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Category Archives: correlation

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29 Friday Jan 2021

Posted by wmosconi in active versus passive debate, asset allocation, behavioral finance, beta, Black Swan, blended benchmark, bond market, Bond Mathematics, Bond Risks, bond yields, book deals, Brexit, business books, CAPE, Charlie Munger, cnbc, Consumer Finance, correlation, correlation coefficient, economics, enhanced indexing, EQ, EU, Fabozzi, Fama, Fed, Federal Reserve, Fiduciary, finance, finance theory, financial advice, financial advisor fees, financial advisory fees, financial markets, Financial Media, Financial News, financial services industry, Forward P/E Ratio, Frank Fabozzi, Geometric Returns, GIPS, Greenspan, gross returns, historical returns, Individual Investing, individual investors, interest rates, Internet Bubble, investing, investing advice, investing books, investing information, investing tips, investment advice, investment books, Irrational Exuberance, LIBOR, market timing, Markowitz, math, MBS, Modern Portfolio Theory, MPT, Nassim Taleb, Nobel Prize, P/E Ratio, passive investing, personal finance, portfolio, Post Brexit, probit, probit model, reasonable fees, reasonable fees for financial advisor, reasonable fees for investment advice, reasonable financial advisor fees, rebalancing, rebalancing investment portfolio, rising interest rate environment, rising interest rates, risk, risk tolerance, risks of bonds, risks of stocks, Robert Shiller, S&P 500, S&P 500 historical returns, S&P 500 Index, Schiller, Search for Yield, Sharpe, Shiller P/E Ratio, speculation, standard deviation, State Income Taxes, statistics, stock market, Stock Market Returns, Stock Market Valuation, stock prices, stocks, Taleb, time series, time series data, types of bonds, Valuation, volatility, Warren Buffett, Yellen, yield, yield curve, yield curve inversion

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Top Five Investing Articles for Individual Investors Read in 2019

09 Monday Dec 2019

Posted by wmosconi in asset allocation, Average Returns, behavioral finance, beta, bond yields, confirmation bias, correlation, correlation coefficient, economics, finance theory, financial advice, Financial Advisor, financial advisor fees, financial advisory fees, financial goals, financial markets, Financial Media, Financial News, financial planning, financial services industry, gross returns, historical returns, Individual Investing, individual investors, investing, investing advice, investing information, investing tips, investment advice, investment advisory fees, investments, market timing, personal finance, portfolio, reasonable fees, reasonable fees for financial advisor, reasonable fees for investment advice, reasonable financial advisor fees, risk, risk tolerance, risks of stocks, S&P 500, S&P 500 historical returns, S&P 500 Index, speculation, standard deviation, statistics, stock market, Stock Market Returns, stock prices, stocks, time series, time series data, volatility, Warren Buffett, yield, yield curve, yield curve inversion

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As the end of 2019 looms, I wanted to share a recap of the five most viewed articles I have written over the past year.  The list is in descending order of overall views.  Additionally, I have included the top viewed article of all time on my investing blog.  Individual investors have consistently been coming back to that one article.

1. Before You Take Any Investment, Advice Consider the Source – Version 2.0

Here is a link to the article:

https://latticeworkwealth.com/2019/09/18/investment-advice-cognitive-bias/

This article discusses the fact that even financial professionals have cognitive biases, not just individual investors.  I include myself in the discussion, talk about Warren Buffett, and also give some context around financial market history to understand how and why financial professionals fall victim to these cognitive biases.

2.  How to Become a Successful Long-Term Investor – Understanding Stock Market Returns – 1 of 3

Here is a link to the article:

https://latticeworkwealth.com/2019/09/23/successful-long-term-investing/

It is paramount to remember that you need to understand at least some of the history of stock market returns prior to investing one dollar in stocks.  Without that understanding, you unknowingly set yourself up for constant failure throughout your investing career.

3.  How to Become a Successful Long-Term Investor – Understanding Risk – 2 of 3

Here is a link to the article:

https://latticeworkwealth.com/2019/09/25/successful-long-term-investor-risk/

This second article in the series talks about how to assess your risk for stocks by incorporating what the past history of stock market returns has been.  If you know about the past, you can better prepare yourself for the future and develop a more accurate risk tolerance that will guide you to investing in the proper portfolios of stocks, bonds, cash, and other assets.

