Dispersion relative to what, exactly?

I participated in a panel discussion last week for the New York Society of Security Analysts (NYSSA). Questions arose regarding the use of standard deviation with GIPS(R) (Global Investment Performance Standards). I used  my standard graphic, which distinguishes between this statistic being used as a risk measure (a longitudinal or across time view, looking at 36 months of composite returns) and as a measure of dispersion (for a single period, where we look at the returns of the accounts within the composite, to see how disparate they are).

One individual mentioned that as a dispersion measure, it measures the account returns relative to the composite's return. While this would be, I believe, the ideal, as one should want to know how returns vary relative to the composite, in reality, most firms measure dispersion relative to the average of the accounts that were present for the full period, and this can be quite a different number.

Consider this: We have a composite that begins with 30 accounts; during the year, 10 disappear, and 10 more are added, meaning 20 are present for the full year. The composite's return is derived on a monthly basis, from the accounts present each month; these returns are then linked to produce the composite's return for the year. If one runs standard deviation across the 20 accounts that were present all year, it won't consider the composite's  return whatsoever; in order to bring that return into the mix, one must manually (i.e., employ a step-by-step approach) calculate standard deviation, using the composite's average as the average against which each account return is measured.

My suspicion is that few firms employ this more accurate approach. Is there much of a difference? Probably not. However, I think it unfortunate that we weren't clearer as to how this measure is to be derived. Perhaps we will in the future. I'll address this in greater detail in our February newsletter.

Let's take risk reporting to the next level

The Global Investment Performance Standards (GIPS(R)) now require compliant firms to include the 3-year, annualized standard deviation for the composite and its benchmark. And while this was a somewhat controversial move, it's here, so we live with it. But, why stop there?

For example, while conducting a recent GIPS verification for Reams Asset Management, a division of Scout Investments, I found the following shown for their Unconstrained Fixed Income Composite:

What can we tell from this? Not much.

Okay, the composite had a significant out performance relative to the index (more than 200 bps); but, look at that standard deviation; looks like a lot of risk was taken! If one truly believes in the value of standard deviation, might it be a good idea to move to the next  step?  That is, to require a risk-adjusted measure, such as (what seems to be the logical choice in this case, given that the risk measure is standard deviation) the Sharpe ratio?

But also observe that we are showing a one-year return and a three-year standard deviation, meaning the match up isn't perfect (and is arguably misleading), and so, let's report what isn't required (but perhaps should also be?): that is, the three-year annualized returns!

A lot more insightful,  right?

In this particular case, the benchmark is an absolute index, so the differences are a bit more pronounced than they might otherwise be. But the point is, I believe, still valid: to compare one-year returns with three-year risk statistics is, as we like to say, mixing apples and oranges. And, showing returns and a risk measure doesn't quite do the job.

And so, I encourage the GIPS Executive Committee to:

1. Require, in addition to the 3-year annualized standard  deviations, the corresponding 3-year annualized returns
2. Require the Sharpe Ratio.

What do you think?

The many faces of standard deviation

Confusion abounds when it comes to standard deviation. Some of the issues include:

• Equal-weighted or asset-weighted?
• Divide by "n" or "n-1"?
• Is it a measure of variability, volatility, or dispersion?
• Is it a measure of risk?
• What's the best way to measure relative to the composite's average return?

I'll be brief, but promise to expound further upon this subject in this month's newsletter.

Equal or asset-weighted?

If you've been reading my stuff for any length of time, chances are you know the answer: EQUAL! Okay, so you're allowed to do asset-weighted, but why would you? What does the number mean or represent? This was an idea that some folks thought made sense almost 20 years ago ("since returns are asset-weighted, shouldn't standard deviation?"), but didn't and doesn't. But if you insist on doing asset-weighted, be my guest.

Divide by "n" or "n-1"?

By "n" we mean the number of accounts. I recall that the AIMR-PPS® flip flopped on this one (the first edition (1993) had one form, the second (1997) a different one [perhaps someone was planning to enter politics, and wanted practice]).

We're supposed to use "n" when we're measuring against the population, and "n-1" when against a sample. Dividing by "n" makes standard deviation a bit smaller. Most firms seem to use "n," so I say "why not join them?" We can debate which is appropriate, but why bother?

Is it a measure of variability, volatility or dispersion?

