Thus, the concept of “risk parity.”  Lever every asset class up until it has the same volatility as common stocks. Under theoretical conditions, one could make extra money doing this, and with less risk than just a common stock portfolio.

That makes sense when few are doing it, but not when many are doing it.  When I worked for Hovde Capital Advisors, I highlighted to the group how hedge funds were forcing every asset class to the same level of riskiness.  A Grants Interest Rate Observer article on Leveraged Non-prime Commercial Paper is etched on my mind as emblematic of that era.

Risk parity can work so long as the total riskiness of the system does not get too high, as it did in 2007-8.  But if it does get too high, the assets that are levered face disadvantages versus volatile unlevered assets.  Failures of leverage feed on themselves, and lead to a real washout.  Failures of growth stocks don’t do that to the economy.

Risk parity turns managers into bankers, or worse yet, asset managers that specialize in non-AAA investment grade portions of structured securities deals.  Most asset managers are not used to thinking like bankers, largely because they think in terms of total return, and because they don’t have a balance sheet.  Their capital can run at will, unlike banks that have deposit stickiness, savings accounts, CDs, ability to borrow from the FHLBs, etc.  The banks can hold the assets to maturity, they have a buffer against losses in their capital, and don’t have to mark to market in an assiduous manner (though they *should* have to do so).

Think of the mortgage REITs in the most recent crisis — the ones that did the best were the least levered and had the longest terms for their repo lines.  In the short run, that costs more than the vain idea that one can roll over their repo lines every night, and that repo haircuts won’t rise.  Crises lead to a failure of both ideas, together with a set of forced sellers driving down the price of assets being repo-ed, which sometimes leads to a cascade where repo terms get progressively tighter, and only those that were the most conservative at the start of the crisis survive.

There is a Wall Street aphorism, “The fool does at the end of a bull market what the wise man does at its beginning.”  Risk parity falls into that bucket.  Early adopters of new asset classes and liability structures typically do well, but when they become mainstream, the dynamics can be ugly, as we learned in 2007-present.

So ignore the idea of risk parity.  Risk managers are not bankers, they don’t have the capacity to play leveraged spread games to maturity.  Risk parity if practiced on a large scale will produce wipeouts akin to the recent crisis.

1. Generating research ideas
2. Doing the research

But here’s my twist: economists and biometricians could submit ideas to a central database, but would be barred from doing that particular project.  No researcher would be allowed to work on his own idea ever again.  Researchers would be assigned research ideas randomly from the central database, allowing for some modest amount of customization as to what types of projects they have the skills to do.

The researchers would then take a fresh look at the ideas, because they don’t have a dog in the fight.  They haven’t been defending a point of view on the idea, so the idea will be investigated with less bias.  This would have the salutary effect of creating more well-rounded researchers that have broader interests, and, more skeptical researchers.  It also might allow journals to publish articles that indicate that a certain area of inquiry is a dead end, which does not get done as often as it should.

This is an attempt to make economics and biometrics into sciences, by forcing more neutrality into the research.  The scientific method requires a neutral observer, but sadly, many researchers become patrons of their pet ideas, and the sorry excuse called “peer review” at the journals does not weed that out.  Peer review reinforces the biases of the majority most of the time.

My proposal will never be adopted because the cozy academic guilds are ever so happy to leave their “research” unchallenged, so that they can keep their cushy jobs, even though they produce little of lasting value.

Summary: if an idea is true, it shouldn’t matter which competent researcher investigates it.  We believe in a neutral observer.  Well, let’s make the observer genuinely neutral, and see how much trash gets discarded, and real truths preserved.

For those that work in the asset markets, it should be abundantly clear that equilibrium is a weak concept at best, reacting slowly over many years.  Mean reversion is slow — four years or so seems to be the periodicity.

Let the economists demonstrate that most markets display equilibria.  It is such an important element of their system, and yet so unproven.

My view is that markets are almost always not in equilibrium.  Being outside equilibrium causes economic actors to allocate or deallocate assets in order to maximize gains or minimize losses.   But the lengths of time for the information to flow, and production decisions to adjust are too long.

