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Cumulative Abnormal Return Calculator

Cumulative Abnormal Return Calculator helps analyze asset performance by comparing actual vs. expected returns. Perfect for event studies, it visualizes CAR insights clearly.

What is it?

The Cumulative Abnormal Return (CAR) Calculator is a tool designed to analyze stock performance by comparing actual returns versus expected market returns over time. It uses historical data to determine whether an asset outperformed or underperformed expectations, often used for event studies in finance.

Formula

The formula for Cumulative Abnormal Return (CAR) is:

CAR = Σ (Actual Return - Expected Return)

  • Actual Return: The stock’s real percentage return during a specific period.
  • Expected Return: The anticipated return based on market index, trend, or model prediction.

How to Use

  1. Input the date, actual return (%), and expected return (%) for each time period.
  2. Add as many rows as needed to include relevant data for the event period.
  3. Click Calculate, and the tool will compute the cumulative abnormal return and display results visually in a line chart.

FAQs

1. What is the purpose of CAR?

CAR assesses whether an asset experienced abnormal returns in response to a specific event (e.g., earnings announcements, mergers).

2. Can this calculator be used for event studies?

Yes! It’s designed to support event studies by evaluating abnormal returns before, during, and after an event.

3. How accurate is it?

Accuracy depends on the quality of your input data for actual and expected returns.

4. What’s the difference between CAR and AR?

  • AR (Abnormal Return) is for single time periods.
  • CAR aggregates AR over multiple periods to provide a cumulative measure.

Key Terms

  • Abnormal Return (AR): Deviation of a stock’s performance from its expected return in a given time period.
  • Expected Return: The return an investor anticipates based on market benchmarks or models.
  • Event Study: Research method evaluating the financial impact of events on security prices.
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