4.  Breakthrough Drugs, Anecdotes, and Statistics – Statistics and Time Series Data – 2 of 3

Here is a link to the article:

https://latticeworkwealth.com/2019/11/20/breakthrough-drugs-statistics-and-anecdotes-time-series-statistics/

I go into detail, without getting too granular and focusing on math, about why statistics and time series data can be misused by even financial market professionals.  Additionally, you need to be aware of some of the presentations, articles, and comments that financial professionals use.  If they make these errors, you will be able to take their comments “with a grain of salt”.

5.  Breakthrough Drugs, Anecdotes, and Statistics – Introduction – 1 of 3

Here is a link to the article:

https://latticeworkwealth.com/2019/11/11/breakthrough-drugs-statistics-and-anecdotes-investing/

I kick off this important discussion about the misleading and/or misuse of statistics by the financial media sometimes with an example of the testing done on new drugs.  Once you understand why the FDA includes so many people in its drug trials, you can utilize that thought process when you are bombarded with information from the print and television financial media.  Oftentimes, the statistics cited are truly just anecdotal and offer you absolutely no guidance on how to invest.

                                       Top of All Time

Are Your Financial Advisor’s Fees Reasonable?  Here is a Unique Way to Look at What Clients Pay For

Here is a link to the article:

https://latticeworkwealth.com/2013/08/07/are-your-financial-advisors-fees-reasonable-here-is-a-unique-way-to-look-at-what-clients-pay-for/

This article gets the most views and is quite possibly the most controversial.  Individual investors compliment me on its contents while Financial Advisors have lots of complaints.  Keep in mind that my overall goal with this investing blog is to provide individual investors with information that can be used.  Many times though, the information is something that some in the financial industry would rather not talk about.

The basic premise is to remember that, when it comes to investing fees, you need to start with the realization that you have the money going into your investment portfolio to begin with.  Your first option would be to simply keep it in a checking or savings account.  It is very common to be charged a financial advisory fee based upon the total amount in your brokerage account and the most common is 1%.  For example, if you have $250,000 in all, your annual fee would be $2,500 ($250,000 * 1%).

But at the end of the day, the value provided by your investment advisory is how much your brokerage account will grow in the absence of what you can already do yourself.  Essentially you divide your fee by the increase in your brokerage account that year.  Going back to the same example, if your account increases by $20,000 during the year, your actual annual fee based upon the value of the advice you receive is 12.5% ($2,500 divided by $20,000).  And yes, this way of looking at investing fees is unique and doesn’t always sit well with some financial professionals.

In summary and in reference to the entire list, I hope you enjoy this list of articles from the past year.  If you have any investing topics that would be beneficial to cover in 2020, please feel free to leave the suggestions in the comments.

Breakthrough Drugs, Statistics, and Anecdotes: Three Things Every Individual Investor Needs to Know – Statistics and Time Series Data – Part 2 of 3

20 Wednesday Nov 2019

Posted by wmosconi in asset allocation, correlation, correlation coefficient, finance theory, financial advice, Financial Media, Financial News, financial services industry, historical returns, Individual Investing, individual investors, investing, investing advice, investing tips, risks of stocks, standard deviation, stock market, Stock Market Returns, time series, time series data

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The first article of this three-part series covered the broad strokes of this issues to be aware of in terms of all the “data” and “relationships” that get thrown around by the financial media (print and television).  Most of the discussion uses data points that are not statistically significant to draw any sort of conclusion.  In fact, time series data is notoriously hard to model and predict the future.  Additionally, the specific time series data of stock market returns is even more difficult.

You can refer to the link below to examine the content of the first article:

https://latticeworkwealth.com/2019/11/11/breakthrough-drugs-statistics-and-anecdotes-investing/

The task at hand for the second article is to put some “meat on the bones” of the discussion.  I realize that anything to do with math and statistics is not easy for everyone (or of interest either).  Therefore, I will be writing a supplemental article that covers the mathematics and statistics in more detail.  The goal here is to be able to identify some of the more common errors that you will encounter.

The first item to talk about is any sort of data that has a substantial trend component.  In layman’s terms, there is a data series where the line graph goes up or down in more of a straight-line manner.  You can think of the Gross Domestic Product (GDP) of the United States here.  Every year the GDP figures will generally go up unless there is a recession.  But, even after the recession passes, the trend for GDP will resume upward.  So, where does the problem come in?