The same applies to theories in finance.  There is no equilibrium, so why argue for it?  Let the finance theorists step forward and show the times where the market was in equilibrium.

Personally, I think that disequilibrium is far more realistic.  This includes actions driven by the Fed or the US Government.

Let me start by quoting the beginning of the abstract:

The intellectual origins of the global financial crisis (GFC) can be traced back to blind spots emanating from within conventional financial theory. These blind spots are distorted reflections of the perfect market assumptions underpinning the canonical theories of financial economics: modern portfolio theory; the Modigliani and Miller capital structure irrelevancy principle; the capital asset pricing model and, perhaps most importantly, the efficient market hypothesis. In the decades leading up to the GFC, these assumptions were transformed from empirically (con)testable propositions into the central articles of faith of the ideology of modern finance: the foundations of a widely held belief in the self-correcting nature of markets and their consequent optimality as mechanisms for the allocation of society’s resources. This ideology, in turn, exerted a profound influence on how we regulate financial markets and institutions.

I have consistently been a critic of modern portfolio theory, the Modigliani and Miller capital structure irrelevancy principle, the capital asset pricing model and, the efficient market hypothesis.  I have also criticized the idea that incomplete markets are a problem, and that derivatives are needed to complete markets.  Trying to make liquid markets out of assets that are naturally illiquid is a fool’s bargain.  I have also argued that derivatives should be regulated as insurance contracts, and subject to the doctrine of insurable interest.

Why don’t academic finance theories work?  Quoting again from the paper:

These theories share a common and highly stylized view of financial markets, one characterized by, inter alia, perfect information, the absence of transaction costs and rational market participants. Yet in reality financial markets – and market participants – rarely (if ever) strictly conform to these assumptions.  Information is costly and unevenly distributed; transaction costs are pervasive and often determinative, and market participants frequently exhibit cognitive biases and bounded rationality.

In short, men are not hyper-rational calculators, like the Vulcans of Star Trek.  Markets for goods and services might be efficient, but not those for assets, where values are not as easily estimated.

Asset markets are frequently reflexive.  As an intelligent former boss once said to me, “When does a company look its best?  Immediately after receiving a loan.  That’s why we wait a few years before shorting a bad company that has just received a significant loan.”

The paper encourages study to understand how markets work in practice, rather than how they work ideally to neoclassical economists.  I heartily agree; I think that the more one studies the structure of asset markets, the more they will understand that there are many approaches to the market, and the popularity of strategies depends a lot on past success.

Quoting again:

Nevertheless, taking a broad look across the financial system, it is possible to identify at least six – in many respects intertwined and overlapping – sources of complexity: technology, opacity, interconnectedness, fragmentation, regulation and reflexivity.

Technology – things move faster, but can people keep up with it.  More data can be gathered by connected players.  It is one reason that I am a low turnover investor.  There are too many playing the short duration game in the market.

Opacity – few can truly understand the economics of most securitizations, or whether the subordination levels are right or not.  Investing in “dark pools” is rarely wise.  And as for the credit guarantors that I have criticized, they could not understand the risks they were taking, because they assumed the credit boom was normal and perpetual.

Interconnectedness – What could be more interconnected than the financial guarantors?  Or the banks who lent to one another, directly and indirectly?

Fragmentation – Securitization makes it tough for owner to understand what is happening several links down the chain.  Guess what?  It’s a lot easier to have your own mortgage loan department, and watch over your own loans.

Regulation – Financial regulation is fragmented, and often co-opted by those regulated.   Because the US government does not get this, market players arbitrage regulators.  Another aspect of it was the moral hazard engendered by the Fed and other regulators, giving the impression that there would be rescues available in any real crisis.

Reflexivity – I have talked about this above.

I would add a seventh source of complexity – leverage.  People underestimate the effects of leverage on managements in managing assets.  When the possibility of bankruptcy arrives, the effects are discontinuous, violent.  This is especially true when debts are layered, where A owes B, who owes C, who owes D, on thin equity bases.  A’s failure to pay has ripple effects, leading to a cascading failure.

