The book I am currently reading, The Checklist Manifesto: How to Get Things Right by Atul Gawande, references a white paper discussing the difference between complicated and complex. The white paper, entitled The Simple, the Complicated, and the Complex: Educational Reform Through the Lens of Complexity Theory, is written by Sean Snyder and is published through The Organization for Economic Cooperation and Development (OECD). It can be found here. Both sources, the book and the white paper, adapted information from the original study by Professors Brenda Zimmerman of New York University and Sholom Glouberman of the University of Toronto where they analyzed Medicare reform in their landmark paper Complicated and Complex Systems: What Would Successful Reform of Medicare Look Like?, which can be viewed here. All three sources discuss the difference between complicated and complex problems.
The following is an excerpt from the book explaining the difference between complicated and complex with an example:
Complicated problems are ones like sending a rocket to the moon. They can be sometimes broken down into a series of simple problems. But there is not a straightforward recipe. Success frequently requires multiple people, often multiple teams, and specialized expertise. Unanticipated difficulties are frequent. Timing and coordination become series concerns.
Complex problems are ones like raising a child. Once you learn how to send a rocket to the moon, you can repeat the process with other rockets and perfect it. One rocket is like another rocket. But not so with raising a child, the professors point out. Every child is unique. Although raising one child may provide experience, it does not guarantee success with the next child. Expertise is valuable but most certainly not sufficient. Indeed, the next child may require an entirely different approach from the previous one. And this brings up another feature of complex problems: their outcomes remain highly uncertain.
Mr. Snyder elaborates on the difference between the two:
Complicated contexts are the realm of expertise and data analysis – the known unknowns. Cause and effect are not self-evident but can be teased out through analysis. The policy maker’s role here is to assemble the requisite minds and encourage differing opinions while avoiding paralysis of analysis. Once cause and effect are understood, interventions can be undertaken to tackle the problem, and, if the required expertise were present during the discussion phase, as in the case of the rocket launch above, the solution should work and be replicable.
The complex is the realm of the unknown unknowns. It is a space of constant flux and unpredictability. There are no right answers, only emergent behaviours... The policy maker’s role in this space is to create safe spaces for patterns to emerge, which is best done by increasing levels of interaction and communication within the system to its largest manageable level. Expertise is useful but not sufficient to solve complex problems – great patience and a sharp eye for new behavioural patterns are the only way forward.
Once an understanding of the difference between complicated and complex is developed, what are the practical implications when problem solving?
The key is recognition. Is the issue is complicated or complex? This will then prompt answers to other questions: Is there a pattern to be followed? Can something be replicated to achieve success? Is one dealing with dynamic characteristics? Can a formula be applied? Will outside expertise solve the problem or only increases the chances of solving the problem? Will a heuristic help?
Despite often being used as synonyms, complicated and complex are very different. It is important to understand the differences between the two and to be able to apply it to problems and decisions in order to take the steps towards resolutions more effectively.
- Joe
Sunday, August 31, 2014
Saturday, August 30, 2014
Benjamin Franklin
I just finished reading Benjamin Franklin's autobiography. While the autobiography was very interesting overall, one takeaway in particular stood out to me:
A few excerpts from the text:
From a child I was fond of reading, and all the little money that came into my hands was ever laid out in books.
He credits reading for some of his other skills:
My mind having been much more improv'd by reading than Keimer's, I suppose it was for that reason my conversation seem'd to be more valu'd.
He was friends with others who read a lot:
My chief acquaintances at this time were Charles Osborne, Joseph Watson, and James Ralph, all lovers of reading.
He even created a library system, one of the first of its kind in the Colonies:
The libraries were augmented by donations; reading became fashionable; and our people, having no publick amusements to divert their attention from study, became better acquainted with books, and in a few years were observ'd by strangers to be better instructed and more intelligent than people of the same rank generally are in other countries.
Reading was a priority, both to learn and for fun:
This library afforded me the means of improvement by constant study, for which I set apart an hour or two each day.
Reading was the only amusement I allow'd myself.
Benjamin Franklin's reading habits remind me of a quote by Charlie Munger:
In my whole life, I have known no wise people who didn't read all the time -- none, zero. You'd be amazed at how much Warren (Buffett) reads -- at how much I read. My children laugh at me. They think I'm a book with a couple of legs sticking out.
