Fooled by Randomness is a book by Nassim Nicholas Taleb on The Hidden Role of Chance in the Markets and in Life. Until I read this book I believed that Luck contributed 99% in determining success. Now I've revised that to 100%.
The primary premise of the book is that we commonly mistake luck for skill. And the author has in his engaging style, used the financial markets to illustrate his point very effectively. There are quite a few outstanding examples he has used that seem obvious and most people, including professionals like traders and even doctors would take decisions based on their understanding of the obvious. Yet, simple mathematics would show them how wrong they are. Let me give a couple of these examples to illustrate the point.
An example of a mistake cited in the book is one that most of us make in handling our financial investments. It revolves around probability, outcome and expectations. Lets say we engage in an investment strategy that has 999 chances in 1000 of making $1 and 1 (Event A) and a chance in 1000 of losing $10,000. The expectation is a loss of $9.
Event - A
Probability - 999/1000
Outcome - $1
Expectation - $0.999
Event - B
Probability - 1/1000
Outcome - (-$10,000)
Expectation - (-$10)
Total - (-$9.001)
Whilst we are quick to spot the problem and hence not take this strategy in a normal bet. Yet we do it all the time in the financial markets. One of the probable reasons could be that the negative outcome is something which we don't anticipate and hence end up ignoring. We focus on the frequency and probability of a profit. The mathematical truth is that "frequency or probability if the loss, in and by itself is totally irrelevant; it needs to be judged by the magnitude of the outcome.
According to Mr. Taleb, one of the major issues that results in us making gross errors is our understanding or rather lack of it in probability and our inherent biases.
"Below is an account of a well-known test. A test of a disease presents a rate of 5% false positives. The disease strikes 1/1,000 of the population. People are tested at random, regardless of whether they are suspected of having the disease. A patient's test is positive. What's the probability of the patient being stricken by the disease.
Most doctors answered 95%, simply taking into account the fact that the test has a 95% accuracy rate. The answer is the conditional probability that the patient is sick and the test shows it - close to 2%. Less than 1 in 5 professionals got it right."
Are you too wondering how is it 2% ?
"Consider that out of 1,000 patients who are administered the test, 1 will be expected to be afflicted with the disease. Out of the population of the remaining 999 healthy patients, the test will identify about 50 with the disease, since its 95% accurate. The correct answer should be the probability of being afflicted with the disease for someone selected at random who presented a positive test is the following ratio:
No. of afflicted persons/No. of true and false positives = 1 / 51
Think of the number of times you'll be given medication that carries damaging side effects for a given disease you were told you had, when you may only have a 2% probability of being afflicted"
The takeaway for me is that in most aspects, especially the financial aspects, most individuals especially experts don't really understand the fundamentals. If you realize this, along with the realization that neither do you, you could become very rich, relatively quickly. I plan to try in 2012, and will let you know in Dec. of 2012 how it al worked out. Until then, happy trading.
The primary premise of the book is that we commonly mistake luck for skill. And the author has in his engaging style, used the financial markets to illustrate his point very effectively. There are quite a few outstanding examples he has used that seem obvious and most people, including professionals like traders and even doctors would take decisions based on their understanding of the obvious. Yet, simple mathematics would show them how wrong they are. Let me give a couple of these examples to illustrate the point.
An example of a mistake cited in the book is one that most of us make in handling our financial investments. It revolves around probability, outcome and expectations. Lets say we engage in an investment strategy that has 999 chances in 1000 of making $1 and 1 (Event A) and a chance in 1000 of losing $10,000. The expectation is a loss of $9.
Event - A
Probability - 999/1000
Outcome - $1
Expectation - $0.999
Event - B
Probability - 1/1000
Outcome - (-$10,000)
Expectation - (-$10)
Total - (-$9.001)
Whilst we are quick to spot the problem and hence not take this strategy in a normal bet. Yet we do it all the time in the financial markets. One of the probable reasons could be that the negative outcome is something which we don't anticipate and hence end up ignoring. We focus on the frequency and probability of a profit. The mathematical truth is that "frequency or probability if the loss, in and by itself is totally irrelevant; it needs to be judged by the magnitude of the outcome.
According to Mr. Taleb, one of the major issues that results in us making gross errors is our understanding or rather lack of it in probability and our inherent biases.
"Below is an account of a well-known test. A test of a disease presents a rate of 5% false positives. The disease strikes 1/1,000 of the population. People are tested at random, regardless of whether they are suspected of having the disease. A patient's test is positive. What's the probability of the patient being stricken by the disease.
Most doctors answered 95%, simply taking into account the fact that the test has a 95% accuracy rate. The answer is the conditional probability that the patient is sick and the test shows it - close to 2%. Less than 1 in 5 professionals got it right."
Are you too wondering how is it 2% ?
"Consider that out of 1,000 patients who are administered the test, 1 will be expected to be afflicted with the disease. Out of the population of the remaining 999 healthy patients, the test will identify about 50 with the disease, since its 95% accurate. The correct answer should be the probability of being afflicted with the disease for someone selected at random who presented a positive test is the following ratio:
No. of afflicted persons/No. of true and false positives = 1 / 51
Think of the number of times you'll be given medication that carries damaging side effects for a given disease you were told you had, when you may only have a 2% probability of being afflicted"
The takeaway for me is that in most aspects, especially the financial aspects, most individuals especially experts don't really understand the fundamentals. If you realize this, along with the realization that neither do you, you could become very rich, relatively quickly. I plan to try in 2012, and will let you know in Dec. of 2012 how it al worked out. Until then, happy trading.