The short answer: yes!

Bill Sharpe, in his 1966 paper used the term "variability" to describe standard deviation (he referred to what we know as the "Sharpe Ratio" as the "reward to variability" (recall it has standard deviation in the denominator) and Jack Treynor's risk-adjusted measure as the "reward to volatility" (it has beta in the denominator)). However, in an email to me not long ago, he said using either the term "variability" or "volatility" is fine. Both of these are used in the context of standard deviation being a measure of risk; what some call "external dispersion."

As for "dispersion," I usually mean this in the same context as some do for "internal dispersion," meaning how the composite's returns compare / vary.

The GIPS® standards (Global Investment Performance Standards) now require both (a) a measure of dispersion (and standard deviation is just one way to accomplish this) and (b) the 36- month, annualized standard deviation for both the composite and benchmark. The former is for a single time period (standard deviation of annual portfolio returns for 2011, for example) and the other across time; a longitudinal measure, if you will (e.g., the 36-month standard deviation of the composite for the period ending 31 December 2011).

Is it a measure of risk?

It depends who you speak to. Since many consider risk to be either (a) the failure to meet the client's objective or (b) losing money, it wouldn't qualify, because it does neither. However, Spaulding Group research has shown that it's the most common measure of risk. And, the GIPS standards now require it (although they've shied away from calling it a "risk measure"). And so, regardless of its detractors, most folks do consider it a measure of risk.

What's the best way to measure relative to the composite's average return?

I saved the best for last. I am conducting a GIPS verification and was validating the client's measure of dispersion; in this case, equal-weighted standard deviation. Because I couldn't match what they had, I tried comparing it to the composite return; let me explain.

If you use Excel, for example, and run the "STDEVP" function against the returns of all account's present for the full year, you're measuring standard deviation against the average of these returns, which in almost all cases will not be the same as the composite's return, meaning it's telling us how disparate the returns are around this average, not the average reported in the presentation. I believe that ideally it should be run against the composite's return. However, this would require several more steps, and couldn't be invoked by simply running a similar function like STDEVP. Too bad.

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And so, standard deviation isn't really so simple, is it?

Dispersion around what exactly?

A verification client called me with the following question: they have historically calculated dispersion around the composite's return; however, their new GIPS(R) (Global Investment Performance Standards) system measures it around the average of the accounts that were present for the full year. Which is better?

To clarify: GIPS compliant firms are required to include a measure of dispersion (e.g., standard deviation, range, high/low, quartile) for each year, provided there were six or more accounts present for the full year (if there are less than six, then it's an option to include dispersion). The composite's annual return is based on the monthly returns, which are linked together. Each month can have a different mix of accounts, because, for example, accounts were removed because they: terminated, fell below the minimum, had a significant cash flow, had a change in strategy, or are now non-discretionary; or accounts were added because they are new, rose above the minimum, returned after removal because of a significant flow, are no longer non-discretionary, and so on.

The only accounts that are used for the dispersion measurement purpose will be those that were present for the full year. If we calculate standard deviation against these accounts themselves, without any reference to the composite's return, then dispersion will be measured against the average of these accounts, which may not (and probably will not) be the same as the composite's annual return. To measure standard deviation against the composite's return, one would have to manually, so to speak, step through the standard deviation formula, inserting the composite's average into the equation, rather then allow the formula (e.g., Excel's STDEVP) run by itself. This would require more effort. You can get differences in results, as you might expect. Here's a quick example:

And so, is either approach okay? Is one method preferred?

The standards do not speak specifically to this question. I would say that both approaches are acceptable. However, I believe dispersion is expected to be about the composite's average (we want to know how actual accounts varied relative to the reported return). But, I suspect that most systems measure dispersion relative to average of the account returns, not the composite's return. In the end, the differences are probably immaterial.

I can't hear you because it's too noisy

Odd title for a blog post, right? Well, it's my silly way to introduce a term which is often bantered about but not often discussed: "noise." No, I'm not talking about the sounds that come through the hotel room while you're trying to sleep or the sounds that interrupt your concentration. I'm speaking of "statistical noise."

In a recent post I introduced an animation that provides an overview of standard deviation. This post could have gone on and on and on, as this is a topic that has many angles on which to comment. And perhaps I'll do that in future posts, but for today we'll discuss noise and standard deviation.

