Why is high risk related with high return?
The current theory about the risky asset returns is that the investment return is proportionally related to the volatility of the investment. In a mathematical form, this relationship can be expressed by the equation.
μ = θ + K σ
Where K is a constant, θ is risk-free return, σ is standard deviation, and μ is the expected return.
The question is why the expected return of risky asset is related to the risk level (standard deviation). Higher risk means higher return. Where does the additional level come from? What is the physical model behind this mathematical equation? Today I think I have solved this physical model problem. This is related to the years of trading experience and my thinking as a hydraulic engineer.
Suppose UBC (uniform building code) is the bible for civil engineers, every practicing civil engineer would buy a copy of UBC at some standard price. Now suppose that the software engineers predict that UBC would be a popular reference book for electronic engineers, chemical engineers, and mechanical engineers. The soft engineers would buy many copies of UBC in order to sell the books later at higher price. So the software engineers would make a profit due to this speculation. The software engineers did that, then the electronic engineers did that, then the chemical engineers did that, and so on. So the demand for UBC is indeed up, so does the book price. After a while, all other engineers except civil engineers realized that the UBC is indeed useless for them. So they are going to sell the acquired books. Then the book price would drop. I think in the stock market, the civil engineers are like the long-term investors (they buy the books for the intrinsic value of the books) while other engineers are the traders (they buy the books because they think they can sell the books at higher prices). So the price of UBC would fluctuate around some intrinsic price.
μ = θ + K σ
Where K is a constant, θ is risk-free return, σ is standard deviation, and μ is the expected return.
The question is why the expected return of risky asset is related to the risk level (standard deviation). Higher risk means higher return. Where does the additional level come from? What is the physical model behind this mathematical equation? Today I think I have solved this physical model problem. This is related to the years of trading experience and my thinking as a hydraulic engineer.
Suppose UBC (uniform building code) is the bible for civil engineers, every practicing civil engineer would buy a copy of UBC at some standard price. Now suppose that the software engineers predict that UBC would be a popular reference book for electronic engineers, chemical engineers, and mechanical engineers. The soft engineers would buy many copies of UBC in order to sell the books later at higher price. So the software engineers would make a profit due to this speculation. The software engineers did that, then the electronic engineers did that, then the chemical engineers did that, and so on. So the demand for UBC is indeed up, so does the book price. After a while, all other engineers except civil engineers realized that the UBC is indeed useless for them. So they are going to sell the acquired books. Then the book price would drop. I think in the stock market, the civil engineers are like the long-term investors (they buy the books for the intrinsic value of the books) while other engineers are the traders (they buy the books because they think they can sell the books at higher prices). So the price of UBC would fluctuate around some intrinsic price.
posted by Unknown at 11:45 AM
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