An eighth source of complexity is use of short-term debt to finance long term assets.  An early precursor to the crisis was the failure of off-balance sheet subsidiaries that were financed with short-term loans.  Similarly, firms that relied on repo funding to finance their inventory of assets had a rough time of it as repo haircuts rose rapidly, and in tandem.

A ninth source of complexity was similar: margin requirements in derivative agreements, where a credit downgrade could lead to a call on capital at the worst possible moment.  This happened with AIG.

A tenth source of complexity which enabled much of the above nine is one that many writers don’t want to talk about, because it exposes many of “victims” to be enablers: yield-seeking.  Why be a lender to complex investment vehicles?  You get more yield.  None of them have blown up.  They are highly rated.  Why not go for the higher yield?  As I have said before, it takes failure to mature an asset class.  All new asset classes look pristine; nothing starts with failure.  Typically the best deals get done first – best quality, best incremental yields.  Then competition drives down quality and yield spreads, but raises quantity.

Without the yield-seeking, many complex financial instruments would never get issued.  Someone had to buy the “safe” tranches of CDOs, CDO-squareds, ABS CDOs, etc., in order to sell the deals.  Many European banks bought them because they didn’t have to put much capital against them for risk purposes, and the added yield helped them meet earnings targets, at a cost of greater illiquidity.

An eleventh source of complexity was the failure of accounting to properly account for these new instruments with volatile fair values.  Fair Value accounting, using market values and their approximations was a step in the right direction, and bitterly opposed by those who were financing illiquid, opaque, financial instruments, while their funding was short-dated with too little equity.

More will come in part 2, soon.  Still without power — a hard providence, be we are surviving it.

I think this is a stupid idea.  (I don’t favor the CAPM either.)  When you borrow money to buy some asset, the distribution of possible returns changes.

Let me give you some analogies.   First, securitization.  Those that invest in non-senior loan tranches get an enhanced yield, but they face a different risk profile than most corporate bond investors.  Corporate bond investors have a high expectation of full payment, but when default occurs, they lose 60-80%.  Investors in securitized bonds rarely get recoveries.  They usually get paid in full or lose it all.

Second, think of banks or REITs.  They lever up safe assets, and they blow up with a higher frequency than do industrial corporate bonds.

Leverage changes the nature of the distribution of possible returns in three ways:

1. The cost of borrowing decreases the return.
2. The returns are levered by the amount of borrowing.
3. To the degree that others do the same thing, the strategy is no longer undiscovered, and superior returns should not be expected.  In a crisis, the borrowed money leads to overshoots as panicked investors bail out en masse.

Personally. I wish we could get rid of the writings of academic economists and finance writers that don’t actively invest.  They don’t get the dynamics of investing, and assume a simple world that does not resemble our world.

My main point is that trying to buy the asset class with the highest return after equalizing volatilities is a fool’s bargain.  Adding leverage changes the nature of decisionmaking, and what tests in the lab will not likely work in real life.  Paper trading does not always translate to real world profits.

But it’s not worth that much.  There are many other character attributes desirable to society aside from being smart.  As a little kid, I was a guinea pig for many of the educational theories they tried to test on me, and I survived them.  Not sure what good they got out of it.

In my adulthood, I learned to appreciate the abilities of others who may be less smart, but they have gifts — empathy, mechanic, insightful into people, technical specialties… everyone has something to give, IF they will give.

Economists have a fixation on rationality, and this article is a partial expression of that.  My answer to the article is the people are limitedly rational.  That’s vague, and won’t fit into mathematical theories, but it is accurate.  It explains why people act rationally in some situations, and why they could be more rational in other situations, assuming that economists really know what is rational.  More goods is better is not an adequate explanation of rational.

A view like mine would make it very difficult for economists to create simple mathematical models of reality.  They would rather live in their fake world, where they can publish nonsense to peers, and keep their cushy jobs.

Both ended up being large losses, and I puzzled about it when I was young.  It did not dent my confidence in the markets because my Mom was such a good investor, looking for  growth at a reasonable price.  And to me, 10-18 years old, watching Wall Street Week with Louis Rukeyser on Friday nights, I gained insights into the markets, and began to appreciate the wisdom of my mother.  The 70s were a tough time to gain a love for the markets, but I played around with paper portfolios until 1982, when I did my last paper portfolio, before heading of to grad school.  (Value Line helped — if you have time, curl up with it and look for neglected companies that offer promise.)

