MetaversePRO DAO: Stability analysis of its early expansion phase

Shout out to the author: Ouija#2621

Disclaimer:

This has been written for informational purposes only and should not be constituted for investment advice or be relied upon by any individual to make investment decisions. The author has invested in META.

TL:DR

1. META’s 5d rolling beta and correlation shows the price of META to be dramatically influenced by the price movements of BTC, ETH and BNB. (There is not enough data to derive any meaningful information from the 30d rolling beta and correlation).
2. The daily volatility (over rolling 5d periods) is greater than BTC, ETH and BNB, however it has moved from being 30% more volatile to 15%. It is still magnitudes larger than stablecoin incumbents which suggests weak price stability.
3. Price comparison of META to stablecoin incumbents reveals smaller drawdowns when BTC, ETH or BNB experience negative returns. However, this does not mean that META is more effective in preserving capital in general as it is still too young. When compared to traditional stablecoins it is objectively less effective.
4. META in its current form is not exhibiting the characteristics of a stable asset.

Purpose

The primary purpose of this analysis is to use a number of metrics in order to highlight META’s characteristics and its behaviour during the early ‘expansion phase’ by comparing stability to selected stablecoins (e.g. USDT, USDC, BUSD, DAI) as well as Bitcoin (BTC), Ethereum (ETH) and its native chain token BNB. There is no expectation of META’s price to be stable in its current phase, however this analysis provides potential indicators of the protocol’s current behaviour in the context of its return profile to date. The analysis will be repeated during the ‘mature phase’ to further critique it’s intended objective. The secondary purpose is to justify the potential allocation of a percentage or nominal amount of the protocol’s treasury reserves to whitelisted protocols with the aim to bolster revenue to the DAO’s treasury in a risk efficient way with a view to ensure future stability.

MetaversePRO, “player one, begin”

MetaversePRO is a fork of OlympusDAO. Choosing to operate on the Binance Smart Chain (BSC) due to the phenomenal growth it has experienced from artworks, to GameFi, to DeFi. MetaversePRO is committing itself to building a fair token-issuing institution that functions to be accepted across the arising Metaverse.

With MetaversePRO becoming integrally linked to the GameFi world and with GameFi serving as a key entry-point for the Metaverse it will be positioned as an indispensable partner resolving early-stage problems Metaverse projects encounter. This interchange creates a long-term and mutually beneficial relationship.

While functioning as already mentioned MetaversePRO also benefits from assets held in their treasury allowing further appreciation and for rebasing of META.

MetaversePRO aims to achieve stability by the creation of its own stablecoin, “backed” by a pool of assets owned by the protocol opposed to being “pegged” to an external currency. Two broad phases include:

1. The expansion phase: The protocol focuses initially on increasing the issuance/supply of META to bootstrap the network while incurring price volatility
2. The Maturation phase: The protocol focuses on managing the supply/issuance of META to stabilise the price

Due to the protocol being in its infancy and ‘expansion phase’ there is no expectation or price stability. To reiterate before continuing, we will attempt to observe and analyse the behaviour of META return profile to assess price stability using the following metrics:

• BTC, ETH and BNB beta
• META correlation with BTC, ETH and BNB
• Daily volatility
• Drawdown analysis — Over time
• Drawdown analysis — Current point in time

Further comments to consider:

• The number of daily observations of META’s price is a lot smaller than BTC, ETH and BNB. Any analysis with data points more frequent than ‘daily’ would result in different takeaways.
• All analysis include data to the 17th of December 2021.
• There is no analysis between centralised and decentralised stablecoins, some outputs however provide insight into their relative effectiveness in the relevant timeframe.

BTC, ETH and BNB beta

Metric purpose: The beta metric determines the sensitivity of the price return of one asset (dependent) against the price return of another asset (independent). Traditionally this metric is used to assess the influence of an equity index (Nasdaq, etc.) can have on an individual stock. A result greater than 1 implies increased sensitivity to the index, suggesting a leveraged-market play. A result less than 1 implies decreased sensitivity to the index, suggesting a diversification play.

Application to crypto: Due to the size of BTC’s market cap, when compared to the broader market (~40%), it has a great influence on the price movements of non-BTC tokens. As a result BTC is viewed as the market/independent asset in this analysis. ETH has also been used as a proxy again due to its large market cap and being the apex altcoin. Lastly BNB was used due to MetaversePRO residing on the Binance blockchain.

