Work Description

The price of Optimism (OP) fell sharply in early November, dropping from highs above $1.30 on November 6 to as low as $0.79 on November 9. In the weeks since, prices have been on the rise, with OP hit $1.19 on December 14.

\n Analyze the network and diagnose some of the possible reasons for the sudden drop, and slow climb, of OP price in recent weeks. Are there any notable trends in users, transactions, or any other metrics that could explain these events? Note any patterns or outliers you see.

In this dashboard, we will check whether the volume of trading OP token has a direct relationship with the price of this token or not? In other words, with the increase in the price of OP, will buyers rush to buy it with the possibility of higher growth or not? On the other hand, sellers will sell their tokens with the possibility that the price will fall after receiving a reasonable profit?

To conduct this study, we proceeded in the following steps:

• First, we need to determine the daily price of the OP token. For this purpose we use the ‍optimism.core.fact_hourly_token_prices table, which contains the hourly price of the OP token, and it is enough to get the daily average of these numbers.
• Then we will get the number of daily transactions of all OP liquidity pools.
• After that, we will draw a linear graph of the daily price and volume of daily trades in one graph.
• We also draw a scatter plot of the price and volume of trades. The slope and the intercept of the regression line of this chart are also determined, and we draw the regression line to see whether this line can be fitted to the above chart or not.
• Based on the statistical functions of Snowflake, we obtain the correlation coefficient of price and volume and calculate the R-squared metric .
• Based on the above parameters, we will draw a conclusion about the main question of this research, i.e. the dependence of the volume of daily transactions on the price of the OP token.

Image Credit : Nomics & NewsBTC

Analaysis of Sushiswap OP Trades

As mentioned above, we start with SushiSwap exchange to check the relationship between OP token volume and price. First we get the daily price of OP, then we draw graphs and calculate the correlation coefficient.

Correlation Coefficient

A correlation of -1.0 indicates a perfect negative correlation, and a correlation of 1.0 indicates a perfect positive correlation. If the correlation coefficient is greater than zero, it is a positive relationship. Conversely, if the value is less than zero, it is a negative relationship. (source)

R-squared is a goodness-of-fit measure for linear regression models. This statistic indicates the percentage of the variance in the dependent variable that the independent variables explain collectively(source)

Image Credit : Slideshare

Key Findings

• The most important point that can be seen from the above graphs is that as the price of OP increases, the volume of OP trades also increases, but it seems that there is little relationship between these two variables, i.e. the volume of purchases and sales and the price of OP.
• The correlation coefficient of these two variables is about 0.54, which shows the relatively good dependence of these two variables, but the R-squared measure shows that only 30% of the changes in the volume of trdaes can be explained by the change in the price of OP.
• Thus, the relationship between the two variables, volume and OP price, can be seen in SushiSwap, but it is not very strong.
• Considering the much lower volume of OP transactions in SushiSwap compared to Velodrome, it is better to obtain the main result by examining Velodrome data.

Velodrome Analysis

We calculate the same analysis and statistics as in the previous section for the Velodrome. Of course, since the volume of OP trades in the Velodrome is much higher than in SushiSwap, more charts have been created for this section.

Can We Fit a Regression Line ?

In the last step of this analysis and according to the observation of the linear relationship between the two variables volume and price, we obtain the formula of the regression line of these two variables and draw it.

As can be seen in the graphs below, the drawn regression line is largely consistent with the distribution of price and volume data.

Takeaway

According to the this analysis, there is a relatively strong relationship between the OP price and the ETH price. The other factors, such as trading volume, do not show a strong relationship with the OP price.

Oh Yes! There is a very clear relationship between volume and price

• This time, considering that OP's daily trading volume is much lower than the previous section, the existence of a direct relationship between two variables, volume and price, is not so clear. The correlation coefficient is about 0.38 and the R-Squared measure, which is equal to 0.15 here, proves a week relationship between the two variables of trade volume and the price.
• According to the statistical criteria (R-Squared), only about 15% of the changes in OP trading volume are related to its price changes.

About Me

Author : Mojtaba Banaie

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Date of Analysis : 2022-12-23

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Twitter ID : @CryptoLizr

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E-Mail : mojtaba.banaie@gmail.com

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Discord : smbanaie#5528

Observations #1 - OP vs ETH Price

The above charts show a strong relationship between the Ethereum price and the OP price.

Considering that the ETH price is not influenced by the OP price and the value of R-squared in the selected range is about 0.6, we can conclude that about 60% of the changes in the OP price are influenced by the fluctuations in the Ethereum price.

OP vs ETH Price : Is there any Relation?

Since the OP token is based on Ethereum, as a first step, we examine the relationship between the price of the token and Ethereum to analyze the price of the OP token.