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. , ranking 100th among stocks traded that day. The travel booking giant's performance reflected mixed market sentiment toward the sector, as investors balanced optimism over post-pandemic travel demand with concerns about macroeconomic headwinds.
Recent analyst commentary highlighted Booking's strategic shift toward higher-margin services like dynamic packaging and ancillary offerings. While the company's third-quarter revenue guidance aligned with Wall Street expectations, investors remained cautious about its exposure to discretionary spending amid rising interest rates. , suggesting short-term positioning by both retail and institutional traders.
Technical indicators showed mixed signals, with the 50-day moving average crossing above the 200-day line in a potential bullish pattern. However, options market activity revealed a bearish skew, . This divergence underscored market uncertainty about the company's ability to maintain profit margins amid competitive pressures from alternative accommodation platforms.
To run this back-test in a robust, reproducible way I need to pin down a few practical details that were not specified: 1. Universe • Do you want all U.S. listed common stocks (NYSE + NASDAQ + AMEX) that have been active since 2022, or a narrower universe such as the current S&P 500 constituents? • Should OTC, ADRs and preferred shares be excluded? 2. Execution convention • Standard practice is to rank each day on the prior day’s trading-volume, enter positions at the next session’s open, and exit at that session’s close (1-day holding period). Is that acceptable? • If you prefer same-day execution (buy at today’s close, sell at tomorrow’s close), please let me know. 3. Position sizing • Equal-weight each of the 500 stocks (i.e., , rebalanced daily – is that the intended sizing rule? 4. Transaction costs / slippage • Should we include any commission or a fixed bps slippage assumption? Once these points are confirmed I can generate the data-retrieval plan and run the back-test.

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