I am going to give a contrived example to illustrate why it is dangerous to compare two series that are trending.  The example will consist of two different equations which are trends.  Both have the same trend component and an error term (we will call that eta).  The variables will be exactly the opposite.  More specifically, the two equations we will use are the following:

Trend_1 = Time + 100 + 0.9 * x + eta

Trend_2 = Time +100 – 0.9 * x + eta

Now the x values and eta values were simply generated by selected variables at random between 0 and 1.  The eta values were also selected at random between 0 and 1.  You can think of eta as representing the general “noise” that occurs on a daily basis when observing stock prices in the financial markets.  So, let’s graph the first 100 observations for these two equations:

Trend_Graph_Statistics_Revised

You will notice that the trend component dominates the line graphs.  However, we know by construction that the two equations which produce trend_1 and trend_2 are fundamentally different.  Now the correlation coefficient between those two equations is 0.9984.  A correlation coefficient of 1 means that the two lines move in lockstep.  Why is this important?  Why is it very dangerous?

Well, financial pundits will talk about these types of graphs all the time.  It looks like there is some relationship, but we know there is very little relationship between the two trends.  In fact, we can look at these equations by subtracting the current value from the previous value to see what changes.   Formally, this topic is called first differencing.  It will allow us to see more clearly what we already know.  Here is the graph:

First_Difference_Graph_Statistics_Revised

Now we have a totally different picture.  We can see that at many times the two trend equations are moving in exactly the opposite direction.  In fact, the correlation coefficient for the first-differenced equations is 0.2675.  There is only a slight positive relationship between the two trends.

In the example above, we can see that looking at the two trends is very deceiving.  Remember that I added the eta term to represent “noise” that is always present in financial market data.  So, anytime someone talks to you about the comparison of two trends, you should be very skeptical.  You always want to see first-differenced data or at least a comparison of changes in some manner.  Otherwise, you will mistakenly assume that there is a strong positive or negative relationship between two time series.

The second example that I am going to use is stock market returns for the S&P 500 Index from 1966 through 2018.  Why start at 1966?  Well, the S&P 500 Index started with its current number of component stocks back in 1957, and I would like to show annual stock returns and also ten-year annualized returns.  This particular topic can get messy quite quickly, so I am not going to cover it in a lot of depth with statistical and mathematical jargon.  For those of you who are interested, I had mentioned that it will be contained in a forthcoming supplemental article.

A great many individuals in the financial markets talk about stock market returns in the same breath as the normal distribution.  What is the normal distribution?  It is the old bell curve that you are familiar with.  The normal distribution is symmetrical and tails off at the end as more and more data points are gathered.  Well, stock market returns are anything but strongly normal.

Let’s first take a look at one-year stock market returns for the S&P 500 Index.

One Year Returns - Histogram - Non Normal

A useful test to see if a particular distribution is normal is the Jarque-Bera test.  Now it is not necessary to know exactly what is being calculated.  However, you should refer to the bottom of the box that reads “Probability”.  The value of 0.179 is called a p-value.  A p-value less than or equal to 0.10 means that we can reject the hypothesis that the one-year distribution of stock returns is normal.  At a value of 0.179, we would not reject the hypothesis of normality for this distribution.  However, the p-value in our case is not large enough to be totally sure and confident. But what about looking at annualized stock market returns over ten-year periods?

We can look at a similar graph to check to see if stock market returns over longer timeframes are indeed akin to the normal distribution (i.e. the bell curve).  Here is the graph:

Ten Year Returns - Histogram - Non Normal

Looking at the same “Probability” value, we have 0.489.  Therefore, we cannot reject the hypothesis that these stock market returns follow a normal distribution. Looking at ten-year annualized stock market data tells us that we can use the normal distribution as an assumption for calculating statistics.

Now why does this matter?  Well, you will here over and over again statistics that apply only to the normal distribution in relationship to actual, observed stock market returns.  We have just seen that stock market returns over the short-term stock returns weakly follow the normal distribution. On the other hand, long-term stock returns are definitely normal. Now I will not get into the technicalities, but time series data is indeed asymptotically normal.  What?  Say again?