Before that, I took one of my Mom’s former favorite stocks which had dipped, James River, and used it in a class at Johns Hopkins, and made a case that an acquisitive paper company could be a good investment.  My case was good to my professor, Carl Christ, “I never heard of this corporation before, what a great company.”  And my Mom, who had sold out of the company, reconsidered and bought again at a lower price, making money until the firm itself was bought out.  (Hey, gotta help with the tuition.)

The paper portfolio that I created in August of 1982 proved to be fun for my students when I was a TA at UC-Davis in Corporate Financial Management.  I mentioned the portfolio in class, and a subset of students asked to see it.  By the time the class ended, the market was up 20%, but the portfolio was up 40%.  By this time the professor had heard about it, and he said, “Oh, you have a portfolio with a beta of two.”  I tried to explain to him that the beta estimates of the portfolio were much lower than that, and that I had “bought” the names cheaply.  but to no avail… once the religion of efficient markets takes hold, no amount of  facts will prevail.

Then there was the Value Line contest around 1984-1985, where I was in the top 1%, but missed the top 25.  I used the top 100 from Value Line (Timeliness Rank 1), but screened them for value in their volatility buckets, as the contest went.  To this day, I think that stockpicking contest was the best ever designed.  If I ever get wealthy, I want to do a series of such contests, using the same principles.

After that, I married my wonderful wife Ruth, and began investing for real, first with mutual funds, and then with individual stocks.  But I failed to follow through in one way — I bought penny stocks through a “bucket shop” and lost a moderate amount of money, which fortunately was dwarfed by the purchase of a home in Davis, CA at just the right time, such that two years later when we had to leave for a new job (AIG), we had made 4x our capital, net of CA taxes.

Then my Mom gave me a copy of Ben Graham’s “The Intelligent Investor,” and my life changed again.  I spent the next seven years analyzing small company value stocks in the midst of a market that favored large caps, and growth.  Still, my picks were good, and kept up with the S&P 500 (beating the Russell 2000 Value by 5% per year).

I appreciate the past, and use the lessons for growth today.  Mom, she keeps investing well, though she has more of a desire for yield today.

Today I think my best skills are company and industry analysis.  Yes, I am a quant, and can design clever ways to outperform the market with some probability, but prefer my own insights to mathematical likelihoods.

As for what I wrote yesterday, I prefer my own stock investing to moving between equity and debt markets, because my alpha exceeds that of the switching strategy, at least for now.  Volatility is higher, but I am in Buffett’s camp, where I will take a noisy 15% over a calm 12%.

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I did not bump into investing as an adult, but had to wrestle with it as a child.  I got to view it through the lenses of practical people who were bright, rather than academics who have a blunted view of investing.  This will bite the academics, but there is more wisdom outside of academia on investing than there is inside academia on investing.  Far better that you leave the confines of academic research and try to apply your methods to investing, messy as it is.  I dare you.  It takes a while to develop the practical knowledge behind good investing.  I’ve seen it from so many angles; if there is anyone with a more diversified career in financial services, I have not met him yet.

I was never attracted to MPT because I had seen my Mom beat the market regularly.  It was confirmed to me, when I found that I could do it also.

But still, I like MPT, and indexing — it sidelines a lot of the competition.  And for most, buying an index is the right way to go.  They don’t have an edge, so why pay the fees and accept the added volatility?

But to those that think they understand investing in academia, I would simply say, “Join the party.  If your ideas are  good, you will do well.  It is a lot harder to turn theories into hard cash, or gold, if you are so inclined.”

When I was young, I trusted my Mom.  That trust was rewarded.  Today, the game is a lot tougher, but I persevere because I know my principles work on average over time.  I have had a poor last eight months, but I will come back in time, because my methods have worked in the past, and nothing that I can see has changed that environment.

