Worth Reading

Worth ReadingToday I offer four fantastic articles for your careful examination, perhaps over the week-end. All are worth your time and attention. 

I’ve seen complexity fail over multiple investment cycles in these types of portfolios, but as Keynes told us, “Worldly wisdom teaches that it is better for the reputation to fail conventionally than to succeed unconventionally.” Somehow simplicity has become the exception while complexity is now the rule.

I believe that meeting long-term spending needs for institutional portfolios and controlling risk can be accomplished through simplicity.  That’s not to say that it’s easy, just less complex.  A complicated portfolio relies on the hope of being smarter than your investing peers and the markets while taking on added risks.  We all know hope is not an investment strategy.

Confessions of an Institutional Investor (via Josh Brown)

The world of investing is infinitely complex. It feels like we need complex strategies to generate returns. The problem is that as Adams says complicated systems are more likely to lead to “opportunities for failure.” We cannot control what the markets do. We can however control our own actions. For the vast majority of investors a simple system that we can follow over time will in all likelihood lead to better outcomes.

Simplify your investing to avoid ‘opportunities for failure’ (from Tadas Viskanta)

How many people here think that this bull market, wonderful as it is, is built on a foundation of robust and impressive macroeconomic growth and policy choices that are laying a foundation for impressive growth in the years that lie ahead? And how many think that it’s [built on the Federal Reserve’s] printing press? I prefer to play in markets that are priced attractively, priced to offer strong, long-term returns, not ones that are expensive.

Where should you put your money now? From Rob Arnott and others (via Fortune)

Modern day investment management resembles, sadly, another old profession – and I’m not thinking of the oldest one, although there may be parallels there as well. Rather, I’m thinking of ancient alchemy with its near constant promises to turn lead into gold, just as investment managers repeatedly offer to transform low returns into high returns. This raises the question as to why investors/people keep falling for the stories offered up by investment managers/alchemists.

No Silver Bullets in Investing (just old snake oil in new bottles) (from the wonderful James Montier)


Finance Blogger Wisdom

ARAs he did last year and the year before, Tadas Viskanta of the indispensable Abnormal Returns asked a panel of independent finance bloggers (including me) a series of interesting questions and has been posting the answers this week while he is on vacation.  I think they are all worth a read.

Sell Signal

SellIn 1993 I was still a relative newbie to the investment world, having made the move from practicing attorney to Wall Street trading floor the year before.  The junk bond market was very hot then – seemingly everyone was looking to get (more) involved.  The investment bankers were happy as bigger and hotter new deals kept getting done.  Traders and salespeople were happy because the markets were hopping.  And investors were happy because prices kept going up and cash kept coming into the junk market. 

Everybody was winning. Continue reading

Is the Yale Model Past It?

Yale Key

It is axiomatic in the investment world that as an asset class becomes more popular, it suffers from both falling expected returns and rising correlations.  In other words, good trades get crowded and their advantages tend to disappear.  This crowding happens because success begets copycats as investors chase returns.  Mean reversion only tends to make matters worse.  In effect, it results in “investing while looking in the rearview mirror” or, as per the title of William Bernstein’s fine new book, Skating Where the Puck Was

The evidence suggests that this overcrowding is precisely what has been happening with respect to the Yale Model.  Continue reading

Edge: Tadas Viskanta

What should we be worried about? In terms of existential threats, there are no shortage of things we can worry about. As Martin Rees writes in his response to the Edge question there are a “cluster of risks with low probability but catastrophic consequences” with which we should be concerned. We were reminded in vivid detail last week of the kind of threats we are going to have to deal with over time.