Expectation: The purpose of MetaversePRO is to create a stablecoin that is not impacted by external forces. In this phase one may expect to see META’s ‘BTC beta’, ‘ETH beta’ and ‘BNB beta’ fluctuate less and a movement towards zero.

Takeaways:

Chart 1a depicts a sharp and erratic first 15 days which has begun to trend towards zero already, this implies that META’s price is showing signs of becoming less influenced by the movements of BTC, it shows more desensitisation in regard to ETH and BNB.

META’s correlation with BTC, ETH and BNB

Metric purpose: A similar metric to beta, by identifying the correlation between price returns of two assets one can assess their co-relation to each other. A result of 1 means perfect correlation while a result of -1 means they are perfectly negative correlation.

Application to crypto: Using BTC, ETH and BNB to represent the ‘market’ we can test META’s price return correlation.

Expectation: A correlation trending towards 0 between BTC, ETH, BNB and META.

Takeaways:

Chart 2a depicts a still fluctuating price correlation between META’s price, BTC, ETH and BNB, this implies it is still influenced by these large-cap tokens. In future analysis this should be expected to trend towards zero to show a reducing influence.

Daily volatility

Metric purpose: To determine the mean/average variability/fluctuation of an asset’s price, over a set period of time. Results that a larger in size denote greater volatility and thus less optimal for a stablecoin.

Application to crypto: Currently the crypto market features a number of ‘stablecoin’ solutions, each with their own risks (e.g. varying levels of centralisation, smart contract risk, etc.). By comparing META’s daily price volatility against existing incumbents (USDT, USDC, BUSD, DAI) as a benchmark one can somewhat assess its effectiveness as a stable/low-volatility asset. BTC, ETH and BNB have been included for further reference.

Expectation: META’s daily price volatility to be trending towards (+/- 0.5), approaching similarity in incumbent stablecoin solutions.

Takeaways:

Chart 3 depicts the daily volatility (over rolling 5d periods) of META, BTC, ETH and BNB. It implies that META’s daily price is much more volatile relative to BTC, ETH and BNB. However, META’s daily volatility has been modestly declining.

In chart 4 and with no surprise META’s daily volatility is seen to be magnitudes larger than that of compared stablecoin solutions. However, again we see a reduction in volatility.

By observing the daily volatility of the mentioned stablecoin solutions in chart 5a (using a rolling 30d period) we can objectively see the daily volatility META is aiming for, being +/- 0.5% around its average.

Drawdown analysis — Over time

Metric purpose: This metric may be used to visually represent the magnitude of historical drawdowns, this allows for highlighting of the trends between these drawdowns. An example could be that assets with a small quantity and magnitude of drawdowns serve to better preserve its value relative to another asset with larger quantities/magnitudes of drawdowns. In theory these drawdowns should become less frequent and of smaller magnitudes over time allowing one to extrapolate that the asset in question is becoming more stable.

Application to crypto: It is easy to conclude the limited ability of BTC, ETH and BNB to preserve value currently, conversely stablecoins are seen as a relatively stable crypto asset. Consideration should be given to the infancy of there solutions and the unavoidable and frequent drawdowns should be expected, however in this phase it is important the magnitude of drawdowns are small.

Expectation: The asset price exhibiting drawdowns of small magnitude.

Takeaways:

Drawdowns by stablecoins although frequent, as seen in Chart 6, one may conclude that META’s price is not yet stable enough to compete with these incumbents. When META moves into its ‘maturation phase’ it should aim to ideally limit drawdowns to ~0.5%.

Drawdown analysis — Current point in time (17th Dec 2021)

Metric purpose: The table below consists of a number of metrics with the intent to demonstrate a more pragmatic/less statistical approach to analysing stability, achieved by logging the daily returns and calculating the quantity of magnitude of the asset price drawdown since the assets inception.

Application to crypto: This analysis is also applied to incumbent stablecoins (USDT, USDC, BUSD, DAI) as well as BTC, ETH and BNB.

Expectation: An asset compared to fiat experiencing no drawdowns is unrealistic. Exceptions include a high percentage of observations where the return price was zero; small drawdowns when BTC exhibits a drawdown (generally and when drawdown thresholds are applied, e.g. greater than 5%, 10% and 15%).

Takeaways: In reference to the table below (data and calculations linked here).