PS — I sometimes say, ” I am a good investor because I learned from my Mom, and I am a good businessman because I learned from my Dad.”  My Dad did excellent work for clients, and was never sued once in 35 years of work.  His reputation of doing quality work at a moderate price preceded him, and allowed him to survive in bad economic environments.  I hope that I can be as good.

Good article and series. A few comments and/or questions for you. First, there is no doubt that both value and momentum work. And while I happen to personally be a big believer in (certain) trend-following approaches, the way in which Covel interacts with people is childish at best. There is room for professional discourse and disagreement, but he has little interest in being professional about anything…at least in the blogosphere/twitterverse world. So, keep at it…be a gentleman and let the other chips fall where they may. Now, a few other areas:

I try to stay polite.  Sometimes I fail, but thankfully, it is not common.

1. First, I’d be interested to have you elaborate a bit further (or point me to a different post) on your views of the Carhart factors. In my mind, there is no doubt that they are betas…but at the same time, there is also no doubt that those betas can and should be used (carefully) as alpha factors as well. Much as my brain has been trained to think about them as simply betas, I’m more than willing to think about them in both ways. They aren’t mutually exclusive, are they?

I have no other post on this.  This series was meant to bring this idea buried in me to the surface.

I think the thing that set me off here is the value factor.  Value is regarded as a risk factor, when if you own enough stocks with the value factor, you will outperform over the intermediate term.  The same applies to momentum, it is a risk factor, but it tends to outperform.  The same can be said for size, small is usually a winner because of neglect.  Beta tends to be negatively correlated with outperformance.

If the factors were neutral, having zero expectation of future performance, they would be betas.  But that is not true even of “beta.”  Thus, most of the time one can make money by tilting to the moneymaking sides of these factors.

Recently, there was an analysis of Berkshire Hathaway for the last decade, showing Buffett had no alpha.  But if you looked at Berky versus the index, Berky beat it by 6%/year.  Buffett asks whether companies are cheap.  If he buys a company because it is specially cheap, or because its associated “risk” factors are cheap, that should be measured as skill, not taking risk.

If we add enough “risk” factors to the analysis, most alphas disappear.  But the ability of managers to buy when a risk factor is cheap does not go away, as does their ability to be “late followers” and lose money as so many retail investors do.

2. Second, and importantly, I don’t believe that every investment strategy can be boiled down to a fairly simple mathematical/quantitative approximation. Therefore, not every strategy can be tested in a purely academic sort of fashion. Take Covel’s trend-following, for instance. There are obviously many ways to do trend-following, but few are so simple as to easily do an historical test. It’s NOT simply momentum (as you well know!), and while momentum and trend-following certainly have some correlation, it would be a disservice to the TF crowd to view one as a proxy for the other. The buy and sell rules, timing of entry points, level of stop loss, etc. are hugely crucial to the success of the strategy.

You are right here, mostly.  What we test are only the quantifiable aspects of the strategy.  We don’t test, we cant test nuances.  Nuances will get lost in the noise.  We are out to test the first approximation of a strategy, not the strategy itself.

Most managers have an initial screen that winnows down the universe of stocks that they will then use their abilities to analyze.  Managers think that only a subset of stocks are worth their time, because that pool is likely to outperform, now let’s get the best of those.

In this sense, we are not testing the fullness of a manager’s processes, but only his initial quantitative screen.  Processes beyond that are alpha, whether positive or negative.

As one who has sat through many dog-and-pony shows (and you, friend, more than me), most managers fall into buckets off of their screens.  What is their investable universe?  We test that.  We can’t test the fine gradations beyond that — the law of small numbers interferes.

But what I will argue regarding trend following is that there is some measure of momentum that explains over 70% of the results of a wide number of trend followers, much as Buffett could point to the “Superinvestors” and claim that they were all one tribe, though the details differed considerably, much as Covel has done with trend following.  The first approximation of the group element is the important part tested.  Maybe we need to use principal component analysis to tease it out, but we do need to simplify the broad parts of the strategy for testing.  We can test the broad stuff.  Beyond that we are stuck.

