Aon Gains Ground on $500M Volume, Ranks 228th in Trading Activity

Generated by AI AgentAinvest Volume Radar
Wednesday, Sep 17, 2025 7:53 pm ET1min read
Aime RobotAime Summary

- Aon (AON) rose 0.40% on Sept 17, 2025, with $500M volume ranking it 228th in trading activity.

- The insurer's risk consulting division secured multi-year contracts in emerging markets amid evolving regulations.

- Analysts highlighted cost optimization and digital transformation efforts boosting investor confidence despite sector challenges.

- Favorable earnings multiples and strategic positioning contributed to the stock's resilience against market headwinds.

On September 17, 2025, , . The insurer’s modest outperformance came amid mixed market conditions and sector-specific dynamics affecting risk management and professional services firms.

Recent developments highlighted Aon’s strategic positioning in evolving regulatory landscapes, particularly in emerging markets where its risk consulting division has secured multi-year contracts. Analysts noted that the firm’s recent earnings guidance emphasized cost optimization initiatives and digital transformation projects, which have bolstered investor confidence despite broader sector headwinds. These factors, combined with a favorable earnings multiple relative to peers, contributed to the stock’s resilience.

To run this back-test accurately I need to pin down a couple of practical details: Stock

– e.g. All primary-listed U.S. stocks (NYSE + NASDAQ); A specific index constituent list (S&P 1500, , .); Another market/universe. Execution convention – common ways to avoid look-ahead bias are: Rank each day’s volume at the close, enter positions the next day at the open, exit at that day’s close (1-day hold); Rank at the open, buy immediately, exit at the next day’s open. Position sizing – equal-weight across the 500 names each day? (If not, please specify.) Once those points are clarified I can fetch the daily volume data, generate the daily re-balanced portfolio, and feed the signals into the back-test engine to produce the return and risk statistics.

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