What is noise?  Well, the often-criticized-but-frequently-cited Wikipedia defines it as "the colloquialism  for recognized amounts of unexplained variation in a sample." We anticipate that there will be some variance, but some of it comes from unknown sources, which makes it difficult to draw conclusions about what is occurring in our sample size or population.

Interestingly, we tend to get more noise as we shorten our time periods. For example, if we measure standard deviation over the past 36 months using daily returns, we're dealing with a great deal of noise. If, however, we lengthen our periods, our noise reduces. Thus, using months is quite common, though one might argue that quarters are better still, and why not move to years? Well, there are probably two reasons. One, for standard deviation to have much value we need at least 30 observations, and 30 quarters would equal 7 1/2 years, which may be too long as an organization can experience a lot of change over such a period. And 30 years would be even more difficult.

Yes, there's noise even in 36 months. And when (as the video pointed out) the distribution is probably not even normal, the value of the statistic is even more questionable / challengeable. No wonder it's a popular statistic both to use and discuss.

An animated view of standard deviation

Today's animated post provides an overview of standard deviation; a very important measure for us performance measurement types!

How many risk measures are enough?

I was teaching our Fundamentals of Performance Measurement course yesterday and came upon a metaphor to use to justify the need for multiple views on risk: John Godfrey Saxe's poem about the blind men and the elephant. You are no doubt familiar with the story, how the blind men go to the elephant, each approaching it from a different part. One thinks that it's like a wall while another thinks it's like a snake. Since none are able to see the "big picture," their observations are very limited.

Well, to me, risk is like that elephant, and if we only use one or two measures, we only see a limited amount of what lies before us. The more measures, the better perspectives.

I love Yale Endowment Fund CIO David Swensen's statement, from his book Pioneering Portfolio Management, that “Quantitative measures of risk for individual portfolios leave much to be desired." Yes, I suspect that most people would agree that they are limited and have a much to be desired. Our only choice is to employ multiple, though limited, measures. A basket that includes Sharpe ratio, M-squared, tracking error, information ratio, value at risk, liquidity risk, extreme risk analysis, and, if you really want to, standard deviation, is a good start, I believe.

You are there! The risk measure designers' annual dinner ...

Imagine for a moment that the designers of the various investment risk measures have gathered for a dinner; perhaps this is an annual event (may as well have it annual, since we like to annualize risk measures, right?). And imagine that you have the opportunity to witness what occurs; perhaps someone videotaped it and placed it on YouTube for all of us to view. We find Bill Sharpe (Sharpe ratio), Leah & Franco Modigliani (M-squared), Jack Treynor (Treynor ratio), Brian Rom (Sortino Ratio), Michael Jensen (Jensen's alpha), Fischer Black (who, along with Jack Treynor, came up with the Information Ratio), and others.

During the pre-dinner cocktail hour a debate ensues, as one after the other guests begins to argue that their formula is the most appropriate to measure and evaluate investment risk. Suddenly, Sir Francis Galton, at 188 years of age, slowly rises from a chair and boldly proclaims that it's quite evident that his is the far superior measure, and he can prove it! After all, his and his alone has been "endorsed" by GIPS(R) (Global Investment Performance Standards). And what, pray tell, is his measure? Well, if the name Francis Galton is unfamiliar to you, his measure surely isn't: standard deviation.

With the 2010 version of the standards all compliant firms must include the three-year annualized standard deviation; what further proof is needed to elevate his metric above the rest. And even if a compliant firm argues that this measure is inadequate for their strategy, they must still show it, along with an explanation as to why it isn't effective and the measure they feel is.

Well, I remain unconvinced, and will (hopefully) soon pen an article that will address this measure's weaknesses at great length (sorry, Frank!).

p.s.,With all due respect to Sir Francis, even the GIPS EC would, I believe, gladly explain that its adoption of standard deviation falls well short of an endorsement for it being numero uno when it comes to risk measures. A recommendation to include a risk measure has been part of the standards since its introduction, and the EC took it upon itself to identify a measure to be used across the board. They, no doubt, recognize many of its shortcomings but also recognize that its an easy measure to calculate and is, in reality, used by most asset managers (as shown in surveys that our firm has conducted). And so, please accept this blog's boldness (and Sir Francis' claims) as a bit of hyperbole.