3. So with #2 as an assumption, the only way to analyze TF is as a group of investors. Is there survivorship bias? Yes, but you have that with value guys, too. Is it enormously dependent on sticking with the system, even when it’s not working? Yes. Is there a good sample of auditable accounts out there? No…not so far as I’m aware. I think the issue that Covel has is that the majority of the best investment returns people have ever put up are from the momentum/TF crowd. However, one should very clearly separate investing from trading. The trading crowd has the ability to put up ginormous returns, but at what cost? Huge volatility, gigantic turnover, etc. that most people are not willing to live with.

Let Covel and his friends try to raise money from the institutional investment community.  We may admit that momentum works, but not the ability to consistently make money off of price/volume action when managing a large amount of money.  If they do have that skill, we need to explore it, and let the behavioral investors analyze it so that we get a first approximation, a factor, to explain it.

Survivorship bias? You bet that is there.  That is why we test mechanized first approximations to a strategy, not the strategy itself.  We test tribes, we don’t test families, much less individuals.

So in the end, as you’ve said before, it comes down to finding a system/approach that has shown the ability to work well for others and sticking with it through the tough times. No approach to investing/trading will be absolutely perfect every month, and most people lack the discipline to actually make it work over time. They switch from system to system, at the most inopportune times.

Thanks for the good work…keep it up!

You would know better than most that though I am generally a value investor, my own strategies are different because I use industries as my primary screen in investing.  And it is nonlinear — I look at those that are running, and those that are dying, but not the middle.  I consider macro factors that many do not, whether I am right or not.

I am one of those managers that would be hard to measure, if one wanted to measure things precisely; I don’t screen, as most managers do.  But I consider value, momentum, and mean-reversion effects to be givens, while I try to analyze what industries and companies will do well.

And that is a reason why I have not fared well with fund management consultants.  Like Covel, I do not fit their paradigm.  Unlike Covel, I would like to fit their paradigm.

But no, I am happy for the present to attract individual investors who want to outperform on a risk adjusted basis over a 5-year  period.  That is my forte, and I will pursue it with investors as my firm goes live at the beginning of 2011.

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Warren Buffett once wrote a piece that is in one the editions of Ben Graham’s The Intelligent Investor, called The Superinvestors of Graham-and-Doddsville.  Buffett chooses nine investors that learned from Ben Graham, including himself, and shows how they outperformed the market averages over many years.

Very nice.  Another win for value investing.  I live in Graham-and-Doddsville for the most part, and have admiration for my neighbors.  No envy here.  I do well enough.

But, even though Buffett knew these investors long ago, and they were all students of Ben Graham, what I don’t know is whether Buffett culled only the best of Graham’s students for his essay.  I think the best of Buffett; I generally think he is an honest guy, but I don’t know for sure.  I write this as a convinced value investor.

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Far better to try to do a general study.  The trouble is that it is difficult to segment the market into value investors, and everyone else.  The category is squishy.  Even if we could define the category well, we would have a hard time aggregating all of the data from all of the brokerage accounts.

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So, what are we left with?  We boil down strategies into their quantitative essences, and measure the performance of the quantitative strategy versus the index.  The result is bloodless, and accurate to the first degree, in analyzing an investment strategy.

This is what the academics do.  Though I disagree with the Carhart factors, because I view them as alphas and not as betas, the basic idea of testing a strategy over the whole of the market is valid, if they take into account a full accounting for transaction costs.

See if the strategy is valid from the first approximation of turning it into a mathematical formula.  For value investing, it has worked.  Value factors have outperformed.  I love being a value investor, and I have been better than most of my competitors.

But that is not enough.  Price momentum factors have also outperformed.  Which brings me to my final point: Michael Covel hand-picked many successful trend followers in the his book, Trend Following.  He had more freedom to pick trend investors than Buffett did to pick value investors.  I give Michael Covel a choice:

• Are you willing to recognize that value investing works, even as momentum investing works?
• Or, do you end up a narrow-minded man who only sees one way to make  money in the markets?

Though I am mainly a value investor, I do not abhor momentum investing.  I incorporate it where I can.

But when Michael Covel chose other trend followers to demonstrate the value of his theory, he was less restrictive than Buffett was, and Buffett’s method was less than scientific.