This is just a fancy way of saying that, as the number of data points (sample size) approaches infinitely, the time series will look like the normal distribution.  Pretty much all financial market and economic data have very few data points.  In fact, you usually need several hundred data points prior to making any assumptions and using the statistics related to the normal distribution (think standard deviation or correlation coefficients).

Thus, most of the banter in the financial media is just subjective notions of what is going on in the stock market and the economy. More often than not, an assertion by someone in the financial print or television media is more of an educated guess than based on a solid mathematical foundation. That fact explains why financial pundits hedge their statements. Like I say half-jokingly, “I see the stock market going up in the next several months, but of course it might not resume its uptrend or could even take a leg downward”.

Well yes, I guarantee you that every day stocks will go up, down, or remain unchanged. This type of daily commentary in the financial press about the short-term performance of stocks (or other financial assets) is just not helpful and can be downright distracting you from investing for your long-term financial goals.

I apologize for getting too detailed in certain parts of this article.  What are the key takeaways?  First, you should be extremely leery of drawing any conclusions from the comparison of two or more data series that are trending upward or downward.  Second, you need to have several hundred observations prior to invoking any reference to the normal distribution.  So, what is left after that?  As you might imagine, there are not too many comparisons or studies that pass the muster to give you insights on investing or actionable information to make changes to your investment portfolio.

Don’t focus on the mathematics or statistics.  All you need to remember are the two takeaways above.  And, first and foremost, you should always be skeptical whenever you are presented with comparisons and statistics related to the financial market or the economy as a whole.

How to Become a Successful Long-Term Investor – Summary

30 Monday Sep 2019

Posted by wmosconi in asset allocation, behavioral finance, correlation, correlation coefficient, Dot Com Bubble, Emotional Intelligence, EQ, financial advice, Financial Advisor, financial goals, financial markets, financial planning, financial services industry, historical returns, Individual Investing, individual investors, investing, investing advice, investing information, investing tips, investment advice, investments, market timing, math, personal finance, portfolio, risk, risk tolerance, risks of stocks, S&P 500, S&P 500 historical returns, S&P 500 Index, standard deviation, statistics, Stock Market Returns, stock prices, stocks, volatility

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asset allocation, behavioral finance, education, finance, historical stock returns, investing, investments, math, mathematics, performance, performance monitoring, portfolio, portfolio management, S&P 500, S&P 500 historical returns, S&P 500 Index, statistics, stock returns, stocks, success, successful long term investing, trading, uncertainty

The discussion of how to become a successful long-term investor in my three-part series is now finished.  However, the journey is an ongoing one that takes discipline, constant learning, and monitoring your emotional reactions to fluctuations in the financial markets.  I discussed the history of stock market returns of the S&P 500 Index (dividends reinvested) from 1957-2018, the concept of risk, and also the futility of trying to engage in “market timing”.  But you may be asking yourself, why didn’t you tell me what stocks, bonds, and other assets to buy to build my investment portfolio?  That is a valid question, and there is an extremely important reason why that gets at the very heart of my overall discussion.

The best way to answer the question posed above is with an analogy.  Now my international readers will have to indulge me with this example.  My favorite sport is football which is the most popular sport in the world.  Most people in the United States refer to it as soccer and only watch if the men’s or women’s teams are competing in the World Cup.  I could tell you all about the reasons why football clubs rarely use a 4-4-2 formation.  Or I could talk about how the 4-2-3-1 formation has evolved in the Bundesliga.  We also could discuss why goalies now need to be good with their feet in order to pass from the backline.  Finally, I might even be more specific and give my rationale for why Liverpool in the Premier League uses a 4-4-3 formation given their current squad for the 2019-2020 season.

My analogy above relates to long-term investing because I would argue that you should not invest a single dollar in the stock or bond markets without knowing about the history of returns, risks and volatility, and “market timing”.  Most Financial Advisors (FAs), Certified Financial Planners (CFPs), and Registered Investment Advisors (RIAs) jump right into the discussion of how to build an investment portfolio taking into account your financial goals and risk tolerance.  This conversation is directly related to the football analogy above.  Without a firm understanding of investing at a high level (or the general way football is played first), you are likely to fail in your resolve to stick with a long-term focus while investing.  For example, when you are asked if you can tolerate a 20% decline in the stock market, how should you answer?  I would say that, if you do not have some grasp of historical returns and the level of risk, you cannot properly answer.  Remember that we covered how often you will experience negative returns (including 20% declines) in the first article.  You need to understand the “composition of the forest before deciding how to deal with the trees”.