• Rows 3–8: Aims to highlight the number of ‘zero’ returns. The USDT is the benchmark with the highest number of observations and high proportion of zero returns (Cell D8 at 32.5% of all observations). META recorded a much smaller amount of ‘zero returns’ (C8 at a 0%), however this metric should be discounted as it doesn’t take into account when the ‘zero’ returns were achieved. An example would be an asset such as ETH which was not frequently priced in its infancy so may still show a high number of ‘zero’ returns.
• Rows 9–11: Shows the amount of daily return observations that exceeded a set of drawdown thresholds. Close to 50% of META’s daily returns have been worse than -5%, this indicates a lack of price instability in addition to a relative basis, this frequency is triple that of the next asset (Cell H9 — BNB).
• Rows 12–14: Measures the average asset return when BTC has a particular magnitude of drawdown. Stablecoin average return profile is strong, with centralised stablecoins presenting a marginal positive return (Cell 12:F14) and the decentralised stablecoin DAI having a marginal positive/negative return (Cell G12:G14). Note META’s price will on average have a positive return when BTC incurs a drawdown over set thresholds (C12:C14), this may be due to the infancy of the protocol, perhaps early protocol stability or a reflection of BNB experiencing a typically smaller negative return serving to amplify its effects on META, conversely an observed negative return would indicate weak stability.
• Rows 15–23: Categorises the amount and proportion of positive, negative and ‘zero’ returns (over the life of the chosen asset) when BTC’s daily return is negative. The importance of this is to view the average return during a negative BTC return. The proportion of META’s return observation between negative (Cell C20) and positive (Cell C17) show doubling in positive returns during a negative BTC return, implying a negatively correlated relationship between the two in this ‘expansion phase’, based on this metric (more data is required to increase the reliability of this correlation). Stablecoins broadly exhibit the same negative and positive return observation; it can be deduced that there is effectively no relationship between them and BTC when BTC incurs a negative return (Cell D17-G17 and D20-G20). It is META’s large magnitude of average returns (Row 18 and 21) in both circumstances which imply a weak stability relative to stablecoins. An ideal asset would have a greater portion of returns in the ‘zero’ return category (Row 23), however note the limitation stated in the first bullet point.

. . . . .

Conclusions:

Some key takeaway points from the above analysis:

1. When applying a more statistical approach to META’s daily return series, a rolling 5d beta (insufficient records of data to acquire a rolling 30d beta) and correlations imply that although volatile META’s price is trending towards stability by minimising the influence that the price movements of BTC, ETH and BNB have on it, which is a key characteristic of a ‘stable’ asset.
2. To be stable, a holder of the asset must have confidence that the asset’s relative price stability will hold during a given time period until which they choose to use that asset (e.g. for transaction purposes or redeployment). Assets with a low daily volatility is the desired objective. Based on this metric, stablecoin incumbents are superior relative to META due to having lower daily volatility.
3. Similar to a ‘stable’ asset exhibiting low daily volatility, a stablecoin’s ability to preserve its value is equally important so that an investor can be confident it will hold its value until such a time they choose to utilise said asset and maximise its value. An example can be seen in the table below, which hypothetically provides an example of the impact of redeploying stable assets when value is preserved. Here we see BTC incur a market drawdown (e.g. -40%) and also drags down an inferior stable asset (e.g. Stable asset 2, -15%), while there would be a degree of value preservation to the order of 25% (-15% minus -40%), it is not as desirable as if the stable asset had completely preserved its value (e.g. Stable asset 1). Therefore, the act of holding superior stable assets in the example would’ve increased the effectiveness of redeployment and been able to capture an extra 0.3 BTC.

Currently how much weight one places on the metrics used in this analysis and the timeframe of data is open to interpretation in reference to the asset’s stability. To take a pragmatic view, confidence in this asset will likely be derived from its ability to maintain a stable price and preserve value until a time in which one chooses to use such asset. On this basis, one may conclude that in its current form META is not representing stability. However, it is important to note that this is NOT expected in the protocol’s ‘expansion phase’. We may glimpse the possibility of the future of this META as seen with OHM’s continued success and trajectory towards stability. The difference seen in the nascent stages of META compared to OHM seems to be the utilisation of treasury assets to further increase the DOA’s revenue thus strengthening the respective project’s trend towards the desired objective.

Brief versions of this exercise will be repeated in the future to assess whether investor behaviour or market forces change or continue with the trends round above. A more detailed analysis will be completed when the protocol transitions to its ‘mature phase’.

Game on!