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Energy Industry Investment Model vs Prototype Model

4/29/2015

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After spending time polishing up my statistical knowledge I created another energy industry prototype model built on what I learned so far.  This prototype uses exactly the same data as the Energy Industry Investment Model.  The difference is that the Energy Industry Investment Model uses unadjusted data while the prototype uses seasonally adjusted monthly % change in data which eliminates serial correlation and makes the data Covariance Stationary. 

Serial Correlation in a situation in which previous period data points are correlated with future periods.  For instance if you measure a car's MPH as it accelerates, A car will show a positive relation between time and MPH. 

Covariance Stationary loosely means that the data is anchored at a value and its variance doesn't change much.  For example, a car traveling on the highway with light traffic would center its speed around 65 MPH even though there are periods where the car will deviate from 65 MPH due to other highway cars shuffling between lanes. 

Without getting too deep into statistics, the data needs to be transformed to eliminate Serial Correlation and become Covariance Stationary before being fed into the model.  Failure to fix them will reduce model accuracy. 

With that in mind it is time to show preliminary results of the new prototype model for the energy industry.  Does it knock out the Energy Industry Investment Model? 
Energy Industry Investment Model vs Prototype Model
Sources: EIA, World Bank, Yahoo Finance
XLE vs Prototype Model
Sources: EIA, World Bank, Yahoo Finance
My charts show that the prototype is unable to wrestle the crown away from the Energy Industry Investment Model.  The prototype model results seem flat and fails to capture the volatility in XLE prices sufficiently.  This puzzles me.  Why would the current model built without considering seasonality, serial correlation, and covariance stationary data be more accurate?

I have two theories:

1.  The current Energy Industry Investment Model despite being built without advanced statistical practices is so effective that it didn't material affect accuracy.

2. The prototype model is built missing a critical statistical transformation or process that I am not currently aware of.

I will explore this and get back to you. 

My outstanding to-do-list still hasn't changed.  Running statistical tests and building a better model is still my first priority.  The only higher priority is watching the Mayweather/Pacquiao fight Saturday. 

My outstanding to-do-list in order of priority:
  1. Continue to run statistical tests on model built quality
  2. Finish building the Stock Market Investment Model
  3. Finish building the Consumer Discretionary Industry Investment Model
  4. Write an energy industry article
  5. Investigate why the price estimate of my Energy Industry Investment Model is much lower than the Energy Select Sector SPDR ETF's (XLE) price.  I'm looking for evidence to support my hypothesis that dividend investors are propping up energy industry stocks.
  6. Investigate dot com era, dot com crash, and subsequent recovery effects on both the energy and consumer staples industry investment models.
  7. Investigate why merchant wholesaler inventory levels affects consumer staples industry stocks.  I suspect two reasons: higher merchant wholesaler inventory levels equate to higher profit margins for consumer staples retailers or inventory levels is a result of future sales expectations. 
  8. Write an article about lessons I learned from Mohegan Sun casino.
  9. Write an article about how to identify stock market tops.

Thank you for reading. I'm looking for a Pacquiao victory. 
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Continuing To Make Progress

4/21/2015

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I was able to adjust EIA's monthly crude oil and petroleum products production data for seasonality - result below.  This allows the Energy Industry Investment Model to better gauge how production impacts the Energy Select Sector SPDR ETF's (XLE) price.  The seasonal index hasn't been committed to the model until I've completed the statistical tests on my investment models.   These tests are necessary to ensure that my models can withstand the scrutiny of investment professionals and built well. 
Crude Oil and Petroleum Products Production
Source: EIA
Fortunately this weekend, I was also able to perform a few statistical tests.  I'm still interpreting the results, there isn't anything noteworthy to report yet.  The tests are a high priority and will be continued this weekend.  Lastly, I also started work on a consumer staples database to better automate the data gathering process. 


My outstanding to-do-list in order of priority:
  1. Continue to run statistical tests on model built quality
  2. Finish building the Stock Market Investment Model
  3. Finish building the Consumer Discretionary Industry Investment Model
  4. Write an energy industry article
  5. Investigate why the price estimate of my Energy Industry Investment Model is much lower than the Energy Select Sector SPDR ETF's (XLE) price.  I'm looking for evidence to support my hypothesis that dividend investors are propping up energy industry stocks.
  6. Investigate dot com era, dot com crash, and subsequent recovery effects on both the energy and consumer staples industry investment models.
  7. Investigate why merchant wholesaler inventory levels affects consumer staples industry stocks.  I suspect two reasons: higher merchant wholesaler inventory levels equate to higher profit margins for consumer staples retailers or inventory levels is a result of future sales expectations. 
  8. Write an article about lessons I learned from Mohegan Sun casino.
  9. Write an article about how to identify stock market tops.