Here are the links to the three articles to have an understanding of first prior to jumping into the mix of long-term investing strategy and building an actual portfolio of investments.

Part 1 – Understanding Historical Stock Market Returns:

https://latticeworkwealth.com/2019/09/23/successful-long-term-investing/

Part 2 – Understanding and Managing Risk:

https://latticeworkwealth.com/2019/09/25/successful-long-term-investor-risk/

Part 3 – Giving up on the Allure of “Market Timing”:

https://latticeworkwealth.com/2019/09/28/successful-long-term-investing-market-timing/

Once you have a firm grasp on these topics, you are ready to get your feet wet in the world of investing.

For those of you wanting a little bit of guidance because your intention is the manage your investments personally, I have written about this topic in the past.  I wrote a two-part series on how to build an investment portfolio and monitor the performance returns of that investment portfolio.  I have included the links below:

Part 1 – Building an Investment Portfolio:

https://latticeworkwealth.com/2013/07/16/how-to-create-an-investment-portfolio-and-properly-measure-your-performance-part-1-of-2/

Part 2 – Monitoring the Performance of an Investment Portfolio:

https://latticeworkwealth.com/2013/07/19/how-to-create-an-investment-portfolio-and-properly-measure-your-performance-part-2-of-2/

Those two articles above will provide you with some ways to go about creating your own investment portfolio without the assistance of a financial professional.  While it does contain a lot of information and suggestions, individual investors who are complete novices may find it easier and less confusing to seek out someone to guide them with investment selection, measuring risk tolerance, and understanding the goals of their financial plan.

In summary, I appreciate you taking the time to read my thoughts in regard to successful long-term investing.  As you can see successful investing has more to do with preparation, setting realistic expectations, and knowing how you personally respond to risk.  These topics need to be studied prior to investing money yourself or before going to seek out investment advice from a financial professional.  If you have any questions, comments, feedback, or disagreements, you can feel free to let me know.

How to Become a Successful Long-Term Investor – Part 3 of 3 – The Folly of Market Timing

28 Saturday Sep 2019

Posted by wmosconi in Alan Greenspan, asset allocation, Average Returns, behavioral finance, bubbles, correlation, correlation coefficient, Dot Com Bubble, finance, finance theory, financial goals, financial markets, Financial Media, Financial News, financial planning, Greenspan, historical returns, Individual Investing, individual investors, Internet Bubble, investing, investing advice, investing information, investing tips, investment advice, investments, Irrational Exuberance, market timing, math, personal finance, portfolio, risk tolerance, risks of stocks, S&P 500, S&P 500 historical returns, S&P 500 Index, statistics, stock market, Stock Market Returns, Stock Market Valuation, stock prices, stocks, Valuation, volatility

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This article is the third and final post in my three-part series on learning how to be a successful long-term investor.  The general theme underlying all of the topics has been developing enough of an understanding of the stock market gyrations and sometimes wild ride to form reasonable expectations at the outset.  Those expectations lead directly into to developing a long-term investment strategy and plan that you are much more likely to stick with through “thick and thin” because you know what is coming.  Of course, you will not know the order in which the ups and downs may come, but you will have a ton of information helpful to be much less likely to lose your nerve or get overly excited.

The last topic will be about “market timing”.  We will delve deeply into the concept and see how very difficult it has been in the past, and, I believe, will continue to be for the foreseeable future.  Now the discussion to follow will be entirely self-contained; however, it might be helpful to take a look at the first two articles to have additional context.  The opening topic was an overview of the history of stock market returns using the S&P 500 Index (dividends reinvested).  Here is a link to that post:

https://latticeworkwealth.com/2019/09/23/successful-long-term-investing/

The second topic was a discussion about the concept of risk.  We explored how it is normally defined, ways that you can gauge your tolerance for risk given the information from the first post, and explored some methods/mindsets to reduce risk in your investment portfolio.  Here is a link to that post:

https://latticeworkwealth.com/2019/09/25/successful-long-term-investor-risk/

So now, we will turn to the topic for the last article.  As mentioned above, we are going to take a look at “market timing”.  In general, the idea of “market timing” is to develop ways to be able to buy stocks when they are very undervalued and also sell stocks right near the market peak to avoid a big downturn.  There are certain variations where an investor is not necessarily trying to time the most opportune time but trade along with the momentum of the stock market and anticipating the next movement prior to other stock market participants.

