Conférence d’Alexander Shestopaloff

Résumé

The Good, the Bad, and Latency: Exploratory Trading on Bybit and Binance.

We present the findings of a large-scale live trading experiment involving the placement of millions of market orders sent at a high frequency on two cryptocurrency exchanges, Bybit and Binance. We analyze the execution outcomes of these orders in comparison to the expected outcome based on the most recent snapshot of the Limit Order Book (LOB) at the time of order submission for two execution modes: one using market orders and the second using marketable limit orders aiming at the best price. Discrepancies between the actual and expected outcomes are due to intermittent LOB updates during a time span resulting from delays on the exchange, delays on the trader’s end, or communication delays between the trader and the exchange. We show these discrepancies are strongly correlated with market factors such as volatility, latency, and LOB liquidity. Notably, we find a consistent disadvantage to the trader, pointing to an adverse selection effect for taker orders: profitable orders (as measured by short-term future PnL returns) tend to achieve worse-than-expected outcomes, while unprofitable orders typically achieve their expected (adverse) outcomes. In the case of market orders, this translates to a worsening of fill prices, while marketable limit orders suffer from a substantial probability of failing-to-fill-immediately. Quantitative researchers who fail to take these effects into account face the familiar litany of underperforming in a live trading environment relative to stellar backtests. To address this concern, we propose parsimonious models to estimate an order’s probability of failing-to-fill-immediately (in case of a marketable limit order) and the worsening of its fill price (in case of a market order), allowing for greater accuracy when carrying out backtests and minimizing the discrepancy between backtest and realized live PnL.

Joint work with Jakob Albers, Mihai Cucuringu and Sam Howison

Preprint available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4677989