Event Study Market Model Calculator

Event Study and the Market Model Calculator

Event Study Market Model CalculatorEvent studies find wide application in research in the fields of finance, economics and law. In finance and economics research, event studies are employed to investigate the effects of announcements of events such as changes in regulations, shocks in the macroeconomic environment, or company initiatives on stock prices or firm value. Event studies may, for example, be used to investigate the effects of board reforms, compensation, workplace safety, changes in taxation, pandemics, dividends and repurchases, equity and debt issuance, or mergers and acquisitions on stock prices. In the field of law, event studies have been used to determine damages in legal liability cases. Have you been wondering where you can find event study help, market model help, or an event study market model calculator? If so you have probably landed in the right place.

Event studies in the field of finance and economics often involve calculating statistics such as stock or security returns, market returns, expected returns, Cumulative Abnormal Returns (CARs), Averaged Cumulative Abnormal Return (ACAR), Average Abnormal Returns (AAR) (alternatively called averaged abnormal returns), and Cumulative Average Abnormal Return (CAAR). Stock returns and market returns can be computed the simple way or with compounding. Calculating the aforementioned  characteristics or statistics can be made easier and faster with the help of an event study market model calculator.

In event study theory, the market model among other models are applied towards determining the expected return based on the efficient market hypothesis. The other models that are commonly used to determine the expected return include the mean adjusted return model, the market adjusted returns model, the market model with Scholes-Williams beta estimation, the market model with GARCH(1, 1) and EGARCH(1, 1) error estimation, the Fama-French 3 Factor Model, and the Fama-French-Momentum 4 Factor Model. The market model, which apparently is the most commonly used model, is sometimes referred to as the Risk-Adjusted Returns Model (since it takes into account market risk), the Ordinary Least Squares (OLS) market model (Fama et al., 1969), the classic market model, the usual market model, or the basic market model.

The market model suggests that the return on stock i at time t is solely influenced by the market return at time t. When using the market model, expected returns are predicted through an OLS regression analysis that regresses stock returns on market returns (usually returns on a market index) over a predetermined estimation window. The relationship between the stock and the reference or benchmark index that has been used in the analysis is described by two parameters derived from the regression analysis: alpha (α) and beta (β). Alpha and beta are computed using data relating to the estimation period.

The expected return, E(Rit|Xt), is predicted using the model:

𝑬(𝑹𝒊𝒕|𝑿𝒕 ) = 𝜶𝒊 + 𝜷𝒊(𝑹𝒎𝒕) +𝜺𝒊𝒕  

Where α and β are constants in the OLS regression model for i stock,

Rmt is the rate of return on the reference index (such as the FTSE 100, FTSE 250, FTSE All-Share, NYSE Composite (DJ), NYSE U.S. 100) on day t,

εit is the error term.

Calculate Expected returns, Abnormal returns, Cumulative Abnormal Returns  Easily and Other Event Study Statistics

When performing an event study that applies the market model, you will most likely need to compute stock returns or securities returns, expected returns (ERs), abnormal returns (ARs), Cumulative Abnormal Returns (CARs), Averaged Cumulative Abnormal Return (ACAR), Average Abnormal Returns (AAR) (alternatively called averaged abnormal returns), and Cumulative Average Abnormal Return (CAAR). Additionally, you will likely need to determine descriptive statistics such as means, standard deviations, medians, modes, minimums, and maximums for different characteristics (such as abnormal returns and cumulative abnormal returns). Computing these statistics can be boring, tedious, time consuming, and confusing especially when several firms/securities and long time periods are involved. However, an event study market model calculator makes computing these statistics easy, fast, and accurate. You can thus rely on an an event study market model calculator to compute expected returns, abnormal returns, cumulative abnormal returns and other event study statistics easily, fast, and reliably.