I am not trying to pick a fight with Michael Covel.  On October 1st, we had a “discussion” over Twitter that he started, and I finished, where we discussed this topic.  Anyone who can re-assemble the full details of the topic please e-mail me, and I will post it.

I tried to be a gentleman, but Covel interpreted me as being a wimp.  I hate that.  A gentle answer discourages wrath, and that is what I aimed for, but he did not perceive it.

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Much as I am not crazy about academics in finance, the way that they analyze strategies is the only fair way of analysis, because it allows for no discretion.

There are two choices for doing an economic analysis in finance:

• Segment investors, and analyze their performance
• Describe the distinct strategies of investors in easy quantitative terms, and show how they perform versus the index.

There are a large number of studies that show that price momentum is a winning strategy.  I agree with those, and let Michael Covel agree with me.  I am not looking for a debate, but an agreement.

With that, I leave it in the hands of my readers.  Why not incorporate both value and momentum into your investing?

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Update: here is a transcript of the discussion with @Covel:

Covel: @AlephBlog You get grief because you don’t understand the subject and ignore the performance.

Merkel: @Covel As you wish sir.

Covel: @AlephBlog http://www.michaelcovel.com/2009/04/25/david-merkel-defending-a-wrong-view-to-the-bitter-end/

Merkel: @Covel I don’t bear grudges, do you?

Covel: @AlephBlog Is this seriously how you debate? Everything is an emotional counter?

Merkel: @Covel No, I still stand by what I wrote.  There are five parts, and you would do well to read them carefully.  My opinion is expressed.

Covel: @AlephBlog If you were serious about the subject you would examine the blind spots in your argument. You don’t and wise people see why.

Merkel: @Covel I responded in detail to your statements; you did not. Your use of “ad hominem” argumentation was without basis. Compare me w/Cramer?

Merkel: @Covel Look, I am fair. Please write a piece that shows pt-by-pt where I am wrong, or affirm that your last piece was that. I will +

Merkel: @Covel re-examine my “prejudices” and write a follow-up.  But, are you willing to be as fair? It’s your ball, run with it.

Covel: @AlephBlog If you are truly intellectually curious write a cogent argument for trend following performance. Don’t be lazy like your review.

Merkel: @Covel I have written many times on the value of using price momentum in investing.  I mentioned that in my reviews a number of times.

Merkel: @Covel Try this, then: http://alephblog.com/2009/01/21/a-different-look-at-industry-momentum/

Covel: @AlephBlog No banana. Explain the decades of trend following performance generated by the traders mentioned in my book. Let’s see it.

Merkel: @Covel In any strategy, those who do the best survive and get known. Using hindsight, they get picked to show that the strategy works.

Merkel: @Covel Buffett used the same argument for value investing in his essay The Superinvestors of Graham and Doddsville http://bit.ly/9IKsDf

Merkel: @Covel My answer to you is that cherry-picking is not analysis. Please do a study of all trend followers to prove your argument.

Merkel: @Covel Comprehensive article on the value of momentum and mean-reversion. http://bit.ly/cCzx2p This is what I think is careful research.

Covel: @AlephBlog Who are failures? Name them. Describe why they failed. Let’s see it. Don’t hide behind “Covel it’s only survivors!”

@edwardrooster @alephblog His argument is idiotic. He is trying to say thousands of trades over decades is luck. That is foolish.

Merkel: @Covel Selection of high performing investors does not prove that a method works. I am not saying anyone’s performance is luck. Momo works.

Covel: @AlephBlog I am out. Even if you read my book, there is no comprehension. Typical bias. Wrong, but unable to accept. You must protect self.

Merkel: @Covel Happy trails. Come back when you want to talk reasonably.  If you get to Baltimore, lunch is on me.

• Not optimize for best return, even if risk adjusted.  I gave extra weight to avoiding the downside.
• Added in the details.  My models were entirely home-grown, and took advantage of my programming abilities to come to a sharper result.  I am not a good theoretical mathematician, but I am good at using math to solve practical problems.

The idea is model completely, and don’t ignore scenarios that could not happen.  My interest rate model had scenarios that mimicked what we actually got, though what we got was not a high probability.