Let’s leave these interesting, albeit existential discussions to those with more knowledge and focus this discussion is on finance and economics. There is a war on savers going on and it is not the one we commonly discuss. While ultra-low interest rates have dramatically changed the calculus for investors something else is going on that has little to do with Fed policy. The vast majority of American investors, or should I say savers, are being left to their own devices with not altogether satisfactory results. Continue reading

Establishing Your Top 10 Investment Default Settings

I pay a lot of attention to the investment process.  In that regard, every investor — personal or professional — ought to have a clear investment plan based upon appropriate personal considerations, goals and outlooks and every investor ought to stick to that plan unless and until something significant changes. But there is a crucial component of the investment process that gets surprisingly little attention:  our investment default settings.  We can use them when we aren’t sure what to do, when we’re deciding what to do, when our circumstances have changed but our plan hasn’t (yet), or when we’re just starting out. 

The idea here is that we all have default settings — known and unknown, acknowledged and unacknowledged — and that those defaults greatly influence how successful we are and become.  Having the right default setting in defined contribution plans make a big difference (more here). I would examine and apply my default settings across and throughout the entire investment process and even suggest that we need to look at our default settings as carefully as we look at anything else.

What follows are my suggested default settings.  Your mileage may vary. Continue reading

Gaming the System

oops2When I was a kid I had a paper route.  One of my customers was a barber who made book on the side.  Shocking, I know.  The giveaway was the group of guys always hanging around but not getting their hair cut and the three telephones on the wall that rang a lot.  Even as a kid I could tell that something was up.

Anyway, each week the barber and I had a wager.  During the NFL season, I picked a winner of the Buffalo Bills game (the Bills were our local team) straight-up.  When I was right, I got double the subscription price, before tip.  When I was wrong, the barber got his paper free.

As it happened, I won a lot of the time – obviously aided a lot by being able to decide which side of the bet I wanted, not having to worry about the spread and (in no small measure) by the Bills being pretty lousy during that period.  One Monday after (yet another) win for me and loss for the Bills, I was feeling pretty haughty (imagine that) and started talking smack to the barber (imagine that).  Finally, my exasperated barber told me something that made a big impression at the time and which resonates still, “Do it against the spread and then we’ll talk.”

We are forward-looking creatures.  We love to make forecasts, predictions and even wagers about the future.  We just aren’t very good at it.

Sports betting is obviously very big business.  Nearly $100 million was bet legally on the Super Bowl alone and CBS reports that over $2.5 billion (with a “b”) is bet at Las Vegas sports books in a year. The sports books make money – a lot of money.  But almost nobody else does, because winning in the aggregate is extremely difficult.

Pundit Tracker compiled all the NFL picks made by the ESPN, Yahoo, and CBS Sports pundits through the 2011-2012 season.  Obviously, these people are all put forward as experts and promoted as such.  Yet if you had placed $1 on each of the pundit’s picks (based on “moneyline” odds) you ended up losing a good deal of money even after removing the sports books’ commission (the “vig”) from the odds – and these picks weren’t even against the spread. My friend Mike Silver of Yahoo Sports topped the list, but even his “bets” only “earned” an 8 percent return for the year and that’s hardly worth the risk.  Spread betting only compounds the difficulty (point spread betting relates to who wins and by how much; moneyline betting relates solely to who wins, albeit with odds factored in).  In fact, had you been relying upon the advice of the “experts” at CBS Sports to bet against the spread this season, you would have lost a lot of money (note the results here).

One major exception to the general rule is the legendary gambler Billy Walters, a crucial member of the famous “computer group,” which used a careful and computerized process to make a fortune and, as a result, to revolutionize sports betting in the 1980s.  Today, Walters uses multiple consultants – mostly mathematicians – just like a hedge fund manager uses analysts and still makes a ton of money.  Walters’s process is to create his own line largely using statistical measures of the teams and then to bet when his view of a game is significantly different from available commercial betting lines.  He’s not opposed to trying to influence betting lines either.  Walters has the power, the money and the reputation to bet on teams that he doesn’t actually favor in order to move the odds. Once that happens, he lays much larger bets on the other side, the side he wanted all along.

