LadyGeek wrote:Correct, but that's what was used as the "risk free" baseline in the data.
NormR must have got up this morning with a black swancloud hovering over his head
LadyGeek wrote:Correct, but that's what was used as the "risk free" baseline in the data.
Douglas Cumming and Sofia Johan, seasoned academic researchers at York University and Holland’s University of Tilburg, respectively, undertook the first effort to compare “fraud risk” among the leading exchanges in Canada, the U.S. and Britain.
Wow that’s an awful lot of words (big ones at that) to say that you don’t know what the future holds and that you can only make an educated guess and that it might be wrong.ghariton wrote:Here's my attempt at defining risk, inspired by the discussion around the entry for risk on finiki.
That's where I am now. But I'm still evolving.
ghariton wrote:There is the kurtosis, which warns that the "once-in-a-hundred-years" events can pop up every decade.
Forget the "Dimon principle." Investors should follow the Feynman principle. When J.P. Morgan Chase's chief executive, James Dimon, disclosed a $2 billion trading loss during a hastily organized conference call on Thursday, he said: "This trading may not violate the Volcker rule, but it violates the Dimon principle." Mr. Dimon didn't say what the Dimon principle is, and a spokesman for the nation's largest bank by assets didn't respond to requests for comment. The Feynman principle, however, is simple: "You must not fool yourself—and you are the easiest person to fool," as the Nobel Prize-winning physicist Richard Feynman put it...
The moguls of J.P. Morgan, in letting a complex risk run wild and denying any potential for error until it was too late, are a reminder that one of the biggest dangers in finance is self-deception. For investors, the bigger the commitment, the more certain they become that they must have been right to make it—and the harder it becomes to let go...So how can investors avoid deceiving themselves?
First of all, remember that "the riskiest moment is when you are right," as the economist Peter Bernstein was fond of saying...
Look at the results of other people and organizations that have tried something similar to the investment actions you are considering. Unless other people have succeeded at it, there isn't any objective reason to believe that you will...
Monitor yourself for vehemence. If you find yourself tempted to ridicule anyone who tells you are wrong, you probably are wrong. The philosopher Bertrand Russell wisely warned that the less evidence someone has that his ideas are right, "the more vehemently he asserts that there is no doubt whatsoever that he is exactly right."
Finally, try the technique that psychologist Gary Klein calls a "pre-mortem." Gather a group of people whose views you respect. Ask them all to imagine looking back, a year from now, at the investment you just made—and that it has turned out to be a disaster. Have them list all the possible causes of the failure. That may well help you see how it might have been avoided.
Above all, remember that the smarter you are, the more easily you can fool yourself.
Bylo Selhi wrote:Food for thought from one of my favourite restaurateurs
LadyGeek wrote:As an engineer, I have a very hard time understanding the many definitions of investing risk. Risk is simple- just take the probability of failure for each component and do some statistics (root sum square, standard deviation, etc.) to come up with the final system risk
However in engineering, past performance must predict future performance or you did something wrong.
This may be why the investing model gets a lot more complicated.
I don't see how it can be any different.
LadyGeek wrote:As an engineer, I have a very hard time understanding the many definitions of investing risk. Risk is simple- just take the probability of failure for each component and do some statistics (root sum square, standard deviation, etc.) to come up with the final system risk. However in engineering, past performance must predict future performance or you did something wrong. This may be why the investing model gets a lot more complicated.
The investing risk publication I referred to in my previous post (Mismeasurement of risk in financial planning) just makes sense to me - I don't see how it can be any different.
In the world of modern finance, a love of numbers has replaced a desire for critical thinking. As long as something has a number attached to it, then it is taken as gospel truth. Research shows that people are often fooled by the use of pseudoscience. Simply making things sound complex makes people believe them more! Risk managers, analysts and consultants are all guilty of using pseudoscience to promote an illusion of safety. We all need to be on our guard against the artificial deployment of meaningless numbers. Critical thinking and scepticism are the most unrated (and scarce) tools in our world.
Despite risk appearing to be one of finance’s favourite four letter words, it remains finance’s most misunderstood concept. Risk isn’t a number, it is a concept or a notion. From my perspective, risk equates to what Ben Graham called a “permanent loss of capital”. Three primary (although interrelated) sources of such danger can be identified: valuation risk, business/earnings risk, and balance sheet/financial risk. Rather than running around obsessing on the pseudoscience of risk management, investors should concentrate on understanding the nature of this trinity of risks.
Root sum square assumes zero correlation. But in finance, almost everything correlates on the downside.(root sum square, standard deviation, etc.)
Shakespeare wrote:Root sum square assumes zero correlation. But in finance, almost everything correlates on the downside.(root sum square, standard deviation, etc.)
Standard deviation assumes a Gaussian distribution. Gaussians are used because they have nice mathematics, but in finance are usually not realistic and underestimate the risk severely.
FinEcon wrote:For investors, anything beyond basic (discrete) financial math is not necessary and will probably make said investor worse off as he/she focuses time and effort on useless confidence building excercises dressed up an elegant mathematics rather than focusing thought on simple, relevant, yet difficult do pin down variables.
Example: rather than performing statistical calcs on financial data for REITs with heavy condo focus in TO, one should think about how dramatic increases in supplied sqft will affect residential rents going forward.
ghariton wrote:(1) I like to have a toolkit that is larger than just the tools I anticipate using. While almost all the work I do around the house requires just screwdriver, hammer and drill, I like to have a saw too, just in case.
ghariton wrote:(2) The big boys who are moving the market are using some pretty sophisticated tools. While I don't expect to take them on nose-to-nose, I think that it helps to have at least some idea of what they are up to.
ghariton wrote:(3) Financial institutions keep inventing new products. While 99% of them are not useful to me, from time to time they come up with one that is useful. Two examples are RRBs and ETFs. But before I invest in something new, I need to understand as much as I can about it.
ghariton wrote:The most important practical conclusion is that one should invest in low-volatility assets -- a point that NormR has made several times on this forum.
ghariton wrote:For example, comparing SPY (an ETF representing the S & P 500) with SPLV (an ETF representing the 100 least volatile of the 500), year by year, I don't see any great advantage to SPLV.
NormR wrote:ghariton wrote:For example, comparing SPY (an ETF representing the S & P 500) with SPLV (an ETF representing the 100 least volatile of the 500), year by year, I don't see any great advantage to SPLV.
Isn't it too early to tell? Yahoo seems to indicate that SPLV started in 2011. Importantly, I'd want to keep an eye on the tax efficiency of such funds. Turnovers might be a bit high.
Volatility is often viewed as being synonymous with risk—a confusion that lies at the heart of the mismeasurement of risk. Volatility is only part of the risk picture—the part that can be easily quantified, which is no doubt why it is commonly used as a proxy for risk. A comprehensive risk assessment, however, must also consider and weigh hidden (or event) risks, especially since these risks may often be far more important.
The confusion between volatility and risk often leads investors to equate low-risk funds with low-volatility funds. The irony is that many low-volatility funds may actually be far riskier than high-volatility funds. The same strategies that are most exposed to event risk (e.g., short volatility, long credit) also tend to be profitable a large majority of the time. As long as an adverse event does not occur, these strategies can roll along with steadily rising NAVs and limited downside moves. They will exhibit low volatility (relative to return) and look like they are low risk. But the fact that an adverse event has not occurred during the track record does not imply that the risk is not there.