- Joe
Benjamin Franklin read a lot.
A few excerpts from the text:
From a child I was fond of reading, and all the little money that came into my hands was ever laid out in books.
He credits reading for some of his other skills:
My mind having been much more improv'd by reading than Keimer's, I suppose it was for that reason my conversation seem'd to be more valu'd.
He was friends with others who read a lot:
My chief acquaintances at this time were Charles Osborne, Joseph Watson, and James Ralph, all lovers of reading.
He even created a library system, one of the first of its kind in the Colonies:
The libraries were augmented by donations; reading became fashionable; and our people, having no publick amusements to divert their attention from study, became better acquainted with books, and in a few years were observ'd by strangers to be better instructed and more intelligent than people of the same rank generally are in other countries.
Reading was a priority, both to learn and for fun:
This library afforded me the means of improvement by constant study, for which I set apart an hour or two each day.
Reading was the only amusement I allow'd myself.
Benjamin Franklin's reading habits remind me of a quote by Charlie Munger:
In my whole life, I have known no wise people who didn't read all the time -- none, zero. You'd be amazed at how much Warren (Buffett) reads -- at how much I read. My children laugh at me. They think I'm a book with a couple of legs sticking out.
- Joe
Friday, August 15, 2014
Arithmetic Versus Geometric Mean
An important concept of investing which can be somewhat challenging to grasp is the difference between arithmetic mean and geometric mean.
Arithmetic mean is also known as the simple average. It is the sum of all numbers divided by the number of observations. For example, the arithmetic mean of 4,5,6, and 7 is 5.5, calculated the following way:
(4+5+6+7)/4 = 5.5
The geometric mean is notably different. As it relates to investing, the geometric mean can be used to calculate a time-weighted compounded rate of return. The formula to calculate geometric mean is the following:
The difference between the two as it applies to investing is best illustrated through an example:
From year 1 to year 2 a stock increases in value by 100%.
From year 2 to year 3 the stock decreases in value by 50%.
The arithmetic return is 25%, calculated as (100%+-50%)/2
The geometric return is 0%, calculated using the formula.
This is a significant difference. If we use some specific stock prices and apply the returns, we can more clearly understand:
From year 1 to year 2 a stock at $20 increases in value by 100% to $40.
From year 2 to year 3 the stock at $40 decreases in value by 50% to $20.
Even though the arithmetic return is 25%, the stock which was worth $20 at the beginning of year 1 is still worth $20 at the end of year 2.
Another example from a different perspective:
You have $100. You lose 10% and then gain 10%. How much do you now have?
The answer is $99 because 10% of 100 is 10 but 10% of 90 is 9.
Even though the arithmetic return is 0%, the geometric return is actually negative.
This is one of the reasons why minimizing losses can be more important than maximizing gains - losses hurt more than gains help, both literally and psychologically through loss aversion.
-Joe
Arithmetic mean is also known as the simple average. It is the sum of all numbers divided by the number of observations. For example, the arithmetic mean of 4,5,6, and 7 is 5.5, calculated the following way:
(4+5+6+7)/4 = 5.5
The geometric mean is notably different. As it relates to investing, the geometric mean can be used to calculate a time-weighted compounded rate of return. The formula to calculate geometric mean is the following:
The difference between the two as it applies to investing is best illustrated through an example:
From year 1 to year 2 a stock increases in value by 100%.
From year 2 to year 3 the stock decreases in value by 50%.
The arithmetic return is 25%, calculated as (100%+-50%)/2
The geometric return is 0%, calculated using the formula.
This is a significant difference. If we use some specific stock prices and apply the returns, we can more clearly understand:
From year 1 to year 2 a stock at $20 increases in value by 100% to $40.
From year 2 to year 3 the stock at $40 decreases in value by 50% to $20.
Even though the arithmetic return is 25%, the stock which was worth $20 at the beginning of year 1 is still worth $20 at the end of year 2.
Another example from a different perspective:
You have $100. You lose 10% and then gain 10%. How much do you now have?
The answer is $99 because 10% of 100 is 10 but 10% of 90 is 9.
Even though the arithmetic return is 0%, the geometric return is actually negative.
