This is an effort to start a new thread based on a topic introduced (by yours truly) into the UI thread. Here’s a copy of my initial post there:
If users want the UI, I have no objection to it being added.
Still, I can’t imagine myself ever using it. While I get what it tries to do, I think it does its job very ineffectively, much like Beta, Sharpe, Sortino and Max DD. I’ve said before and I’ll repeat here that the whole area of risk management is one that has been very badly bungled by the quant community as a whole – and UI is just another instance of, pardon my language, mathematical masturbation.
The problem is that all these measure focus entirely on historical stock prices, which do not tell us anything about the factors that may cause a stock to sustain an exorbitant loss in the future.
Stock price movements are caused by combinations of three things; market factors, company-specific factors, and randomness (this is an important contribution from academic finance; to bad they forget all about it when they moved on to other forms of risk analysis).
2008, the period that supplies Max DD for those of us who test that far back, was almost entirely due to market factors and randomness. And we all know, in retrospect, what those market factors were; evaporation of liquidity and credit due to problems in the banking sector, primarily in real estate etc. etc. etc.
Randomness is more a convenient word than a genuine phenomenon. It simply refers to factors we can’t effectively measure and bring into our database. In 2008, a big item that fell into this category was “Who owns the stock and how badly do they need to raise cash?” Oddly, shares of better quality companies were the ones best able to attract reasonable bids and, hence, were the ones most aggressively sold by strapped hedge funds, etc. Those of you who were here at the time should remember how frustrated we were about that, and forum threads with titles like “factor reversal.”
The third factor, of course, is company-specific characteristics; stability of the business, balance sheet, size (particularly insofar as it provides a cushion for survival and internal diversification), etc. We can even count stock valuation. In 2008, this accounted for very little, if any, of the big drawdown. (In 2000-02, on the other hand, valuation was a huge factor.)
2011, the second biggest drawdown many of us see, was also one in which company factors played little if any role. This was primarily a market-based thing, a new-driven crisis due based on near simultaneously blowups in the Middle East, the Euro and the D.C. budget situation.
UI, Sharpe, Sortino, Beta, Standard Deviation, Value at Risk, Information Ratio, etc. do not address any of those three relevant factors and were useless to cue investors ahead of time to the drawdowns to which they were exposed going forward. You can even see that on the stockcharts demo charts. Like other metrics based entirely on a statistical report card on stock price, UI was great at flashing warnings – after the stocks had already tanked.
That said, we really, really do need to be having some serious conversations about risk management. Rising interest rates (not rally a matter of “if” but now more a question of “when”) do not have to send stock prices lower. While it is true that higher rates will one way or another boost the denominators in valuation formulas (thus pushing valuations down), the conditions that would lead to higher rates (stronger levels of business activity) would also push numerators up (thus adding to valuations). So actually, there really is no clear-cut answer as to the impact of rising rates on stock prices. But, but, but there can be a monstrous difference between “should” and “will.” Popular financial rhetoric suggesting rising rates must be bad for stocks has been so widespread for so long, I fear there are way too many in the investment community who rightly or wrongly believe it and who will act on that assumption.
So we need to really think about risk. And we should not lull ourselves into false senses of security we might get from historical share-price report cards accumulated under conditions that may not resemble those that most threaten to cause us financial pain. (Actually, on Monday Marco and I were discussion the sort of metrics I’d use to screen for R2G models and one of the things I said was I’d eliminate R2Gs that didn’t show AT LEAST 50% max drawdown; I just assume if someone is showing less, they’re using a curve fitted timing model). I know we all hate drawdown. But what we want is not what’s important. It’s what we can deliver going forward.
Risk control in the future will take some creativity. Forget Wikipedia. Forget StockCharts. Forget Investopedia. Forget all that other stuff. What’s out there doesn’t work. (I’d have thought people would have figured that out after 2008, but I guess not). Think creatively right here on p123. There are a lot of smart people here and frankly, I’m a lot more interested in what can be invented/created right here then I am in rehashes of the same nonsense that has repeatedly been shown to be just that, nonsense. I encourage users to work individually and/or to trade ideas in the forums.
We can’t do anything about the randomness factor. That’s something with which we’ll just have to live.
As to market factors, I suggest trying to work with the economic data we added to the platform most recently. It won’t be easy because we have so few datapoints that reflect rising rates and/or bear markets based on economic fundamentals. But the well is not completely dry. So let’s all put on our thinking caps and see what, if anything, we can figure out with the resources we have.
Researching company factors likewise runs into downside sampling challenges. The well isn’t completely dry, but our cups aren’t exactly running over. But we do, at least, have a really terrific company toolbox with which to work. I suggest we try to develop stock strategies that mitigate stock-specific risk by modelling fundamental factors most associated with bad stock action.
I presented a sample approach earlier this year in this post: https://www.portfolio123.com/mvnforum/viewthread_thread,8333#43221.
For something more general, perspective, you may also want to check this paper: http://www.econ.yale.edu/~af227/pdf/Buffett%2...ller%20and%20Pedersen.pdf.
The paper latter talks mainly about how use of minimal-cost leverage enhanced Buffett’s alpha but alos addresses his stock selection approach.
Those who do want to try to get a handle on risk will need to be a bit scrappy. We won’t find everything we’re looking for on the p123 platform right now, so we may have to adapt. (We can’t really spec and offer something that hasn’t yet been invented.) For example, in a backtest sortino or standard deviation might be our main dependent variables, not return or alpha. And we may have to chop up out test samples for better visibility in seeing which before-the-fact fundamentals are associated with more favorable levels of future sortino, for example. But what the heck: I’m sure the Jobs family garage wasn’t the most ideal workshop for young Steve Jobs and his pal Steve Wozniak. So let’s work with what we have right now. And as we come up with things that could conceivably be added to the p123 platform, well, you’ve seen our track record in this regard.