Volatility of Monthly Returns of Timken Compared to the Vanguard S&P 500 Index ETF

Here is the graph of monthly returns between June 2019 and September 2022 of Timken (TKR) plotted against Vanguard S&P 500 Index ETF (VOO):

Exhibit: Monthly Returns of VOO and TKR between June 2019 and September 2022

Monthly Returns of VOO and TKR between June 2019 and September 2022
(Source: Data Provided by IEX Cloud, Monthly Returns Calculated in Microsoft Excel, Graph Plotted in R Studio using ggplot package)
Click on the image to enlarge it.

The monthly returns of Timken have a very strong positive correlation of 0.77 with the S&P 500 Index. The very low p-value (p = 6.2e-09) indicates that the monthly returns of the S&P 500 Index have an effect on Timken's monthly returns.  

The Beta value indicates the monthly return volatility of Timken compared to the S&P 500 Index. Yahoo Finance provides a Beta value of 1.59 based on monthly returns over the past five years. A linear regression of the monthly returns between June 2019 and September 2022 yields a Beta of 1.48. The coefficient of Vanguard's monthly return is the volatility of Timken. The coefficient is the linear regression line's slope and Timken's Beta value. In other words, as the monthly return of the Vanguard S&P 500 Index ETF changes by 1%, Timken's monthly return can change by an average of 1.48%.  

Timken's Beta value is one of the highest I have seen. Here are the Beta values of some of the stocks in another post on this blog.  

Here's the output of the linear regression between the monthly returns of Vanguard S&P 500 Index ETF and Timken:

Call:

lm(formula = TKR_Monthly_Return ~ VOO_Monthly_Return, data = VOOandTKR)

Residuals:

      Min        1Q    Median        3Q       Max 

-0.132602 -0.047815 -0.000585  0.059694  0.137770 

Coefficients:

                   Estimate Std. Error t value Pr(>|t|)    

(Intercept)        0.001198   0.011348   0.106    0.916    

VOO_Monthly_Return 1.489061   0.199966   7.447 6.17e-09 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.07103 on 38 degrees of freedom

Multiple R-squared:  0.5934, Adjusted R-squared:  0.5827 

F-statistic: 55.45 on 1 and 38 DF,  p-value: 6.168e-09  

  

Beta for Boeing, Sealed Air, Lennox International, Colgate-Palmolive & Cisco

I write about various companies on Seeking Alpha, covering Sealed Air, Lennox, Colgate-Palmolive, and Cisco Systems. I calculated the Beta of the monthly returns for these stocks compared to the Vanguard S&P 500 Index.  Here's the table showing the beta:  

Exhibit: Beta of Cisco, Colgate-Palmolive, Lennox International, Sealed Air, and Boeing

The beta of Cisco, Colgate-Palmolive, Lennox International, Sealed Air, and Boeing

You can read my articles on Seeking Alpha, which needs a subscription, by following the links below:

•  Sealed Air: Misclassified and Misunderstood
• Cisco Systems: Great Margins, But Lacks Growth
• Colgate-Palmolive Stock is Overvalued
• Lennox International May be Fully Valued

   

Boeing's Monthly Return Volatility Compared to the Vanguard S&P 500 Index ETF From June 2019 to August 2022

 Given its dominant position in the aerospace market, one would think Boeing's (BA) monthly returns would be less volatile than the S&P 500 index (VOO). But, Boeing has endured a lot in the past few years. First came the trade war with China that froze Boeing out of the second-largest aerospace market in the world.  Then came the COVID-19 pandemic that grounded airlines worldwide and brought Boeing to its knees. We did not even talk about the 737 Max plane crash in Ethiopia that kicked off the disastrous few years for Boeing.  

Boeing has never fully recovered from either the trade war or the pandemic. Boeing remains frozen out of the Chinese market, and airlines are only now seeing air travel return close to pre-pandemic levels (Exhibit 1).