Standard deviaton: equal- or asset-weight

Let's address the subject of standard deviation, but not from a risk perspective, but rather as a dispersion measure.

Way back in 1997, when the AIMR Performance Presentation Standards (AIMR-PPS(R)) introduced the requirement for firms to disclose a measure of dispersion, they encouraged firms to show asset-weighted standard deviation rather than equal-weighted, because, after all, the composite returns were asset-weighted, why shouldn't dispersion? AIMR introduced a formula to do just this.

Well, a funny thing happened when we went to the last edition of the Global Investment Performance Standards (GIPS(R)) in 2006: nowhere do we find the asset-weighted standard deviation. Where did it go? The Handbook provides the math to derive the equal-weighted measure but not asset-weighted. Other than in Q&As, we see nary a word on asset-weighting. Is this a sign of a change in belief in the value of the asset-weighted approach? I believe it is, although firms can continue to show asset-weighted, if they would like.

But why would you? How do you interpret or explain it? Equal-weighted standard deviation has an understood meaning, but asset-weighting, to my knowledge, doesn't. It's more complex to derive and provides you with what benefit? And, why would using the beginning of the year market value for an annual measure improve upon the tried-and-true equal weighted standard deviation? I say, put an end to this measure and go with the traditional one. It's easier to calculate, is more widely accepted, and is interpretable!

Standard Deviation ... a risk measure or not?

Standard deviation is a much misunderstood measure, in spite of its common use.

First, is it a risk measure? It depends on who you ask. It's evident that Nobel Laureate Bill Sharpe considers it to be one, since it serves this purpose in his eponymous risk-adjusted measure. Our firm's research has shown that it is the most commonly used risk measure.

And yet, there are many who claim that it does anything but measure risk. What's your definition of risk? If it's the inability to meet a client's objectives, how can standard deviation do this? But, for decades individuals have looked at risk simply as volatility.

As to volatility, is it a measure of volatility or variability? In an e-mail response to this writer, Bill Sharpe said that the two terms can be used in an equivalent manner.

The GIPS(R) (Global Investment Performance Standards) 2010 exposure draft includes a proposed requirement for compliant firms to report the three year annualized standard deviation, which appears to have survived the public's criticism and will be part of the rules, effective 1 January 2011. But, will it be called a "risk measure"? This remains unclear.

Interpreting standard deviation is a challenge, since the result's value will vary based on the return around which it's being measured. Example: your standard deviation is 1 percent; is this good or bad? If your average return is 20%, then to know that roughly two-thirds of the distribution falls within plus-or-minus 1% doesn't seem bad at all, but if your average return is 0.50%, then doesn't 1% sound a lot bigger? In reality, it's better to use it to compare managers or a manager with a benchmark. Better yet, as part of the Sharpe Ratio, as this brings risk and return together.

I could go on and on, but will bring this to a close. Bottom line: it's easy to calculate (if we can agree on how (didn't address this today)), in common use, and has a Nobel Prize winner's endorsement. Will it go away? Not a chance. If you're not reporting it, you probably should be.

Annualized standard deviation ...yes!

Okay, so the decision has been made: effective January 2011, GIPS compliant firms must report a 36-month annualized standard deviation, on an annual basis (that is, for all years starting with 2011). Further clarity is in order.

First, is standard deviation risk? There is hesitation to call it that, because a lot of folks don't consider it risk. But if it's not risk, why show it? Granted, not everyone thinks of volatility as being a risk measure, but most firms report that they use standard deviation as a risk measure. If volatility isn't risk, then is volatility such a valuable measure that we need to see it reported?

I think it's a mistake NOT to call standard deviation risk: the fact that not everyone agrees shouldn't be a reason not to. There is disagreement about much of the standards, but that doesn't stop these items from being included. It's even more confusing not to call standard deviation risk. Is someone going to be offended if we call it "risk"? I think not.

Is the Sharpe ratio a risk measure? Technically it's a risk-adjusted return. And, what risk measure is used to adjust the return? Yes, you're right: standard deviation. But if standard deviation isn't risk, then I guess the Sharpe ratio can't be a risk-adjusted measure. Who's going to tell Bill?

Okay, and so HOW do we calculate standard deviation? First, use 36 months ... not days, not quarters, not years: months! You will also be required to include the annualized return for each 36 month period. What if you don't have 36 months' of composite returns? Then don't show this until you do (well, actually, you arguably can show a standard deviation for the period you have, but you're not required to until you reach 36 months).

