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Enrich Your Future 16: The Estimated Return Is Not Inevitable

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Manage episode 445255982 series 2406056
Inhalt bereitgestellt von Andrew Stotz. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Andrew Stotz oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

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Apple | Listen Notes | Spotify | YouTube | Other

Quick take

In this episode of Enrich Your Future, Andrew and Larry Swedroe discuss Larry’s new book, Enrich Your Future: The Keys to Successful Investing. In this series, they discuss Chapter 16: All Crystal Balls are Cloudy.

LEARNING: Estimated return is not always inevitable.

“If returns are negative early on, don’t withdraw large amounts because when the market eventually recovers, you won’t have that money to earn your returns.”
Larry Swedroe

In this episode of Enrich Your Future, Andrew and Larry Swedroe discuss Larry’s new book, Enrich Your Future: The Keys to Successful Investing. The book is a collection of stories that Larry has developed over 30 years as the head of financial and economic research at Buckingham Wealth Partners to help investors. You can learn more about Larry’s Worst Investment Ever story on Ep645: Beware of Idiosyncratic Risks.

Larry deeply understands the world of academic research and investing, especially risk. Today, Andrew and Larry discuss Chapter 16: All Crystal Balls are Cloudy.

Chapter 16: All crystal balls are cloudy

In this chapter, Larry illustrates why past returns are not crystal balls that predict future returns.

According to Larry, the problem with all forecasts that deal with estimations of probabilities is that people tend to think of them in a deterministic way. He says that as an investor, you should think about returns with the idea that distribution and estimate are only the middle points.

Your plan has to be prepared for either the good tail to show up, which is easy to deal with and usually will allow you to take chips off the table and reduce your risk because you’ll be well ahead of your goal. But if the bad tail shows up, you may have to either work longer, plan on saving more, or rebalance, which means buying stocks at a tough time.

The threat of sequence risk

To demonstrate the danger of sequence risk, Larry asks us to imagine it’s 1973, and stocks have returned 8% in real terms and 10% in nominal returns. We’ve had similar results over the next 50 years. Say an investor in that time frame decides to withdraw 7% yearly from their portfolio in real terms because they know with their clear crystal ball that they will get 8% for the next 50 years.

This means if they take out, say, $100,000 in the first year, and inflation is 3%, to keep their actual spending the same, they have to take out $103,000. According to Larry, this investor will be bankrupt within 10 years due to the sequence of returns, which is the order in which the returns occur, not the returns themselves.

As you can see in the table below, despite providing an 8.7% per annum real return over the 27 years, because the S&P 500 Index declined by more than 37% from January 1973 through December 1974, withdrawing an inflation-adjusted 7% per annum in the portfolio caused it to be depleted by the end of 1982—in just 10 years! (Note that from January 1973 through October 1974, when the bear market ended, the S&P 500 lost 48%.)

Sacrificing expected returns

Larry says this example shows the danger of sequence risk and illustrates that the order of returns matters significantly in the decumulation phase because systematic withdrawals work like a dollar-cost averaging program in reverse—market declines are accentuated. This can cause principal loss, which the portfolio may never recover from.

In this case, the combination of the bear market and relatively high inflation caused the portfolio to shrink by almost 56% in the first two years. For the portfolio to be restored to its original $1 million level, the S&P 500 Index would have had to return 127% in 1975. And because of the inflation experienced, the amount to be withdrawn would have needed to increase from $70,000 to over $90,000. In such cases, the odds of outliving one’s assets significantly increase if you don’t adjust the plan (such as increasing savings, delaying retirement, or reducing the spending goal).

The order of returns matters

According to Larry, our investor made the mistake of treating the single-point estimate as if it were an inevitable outcome and not a single potential outcome within a broad spectrum of potential outcomes.

Another mistake our investor made was failing to consider that his investment experience might be different from the return over the entire period because of the impact of his withdrawals. In other words, the order of returns matters, not just the returns over the entire period.

Estimated return is not inevitable

Larry insists that since we live in a world with cloudy crystal balls, and all we can do is estimate returns, it is best to avoid treating a portfolio’s estimated return as inevitable. Consider the possible dispersion of likely returns and calculate the odds of successfully achieving the financial goal.

The goal is generally, though not always, defined as achieving and maintaining an acceptable lifestyle—not running out of money while still alive. In other words, the goal is not to retire with as much wealth as possible but to ensure you do not retire poor and risk running out of assets while still alive.

Using a Monte Carlo simulator to forecast the potential dispersion of returns

Larry says that forecasting the potential dispersion of returns is best accomplished through a Monte Carlo simulator—a computer simulation that uses random processes to model the impact of risk and uncertainty in financial and investment forecasting.

This tool allows one to see the probabilities of different possible outcomes of an investment strategy. The computer program will produce numerous random iterations (usually at least 1,000 and often many thousands), letting one see the odds of meeting a goal. Since thousands of iterations are run, one must think about probabilities instead of just one outcome.