Exhibit 1: TSA Checkpoint Travel Number September 17, 2022 - September 26, 2022

TSA Checkpoint Travel Numbers (Source: TSA.GOV)

Now, the world is grappling with slowing growth due to high inflation and interest rates, which is putting further pressure on Boeing. By the looks of it, Boeing stock may take a decade or more to recover its losses if it ever recovers. Boeing's stock has dropped from $440 in March 2019 to $127 as of September 27 - a loss of 71%.  

Due to these massive crises, Boeing's stock returns have become unhinged from that of the S&P 500 index. A linear regression of the monthly returns of the Vanguard S&P 500 Index and Boeing yields a very high beta of 1.35 (slope of the regression line). The value of 1.35 is the coefficient of the monthly returns of the Vanguard S&P 500 Index ETF (VOO).  Yahoo Finance displays a beta of 1.36 based on 5-year monthly returns.  One can expect any change in the Vanguard ETF to be magnified by Boeing.  For every 1% change in monthly returns of the S&P 500 index, Boeing's monthly returns are expected to change by 1.35%. Also, just 25% (Adjusted R-Squared in the RStudio output below) of Boeing's returns are explained by the monthly returns of the S&P 500 Index.  

Exhibit: Vanguard S&P 500 Index ETF and Boeing Monthly Returns [June 2019 - August 2022]

Vanguard S&P 500 Index ETF and Boeing Monthly Returns [June 2019 - August 2022]
(Source: Data Provided by IEX Cloud, Author Calculations Using RStudio)

Here's the output from the linear regression conducted on RStudio: 

> lmBAVOO = lm(BA_Monthly_Return~VOO_Monthly_Return, data = VOOandBA)

> summary(lmBAVOO)

Call:

lm(formula = BA_Monthly_Return ~ VOO_Monthly_Return, data = VOOandBA)

Residuals:

     Min       1Q   Median       3Q      Max 

-0.26036 -0.07433 -0.00562  0.07323  0.33452 

Coefficients:

                   Estimate Std. Error t value Pr(>|t|)    

(Intercept)        -0.02348    0.02007  -1.169 0.249682    

VOO_Monthly_Return  1.35442    0.36247   3.737 0.000628 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.1229 on 37 degrees of freedom

Multiple R-squared:  0.274, Adjusted R-squared:  0.2543 

F-statistic: 13.96 on 1 and 37 DF,  p-value: 0.0006279

      

    

 

  

 

 

Linear Regression of Monthly Returns of Sealed Air Corp and the Vanguard S&P 500 Index ETF

Sealed Air Corporation is a global provider of packaging solutions to various industries. The company provides various packaging products to pack red meat, medical and life science products, cheese, electronics, and other products.  

Exhibit: Sealed Air Corporation Revenue by Region and Product Type

(Source: Sealed Air Q2 FY 2022 Investor Presentation on August 2,2022)

Sealed Air has very high volatility. This high volatility may be due to heavy dependency on consumer spending. If consumer spending is weak, they may buy less packaged red meat or packaged cheese, resulting in reduced revenue for the company.  

Here is the graph of monthly returns of Sealed Air (SEE) plotted against Vanguard S&P 500 Index ETF (VOO):

Exhibit 1: Monthly Returns of Sealed Air Corp. and Vanguard S&P 500 Index ETF [June 2019 -  August 2022]

Monthly Returns of Sealed Air Corp. and Vanguard S&P 500 Index ETF [June 2019 -  August 2022]

(Source: RStudio, ggplot, Data Provided by IEX Cloud)

Results of the linear regression of monthly returns of Sealed Air Corporation against Vanguard S&P 500 Index ETF:

> lmSEEVOO = lm(SEE_Monthly_Return~VOO_Monthly_Return, data = VOOandSEE)

> summary(lmSEEVOO)

Call:

lm(formula = SEE_Monthly_Return ~ VOO_Monthly_Return, data = VOOandSEE)