The event study market model calculator or simply, the market model calculator, is a Microsoft excel file that performs several functions and can thus provide invaluable event study help, market model help, and expected return help. It is designed to be a:

  • Market model calculator
  • Event study calculator
  • Stock returns calculator
  • Benchmark market returns calculator
  • Market model alpha and beta calculator
  • Expected returns calculator
  • Abnormal returns calculator
  • Cumulative abnormal returns calculator
  • Averaged cumulative abnormal returns calculator
  • Average abnormal returns calculator (Averaged abnormal returns calculator)
  • Cumulative average abnormal return calculator

The event study market model calculator can be used to compute the different statistics for a maximum of 100 companies/securities/stocks over several time periods (days/weeks/months) around the announcement. The calculator relies on the OLS market model to determine expected returns and abnormal returns. Specifically, it computes the following statistics:

  • Stock returns
  • Benchmark/reference/market returns
  • alpha and beta coefficients
  • Expected returns
  • Abnormal returns
  • Cumulative abnormal returns
  • Averaged cumulative abnormal returns
  • Average abnormal returns
  • Cumulative average abnormal return
  • Descriptive statistics such as standard deviations, medians, modes, minimums, maximums, and percentage of positive abnormal returns.

Two Calculators

Here are two event study market model calculators worth considering for use in your study.

  1. Event study market model calculator – Simple: This event study market model calculator computes returns using the simple formula.
  2. Event study market model calculator –  Compound:  This Event study market model calculates security and benchmark index returns using the logarithmic formula (Natural log). In other words returns are calculated with compounding. 

Solved ABCD Statistics Questions

Solved: ABCD Statistics Questions

  1. ABCD is a fast food restaurant, and has a number of franchisers across the South Wales regions. Recently the Head Office of ABCD received a number of complaints from customers that the queuing time is too long. Each franchiser has randomly chosen 100 customers and recorded their waiting time until food is served. The results are shown in table 1.

Statistics-Questions-SW-Just-Go-table

(a) What is the average waiting time (arithmetic mean) for each franchiser? Which franchiser has the shortest/longest waiting time?

(b) What is the overall average waiting time and standard deviation? Which franchiser should improve their performance and why.  

(c) The Head Office wants to know what the most occurring waiting time in each franchiser is. Explain the concept of the mode, mean, and median and help managers of each franchiser find the right number to report back to the Head Office.

2. ABCD is investigating an option to invest in an online booking system, where customers can order food prior to their visit. The management team is thinking of either developing a mobile app or booking through their website. Before making the final decision, the company conducted a pilot study using both platforms to explore the relationship between online orders and sales revenue. Orders (x) are in 000s and sales revenue (y) is in £000s. Summary data for 6 franchisers was as follows;

(a) Calculate correlation coefficient, r, for each options, clearly showing
calculations, and explain the meaning
(b) Calculate the equation of the least squares regression line (i.e. y = a + bx).
(c) The market research shows that if the company introduces the online booking system, there will be an increase of orders to 20,000. In this case, what might be the estimated sales revenue if there is (a) a Mobile App, and (b) a Website booking? Which system should the company develop?

3. ABCD has field-tested two booking platforms – Mobile App and Website on 1,000 volunteers. At a test volunteers were asked to order their food using the Mobile App and Website system, and asked to rate each system. The results of the test are as follows.

  Mobile App Website
Easy to navigate 385 245
Easy to Order 265 105

Calculate the following probabilities:
(a) that a volunteer who has said that it was easy to navigate
(b) that a volunteer who used the Website and has said that it was easy to order
(c) that a volunteer has used the Mobile App, given that the person said it was easy to order
(d) Based on findings, suggest what system the company should develop to improve customer experiences.

4. ABCD reviewed how much customers spend per order. It has found that the overall spending can be said to be normally distributed with a mean of £22 and a standard deviation of £5.

(a) What percentage of customers have spent less than £15?

(b) As a part of promoting the new online booking system, the company is thinking of offering discount on top 10% of most spent customers. If a customer wants to receive the discount offer, what’s the minimum amount they have to spend on the order?

(c) What if a standard deviation of the sample is £10 instead of £5, how would it affect their discount offer? Would this be a good deal for customers?

Solutions

Question 1:

What is the average waiting time (arithmetic mean) for each franchiser? Which franchiser has the shortest/longest waiting time?

The arithmetic mean can be calculated using the formula when dealing with grouped data
=∑mf/n
Where: m is the class midpoint

Worked out Solutions
Means:
Cardiff = 8.05
Newport = 6.2
Swansea = 8.2

overall average waiting time

Find worked out, step by step solutions >>>

 

 

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