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One of the themes that I came away with from the Denver conference last week was look through the windshield, not the rearview mirror.  But much of the investment industry, and retail investors are destined to  look through the rearview mirror.  I, as an actuary, have been unfairly accused of driving life insurance companies through the rearview mirror, look at this and say that we can look through the windshield, but we have to be more than the common shlubs who are the majority of the market.

To do that we have to adopt an independent disposition, and not care about raising funds, but only earning returns for clients.  If we build it, they will come.  In one sense, it is like someone who has a beautiful singing voice, but who avoids pride, and admires his voice as if it were someone else’s voice. (Apologies/Credit to C. S. Lewis)

The main point here is to look through the windshield, and exercise intelligent independent judgment.  Analyze the situation, and figure out where there is an advantage as a businessman.  The tools of modern portfolio theory will be useless here, so ignore them.  They only sharpen/obscure our understanding of the past/present by calculating parameters that are not stable or predictive.

The only positive thing about Modern Portfolio Theory is that it sidelines a bunch of bright guys who would otherwise be competitors in the markets.  Sun Tzu would admire this tactic — getting a large portion of the opposition to become peaceniks because the expected value of the war is zero or negative.  It’s as if an economic Tokyo Rose is broadcasting that competition in financial markets is futile — in aggregate, everyone will get average performance, so why fight to get better performance?  It’s futile; give up; go home.

I would simply say there is always a decent amount of lazy investors in the market. Smart investors can get better returns through paying careful attention to what seems to offer the best returns on a forward-looking basis.

Part of looking through the windshield is avoiding noneconomic constraints.

1) Do I care where a company is located? Yes. I want a place where the rule of law is honored.  As many have commented at my blog, does that include the US?  Yes, for now.  Global diversification is important.  That said, it will be interesting to see what will happen to investments should we see tariffs, foreign exchange controls, and expropriation.  At least in you own home country you only have to deal with the “devil you know.”

2) Do I care whether a company has a large or small market capitalization?  Not now.  Even if my asset management firm grows, I will adjust my strategy to include attractive small caps at lower target percentages.  If my buying begins to affect the stock price, I will take smaller positions.

3) Do I care if a stock is “a growth stock” or a “value stock?”  No, I care more about industry and firm prospects relative to price.  I will pay up on occasion.  Still, mostly I try to buy them cheap, and it biases me toward “value stocks.”

4) Do I care about whether a stock is volatile or not?  Yes.  Stock price volatility is a sign of low creditworthiness, and usually I only buy higher quality stocks.

5) Do I care about price momentum?  Yes.  Typically, I buy companies that have strong current momentum, or poor momentum over 3-5 years.  Is it what I focus on?  No.

6) Do I care if I have an “undiversified” portfolio?  No.  I want to be in the right place at the right time on average.  Mimicking the index is a recipe for mediocrity.

7) Do I care if I am holding cash?  Yes.  I’d rather be in stocks, but will build up cash if I have to.  Cash moderates volatility in a concentrated portfolio, and allows for opportunistic purchases.

8 ) Do I care if I underperform?  You bet.  It burns a hole in my gut.  But it doesn’t make me change my methods.  It will make me sharpen my analyses.

A large part of the idea is to focus on risks, not risk.  Academics focus on univariate risk, with its simplistic math — beta, standard deviation, skewness, and all of the half-measures and ratios that stem from them.  I can’t model my methods in full, but I look at the risks in particular for each of my investments.  Every investment has to justify its existence in my portfolio independently.  I don’t do correlations; they are not reliable.

I also don’t go in for the four Carhart risk factors — beta, size, value/growth, and price momentum.  I don’t think of them as “betas,” but as “alphas.”  These are factors that can be taken advantage of when they are cheap or rich.  They are not risk factors, they are simply factors.

In closing, there has been a shift in the environment from inflation to deflation.  How does that affect investment choices?  My guess: buy well-financed companies with a low price to tangible book.  Stagflation?  In the ’70s the answer was low P/E with pricing power.

The closing segment of this series will focus on how to do statistically valid studies of investment performance.  I know at least one person who may be annoyed by what I say, but it is important to try to be fair in investment analysis, lest we lead others astray.