Residuals:

     Min       1Q   Median       3Q      Max 

-0.13572 -0.03866  0.01319  0.03375  0.14587 

Coefficients:

                    Estimate Std. Error t value Pr(>|t|)    

(Intercept)        -0.002498   0.009056  -0.276    0.784    

VOO_Monthly_Return  1.144479   0.163536   6.998 2.85e-08 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.05547 on 37 degrees of freedom

Multiple R-squared:  0.5696, Adjusted R-squared:  0.558 

F-statistic: 48.98 on 1 and 37 DF,  p-value: 2.849e-08

Sealed Air Corporation has a higher volatility than the S&P 500 Index, with a Beta of 1.144. The company's monthly returns positively correlate with the Vanguard S&P 500 Index ETF. The correlation is 0.75.  

The linear regression yields an adjusted R-squared of 0.55, indicating that about 55% of Sealed Air's monthly returns can be explained by the monthly returns of the S&P 500 Index. 

Sealed Air stock may be risky due to its high volatility compared to the market. But, if the stocks are bought at a reasonable or low valuation, they may yield returns that exceed the market's return.   

     

Linear Regression of Monthly Returns of Cisco Systems and the Vanguard S&P 500 Index ETF

Here is the graph of monthly returns of Cisco Systems (CSCO) plotted against Vanguard S&P 500 Index ETF (VOO):

Exhibit 1: Monthly Returns of Cisco Systems and Vanguard S&P 500 Index ETF [June 2019 -  August 2022]

Monthly Returns of the Vanguard S&P 500 Index ETF and Cisco Systems Inc.

(Source: RStudio, ggplot, Data Provided by IEX Cloud)

Results of the linear regression of monthly returns of Cisco Systems against Vanguard S&P 500 Index ETF:

VOOandCSCO <- read_excel("/CSCO_VOO_LM_September_2022.xlsx", sheet = "Sheet1")

lmCSCOVOO = lm(CSCO_Monthly_Return~VOO_Monthly_Return, data = VOOandCSCO)

summary(lmCSCOVOO)

Call:

lm(formula = CSCO_Monthly_Return ~ VOO_Monthly_Return, data = VOOandCSCO)

Residuals:

      Min        1Q    Median        3Q       Max 

-0.156924 -0.031998 -0.008248  0.038045  0.127839 

Coefficients:

                   Estimate Std. Error t value Pr(>|t|)    

(Intercept)        -0.01062    0.01049  -1.012    0.318    

VOO_Monthly_Return  0.91708    0.18946   4.841 2.31e-05 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.06426 on 37 degrees of freedom

Multiple R-squared:  0.3877, Adjusted R-squared:  0.3712 

F-statistic: 23.43 on 1 and 37 DF,  p-value: 2.306e-05

The slope of the regression corresponds to the beta of the stock. In this case, Cisco Systems has a beta of 0.91. 

The adjusted R-squared is 0.37. About 37% of Cisco's monthly return is explained by the returns of the S&P 500 index.  

Cisco Systems cannot protect a portfolio against market volatility since it has a beta value close to 1. Cisco's stock will almost entirely reflect the volatility in the market.      

 

Musings on Economic Growth, Buybacks, and Inflation

We are entering an era of slow growth, especially in the U.S. and Europe. The older demographics and lower productivity are to blame for the low growth. Economic growth was already slow in the 2010s, but artificially low-interest rates from the Fed caused multiple expansions in the stock market. I see these Asset Managers and VCs criticize the Fed and the Government for inflation today, but those guys did not give credit to the Fed and the Government for all the billions they made in profits due to the cheap money policies. Homeowners benefited from the artificially low-interest rates, but most would never call it a hand-out.