Thank you for your patience while I run my statistical tests. 
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Swimming In The Sea Of Statistics

4/16/2015

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On Sunday, I published my blog: "Is The Consumer Staples Industry Just Spinning My Wheels?".  I presented a lot of macroeconomic data from the U.S. Census Bureau and Bureau of Economic Analysis.  It took a lot of time to find and compile them, but I think it's good information for me to follow.    The blog also used the Consumer Staples Industry Investment Model rebuilt with U.S. Census Bureau adjusted merchant wholesaler data.  Here is a visual representation of how the data changed and how the rebuilt vs original models look.  It didn't have a material difference on model results.  
Nondurable Wholesaler Monthly Sales: After U.S. Census Adjustment vs Original
Source: U.S. Census Bureau
Prices: Consumer Staples Industry Investment Model vs XLP
Sources: U.S. Census Bureau, Yahoo Finance
This week I've also begun reviewing my CFA quantitative methods chapters in preparation for model testing.  I've been experimenting on various ways to seasonally adjust the crude oil and petroleum products production data for my Energy Industry Investment Model.  A simple moving average is ruled out because it underestimates the magnitude of near term changes in production.  Something more sophisticated will be used.  I was also able to find someone knowledgeable about statistcis in my network who can guide me if I get stuck.  

In the near term I will focus on model testing rather than publishing articles.  I'll continue to provide weekly model results on both the Consumer Staples and Energy Industry models on my website.

My outstanding to-do-list in order of priority:
  1. Energy Industry Investment Model - Fix seasonality in crude oil and petroleum products production
  2. Finish building the Stock Market Investment Model
  3. Finish building the Consumer Discretionary Industry Investment Model
  4. Write an energy industry article
  5. Investigate why the price estimate of my Energy Industry Investment Model is much lower than the Energy Select Sector SPDR ETF's (XLE) price.  I'm looking for evidence to support my hypothesis that dividend investors are propping up energy industry stocks.
  6. Investigate dot com era, dot com crash, and subsequent recovery effects on both the energy and consumer staples industry investment models.
  7. Investigate why merchant wholesaler inventory levels affects consumer staples industry stocks.  I suspect two reasons: higher merchant wholesaler inventory levels equate to higher profit margins for consumer staples retailers or inventory levels is a result of future sales expectations. 
  8. Write an article about lessons I learned from Mohegan Sun casino.
  9. Write an article about how to identify stock market tops.

Thank you for your patience.  
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Is The Consumer Staples Industry Just Spinning My Wheels?

4/11/2015

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XLP and S&P 500 struggling for direction
Source: Yahoo Finance
Recently, the U.S. Consumer Staples Industry as represented by the Consumer Staples Select Sector SPDR ETF (XLP) as well as his friend the S&P 500 are struggling for direction.  It's important to look at the S&P 500 as stocks are influenced by the overall stock market especially with significant XLP's large cap membership.  Historically, the pair have had distance between them. During the Dot Com era they moved oppositely, while during the mid 2000s, XLP lagged the S&P 500 for several years.  Since the Great Recession, XLP and the S&P 500 are best friends. 
Prices: XLP vs S&P 500
Source: Yahoo Finance
Is The Consumer Staples Industry Just Spinning My Wheels? We'll look at at both industry and macroeconomic level data to find where the industry is heading:

Industry Level Data

Industry Data is supportive of growth as the National Retail Federation expects retail sales to grow 4.1% in 2015, on top of last year's growth of 3.5% last year.  Although my charts below for Retail Trade and Food Services does include automobiles and restaurants, I see automobiles and restaurants moving together with retail trade as spending and consumer confidence improves. The University of Michigan's Index of Consumer Sentiment reports an index level of 95.0 for March 2015, which are pre-recession levels.  I'll talk more about the index under macroeconomic data later.  Going back to the charts, I broke out the consumer staples associated retail data which highlights the consumer staples' less volatile retail sales.  The exception is the warehouse clubs and superstores group which grew rapidly before the Great Recession.  I graphed volatile gasoline station sales separately from retail sales.  Despite the current crude oil price slump, consumers are not spending their gas savings on other retailers. 
Select Consumer Staples Retail Sales Figures
Source: U.S. Census Bureau
Select Consumer Staples Retail vs Discretionary Retail Sales Figures
Source: U.S. Census Bureau
My Consumer Staples Industry Investment Model doesn't take into account retail sales directly because it's built on merchant wholesaler data.  When I first created the model I saw a better fit with merchant wholesaler data.  The reason is because many large consumer staples companies have their own distribution and warehouse networks regardless of whether they participate directly in retail sales.  Their performance would more closely mimic wholesalers rather than retailers.  I show below how similar nondurable wholesaler sales is compared to consumer staples retail sales.
Monthly Sales: Nondurable Wholesaler vs Consumer Staples Retail
Source: U.S. Census Bureau
Macroeconomic Data