Do we divide by "n" or "n-1" (where "n" is the number of months (i.e., 36))? No decision has been made yet, though it appears from comments at this week's conference that "n" might win out. We use "n" for the population and "n-1" for a sample; some might argue that it would be wrong to use "n," while others would argue that it's wrong to uses "n-1." This is debatable and controversial, no doubt. And, no doubt more details will follow.

Standard deviation: dispersion vs. risk

Standard deviation is a commonly used statistic, well known by many long before they enter the world of performance measurement, which serves multiple purposes and thus engenders confusion.

The GIPS 2010 draft proposed a requirement that a 36-month annualized standard deviation be shown by GIPS(R) compliant firms. While it remains unclear whether this will stick (because of the opposition expressed by those who commented), it remains a commonly used risk measure. It reports the volatility in returns over some time period.

GIPS requires compliant firms to report a measure of dispersion when there are six or more accounts present for the full time period (e.g., if reporting for 2008, you're required to show a measure of dispersion if there were six or more accounts in the composite for the full year). Standard deviation is often used for this purpose. It shows the dispersion of the returns across all of the accounts for that period. For example, if for 2008 the firm reported a return of 13.04%, we would look at all of the individual account's annual returns and compare them.

Hopefully, the accompanying graphic helps contrast the uses of standard deviation.

GIPS 2010 ... the people have spoken II

Continuing our discussion on some of the key findings from the feedback to the proposed changes to GIPS(r) ...

Recall that the Executive Committee proposed a new recommendation, 0.B.2, that compliant firms provide their existing clients with a copy of their corresponding GIPS presentation on an annual basis. More than a third of the individuals who offered comments at all specifically commented on this proposal. And, of the 36 who responded, I only counted one that supports this idea...the rest said "no." This was, as you'll recall, one of those "hot button" items that I was especially concerned with. And even though this is merely a recommendation, individuals pointed out that since there's another recommendation that compliant firms comply with all recommendations, and further since recommendations are "best practices," this idea wasn't deemed a good one. Hopefully it will be dropped from the final version.

Paragraph 4.A.20 is to be expanded, as per one of the proposals, to include a description of risk in the composite description within the presentation. I counted more than 70 responses. And these responses tended to be of three types: "yes," "no," and "need more guidance." Almost half voted "no." As one who also offered this response, I'm obviously hoping that the requirement gets dropped, but we'll have to wait to see how the EC handles this "mixed bag" of comments.

And speaking of risk, paragraph 4.A.29 is a proposed requirement that firms provide 3-year annualized standard deviation. I've addressed this topic at length, indicating how I had been "on the fence" and then "fallen off," to conclude that this isn't a good idea. (As for "falling off the fence," I used language like this in our June newsletter, which caused a response from my friend Carl Bacon, which will appear in our upcoming July issue). Close to 70 folks commented on this, with roughly two-thirds saying "no." With such an overwhelming opposition, I am hopeful this will be dropped and replaced with a requirement for A risk disclosure, but of the firm's choosing. I think this would be much more welcome by the GIPS and investment community.

GIPS 2010 ... you have spoken!

At last count there are almost 120 comment letters on the GIPS website regarding the proposed changes to the standards (visit http://www.gipsstandards.org/news/releases/2009/view_comments.html). Some are as short as a paragraph or two, while others exceed 20 pages. So far I haven't read them all but am making it through quite a number of them.

My unofficial assessment is that there are certain recommended changes that folks are very strongly opposed to:

• the recommendation that compliant firms provide their clients with the GIPS composite presentations for the composite(s) they're in on an annual basis. Not much support here.
• the requirement for 3-year annualized standard deviation. While many folks support having risk, there doesn't seem to be much support for the measure being standard deviation.
  
• the requirement to disclose, for a year, corrections to any material errors on composite presentations. This has received a lot of "push back," which is interesting since the requirement goes into effect this coming January (because of the GIPS Executive Committee's approval of the revised Error Correction Guidance Statement). If this does get rejected from GIPS 2010, will this mean that the GS gets dropped? Hopefully so.
• the requirement to disclose the percent of "proprietary assets." Some mixed views here. Some folks feel the definition is too broad (as it includes investments of senior management, as well as owners and the firm). Many others reject it entirely.
• the requirement to not provide a presentation to prospects below the firm's minimum wasn't well received, either. A few correctly pointed out that this wasn't a change from a recommendation to a requirement.
  

