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Tiny Trades, Big Questions: Fractional Shares

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This paper investigates fractional share trading. Using a latency-based method for identifying a large sample of fractional share trades, we find that high-priced stocks, meme stocks, IPOs, SPACs, and popular retail stocks exhibit considerable numbers of tiny trades. We surmise this is due to dollar-based order entry, with many tiny trades being fractional components of larger orders. We show that fractional retail trades identified by our RHDW-FT metric are predictive of future liquidity and volatility, suggesting an information content to tiny trades. We provide evidence that our metric is a useful proxy for capturing app-based retail trading. We identify how data and reporting protocols preclude knowing the extent of fractional share trading, inflate volume data, and provide censured samples of these off-exchange trades.
Title: Tiny Trades, Big Questions: Fractional Shares
Description:
This paper investigates fractional share trading.
Using a latency-based method for identifying a large sample of fractional share trades, we find that high-priced stocks, meme stocks, IPOs, SPACs, and popular retail stocks exhibit considerable numbers of tiny trades.
We surmise this is due to dollar-based order entry, with many tiny trades being fractional components of larger orders.
We show that fractional retail trades identified by our RHDW-FT metric are predictive of future liquidity and volatility, suggesting an information content to tiny trades.
We provide evidence that our metric is a useful proxy for capturing app-based retail trading.
We identify how data and reporting protocols preclude knowing the extent of fractional share trading, inflate volume data, and provide censured samples of these off-exchange trades.

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