IRP

IFP 6014Dominique LimboApril 5, 2023

Analysis on the Capital Asset Pricing Model (CAPM) on Microsoft (MSFT) and Apple (AAPL) Stocks and the variables affecting their estimated returns

Summary Limitations and Recommendations

05

Results and Analysis

04

Methodology

03

Related Literature

02

Introduction

01

Index

Rossi, 2016

CAPM is a widely used standard for assessing investment success.

01

Introduction

Analysts, investors, and business managers frequently use the Capital Asset Pricing Model (CAPM) to calculate the beta risk measure and estimate returns in relation to the market return. To examine which technical factors have the most impact on the direction of stock returns estimates. This study focuses on Microsoft and Apple stocks.

Background and Aim of the Study

02

Review of Related Literature

CAPM

Macroeconomic Variables

Macroeconomic variables have a significant impact on stock market returns in Kenya (Ouma and Muriu, 2014). Pivot point estimates trends of the direction of price and identified a point where the market can shift (Mitchell, 2019) Rate of change is known to be a momentum indicator for stocks (Banjamin, 2019)

CAPM assumes that all investors have access to the same data, which is unrealistic (Rossi, 2016) Despite its drawbacks, CAPM is still useful as a standard for assessing investment performance (Rossi, 2016) Investors should consider using multiple models to evaluate the success of assets instead of relying solely on CAPM (Rossi, 2016)

Related Literature

Technology Stock Performance

Three Factor Model

Both the market risk and size risk factors are significant in explaining the returns of Turkish stocks, while the book-to-market ratio factor was found to be insignificant (Gökgöz, 2007). The limitations of the CAPM in emerging markets highlight the need for more factor models to explain the returns (Gökgöz, 2007).

Technology stocks have significantly higher returns than the market as a whole and exhibit a positive correlation with market risk (Assefa, Haroon, and Raphael, 2020). CAPM may not be an accurate model for explaining the returns of technology stocks (Assefa, Haroon, and Raphael, 2020).

Related Literature

03

Methodology

Data Analysis

Data Description and Collection

Research Design

Step 3

Descriptive Statistics Pearson Correlation Coefficient Augmented Dickey Fuller Test Time Series Model for First Difference Diagnostic Tests

Step 2

Focused on Apple and Microsoft Stocks Technical indicators such as Pivot Point and Rate of Change Capital Asset Pricing Model equation with variables including Nasdaq Market Return, 1-Yr Beta, and the Risk-Free Rate The study collected data solely from the first day of trade, which began on February 2, 2013, and continued up to February 2, 2023, covering monthly data from each year period.

Step 1

This study used a systematic sampling design based on several criteria, which were reported in a recent Forbes Advisor article by Treece (2023) entitled "10 Best Tech Stocks of February 2023" Choice of stock included their substantial market capitalization volumes, high value, and reported average annualized returns of 22.2% and 25.9%, respectively (Treece, 2023)

Methodology

Er =(Rf)+ [ β x (NDX – Rf)]Where: Er = Expected Returns Rf = Risk Free Rate Β = Stock Beta NDX = Nasdaq Market Return

Capital Asset Pricing Model Equation (Sharpe and Lintner)

=β0+[ β1 (NDX)]+ β2PPt + β3 ROCt+ μ Where: Y = Expected Returns NDX = Nasdaq Market Return PP= Stock Price Pivot Point at time t ROC= Stock Price Rate of Change at time t

Time Series Model

Ha2: β1 ≠ 0; The stock price rate of change does not affect returns on Apple (AAPL) stocks.

Ho2: β1 = 0; The stock price rate of change does not affect returns on Apple (AAPL) stocks.

Ho1: β1 = 0; The stock price pivot point affects returns on Microsoft (MSFT) stocks.

Ha1: β1 ≠ 0; The stock price pivot point does not affect returns on Microsoft (MSFT) stocks.

Statement of Hypothesis:

Which technical variables positively or negatively affect returns on Microsoft (MSFT) and Apple (AAPL) stocks?

Research Question:

04

Results and Analysis

An increase or decrease in Market Return and Rate of Change leads to an increase in the Expected Return.The Pivot Point's increase in the Expected Return results in a decrease in Pivot Point.

Microsoft

Pearson Correlation Coefficient

Market Return, Rate of Change, and Pivot Point variables have positive linear relationship indicating that if the variable increased or decreased, the Expected Return follows the same direction.

Apple

Pearson Correlation Coefficient

First difference transformation technique was applied to ensure the stationarity of these variables.

