Intraday patterns of price clustering in Bitcoin

In this study, an investigation is conducted into the phenomenon of price clustering in Bitcoin (BTC) denominated in the Japanese yen (JPY). It answers two questions using tick-by-tick data. The first is whether price clustering exists in BTC/JPY transactions, and the other is how the scale of price clustering varies throughout a trading day. With the assistance of statistical measures, the last two digits of BTC price were discovered to cluster at the numbers that end with ’00’. In addition, the scales of BTC/JPY clustering at ’00’ tended to decline at the specific hour intervals. This study contributes to the emerging literature on price clustering and investor behavior.

Accounting Information Quality and the Clustering of Stock Prices

The foundation of economic theory is based on the premise that prices will converge to their equilibrium value. However, prior research has documented that stock prices cluster on round pricing increments. In this study, we develop and test the hypothesis that audit quality and the management of earnings—both of which affects the information environment of the firm—influence the degree of price clustering. Results show that firms with Big 4 auditors have less clustering in their stock prices while firms with higher abnormal audit fees, more discretionary accruals, and firms that tend to manipulate earnings have a higher degree of price clustering. These findings support our hypothesis and suggest that accounting information quality helps explain the price clustering anomaly and subsequently influences the efficiency of financial markets.

Price Clustering After the Introduction of Bitcoin Futures

Economic theory suggests that introduction of derivative contracts can improve the informational efficiency of the underlying asset prices (Danthine, 1978). In this study, we examine the impact of the introduction of Bitcoin futures on price clustering in Bitcoin. Our findings suggest that price clustering in Bitcoin meaningfully decreases post the introduction of its futures contracts.

ANTITRUST DAMAGES IN FINANCIAL MARKETS

I briefly review the standard regression methods used to estimate damages in antitrust actions, and I analyze how these would be applied to cases in financial markets. I consider applications to three different financial market cases. The first is the NASDAQ odd-eighths litigation, where existing antitrust methods closely resemble the analyses published in the academic literature on this issue. The second type of case is bond market antitrust litigation, where the expert faces an additional hurdle because they have to estimate bid-ask spreads. The third type of case is related to the LIBOR manipulation scandal. I analyzed why existing methods provide a poor fit for the LIBOR damage calculations. Lastly, I evaluate IPO issuance fees as an example of price clustering in financial markets that has not let to antitrust litigation.