Event Study #3 | The Closing Price Is Not Always the Right Price

This is the third article in the series “Building an Event Study for the Vietnamese Stock Market”.

• Event Study #2 | Intraday Market Data: 7 Critical Signals Beyond the Close
• Event Study #1 | Building Powerful Research for Vietnam's Stock Market

In the previous article, Historical Price was viewed from a broader perspective.

A trading day is more than an opening price, a high, a low, and a closing price. Behind those numbers are trading activity, foreign investor flows, proprietary trading, and other information that can help describe what actually happened in the market.

But once the process of building an Event Study begins, a seemingly simple question appears:

If we want to calculate a stock's return, which price should we actually use?

The question is more important than it first appears.

An Event Study does not directly analyze a sequence of prices.

It analyzes returns.

And returns are calculated from prices.

That means a decision made at the very beginning can propagate through the entire research pipeline.

A Simple Example

Suppose a stock is trading at VND 100,000 on Day 1.

On the following day, its closing price is VND 90,000.

The calculation seems straightforward:

Return = 90,000 / 100,000 - 1 = -10%

The stock has fallen by 10%.

Now change one detail.

Suppose the company carries out a corporate action between the two trading days, causing the reference price to be adjusted.

Simply comparing the two observed prices may no longer represent the economic return experienced by an investor.

This is where adjusted prices become important.

A Change in Price Does Not Always Mean a Change in Value

Imagine a stock trading at VND 100,000.

The company announces a 20% stock dividend.

After the adjustment, the reference price may fall to approximately VND 83,333.

Looking only at the unadjusted price series, the chart appears to show a substantial decline.

But what actually happened?

The investor did not simply lose roughly 16.7% of the investment's value.

The number of shares held also changed.

Part of the price movement therefore came from the corporate action itself, rather than purely from a change in the market's expectations about the company.

This distinction matters in an Event Study.

The purpose of an Event Study is to examine how the market reacts around an event. The methodology does so by comparing actual returns with expected returns and using the difference to estimate abnormal returns.

If the return series already contains price movements that do not properly represent changes in the underlying investment, those effects can carry into the subsequent analysis.

So, Is close_price Wrong?

No.

That distinction is important.

close_price is not a wrong price.

It represents the closing price observed in the market on a given trading day.

The issue is its purpose.

If the question is:

“At what price did the stock close on that day?”

then close_price provides a direct answer.

But if the question is:

“What return did the stock generate between these two points in time?”

then we need to consider whether the price series needs to be adjusted.

This is the difference between an observed price and a research-ready price series.

Looking Inside DataCore's Historical Price

This is also why a Historical Price dataset should not necessarily contain just one price field.

DataCore's Historical Price dataset includes fields such as:

close_price

basic_price

adj_ratio

These are not simply three different names for the same number.

They provide different pieces of information that can be used to understand and process the price series according to the research objective.

When building a research pipeline, the important question is therefore not:

“Which field is the most commonly used?”

It is:

“What exactly does this field represent?”

From Price to Return

This is where the series makes an important transition.

Historical Price gives us a sequence such as:

Date          Price

01/07         100
02/07         102
03/07         101
04/07         105

But an Event Study needs something different:

Date          Return

01/07           -
02/07         2.00%
03/07        -0.98%
04/07         3.96%

Return transforms price information into a measure that can be compared across trading days.

Once stock returns are available, they can be placed alongside market returns.

From there, the research process can move toward:

Stock Return
      │
      ▼
Market Return
      │
      ▼
Expected Return
      │
      ▼
Abnormal Return

Daily stock returns are therefore a fundamental input in Event Study methodology. Classic methodological research has specifically examined the properties of daily stock returns and how those properties affect Event Study procedures.

But There Is Still Another Question

Even after choosing an appropriate price series, another question remains:

How should the return be calculated?

One common approach is the simple return:$$R_t = \frac{P_t}{P_{t-1}} - 1$$

Another is the log return:$$r_t = \ln\left(\frac{P_t}{P_{t-1}}\right)$$

These two measures are closely related for relatively small price movements, but they are not identical.

And this will be the focus of the next article.

Once we have answered:

“Which price should we use?”

the next question becomes:

“How do we turn that price series into a reliable return series for an Event Study?”

From a Price to a Research Dataset

Perhaps the most important takeaway from this article is simple.

In an Event Study, close_price is only the starting point.

An observed price needs to be interpreted in its proper context.

Corporate actions need to be considered.

Adjustments need to be understood.

Returns need to be calculated consistently.

Only then can stock returns become a reliable input for the next stages of the research process.

In other words:

Having Historical Price data does not automatically give us returns. And having returns does not automatically give us a reliable Event Study.

The quality of the research is built through these seemingly small decisions.

Coming Next

Event Study #4 | From Historical Price to Daily Return: Turning Price Movements into Research-Ready Data

The next article will take the price series discussed here and turn it into daily returns step by step.

That will give us the next building block needed to move from individual stock returns toward market returns - and eventually, abnormal returns.