“Market timing” is notoriously difficult to do.  But you will see considerable time devoted every day to financial market television and periodicals advising individual investors what trades to make.  I would submit that following things and pundits on a daily basis adds to “noise” and “information overload”.  Additionally, for every guest that predicts a big leg up in the market, there will be another guest later in the day who tells you that we are in a bubble and stocks will drop dramatically soon.

Another lesser talked about item is the main guests that are invited to speak on television or are quoted in financial periodicals.  Typically, the guest introduction will be prefaced by this man/woman predicted the last major move in the stock market and we are so lucky to have him/her back again.  While these guests are great to hear from, there is a severe amount of “selection bias”.  What do I mean by “selection bias”?  You will rarely see a guest brought on to be lambasted for a prediction that never came to fruition or was just flat out wrong.  The vast majority of guests on television or market experts in financial articles will be the ones who made a very prescient call on the direction of the stock market.

The promise of “market timing” is still so enticing.  It normally relates to the fear of losing money or the greed of just not wanting to miss the next big bull market trend upward in the stock market.  However, the ability to call the market tops or bottoms has proven to be pretty much a 50/50 flip of the coin (now I am being generous at that).  One of the examples that I love to give is the coining of the term “irrational exuberance”.  The former chair of the Federal Reserve, Alan Greenspan, used that new term to state that the stock market was in what he thought was a bubble.  Little do people remember, but he first gave the speech in December 1996 to refer to what would become the Dot.Com bubble and bust.  Greenspan was proven right but the top of that bubble occurred in March 2000.  I use that example because irrational activity in the markets can persist for much, much longer than you might expect.

So, now I know that some people reading this post will be able to point to experts who made the great calls or even their own calls on the direction of the stock market.  Well, I will start off the discussion by showing that “market timing” is indeed somewhat possible.  But it takes much longer periods of time than you might think at first.  Here is how we will proceed in the analysis.  I discussed how the long-term historical average of the S&P 500 Index from 1957-2018 has been 9.8%.  It would seem logical then that, if stock market returns were below that average or above that average for a certain length of time, you could just do the opposite figuring that stock market returns would eventually trend back to that average (in the jargon reversion to the mean).

The problem is, as I briefly mentioned in the last paragraph, that the time period needs to be so long that it is almost untenable for individual investors to practically implement.  In fact, we have to use 15-year annualized returns to illustrate the theory.  So, if the stock market has been below/above trend, we will buy/sell because an inflection point has to come.  Let’s take a look at it graphically to drive the point home:

Fifteen Year Correlation

In the graph depicted above, we have exactly the returns we would like to see.  The blue dots are the past 15 years of stock market returns, and the orange dots are the next 15 years of stock market returns.  The dots are what we would term to have an inverse relationship.  In fact, for all of you somewhat familiar with statistics, the correlation coefficient is -0.857.  Therefore, there is a really strong relationship here that leads us to the promise of “market timing”.  Should we give up on it so early?

The problem with “market timing” is that, for any length of time less than 15 years of annualized stock returns, there really is no relationship (at least no actionable trading of stocks for your investment portfolio).  Let’s take a look at the same concept in the first graph with a look at one-year and three-year current and then future returns:

One Year Correlation

Three Year Correlation

Using the one-year and three-year current and then future stock market returns of the S&P 500 Index, our dots just kind of do not follow a discernable pattern.  Again, for the statistically inclined folks out there, the correlation coefficients are -0.10 and -0.041, respectively.  As always, we won’t get too waded down into the mathematical weeds but a correlation coefficient close to 0 means that there is essentially no correlation/relationship between the two.  To make an analogy, you can think of what is the correlation between birds in your backyard and the number of jars of pickles for sale at your local grocery store?  Well, there should be no relationship whatsoever.  Even if there were, it would not make any sense.  In our case here, there is at least some logic underlying our premise of the most recent return on the S&P 500 Index and the future returns over that same time period.  As we see though, there is really nothing actionable to embark upon for individual investors to properly engage in “market timing”.