Business Insider is reporting that the corporate bond market is in deep trouble. CEOs spent $1 trillion on share buybacks each year to pad their income while their company's balance sheets deteriorated. Oracle spent over 85% of its operating cash flow on share repurchases. Even after all these buybacks, Oracle's stock is way down. No amount of financial engineering can save a company with zero revenue growth.

Oracle can afford buybacks, but many other companies were spending more than their operating cash flow on buybacks and dividends. Essentially, they borrowed money at ultra-low interest rates to fund their buybacks. Even after all these buybacks, Oracle's stock is way down. No amount of financial engineering can save a company with zero revenue growth.

The Biden administration should not bail out corporations for their mistakes and let companies go through the bankruptcy process for the way they mishandled shareholder wealth. We might see a wave of bankruptcies next year (2023). Let's return to our capitalist roots.  It was a mistake to bail out AIG with $170 billion during the 2008 crisis. We spent trillions bailing out corporations for their mistakes in both 2008 and again in 2020.  The US airlines went bankrupt in a week during March 2020.  The US airlines spent all their money on buybacks and had nothing saved for a rainy day. I saw this ad from a Japanese company during the 2020 COVID crisis. They asked applicants to apply to their company and said employees need not worry about getting paid.  They said they have enough money on their balance sheet to pay every employee even if they had zero revenues for 20 years.

Most of the inflation is caused by supply chain disruptions to food supplies and other essentials. No amount of lowering the money supply will reign in inflation caused by supply chain disruptions in food unless we want people to suffer from hunger.

Our problem will be slower economic growth and not inflation a year from now (2023). Inflation will be high compared to the 2010s, but it will settle at a much lower level than its current rate of 6% to 8%. Even this higher level will most likely be due to supply-side challenges. The money supply is already contracting rapidly.

Linear Regression of Monthly Returns of Colgate-Palmolive against Vanguard S&P 500 Index ETF

Here is the graph of monthly returns of Colgate-Palmolive (CL) plotted against Vanguard S&P 500 Index ETF (VOO):

Exhibit 1: Monthly Returns of Colgate-Palmolive and Vanguard S&P 500 Index ETF [June 2019 -  August 2022]

(Source: RStudio, ggplot, Data Provided by IEX Cloud)

Results of the linear regression of monthly returns of Colgate-Palmolive against Vanguard S&P 500 Index ETF:

> VOOandCL <- read_excel("/CL_VOO_LM_September_2022.xlsx", sheet = "Sheet1")

> lmCLVOO = lm(CL_Monthly_Return~VOO_Monthly_Return, data = VOOandCL)

> summary(lmCLVOO)

Call:

lm(formula = CL_Monthly_Return ~ VOO_Monthly_Return, data = VOOandCL)

Residuals:

      Min        1Q    Median        3Q       Max 

-0.084505 -0.025451  0.002263  0.028820  0.122836 

Coefficients:

                    Estimate Std. Error t value Pr(>|t|)   

(Intercept)        0.0002236  0.0067940   0.033  0.97392   

VOO_Monthly_Return 0.3471172  0.1226847   2.829  0.00749 **

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.04161 on 37 degrees of freedom

Multiple R-squared:  0.1779, Adjusted R-squared:  0.1557 

F-statistic: 8.005 on 1 and 37 DF,  p-value: 0.007492

The slope of the regression corresponds to the beta of the stock. In this case, Colgate-Palmolive has a beta of 0.34. 

The adjusted R-squared is 0.15. About 15% of Colgate-Palmolive's return is explained by the returns of the S&P 500 index.  

Colgate-Palmolive can protect a portfolio against market volatility since it has a beta value substantially less than 1.    

