Archive for the ‘Economics & Markets’ Category
I asked my assistant to do an updated stock market seasonality study.
The data we used was the S&P 500 index from 1927 which we found in Nobel Prize winner Robert Shiller’s database.
We assumed that at the beginning of each year we invested $1 in the index, and we observed how the investment fluctuated over the year. Then we took the average over three different periods of time: the last 20 years, the last 50 years, and the last 86 years.
Here is the chart we got: Read the rest of this entry »
Yesterday I received an email from a doctor client of mine telling me how he had a conversation with some fellow doctors, and all of them are pulling their money out of stocks because they feel that with the market breaking new high after new high, a crash is imminent. He wanted my opinion.
First of all, while all of his doctor friends might feel a market crash is imminent and certain, there is simply no such thing as certainty in the stock market. All we can work with are odds. The following are the odds of market corrections:
|Magnitude of market decline||Frequency of occurrence (out of 64 years from 1950-2013)|
|>5%||Every year (94%)|
|>10%||Every two years (58%)|
|>20%||Every five years (20%)|
|>30%||Every ten years (10%)|
|>40%||Every fifty years (2%)|
My study also shows that the market breaking a new high does not substantially change the odds of returns. In other words, the odds of the market dropping over 20% in the next twelve months are still about one in five; the odds of the market dropping over 30% in the next twelve months are still about one in ten.
Read the rest of this entry »
Last month I did a study to understand why equally weighted the S&P 500 index RSP has outperformed value weighted S&P 500 index SPY by almost 3% a year since its inception. My conclusion is that it’s mostly due to Fama French risk factor loading.
However, my research also found after removing the effect of risk factors, RSP has a slight alpha advantage over SPY. I conjecture this alpha advantage is due to the fact that RSP requires annual rebalancing and SPY does not. In other word, this could be the so-called “rebalance bonus.”
To test its robustness, I extended my study to six pair of Fama French “indices.”
1. Equity premium is the additional “wage” one can earn from taking stock market risk over not taking stock market risk.
2. Small cap premium is the additional “wage” one can earn from taking small company risk over taking large company risk.
3. Value premium is the additional “wage” one can earn from taking non-growing company risk over taking growing company risk.
Those who are ardent believers of an efficient market such as Nobel Prize winner Eugene Fama usually believe all returns should be the result of taking risk and that simple actions like rebalancing periodically should not produce additional returns.
Those who believe the market is emotion-driven, such as Nobel Prize winner Robert Shiller, believe in a rebalancing “bonus”. Since the market is either over-priced or under-priced from time to time, rebalancing allows us to take advantage of this market mispricing.
The return differential of RSP vs SPY provides an excellent control experiment to test whether this illustrious rebalancing “bonus” actually exists. SPY and RSP invest in the same 500 largest stocks of the US. SPY being a cap-weighted fund, does not require rebalancing, while RSP being a equally weighted fund requires periodic rebalancing.
Since its inception on March 9, 2003, RSP has returned 193%. At the same time, SPY has only returned 97%. This is extremely puzzling as both RSP and SPY hold the same S&P 500 stocks.The only difference is that SPY is a cap-weighted fund and RSP is an equally-weighted one. This begs the question, is RSP’s outperformance normal; and more importantly, is it likely to continue?
To answer the question I asked my intern Nahae Kim to run a regression based on the Nobel Prize winning Fama-French Three Factor Model.
R(x) – rf = alpha + beta1*(Rmkt – rf) + beta2*SML + beta3*HML
Where R(x) is the return of the selected fund, x being either RSP or SPY, alpha is the “skill” of the fund, beta1 is the market risk loading, beta2 is the small cap risk loading and beta3 is the value risk loading.
Here is what I got from the two regressions.
Recently, a prospective client of mine sent me an email asking about my thoughts on Bill Bernstein’s new book “Deep Risk.” I have not read the book yet, but I do have my own ideas about deep risk vs shallow risk.
I define shallow risk as a potential loss that you can recover from and deep risk as a loss that you cannot recover from.
Market volatility, for example, is a shallow risk. It is very visible and it is scary, there is even a TV channel devoted to it. (That TV channel is called CNBC.)
But taking on shallow risk is how you earn your investment keep. Thus, it should not be feared, it should be welcomed.
Now what are the deep risks you should ardently avoid? I can think of three: inflation risk, behavior risk and agency risk.