Insurance Depositor Strategy

I have recently analysed possible strategies for Tracer insurance pool depositors. The purpose of this analysis is to inform Tracer community members of ways in which they can achieve market exceeding risk weighted returns by utilising active management and market research.

Vision of the Insurance Pool Function

There is effectively two forces acting on an insurance pool deposit that determines if a depositor holds their position or withdraws. These forces are the return they receive and the fee they will realise on withdrawal . Both forces create more incentive for depositors to exit a position as the health of the pool increases. This will eventually lead to an equilibrium pool health, where the volume of deposits equals the volume of withdrawals.

My expectation for Tracer’s insurance pools is that there will be different equilibrium points for different markets, depending on the market’s non-systematic risks. Non-systematic risks are risks that do not directly correlate to an increased return. In Tracer’s insurance pools, these risks include the volatility of the underlying pool derivative, the liquidity risk of the market, the weighted average leverage multiple and the percentage of the pool that is system owned. We expect to see different equilibrium pool health for different levels of non-systematic risk because there will be less demand for insurers to participate in higher risk pools. This will result in the equilibrium point of the insurance pool being lower for riskier markets as depositors will only participate in the insurance pool if the pool yield is high. As the market matures, the system owned portion of the pool accumulates withdrawal fees and the pool moves towards its target.

Basic Investment Strategy

Making a deposit in a tracer insurance pool is an investment. Like any investment there are certain degrees of risk and return. Insurers can choose to invest in whatever markets satisfy their risk profile - with lower equilibrium pools presenting higher risks/returns and higher equilibrium pools presenting lower risks/returns. Further, those who research and develop strategies to maximise their risk weighted return will see the greatest benefit. In saying this, like the share market, anyone can make profits over time but, by looking deeper into the dynamics of the investment, these profits could be amplified or the level of risk taken could be decreased.

This could be done via a like for like comparison of markets of the same level of non-systematic risk. In this case, the insurance pool with a lower equilibrium would be preferred. This would maximise return for a given risk. Alternatively, a depositor could analyse pools with the same return (i.e. pool health) and then compare these pools based upon their level of non-systematic risk. In this case, the pool with the lowest level of non-systematic risk would be preferred. This would minimise risk for a given return. Creating a spread sheet and identifying the best investment options through such comparisons could be one way depositors could achieve market exceeding risk weighted returns.

Initially, it would be beneficial to deposit funds into a range of new, low risk markets to take advantage of high yields from low insurance pool health. Since the derivative is relatively stable and liquid, the chances of the insurance pool being drawn-on is low and thus, by making this investment, the insurer is making a high return for relatively low risk. This takes advantage of excess yields on offer up until the pool reaches equilibrium: the longer the pool takes to reach equilibrium the more the depositor will benefit.

It is worth noting that while the pool is below its equilibrium, there is more systematic risk (due to lower pool health) which is correlated to a higher investment yield. Assuming that all other pools are in equilibrium, the non-systematic risk of the pool will be lower than all other markets at the same pool health. Thus, the out of equilibrium pool presents the lowest risk option compared to all other pools offering the same return. This holds true up until the pool reaches its equilibrium.

Utilising the trading of insurance fund deposit tokens (iTokens) could also be a good way to close short-term positions without paying significant withdrawal fees. The trading of insurance deposits can only be beneficial to both sides when the loser is the insurance pool: it does not receive a withdrawal fee.

Key takeaways:

  • Analysis and comparisons will derive better investment decisions then passively allocating funds between all markets (Active management of funds preferred).
  • Diversification is preferred to eliminate systematic risk.
  • Take advantage of market lag: be the first one to deposit in stable market pool as they will generate high risk-adjusted returns until the market reacts. The slower the market is to react, the more benefit the depositor will see. This can be done as well for volatile markets but the risks are high as low insurance pool health gives the depositor high exposure to fees.
  • Deposit trading is preferred to withdrawing funds.

Identifying Pool Risks

Systematic risks are market wide risks which directly correlate with returns. As a result, they cannot be mitigated but rather form the basis of the market dynamics.

A key factor causing risk is the health of the insurance pool. A less healthy insurance pool leaves individual depositors more exposed to pool fees. However, since this factor is directly related to returns, it is a systematic risk and should not be analysed when making investment decisions. The only time it should be taken into account is when looking at an investors risk profile and assessing what degree of risk an investor is willing to take.

Additionally, there are four key non-systematic risks that can be analysed in order to deliver a more attractive insurance strategy.

The volatility of the underlying asset in the market is a key risk as larger fluctuations in market price will increase the likelihood of a liquidation event occurring for leveraged traders. All else held constant, insurance depositors should target the insurance pools of less volatile markets.

Proxy - Volatility can be measured using the standard deviation of historical asset prices. It would be best to calculate a trailing average standard deviation, putting more weight on recent volatility rather than outdated data.

When there is low market liquidity, it is more likely that a large liquidation event will see excess price slippage that could deplete an investors margin. While asset volatility risk increases the likelihood of a liquidation event occurring, the liquidity risk increases the likelihood of a liquidation event, resulting in insurance pool expenses.

Proxy - Analysing total volume traded compared to the order book depth at certain price deviations, such as 1% and 5% from market, provides a multiple which represents market liquidity. The lower this value is, the less slippage is likely to occur during liquidation.

Another non-systematic risk is the portion of the pool which is system owned capital. These funds act as a buffer from which expenses are drawn before that of the pool depositors. Hence, a higher proportional value of this buffer in a pool with the same return would reduce the non-systematic risk of the investment.

Proxy - This figure should be publicly available and may be represented as a percentage of total pool value.

Finally, the average leverage of the traders should be considered as it determines the exposure of margins to market price volatility. Specifically, markets with a higher average leverage are more exposed to price volatility and thus have a higher chance of a liquidation event occurring. Refer to table below.

Proxy - Total notional value of market divided by total margin value would yield the average leverage of that market without having to access leverage information of each individual trader.

10 investors 1 investor
2x leverage 11x leverage
$10 margins $10 margin
Leverage notional value = $100 Leverage notional value = $100
Insurance pool target = $1 Insurance pool target = $1
Lower maintenance margin Higher maintenance margin
Margin has less exposure to price movement Margin has more exposure to price movement
Lower chance of liquidation Higher chance of liquidation
Less risky insurance pool More risky insurance pool

Non-systematic risk evaluation - A hypothetical example

Insurance pool markets A-D have the same insurance pool health. In this case, A would present the lowest risk option for the return targeted.

For more information, refer to the link below:

Disclosure: This point system is completely hypothetical and was made solely to demonstrate one way in which investment decisions could possibly be made.


Great work!

Historical volatility is easy to calculate, but how is exactly Risk B measured in terms of the timeframe?
Historical trading volume v.s. snapshot of the historical Orderbook?

And if it is the AMM, I assume that the size is the proxy.

I am acutally not quite clear about that who onws the buffer part of the pool?