Geoff Considine

Using Default Risk to Limit Downside in Individual Stock Investing

Quaazy1:

Any Monte Carlo model that does not account for correlation between positions is essentially pointless. QPP has a sophisticated tool for capturing and managing the correlations between all positions. QPP is actually considerably more sophisticated that a tools based on Style Analysis in this regard because it captures all correlation effects and not just correlations due to mutual correlation to indexes.

I have performed long-term out-of-sample tests on portfolios of assets and have shown that QPP does a solid job of generating expected risk and return in total portfolios of correlated assets.

Using Default Risk to Limit Downside in Individual Stock Investing

Hi Quaazy1:

The current version of QPP assumes no serial correlation in return in the simulation. This is measured historically, however. This is okay for investors with time horizons beyond about a year because the dcay time scale for autocorrelation is about a year in most studies. QPP is not intended to be a momentum investing tool.

Using Default Risk to Limit Downside in Individual Stock Investing

Bear Stearns Part 2: The comment above is especially notable given that Moody's had BSC rated at A2 until 3/14/08, at which time Moody's downgraded BSC to Baa1. QPP's projected 1% / 1 year risk as calculated at the end of February is in line with credit ratings right on the edge of junk (see chart in this article).

Using Default Risk to Limit Downside in Individual Stock Investing

FYI: Bear Stearns had a 1-year, 1% ile projected return in QPP of -75% for the period ending 2/29. In the article above, I suggested that individual investors avoid stocks with 1% ile projected return worse than -50% to -60%. BSC would have been avoided on this basis.

Using Default Risk to Limit Downside in Individual Stock Investing

Hi Manhapf:

The idea of using QPP as a leading projection of upgrades or downgrades is an interesting one--and you can look for future articles on this. I have been doing some testing and it appears that QPP has shown very high tail risk prior to some recent downgrades.

Black Swans, Real Estate and Financial Stocks

Mithrandir is correct. A lot of the problem with dmnieren's focus on five multi-month swings is that it misses the fact that when you even look to an annual basis, things get much better. Then there is the related issue of 'timing bias.' A good model like QPP estimates the risk over a specific future period (12 months in this article). To note that there have been some really bad events misses the more important statistic of the likelihood of such bad events over the next N months.

I cannot help but feel that some portfolio of the popularity of black swan thinking (as expressed here) has to do with a lack of understanding of statistics.

Black Swans, Real Estate and Financial Stocks

FH: Okay, don't stretch the metaphor too far. First, you should not lose all your savings on one position even if the firm goes belly up--this is the first core precept of portfolio thinking: be able to live through a low percentile event. If your primary point is the risk of false confidence, here is the question. If a model has been shown over a range of market conditions to provide plausible warnings of the potential for extreme events, are you better off using it or not? If you place bets such that you will only thrive if a model is near perfect (like LTCM), you will blow eventually. On the other hand, if you use a model prudently to manage overall portfolio risk, the model can help you to design a better portfolio. This is a major issue in much of quantitative finance and it is a thriving area of study. Investors will be missing some tools that are standard in professional portfolio management if they simply believe Mr. Taleb that the world is so fundamentally unpredictable that models are useless.

Black Swans, Real Estate and Financial Stocks

To VAMC:

While testing models after the fact it is always a good idea to be careful. The model I used QPP was run with default inputs used in my articles for years. This is not a case of over-fitting. There is no reverse engineering issue here.

The bottom line here is that you and everyone else are free to disregard available models because you feel they have the potential for 'black swan blindness.' You may as well argue that weather forecasts are pointless--and you are free to do so. Just carry your umbrella and slicker every day.

Black Swans, Real Estate and Financial Stocks

To dmnieren:

I appreciate your enthusiasm, but you are not grasping the numbers. First of all, the probability of a cumulative 12-month decline is different than the various partial years, etc. Just to prove a point, I have gotten the 25-year history of C and analyzed the 2.5th percentile in returns for all 12-month periods. Guess what--its -36%! So, my analysis was predicting a substantially higher probability of the observed loss than history.

Black Swans, Real Estate and Financial Stocks

I agree with Mr. Meisel above.