This is one of the reasons why minimizing losses can be more important than maximizing gains - losses hurt more than gains help, both literally and psychologically through loss aversion.
-Joe
Saturday, August 9, 2014
Correlations and Investing
One of my favorite bloggers is Ben Carlson. He is a CFA (Chartered Financial Analyst) and author of the blog A Wealth of Common Sense. I would strongly recommend you check out his blog by clicking on the link here.
Mr. Carlson has had some great posts recently on correlations as it relates to investing. To preface, investors often look for lowly correlated, negatively correlated, or uncorrelated assets because this is a basic principle behind diversification, famously referred to as the only free lunch in investing. However, just because an asset has a low correlation or is uncorrelated with another does not make it a good investment. As Mr. Carlson writes, this is because correlations are dynamic, not static, meaning they change over time. Additionally, the risk-return tradeoff still must be considered when deciding between investment assets. For example, Mr. Carlson notes how "cash has little correlation with the S&P 500, just as commodities do, but that doesn’t mean it makes sense to hold cash over the long run." Furthermore, investing solely for the sake of negative correlation can be inappropriate as well:
The problem with a focus exclusively on correlation is that stocks are up on average three out of every four years. So there isn’t an investment that perfectly offsets the risk and returns from stocks with similar performance. Correlations also tend to change when high returning strategies are discovered by the wider investing community.
In other words, since stocks are up on average three out of every four years, assets negatively correlated with stocks must be down on average three out of every four years.
Another issue is that when everything goes extremely poorly (i.e. a depression or recession), the correlation concept fails. Mr. Carlson writes:
The other problem with diversification is that it can fail you at the worst possible times. We saw this in the 2008 crash when everything got killed, save for cash and U.S. Treasury bonds. When markets go terribly wrong, correlations tend to go to 1 (everything falls together).
Overall, investing in assets solely because they provide negative correlation, low correlation, or are uncorrelated can be a dangerous strategy. That being said, diversification is an essential aspect of investing and correlation is a significant part of diversification. However, each assets must be considered from a risk-return standpoint both from a individual standpoint as well as from a comprehensive and holistic point of view.
- Joe
sources:
A Lesson in Portfolio Correlations via A Wealth of Common Sense
William Bernstein on Diversification via A Wealth of Common Sense
There’s No Such Thing As Precision When Investing via A Wealth of Common Sense
Mr. Carlson has had some great posts recently on correlations as it relates to investing. To preface, investors often look for lowly correlated, negatively correlated, or uncorrelated assets because this is a basic principle behind diversification, famously referred to as the only free lunch in investing. However, just because an asset has a low correlation or is uncorrelated with another does not make it a good investment. As Mr. Carlson writes, this is because correlations are dynamic, not static, meaning they change over time. Additionally, the risk-return tradeoff still must be considered when deciding between investment assets. For example, Mr. Carlson notes how "cash has little correlation with the S&P 500, just as commodities do, but that doesn’t mean it makes sense to hold cash over the long run." Furthermore, investing solely for the sake of negative correlation can be inappropriate as well:
The problem with a focus exclusively on correlation is that stocks are up on average three out of every four years. So there isn’t an investment that perfectly offsets the risk and returns from stocks with similar performance. Correlations also tend to change when high returning strategies are discovered by the wider investing community.
In other words, since stocks are up on average three out of every four years, assets negatively correlated with stocks must be down on average three out of every four years.
Another issue is that when everything goes extremely poorly (i.e. a depression or recession), the correlation concept fails. Mr. Carlson writes:
The other problem with diversification is that it can fail you at the worst possible times. We saw this in the 2008 crash when everything got killed, save for cash and U.S. Treasury bonds. When markets go terribly wrong, correlations tend to go to 1 (everything falls together).
Overall, investing in assets solely because they provide negative correlation, low correlation, or are uncorrelated can be a dangerous strategy. That being said, diversification is an essential aspect of investing and correlation is a significant part of diversification. However, each assets must be considered from a risk-return standpoint both from a individual standpoint as well as from a comprehensive and holistic point of view.
- Joe
sources:
A Lesson in Portfolio Correlations via A Wealth of Common Sense
William Bernstein on Diversification via A Wealth of Common Sense
There’s No Such Thing As Precision When Investing via A Wealth of Common Sense
Subscribe to:
Posts (Atom)