The Consumer Staples Select Sector SPDR ETF (XLP) as well as the S&P 500 contain many very large companies with global operations.  The macroeconomic environment will have a larger impact on these companies.  It's easy to get distracted by the U.S. dollar's rise, oil prices, and slowing world economies.  The January 2015 International Monetary Fund's (IMF) GDP estimates include these global effects.  The below shows that World Real GDP and U.S. Real GDP is increasing but U.S. growth slows in 2016. 
GDP Growth: World vs U.S.
Source: International Monetary Fund
U.S. sales are still a significant part of consumer staples companies. Focusing on the medley of U.S. economic data in the two charts below, we see that despite a lack of growth in full time real median weekly earnings, the size of the full time workforce has almost increased back to pre-recession highs.  This larger workforce provides more disposable income for a growing U.S. population to spend on consumer staples products.  Despite the recent weak jobs report, it's important not to lose sight that job growth was positive.  As future U.S. population growth in the far future slows, consumer staples stock performance may level off. 
U.S. Weekly Earnings and Full Time Workforce
Source: U.S. Census Bureau
U.S. Population Growth
Source: U.S. Census Bureau
The charts below shows personal consumption expenditures, savings/savings rate, and consumer sentiment.  Savings rate is inversely related to recessions while consumer sentiment moves with recessions.  I would pay close attention to these indicators.  Consumers are spending more as consumer sentiment is rising, this can be shown in the savings rate decline.  The University of Michigan reports that for March 2015, consumer sentiment reached an all time high.  In closing it mentions that consumer spending will rebound due to favorable job opportunities and that few consumers expect rising interest rates to hamper their purchases.  This is great news for investors. 
U.S. Consumption and Savings
Source: Bureau of Economic Analysis
Consumer Sentiment
Source: University of Michigan
I'm excited that both industry and macroeconomic data are encouraging.  After entering merchant wholesaler, National Retail Federation estimates of retail sales as a proxy for wholesaler sales growth, and general stock market (S&P 500) data into my Consumer Staples Industry Investment Model I calculate a mid $50 value for XLP.  I also plotted historical XLP prices versus the Consumer Staples Industry Investment Model to show model accuracy.  At the moment, I don't have a quantitative view of general stock market performance (S&P 500), but I'm working on a model that considers GDP and consumer sentiment data which can later be combined with the consumer staples model. 
Consumer Staples Industry Investment Model Estimated Price vs XLP
Prices: Consumer Staples INdustry Investment Model vs XLP
Sources: National Retail Federation, U.S. Census Bureau, Yahoo Finance
Is the Consumer Staples Industry Just Spinning Your Wheels? 

My model estimates that the U.S. consumer staples industry is slightly undervalued based on current industry and macroeconomic data therefore the consumer staples industry as represented by XLP has room to grow.  Because the S&P 500 is XLP's best friend, the stock market's volatility affects the consumer staples ETF's price.  Luckily for both friends, the U.S. economy hasn't peaked.  Consumer Sentiment has only been above 90 for four months but generally has to stay at a high level for an extended period of time before a recession comes along; also the savings rate hasn't fallen below 4%.  Finally positive GDP growth from the IMF despite and positive U.S. economic data provides support.

Lastly, the consumer staples industry produces essential goods that will still be in high demand regardless of the economy making consumer staples stocks less volatile during economic downturns.  If you're not convinced about my bullish view on the economy you should still consider having consumer staples stocks for your equity portfolio.
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'Tis The Season To Be Busy

4/8/2015

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I got caught up in another busy 2-3 weeks at work.  Hope I don't need to head into the office this weekend.  At the rate my work is going I'm at risk of burnout. 

There's been a few developments for Adrian's Investment Models I want to highlight

First, I'm still working on the consumer staples article: "Is The Consumer Staples Industry Just Spinning My Wheels?".  I'm about 60% done.  Besides work and recovering from a busy work schedule slowing down my progress on the article, I'm taking more time to conduct deeper analysis and to provide more data to back up my points. 

Second, it's been brought to my attention that more statistical tests are needed on my investment models to confirm/increase accuracy and to ensure that it's built properly.  To give you an example, picture an investment model as a car.  The car runs and has been tested in various real world driving situations (backtests), however, the engineers have not conducted detailed simulation runs to document engine response, fuel efficiencies, and breaking ability (statistical tests).   Therefore, for the next few weeks I will be running a set of statistical tests on my models.  I've already reached out to statistics experts in my network to guide me in the right direction.  I will blog once I have results. 

