USDT and USDC transfer-value distributions are heavy-tailed with fitted power-law exponents around 1.4 to 1.8, and smart-contract-to-smart-contract transfers show consistently larger exponents than transfers involving regular accounts.
Inverse Cubic Law for the Probability Distribution of Stock Price Variations
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abstract
The probability distribution of stock price changes is studied by analyzing a database (the Trades and Quotes Database) documenting every trade for all stocks in three major US stock markets, for the two year period Jan 1994 -- Dec 1995. A sample of 40 million data points is extracted, which is substantially larger than studied hitherto. We find an asymptotic power-law behavior for the cumulative distribution with an exponent alpha approximately 3, well outside the Levy regime 0< alpha <2.
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Scaling laws of Stablecoin Transactions: Evidence from USDT and USDC on the Ethereum blockchain
USDT and USDC transfer-value distributions are heavy-tailed with fitted power-law exponents around 1.4 to 1.8, and smart-contract-to-smart-contract transfers show consistently larger exponents than transfers involving regular accounts.