Projecting the likelihood of success

Divide the Monte Carlo simulation based on your investment life into an accumulation phase when you’re working and making contributions and a distribution phase that begins when you retire and lasts as long as you live. The inputs into the Monte Carlo simulation are:

  • The investment assumptions (expected returns, standard deviations, and correlations)
  • Future deposits into the investment account
  • The desired annual withdrawal amount
  • The years the account must last

The output is summarized by assigning probabilities to the various investment outcomes.

The ultimate goal is to ensure you are comfortable with the projected likelihood of success—the odds you can withdraw sufficient funds from the portfolio each year and still achieve your financial goal.

Nobody can predict the future when people are involved

In conclusion, Larry reminds investors that crystal balls will always be cloudy when forecasting the future, be it the weather or stock market returns. He quotes Alan Greenspan’s advice: “Learn everything you can, collect all the data, crunch all the numbers before making a prediction or a financial forecast. Even then, accept and understand that nobody can predict the future when people are involved.”

However, Larry adds that the inability to forecast the future accurately does not render forecasting useless. It just means we must accept this shortcoming and take it into account. Another essential investment advice is to never make the mistake of treating even the highly likely as if it were inevitable.

Further reading

  1. Didier Sornette, Why Stock Markets Crash (Princeton University Press 2002), p. 322.

Did you miss out on the previous chapters? Check them out:

Part I: How Markets Work: How Security Prices are Determined and Why It’s So Difficult to Outperform


Part II: Strategic Portfolio Decisions


About Larry Swedroe

Larry Swedroe was head of financial and economic research at Buckingham Wealth Partners. Since joining the firm in 1996, Larry has spent his time, talent, and energy educating investors on the benefits of evidence-based investing with an enthusiasm few can match.

Larry was among the first authors to publish a book that explained the science of investing in layman’s terms, “The Only Guide to a Winning Investment Strategy You’ll Ever Need.” He has authored or co-authored 18 books.

Larry’s dedication to helping others has made him a sought-after national speaker. He has made appearances on national television on various outlets.

Larry is a prolific writer, regularly contributing to multiple outlets, including AlphaArchitect, Advisor Perspectives, and Wealth Management.

[spp-transcript]

Connect with Larry Swedroe


Andrew’s books


Andrew’s online programs


Connect with Andrew Stotz:


  continue reading

846 Episoden

Artwork
iconTeilen
 
Manage episode 445255982 series 2406056
Inhalt bereitgestellt von Andrew Stotz. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Andrew Stotz oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Listen on

Apple | Listen Notes | Spotify | YouTube | Other

Quick take

In this episode of Enrich Your Future, Andrew and Larry Swedroe discuss Larry’s new book, Enrich Your Future: The Keys to Successful Investing. In this series, they discuss Chapter 16: All Crystal Balls are Cloudy.

LEARNING: Estimated return is not always inevitable.

“If returns are negative early on, don’t withdraw large amounts because when the market eventually recovers, you won’t have that money to earn your returns.”
Larry Swedroe

In this episode of Enrich Your Future, Andrew and Larry Swedroe discuss Larry’s new book, Enrich Your Future: The Keys to Successful Investing. The book is a collection of stories that Larry has developed over 30 years as the head of financial and economic research at Buckingham Wealth Partners to help investors. You can learn more about Larry’s Worst Investment Ever story on Ep645: Beware of Idiosyncratic Risks.

Larry deeply understands the world of academic research and investing, especially risk. Today, Andrew and Larry discuss Chapter 16: All Crystal Balls are Cloudy.

Chapter 16: All crystal balls are cloudy

In this chapter, Larry illustrates why past returns are not crystal balls that predict future returns.

According to Larry, the problem with all forecasts that deal with estimations of probabilities is that people tend to think of them in a deterministic way. He says that as an investor, you should think about returns with the idea that distribution and estimate are only the middle points.

Your plan has to be prepared for either the good tail to show up, which is easy to deal with and usually will allow you to take chips off the table and reduce your risk because you’ll be well ahead of your goal. But if the bad tail shows up, you may have to either work longer, plan on saving more, or rebalance, which means buying stocks at a tough time.

The threat of sequence risk

To demonstrate the danger of sequence risk, Larry asks us to imagine it’s 1973, and stocks have returned 8% in real terms and 10% in nominal returns. We’ve had similar results over the next 50 years. Say an investor in that time frame decides to withdraw 7% yearly from their portfolio in real terms because they know with their clear crystal ball that they will get 8% for the next 50 years.

This means if they take out, say, $100,000 in the first year, and inflation is 3%, to keep their actual spending the same, they have to take out $103,000. According to Larry, this investor will be bankrupt within 10 years due to the sequence of returns, which is the order in which the returns occur, not the returns themselves.