Walters is staggeringly rich (according to 60 Minutes, he is “worth hundreds of millions of dollars”), but he claims a lifetime winning percentage of only 57 percent, as compared to the break-even of 52.38 percent (the winning percentage sports gamblers need to hit to offset paying out a 10 percent vig on their losing bets).  Even so, while he has had losing months (randomness can overcome a good process for substantial periods of time), he has never had a losing year during this 30-year streak.

But that winning streak only started after he made a major change in his approach.  By his own account, Walters lost his shirt many times over before becoming focused, data-driven and careful to play the long game (making a profit while losing 43 percent of the time requires it, especially because the losing streaks can be very long indeed).  One key is lots of bets – whenever the data suggests a significant edge – with bet size being determined by the extent of the edge.

The betting market in Las Vegas isn’t much different from Wall Street. Fed by rumor, speculation and greed, teams, like investments, can grow hot or cold for no good reason.  Moving lines is remarkably similar to market bubbles. Walters insists that “[b]etting on a ball game is identical to betting on Wall Street.”  Walters even claims that he has lost a lot of money in the markets and thinks the Wall Street “hustle” is far more dangerous than that in Las Vegas.

It should be no surprise then that many Wall Streeters have gambling histories, most prominently Ed Thorp.   For more information, read Scott Patterson’s excellent book, The Quants.  I even know a few.

I grew up in this business in the early 90s at what was then Merrill Lynch.  My decade of legal work in and around the industry didn’t prepare me for big-time Wall Street trading.  I’d ride the train to Hoboken early in the morning, hop on a ferry across the Hudson, walk straight into the World Financial Center, enter an elevator, and press 7. Once there, I’d walk into the fixed income trading floor, a ginormous open room, two stories high, with well over 500 seats and more than twice that number of computer terminals and telephones.  When it was hopping, as it often was, especially after a big number release, it was a cacophonous center of (relatively) controlled hysteria.

It was a culture of trading, which makes sense since it was, after all, a trading floor.  And it wasn’t all that different from a sports book.  Most discussions, even trivial ones, had a trading context. One guy (and we were almost all guys) is a seller of a lunch suggestion. Another likes the fundamentals of the girl running the coffee cart. Bets were placed (of varying sorts) and fortunes were made and lost, even though customers did most of the losing because we were careful to take a spread (think “vig”) on every trade. The focus was always on what was rich and what was cheap and the what if possibilities of and from every significant event (earthquake in Russia – buy potato futures).  The objective was always to make the most money possible, the sooner the better.

One of my colleagues there was an excellent trader who traced his success to his “training” as a gambler.  While in college, in the days before the internet and relatively uniform betting lines, he would find a group of games he wanted to play (via a system not nearly as sophisticated as the one Walters used and uses) and would then place bets with bookies in the cities of the teams playing.  In each case he’d bet against the team located in the city of the applicable bookie.  Because the locals disproportionately bet on the local team, the point spread would be skewed, sometimes by a lot.  Thus he had an excellent true arbitrage situation with a chance to win both sides of the bet, which happened a lot.  He traded mortgages in much the same way.

Interestingly, value was almost never at issue on the trading floor. The idea was to exploit inefficiencies and – especially – the weaknesses of whoever was on the other side of the trade right then. Michael Lewis’s wonderful first book, Liar’s Poker, re-issued in 2010 and perhaps (finally) being made into a movie, captures this culture (in his case, at Salomon Brothers) pitch perfect.

Now that the focus of what I do has changed, I am primarily consumed with finding value through investing – which must be distinguished from trading. As Barry Ritholtz puts it, “[t]rading (as opposed to investing) is more about laying out probabilities of risk versus reward; investing is about valuations within the longer secular macro picture.” I would suggest that trading is about selling what is rich and buying what is cheap while investing is about finding, acquiring and holding on to value. That distinction is, I think, the key to why so many analysts misapprehend the market relevance of another terrific Michael Lewis book (which has been made into a movie), Moneyball.