Before we totally give up on “market timing”, we can take a look at the same charts but extending the time periods to five years and ten years.  Let’s take a look at those two graphs:

Five Year Correlation

Ten Year Correlation

The correlation coefficient for the five-year chart is 0.028, so we cannot really use that long of a time period either.  I will admit that the ten-year chart looks a little more promising.  We have a graph that looks somewhat more like the fifteen-year graph that I started off with.  In fact, the correlation coefficient is -0.276.  And a negative number is what we want to see in order to try “market timing”.  Unfortunately, the number is really not strong enough to not get caught.  By this I mean, we can see that “market timing” would have worked from 1975-1985 and also from 1990-2001 roughly.  However, 1965-1975 has a grouping of returns that don’t work and 2002-2008 has mixed results as well.  Note that there are less data points because there needs to be at least 10 years of future returns in order to compare the current record of 10-year annualized returns with what the next 10 years of stock returns will end up being.

Overall, we have seen that “market timing” in the short term (even as defined out to five years) does not really have much, if any, predictive power.  Therefore, if you make decisions related to “market timing” based upon how the stock market has performed in any time period five years or less, it is clearly a “fool’s errand” or incredibly difficult to do.  And by the latter, I mean that you can reliably do so over more than one major change in market direction.  The majority of market pundits that you will see or read about have made one correct call which is not nearly enough to judge his/her investing acumen related to “market timing”.

I will close out the discussion of “market timing” by using the Financial Crisis and ensuing Great Recession.  Many folks correctly called (or were proven right without the reason for the bubble matching their investment thesis) this major stock market inflection point.  They correctly saw the unsustainable bubble in housing, the rise of financial stocks, and the buildup of toxic securities like subprime loans.  However, many of those same individuals never changed their investment thesis and failed to tell individual investors to return to the stock market and buy.  Essentially there are still folks that will tell you we are in a bubble.  Now I am not bold and/or grandiose enough to weigh in on the current value of the stock market.  But you need to know that most of the people who call a wicked crash in stocks or a massive bull market do not change their investment thesis prior to the next big turn.

For example, let’s say that you learned about stock investing 10 years or so ago and decided to invest $1,000.00 in the S&P 500 Index toward the end of October 2007.  And yes, this was the absolute worst time to invest in stocks.  Sadly, by March 2009, you would have lost 50% of your investment and have only $500.00 at that point in time.  You might feel great if you listened to someone who called the top and told you that the fourth quarter of 2007 was the absolute worse time to buy stocks.  But I am willing to bet that this same person would not have told you when it was “safe” to invest again.  If you knew to expect bouts of extreme volatility in the stock market beforehand, you could have kept your money in the stock market.  At the end of December 2018, you would have had $1,712.36 using our 13.1% 10-year annualized return over that time.  If the original market predictor of catastrophe told you to just keep your $1,000.00 in the bank you would have $1,160.54 (assuming generously that you could earn 1.50% over the ten years in your bank saving account).  Adjusting the hypothetical investor who simply kept his/her money in stocks back to inflation, he/she would have $1,404.73 (assuming 2.0% inflation over the last 10 years which is higher than was actually experienced).  At the end of December 2018, you would have a bit more than 21% higher in inflation-adjusted dollars than the person who just never invested (or took his/her money out of stocks right at the end of October 2007 but never returned to stocks).

Now I will admit that my hypothetical scenario would have tried the “intestinal fortitude” of the most seasoned professional investors after seeing a 50% market drop over 1.5 years.  My only point with the example is that, even if you could not have held your nerve to remain invested in stocks over the Financial Crisis, the investment pundit(s) who tells you the exact top with a brilliant prediction also needs to tell you when to invest or sell again in the future (i.e. “market timing”).  Rarely will you see such a prognosticator that can totally change their investment thesis to get the next call right.  You are much better off abstaining from “market timing” and sticking to your long-term investment strategy.  Of course, that may indeed call for selling or buying a portion of stocks at certain given points to change your investment portfolio allocation to match your risk tolerance and financial goals.  But trying to utilize “market timing” to be in and out to experience hardly any losses and capture all the gains is just not realistic, so you might as well discard the entire investment strategy of “market timing”.

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