As you can see in the table below, despite providing an 8.7% per annum real return over the 27 years, because the S&P 500 Index declined by more than 37% from January 1973 through December 1974, withdrawing an inflation-adjusted 7% per annum in the portfolio caused it to be depleted by the end of 1982—in just 10 years! (Note that from January 1973 through October 1974, when the bear market ended, the S&P 500 lost 48%.)

Sacrificing expected returns

Larry says this example shows the danger of sequence risk and illustrates that the order of returns matters significantly in the decumulation phase because systematic withdrawals work like a dollar-cost averaging program in reverse—market declines are accentuated. This can cause principal loss, which the portfolio may never recover from.

In this case, the combination of the bear market and relatively high inflation caused the portfolio to shrink by almost 56% in the first two years. For the portfolio to be restored to its original $1 million level, the S&P 500 Index would have had to return 127% in 1975. And because of the inflation experienced, the amount to be withdrawn would have needed to increase from $70,000 to over $90,000. In such cases, the odds of outliving one’s assets significantly increase if you don’t adjust the plan (such as increasing savings, delaying retirement, or reducing the spending goal).

The order of returns matters

According to Larry, our investor made the mistake of treating the single-point estimate as if it were an inevitable outcome and not a single potential outcome within a broad spectrum of potential outcomes.

Another mistake our investor made was failing to consider that his investment experience might be different from the return over the entire period because of the impact of his withdrawals. In other words, the order of returns matters, not just the returns over the entire period.

Estimated return is not inevitable

Larry insists that since we live in a world with cloudy crystal balls, and all we can do is estimate returns, it is best to avoid treating a portfolio’s estimated return as inevitable. Consider the possible dispersion of likely returns and calculate the odds of successfully achieving the financial goal.

The goal is generally, though not always, defined as achieving and maintaining an acceptable lifestyle—not running out of money while still alive. In other words, the goal is not to retire with as much wealth as possible but to ensure you do not retire poor and risk running out of assets while still alive.

Using a Monte Carlo simulator to forecast the potential dispersion of returns

Larry says that forecasting the potential dispersion of returns is best accomplished through a Monte Carlo simulator—a computer simulation that uses random processes to model the impact of risk and uncertainty in financial and investment forecasting.

This tool allows one to see the probabilities of different possible outcomes of an investment strategy. The computer program will produce numerous random iterations (usually at least 1,000 and often many thousands), letting one see the odds of meeting a goal. Since thousands of iterations are run, one must think about probabilities instead of just one outcome.

Projecting the likelihood of success

Divide the Monte Carlo simulation based on your investment life into an accumulation phase when you’re working and making contributions and a distribution phase that begins when you retire and lasts as long as you live. The inputs into the Monte Carlo simulation are:

  • The investment assumptions (expected returns, standard deviations, and correlations)
  • Future deposits into the investment account
  • The desired annual withdrawal amount
  • The years the account must last

The output is summarized by assigning probabilities to the various investment outcomes.

The ultimate goal is to ensure you are comfortable with the projected likelihood of success—the odds you can withdraw sufficient funds from the portfolio each year and still achieve your financial goal.

Nobody can predict the future when people are involved

In conclusion, Larry reminds investors that crystal balls will always be cloudy when forecasting the future, be it the weather or stock market returns. He quotes Alan Greenspan’s advice: “Learn everything you can, collect all the data, crunch all the numbers before making a prediction or a financial forecast. Even then, accept and understand that nobody can predict the future when people are involved.”

However, Larry adds that the inability to forecast the future accurately does not render forecasting useless. It just means we must accept this shortcoming and take it into account. Another essential investment advice is to never make the mistake of treating even the highly likely as if it were inevitable.

Further reading

  1. Didier Sornette, Why Stock Markets Crash (Princeton University Press 2002), p. 322.

Did you miss out on the previous chapters? Check them out:

Part I: How Markets Work: How Security Prices are Determined and Why It’s So Difficult to Outperform


Part II: Strategic Portfolio Decisions


About Larry Swedroe

Larry Swedroe was head of financial and economic research at Buckingham Wealth Partners. Since joining the firm in 1996, Larry has spent his time, talent, and energy educating investors on the benefits of evidence-based investing with an enthusiasm few can match.

Larry was among the first authors to publish a book that explained the science of investing in layman’s terms, “The Only Guide to a Winning Investment Strategy You’ll Ever Need.” He has authored or co-authored 18 books.

Larry’s dedication to helping others has made him a sought-after national speaker. He has made appearances on national television on various outlets.

Larry is a prolific writer, regularly contributing to multiple outlets, including AlphaArchitect, Advisor Perspectives, and Wealth Management.

[spp-transcript]

Connect with Larry Swedroe


Andrew’s books


Andrew’s online programs


Connect with Andrew Stotz:


  continue reading

846 Episoden

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