Augmented Dickey Fuller Test (MSFT)

First difference transformation technique was applied to ensure the stationarity of these variables.

Augmented Dickey Fuller Test (AAPL)

R-Squared: 0.4207 Adjusted R-Squared: 0.4055

Dependent Variable: Microsoft's Expected Return

Time Series Model (MSFT)

Dependent Variable: Apple's Expected Return

R-Squared: 0.2870 Adjusted R-Squared: 0.2684

Time Series Model (AAPL)

Homoskedastic, Presence of serial correlation, Moderate multicollinearity Pivot Point and Expected Return not normally distributed

Diagnostic Tests (MSFT)

Homoskedastic, Presence of serial correlation, Moderate multicollinearity Pivot Point not normally distributed

Diagnostic Tests (AAPL)

05

Summary, Limitations, and Recommendations

Summary and Limitations

The study is limited to two technology stocks and three key variable return indicators, and other studies have considered additional variables that were not included in this research. (Rossi, 2016)

The study supports the idea that the CAPM may not be an accurate model for explaining the returns of technology stocks, especially with the use of the Pivot Point. (Assefa, Haroon, & Raphael, 2020; Gokgoz, 2007)

Pivot Point is a statistically significant predictor of expected returns for Microsoft, while it has a positive relationship with expected returns for Apple.

The Rate of Change may be an unreliable predictor for both models of the expected return in the regression model.

Consider analyzing mpact of interest rate policies on stock prices

Central Banks

Consider Pivot Point in investment decisions.

Investors

Insight for factors influencing technological stock returns.

Academe

The study can be extended to examine additional factors that influence stock returns.

Researchers

Recommendations

Assefa, T., Haroon, B. and Raphael, S. (2020). Tech Stock Returns and Empirical Analysis of CAPM. Journal of Accounting and Finance, 20(5). doi:10.33423/jaf.v20i5.3189. [Accessed: 10.01.2023]Benjamin, J., Altrad, S., Tousios, S., & Harte, J. (2019, March 20). Trading with the Rate of Change (ROC) Indicator – Part 1. Retrieved from https://www.orbex.com/blog/en/2017/09/trading-rate-change-roc-indicator-part-1.[Accessed: 28.02.2023] Gökgöz, F. (2007). Testing the Asset Pricing Models in Turkish Stock Markets: CAPM vs Three Factor Mitchell, C. (2019, July 08). How Much You Can Make Forex Day Trading. Retrieved From https://www.thebalance.com/how-much-money-can-i-make-forex-day-trading-1031013. [Accessed: 28.02.2023] Model. International Journal of Economic Perspectives, [online] 1(2), pp.103–117. Available at: https://content.ebscohost.com/ContentServer.asp?T=P&P=AN&K=37167666&S=R&D=bth&EbscoContent=dGJyMNHX8kSep7A4zOX0OLCmsEqep7dSsai4TLKWxWXS&ContentCustomer=dGJyMPGotlCzrK9LuePfgeyx44Dt6fIA [Accessed: 10.01.2023] Laura, M. and Fahad, N. (2017). The Classical Approaches to Testing the Unconditional CAPM: UK Evidence. International Journal of Economics and Finance, [online] 9(3), p.220. Available at: https://doi.org/10.5539/ijef.v9n3p220 [Accessed 10.01. 2023].

References

Ouma, W and Muriu, P. (2014). The Impact of Macroeconomic Variables on Stock Market Returns in Kenya. www.ijbcnet.com International Journal of Business and Commerce, [online] 3(11). Available at: https://ijbcnet.com/3-11/IJBC-14-31001.pdf. [Accessed: 01.10.2023] Rossi, Matteo. (2016). The Capital Asset Pricing Model: a critical literature review. Global Business and Economics Review, Vol 18. No.5, pg604-617. doi:10.1504/GBER.2016.10000254. [Accessed: 01.10.2023] Susanti, E., Grace, E., and Ervina, N. (2020). The Investing Decisions during the COVID-19 Pandemic by Using the Capital Asset Pricing Model (CAPM) Method in LQ 45 Index Companies. International Journal of Science, Technology & Management, [online] 1(4), pp.409–420. doi:10.46729/ijstm.v1i4.66. [Accessed: 01.10.2023]. Treece, D.D. (2023) 10 best tech stocks of February 2023, Forbes. Forbes Magazine. Available at: https://www.forbes.com/advisor/investing/best-tech-stocks/ (Accessed: February 28, 2023).

References

Q & A