GLP Tail Risk
The market is falling again. If traders betted correctly and made massive gains when market falls, GLP holders would get rekted. This is known as the GLP tail risk since it’s considered a low-probability event. And I’ll try to assess it in this article. But first, let me explain the relationship between traders and GLP holders. The best way to do it is through an example, so I placed a trade and got myself liquidated. The screenshot below shows the details. I paid 30c borrow fee and $5 liquidation fee. My PnL was -$5.88. The 30c borrow fee and $5 liquidation fee and my $5.88 loss were to be paid out to GLP holders and GMX stakers as ETH/AVAX rewards.
If you are a trader, you probably only care about your effective PnL after subtracting borrow and liquidation fees. In my example, that’s -$11.18. But if you are a GLP provider, you will also want to care about traders’ PnL before borrow and liquidation fees because it affects GLP price1. So I analyzed traders’ daily PnL data, both before and after borrow and liquidation fees, of the past 353 days. The method I used is called the sampling distribution of the sample mean. If you don’t know what it is, I suggest you look it up because it’s a fundamental knowledge point in statistics. Khan Academy has some good videos on it.
Arbitrum
Arbitrum GMX traders on average lost $98,121 per day before borrow and liquidation fees in the past 353 days, and $231,184 per day after fees.
Before accounting for borrow and liquidation fees, for every 1,000 simulations of possible futures, there are 4 of them where traders will on average make money. And for every 100,000 simulations, there are 3 of them where traders on average make more than $50K per day.
After accounting for borrow and liquidation fees, the chances for traders to make money collectively is close to zero.
Avalanche
Arbitrum GMX traders on average lost $35,329 per day before borrow and liquidation fees in the past 231 days, and $94,014 per day after fees.
Before accounting for borrow and liquidation fees, for every 1,000 simulations of possible futures, there are ~7 of them where traders will on average make money. Yet the chances of traders on average making more than $50K per day is almost zero.
After accounting for borrow and liquidation fees, the chances for traders to make money collectively is close to zero.
Data & Code
Arbitrum Data (2021-09-01 ~ 2022-08-19) and Python Notebook
Avalanche Data (2022-01-07 ~ 2022-08-25) and Python Notebook
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According to KR from GMX’s team, the contracts read the current PnL of all outstanding traders and reflect it in the price to avoid massive movement of GLP price when positions close. So in my trade example, the PnL, leading up to -$5.88, was continuously baked in GLP’s price.