To FH: your comments suggest that you are not really familiar with modern financial modeling. Modern risk modeling is very useful in helping investors estimate the risk levels of their portfolios. These models are well-tested and benchmarked (the good ones at least). This does not mean that users should be naiive with regards to the limits of the models. They are far from perfect representations of reality--but they are still very useful.


Mr. Taleb is correct that we need to understand the limits of models. Professional energy traders rely on weather forecasts--knowing that these forecasts decrease in accuracy as you go out in time. If I know that there is a 5% chance of 100+ Deg high temperatures in Chicago on a given day, I would manage my positions accordingly. I would not simply ignore the forecast because I knew that the forecast model was imperfect.

Now, I do not hope to convince you or anyone else in such a short article or comments below. I do hope to stimulate interest in the solid use of portfolio management tools such as those that Mr. Taleb dismisses as useless. There is an enormous well-established discipline of quantitative portfolio management and I believe that the basic lack of understanding of this discipline is a major source of information asymmetry between investors. Companies like RiskMetrics, SunGard, and (on a much smaller scale) my own little firm provide well-tested tools. No reasonable practitioner would suggest that people have too much belief in such tools, but they are an important tool in one's arsenal.

When David Swensen of Yale says that he is targeting a specific average return on the Yale endowment with a specific target standard deviation in return, where do you think he gets these numbers?

If you want to get a sense of what it being done by practitioners, simply do a web search on "Basel II VaR."

Have a look at the CFA curriculum if you want more information on modern methods, too.

Black Swans, Real Estate and Financial Stocks

I am in agreement with ZB and User 127562: people don't like to look hard at numbers. Mr. Taleb's sweeping rejection of portfolio theory is the wrong solution--he has created a rhetorical position that cannot be disproven. If models did predict non-vanishing probability of a certain scale of event, it's not a black swan (by his definition). There is no way to reject Mr. Taleb's hypothesis from a quantitative standpoint.

Now, I agree with Susan, too: Mr. Taleb's arguments are often worthy of thought and discussion. When he says, quite bluntly, that portfolio theory and quantitative methods as a whole are useless (as in the quote above) and even itellectually lazy, he is taking it too far.

I am a big fan of logic and philosophy, and Mr. Taleb often uses strategies that are ill-founded. By using LTCM as an example, he is saying "hey, look at this case where smart people put too much faith in quantitative finance" and extrapolating to saying that the entire edifice of portfolio theory is wrong. There is a big unsupported leap in logic here. The insurance and banking industries have used these types of models very successfully for quite some time--and will continue to.

Anyway, this is a useful topic and the 'black swan' metaphor motivates good discussions. Thanks.

Jim Cramer's 10 Predictions for 2008

Mr. Cramer is a key agent of market inefficiency. His picks and analysis have consistently been shown to under-perform the market, yet his books are best-sellers, his TV show is a hit, etc. There were some good articles on SA that discussed his 'track record.'

Low-Beta Portfolio Strategies: Devising A Low Risk Game Plan For the Current Market

Here's a great argument for the low Beta / low R^2 portfolio from Ben Bernanke:

biz.yahoo.com/ap/07011...

Low-Beta Portfolio Strategies: Devising A Low Risk Game Plan For the Current Market

Also, here is an article about the phenomenon that some stocks and sectors seem to get more correlated when they have negative returns:

www2.gsb.columbia.edu/...

The authors suggest an additional interesting idea: that this correlation, which increases total portfolio downside is the risk that investors take when they try to use momentum investing strategies. This is an interesting idea.

Low-Beta Portfolio Strategies: Devising A Low Risk Game Plan For the Current Market

By the way, I noticed that Berkshire Hathaway has recently dramatically upped their holdings in JNJ. I recently wrote an article about Berkshire's equity holdings and noted that they very effectively exploited low correlation assets:

financial.seekingalpha...

This weekend, I read this article from SA that noted that BRK has just increased holdings in JNJ--it was not in the topc twenty when I wrote that article but it is now the 8th largest equity holding:

biz.yahoo.com/seekinga...

Hmm. Interesting.