidation, their collateral would be forfeited and used to pay each member of the long pool with a percentage representing their amount of long tokens against the total supply of active long tokens currently inside the pool.
In this instance, a long trader holding 1,000 tokens of a total of 100,000 would receive 1% of all positions being liquidated in the opposing short pool. Additionally, traders would also be able to keep adding collateral to their positions in order to decrease their leverage ratio and increase their liquidation point. In this model, short traders are essentially betting against long traders and vice versa, requiring no liquidity investment from the exchange while still accruing a nominal transaction fee for maintaining the platform.
The system outlined above serves as a general summary of this theoretical platform service, but further research and parameter modeling is still being developed in order to optimize the potential of bringing this capability to market.
Other things to consider:
The health ratio of an open trade, if trading against the user but not reaching the liquidation point quite yet could limit the amount of rewards they receive of opposing pool liquidations. Following from the previous example, if the price of BTC is $44,000 any long positions being liquidated at that point would only reward our hypothetical short trader as if they only hold 5,000 short tokens since their position is 50% towards being liquidated themselves. Perhaps the alternative could be true as well in which a positive health ratio would increase the number of their synthetic tokens in much the same but opposite way.
Unlike traditional financial systems in which the leverage multiplier directly equates to the multiplier of profits as well, in this model that wouldn’t be the case because the multiplier serves only to increase the amount of short/long tokens a given trader holds in relation to their collateralized debt position. Since that amount is used to calculate the percentage of all pool profits they are entitled to it becomes a lot harder, perhaps impossible, to calculate risk to reward before entering a position in such a dynamic reward model.
Initiating every individual market might present some challenges up until a point in which a sort of market equilibrium between longs and shorts is established, requiring the need for initial liquidity provision or a grace period to allow the build up of countering trades. Though in theory, if a market initiates in a very lop sided iteration, it would be an incentive in and of itself to counter trade against the crowd because the rewards would be split among a much smaller pool of participants.
This is very much a half baked idea I was messing with in the middle of a flight with no Wi-Fi and only the Indigo white paper keeping me company for inspiration. I am very excited to at the very least initiate this conversation within the community and hopefully receive any help in improving this model from more knowledgeable members as I think the full economic implications and potential prototyping are probably beyond my depth.