 

Linear Regression of Monthly Returns of Lennox International against Vanguard S&P 500 Index ETF

Here is the graph of monthly returns of Lennox International (LII) plotted against Vanguard S&P 500 Index ETF (VOO):

Exhibit 1: Monthly Returns of Lennox International and Vanguard S&P 500 Index ETF [June 2019 -  August 2022 

(Source: RStudio, ggplot, Data Provided by IEX Cloud)

Results of the linear regression of monthly returns of Lennox International against Vanguard S&P 500 Index ETF:

VOOandLII <- read_excel("/LII_VOO_LM_September_2022.xlsx", sheet = "Sheet1")

lmLIIVOO = lm(LII_Monthly_Return~VOO_Monthly_Return, data = VOOandLII)

> summary(lmLIIVOO)

Call:

lm(formula = LII_Monthly_Return ~ VOO_Monthly_Return, data = VOOandLII)

Residuals:

      Min        1Q    Median        3Q       Max 

-0.090246 -0.052733 -0.001907  0.040310  0.108446 

Coefficients:

                    Estimate Std. Error t value Pr(>|t|)    

(Intercept)        -0.010082   0.009416  -1.071    0.291    

VOO_Monthly_Return  0.995050   0.170040   5.852 9.97e-07 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.05767 on 37 degrees of freedom

Multiple R-squared:  0.4807, Adjusted R-squared:  0.4666 

F-statistic: 34.24 on 1 and 37 DF,  p-value: 9.966e-07

The slope of the regression corresponds to the beta of the stock. In this case, Lennox International has a beta of 0.995. Lennox's beta is close to the S&P 500 beta, so Lennox will move in line with the market.  

The adjusted R-squared is 0.46. About 46% of Lennox's return is explained by the returns of the S&P 500 index.  

Welch Two Sample t-test of Daily Price Returns of J.M. Smucker and Mondelez

J.M. Smucker and Mondelez are consumer staples companies with similar financial performance. Both companies compete in similar product categories, especially when it relates to snacks. But, Mondelez has a vast international operation, while J. M. Smucker is more focused on the U.S. with very little So, I wanted to see if the mean daily returns are the same between the two stocks.

First, I downloaded the daily price return data for the past six months for both J.M. Smucker (SJM) and Mondelez (MDLZ) from IEX Cloud. 

I did a correlation between the daily price returns of the two companies using R:

> cor(SJM_6Month_ClosingPrice_Daily_Return_Data$changePercent, MDLZ_6Month_ClosingPrice_Daily_Return_Data$changePercent) 

[1] 0.5815403

The correlation in the daily returns between the two companies was 0.58 for the past six months. It is a positive correlation, but I would not consider this as a strong correlation in returns between the two companies. I would consider it a strong correlation if it was at or above 0.70. This came as a surprise given that both the companies are in the consumer staples sector and that sector has performed very well since December 2021. 

Next, I wanted to calculate the p-value for the Welch two-sample t-test between means of the daily returns.  The null hypothesis is that the difference in mean daily returns between J.M. Smucker and Mondelez is zero. The alternate hypothesis is that the difference is not zero. The p-value is 0.9035, which means the null hypothesis can be resoundingly rejected. The t-test command in R and the result set is presented below. The J. M. Smucker had a mean daily return of 0.0893% and Mondelez had a daily return of 0.0717%. There is a 1.7 basis points difference in returns with J. M. Smucker having a slightly larger daily return than Mondelez.       

> t.test(SJM_6Month_ClosingPrice_Daily_Return_Data$changePercent,         MDLZ_6Month_ClosingPrice_Daily_Return_Data$changePercent)

Welch Two Sample t-test

data:  SJM_6Month_ClosingPrice_Daily_Return_Data$changePercent and MDLZ_6Month_ClosingPrice_Daily_Return_Data$changePercent

t = 0.1214, df = 239.4, p-value = 0.9035

alternative hypothesis: true difference in means is not equal to 0

95 percent confidence interval:

 -0.002682718  0.003035099

sample estimates:

   mean of x    mean of y 

0.0008936508 0.0007174603 

Finally, here's the scatter plot of daily price change of J.M. Smucker (SJM) and Mondelez (MDLZ).

(Data Source: IEXCloud.io, Plot Created using RStudio)