I don't know if there will be more letters posted or not. I think it's very fair that the GIPS EC has (a) allowed us to comment and (b) posted these comments for everyone to read. I'm very pleased that SO many individuals and firms took the time to comment. I'm also thrilled by the comments from many country sponsors, especially from some of the newer ones (e.g., Pakistan). The EC welcomes these voices. The EC works hard to make the standards better and must consider lots of ideas. I'm aware that some of what has been presented isn't supported by 100% of this group, which shouldn't be surprising. The EC will, I'm sure, consider all the comments before finalizing what will end up in the next edition. And, I know they will be VERY busy over the next few months working on this. AND, I know that the CFA Institute's staff will be VERY busy, too, as they assemble these materials. We owe the volunteers and the CFA Institute our thanks and appreciation, as this isn't an easy task. We are all looking forward to learning more in the coming months.

One important point to know: this ISN'T a vote; that is, I don't expect the EC to tabulate the "pros" and "cons" and decide what to do based on what was sent in. But, I believe they definitely take into consideration what has been written.

Moneyball & performance measurement

As often happens when I read, I stumble upon quotes which I will want to employ in my speaking and writing. Here are just a few from Michael Lewis' Moneyball, along with commentary:

- The meetings, from their point of view, are all about minimizing risk (p. 27): Here, the author is speaking about draft meetings. And, the notion of minimizing risk is quite a standard aspect of our world, yes?

- Teach him perspective-that baseball matters but it doesn’t matter too much. Teach him that what matters isn’t whether I am strick out. What matters is that I behave impeccably when I compete. The guy believes in his talent. (53): Actually, this quote has nothing to do with our field, but is much broader...one of perspective...that we should avoid taking things too seriously. Being reminded of this isn't so bad, right?

- When we state it that way, it becomes, or should become, crystal clear that the most important isolated (one-dimensional) offensive statistic is the on-base percentage. (58): Here we learn of one of the key "ah has" of the analysis of baseball statistics: that the wrong ones are often being used. Should make us reflect on what we do and whether we're doing it right (such as the overuse of time-weighting and standard deviation).

- I didn’t care about the statistics in anything else. I didn’t, and don’t pay attention to statistics on the stock market, the weather, the crime rate, the gross national product, the circulation of magazines, the ebb and flow of literacy among football fans and how many people are going to starve to death before the year 2050 if I don’t start adopting them for $3.69 a month; just baseball. Now why is that? It is because baseball statistics, unlike the statistics in any other area, have acquired the powers of language. (Bill James, 1985; Baseball Abstract) (64): being focused isn't such a bad thing.

- What he writes may be good, but why he writes is something you particularly want to hear more about (64): Something I can relate to, from a personal standpoint. Can't say why it is, but I do enjoy writing.

- The statistics were not merely inadequate; they lied. (67): This one makes me think primarily of the use of standard deviation, which, given the non-normal state of returns, will result in inadequate and false information.

- The meaning of these performance depended on the clarity of the statistics that measured them (68)

I'll share more in the future. But, for now I hope that I'm motivating you to pick up a copy.

What happens if you use the wrong stats?

Continuing our discussion of Michael Lewis' Moneyball, I think there's a HUGE parallel between baseball statistics and what we do in investment performance measurement. Both deal with measuring performance: the performance of baseball players / the performance of money managers.

Lewis points out that for the first 150 years of baseball, the wrong statistics were used to evaluate the performance of players. As a result, the wrong ones were often rewarded and chosen, resulting in teams not doing as well as they had expected, given the "talent" they selected.

While investment performance's history is much shorter than baseball's (roughly 40 years), we have had the same challenges because we quickly adopted certain measures (e.g., standard deviation for risk, time-weighting for performance) which arguably are WRONG much of the time! And so, what's the consequence? Misleading information, misinterpretation of results, mis-allocation of resources.

Not everyone in baseball has "signed on" to the new statistics, although those who haven't will continue to suffer. The same can be said in our industry, where most firms have yet to see the wisdom of alternative measures. We should be glad that it hasn't taken us 150 years to figure out the error of our ways.