Third,  I'm going to make tweaks on both the Energy and Consumer Staples Industry Investment Models.  For the energy model, I am going to adjust the crude oil and petroleum production data for seasonality, that should smooth out model results.  I don't expect it to significantly impact model results, but it will require me to rebuild the model and re-run the backtest.  For the consumer staples model, the U.S. Census bureau adjusted historical data based on their Annual Wholesale Trade Survey and results from the 2012 Economic Census.  This will also require me to rebuild the model and as a safety precaution re-run the backtest.  I will try to finish them this weekend. 

My outstanding to-do-list in order of priority:

  1. Finish my article: "Is The Consumer Staples Industry Just Spinning My Wheels?".
  2. Energy Industry Investment Model - Fix seasonality in crude oil and petroleum products production
  3. Consumer Staples Industry Investment Model - Update model for changes in annual merchant wholesaler update
  4. Finish building the Stock Market Investment Model
  5. Finish building the Consumer Discretionary Industry Investment Model
  6. Write an energy industry article
  7. Investigate why the price estimate of my Energy Industry Investment Model is much lower than the Energy Select Sector SPDR ETF's (XLE) price.  I'm looking for evidence to support my hypothesis that dividend investors are propping up energy industry stocks.
  8. Investigate dot com era, dot com crash, and subsequent recovery effects on both the energy and consumer staples industry investment models.
  9. Investigate why merchant wholesaler inventory levels affects consumer staples industry stocks.  I suspect two reasons: higher merchant wholesaler inventory levels equate to higher profit margins for consumer staples retailers or inventory levels is a result of future sales expectations. 
  10. Write an article about lessons I learned from Mohegan Sun casino.
  11. Write an article about how to identify stock market tops.

Thank you for your patience as I try to balance work and my website. 
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I'm Finally Working On My Consumer Staples Blog Post

4/1/2015

1 Comment

 
I was hoping to finish my Stock Market Investment Model last weekend so I can use it for the Consumer Staples Industry Model.  Although I wasn't able to finish it, I made enough progress to run the current version of the model with a few minor adjustments. I'm going to feed a GDP forecast through to get model results. Knowing where the stock market may be going will help determine where the consumer staples industry as represented by the Consumer Staples Select Sector SPDR ETF (XLP) is heading.  I have finishing the consumer staples article as my must do item this weekend.  I will review the data I to build my article.  Below is an updated retail sales chart I will likely use for the article.  It highlights the lower volatility of consumer staples retail sales, especially during the Great Recession, versus the rest of the retail industry.
Select Consumer Staples Retail Sales Figures
Source: U.S. Census Bureau
As a side note, my models are adaptable and can be built on top of other ETFs and mutual funds.  I did this for the Consumer Staples Industry Investment Model backtest, I used the Fidelity Select Consumer Staples Portfolio (FDFAX) due to limited XLP historical data.  Adding the model on top of other products will be a project for another time.

After the consumer staples article is posted, I want to write about the energy industry again.  I haven't thought of a topic yet.  Today, I read in the news that weekly U.S. crude oil production fell from 9.42 to 9.39 million  It isn't much compared to the rise in production over the last few years.  Here is a quick historical chart of weekly crude oil production and stocks where today's drop isn't big enough to see.  The red line is the much publicized issue of rising crude oil stocks.
Crude Oil Production and Stocks
Source: EIA
In terms of my list, I added building a semi/fully automated energy industry database to pull in EIA and other energy industry data.  Having this database will streamline the process of researching and writing.

My outstanding to-do-list in order of priority:

  1. Finish my article: "Is The Consumer Staples Industry Just Spinning My Wheels?".
  2. Build the Stock Market Investment Model (tweaking and more backtesting).
  3. Finish building the Consumer Discretionary Industry Investment Model.
  4. Investigate why the price estimate of my Energy Industry Investment Model is much lower than the Energy Select Sector SPDR ETF's (XLE) price.  I'm looking for evidence to support my hypothesis that dividend investors are propping up energy industry stocks.
  5. Investigate dot com era, dot com crash, and subsequent recovery effects on both the energy and consumer staples industry investment models.
  6. Investigate why merchant wholesaler inventory levels affects consumer staples industry stocks.  I suspect two reasons: higher merchant wholesaler inventory levels equate to higher profit margins for consumer staples retailers or inventory levels is a result of future sales expectations. 
  7. Write an article about lessons I learned from Mohegan Sun casino.
  8. Write an article about how to identify stock market tops.
  9. Build an energy industry database to assist in research and writing

Thank you for reading.
1 Comment

    Adrian Wong

    I'm just a guy who is passionate about investments.  Go to "About Adrian" for more information about me

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