0xreviews / crvusd-arbitrage-analytics

crvUSD Arbitrage Analystics

This tool visualizes crvUSD LLAMMA pool's arbitraging process and conducts statistical analysis.

Getting Started

• Install

poetry install

• Generate arbitrage tokenflow chart by transacation hash (dot file and png file)

poetry shell

python crvusd_arbitrage_analytics/tokenflow.py 0x0806a484daf46bf1948185fac7f13613268da0969d638bc87dc934eefeab6b13

Basic Use

Fetch all arbitrage data and automatically classify, statistics, and generate tokenflow chart.

0. Fetch all arbitrage transacation data, and collateral price data, save raw data in data/original
1. Wash raw data, save csv file and json file in data/csv/tokenflow_data_[collateral], data/json/tokenflow_data_[collateral]
   • Automatically identify the behavior type of each token transfer
   • Log all swap pools
   • Group all tx steps, e.g. flashswap, sfrxETH stake/unstake, WETH deposit/withdraw, token swap in/out
2. Classify all arbitrage tokenflow
3. Generate statistical graphs
4. Generate tokenflow chart for each arbitrage category

python scripts/0_fetch_data.py
python scripts/1_wash_data.py
python scripts/2_sort_data.py
python scripts/3_draw_graph.py
python scripts/4_statistics_data.py

Results

Some statistical graphs and token flow charts (statistics date: 2023-08-09):

Statistics

Daily revenue and gascost

revenue volume scatter

sfrxETH Dominance

wstETH Dominance

WBTC Dominance

WETH Dominance

Tokenflow

sfrxETH LLAMMA Pool

The three most frequently used arbitrage methods:

wstETH LLAMMA Pool

The three most frequently used arbitrage methods:

WBTC LLAMMA Pool

The three most frequently used arbitrage methods:

WETH LLAMMA Pool

The three most frequently used arbitrage methods:

Daily hard-liquidations

More data and picture results can be seen in results folder.