# Understanding stock reactions to quarterly financial results announcements

This study delves into the dynamics of stock price movements in response to financial results announcements. The objective is to investigate how stock prices of companies are affected on the announcement day and the subsequent seven days following the release of financial results. Using historical stock price data and financial results announcement dates, this study examines whether there is a discernible pattern in how stock prices react to different types of financial results.

The study includes banking and financial services, pharmaceutical, and power, healthcare, and FMCG sector stocks listed on the Bombay Stock Exchange and Nifty-50 indexes. Period of the data is April 2018 to March 2023. Further, event window considered is announcement day (T), two days preceding the announcement day (T-1 and T-2), and 7 days following the announcement day (T+1, T+2, T+3, T+4, T+5, T+6, and T+7). Multiple statistical analysis methods are applied, such as trend analysis, T-Test and Anova using Python.

### To identify the variables relevant for calculating the impact of returns announcement on stock prices

**Purpose:** Perform an empirical review of recent studies to identify variables for creating a stock price prediction model.

**Method:** Empirical review of 40 past studies conducted in the last 10 years. The findings will be presented in the form of a table displaying the parameters:

- Author/s (year)
- Aim of the study
- Methodology
- Key variables
- Findings
- Limitation of the study

**Requirement:** Less emphasis on expression of theory, more on application of statistics. Therefore, the chosen studies must contain empirical evidence and not be based on theory alone. Prior knowledge of financial research, systematic and empirical reviews, and statistical applications is recommended.

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### To create a prediction model for stock price movement after quarterly results announcement for the Bombay Stock Exchange

**Purpose: **Create a model that predicts stock price movement after announcement of quarterly results to maximise investors’ returns.

**Method:** This involves a two-stage analysis.

**Stage 1-** to assess the impact of event (result announcement) on stock price movement. Event study methodology using the result announcement date as ‘T’, and a 5-day event window (T-2, T-1, T, T+1, & T+2). After identifying the variables in Goal 1, we will calculate value of daily stock return and daily market return. Then we will calculate the:

- Expected return
- Abnormal return
- Average abnormal return
- Standard error

**Stage 2-** to compare the impact for different quarters. Here we want to see if the markets react differently for Q4 than Q1, Q2, or Q3. This calculation will include additional data like P/E ratio, D/E ratio, and market cap data. It will include the following steps:

- Calculate the %age change in financial return (Q-o-Q) and stock price
- Trend analysis for visualization
- Classify the stocks as ‘loss’ or ‘profit’ depending upon the change
- Calculate the absolute change
- Apply ANOVA to compare the absolute change
- Creating a prediction model for two-day movement post result announcement

**Requirement:** Sound knowledge of technical analysis, working knowledge of Python and STATA software.

To contribute and publish select a pending milestone.

There are no completed milestones.