Moneyball focuses on the 2002 season of the Oakland Athletics, a team with one of the smallest budgets in baseball.  At the time, the A’s had lost three of their star players to free agency because they could not afford to keep them.  A’s General Manager Billy Beane, armed with reams of performance and other statistical data, his interpretation of which was rejected by “traditional baseball men” (and also armed with three terrific young starting pitchers), assembled a team of seemingly undesirable players on the cheap that proceeded to win 103 games and the divisional title. If that sounds a lot like the Billy Walters approach to you, you’re right.

Unfortunately, much of the analysis of Moneyball from an investment perspective is focused upon the idea of looking for cheap assets and outwitting the opposition in trading for those assets.  Instead, the crucial lesson of Moneyball (like the Walters process) relates to finding value via underappreciated assets (some assets are cheap for good reason) by way of a disciplined, data-driven process.  Instead of looking for players based upon subjective factors (a “five-tool guy,” for example) and who perform well according to traditional statistical measures (like RBI and batting average, as opposed to on-base percentage and OPS, for example), Beane sought out players that he could obtain cheaply because their actual (statistically verifiable) value was greater than their generally perceived value. Beane sought out players in much the same way that Walters seeks out mispriced spreads.

In some cases, the value difference is relatively small.  But compounded over a longer-term time horizon, small enhancements make a huge difference.  In a financial context, over 25 years, $100,000 at 5%, compounded daily, returns $349,004.42 while it returns nearly $100,000 more ($448,113.66) at 6%.  That’s a key reason why Walters is anxious to place lots of bets.

But why are successful investors, successful prognosticators and successful betters so rare?  I have three reasons to suggest.

The first is our human foibles – the behavioral and cognitive biases that plague us so readily. These issues make us susceptible to craving the next shiny object that comes into view and our emotions make it hard for us to trade successfully and extremely difficult to invest successfully over the longer-term.  Recency bias and confirmation bias – to name just two – conspire to inhibit our analysis and subdue investment performance.  Roughly half of each year’s NFL play-off teams fail to make the play-offs the next season.  Yet our predictions (and bets) disproportionately expect last year’s (or even last week’s) successes to repeat.  Another problem is herding.  On average, bettors like to take favorites. Sports fans (and even analysts) also like “jumping on the bandwagon” and riding the coattails of perennial winners. Sports books can use these biases to shade their lines and increase their profit margins.  So can the Street.

Experts are prone to the same weaknesses all of us are, of course, as Pundit Tracker’s look at the predictions of NFL “experts” noted above so clearly demonstrates.  Philip Tetlock’s excellent Expert Political Judgment examines why experts are so often wrong in sometimes excruciating detail. Even worse, when wrong, experts are rarely held accountable and they rarely admit it. They insist that they were just off on timing (“I was right but early!”), or blindsided by an impossible-to-predict event, or almost right, or wrong for the right reasons. Tetlock even goes so far as to claim that the better known and more frequently quoted experts are, the less reliable their guesses about the future are likely to be (think Jim Cramer), largely due to overconfidence, another of our consistent problems.

We should never underestimate information asymmetry either.   Information asymmetry is the edge that high frequency traders have and why Billy Walters focuses on player injuries and their impact in addition to his models.  At a broader level, it’s why it’s so difficult to “beat the market.”  Obviously, someone is on the other side of every trade.  When you make a trade, what’s your edge vis-à-vis your counterparty?

The third reason is just plain luck.  The world is wildly random.  With so many variables, even the best process can be undermined at many points.   Pundit Tracker describes the “fundamental attribution error,” the error we make when we overweight the role of the individual and underweight the roles of chance and context when trying to explain successes and failures.

While watching SportsCenter earlier this week, where the big story remained Monday night’s controversial (to say the least – it even forced the NFL to settle its lock-out of its regular officials) touchdown call that gave the Seattle Seahawks a 14-12 victory over the Green Bay Packers, I was struck by the huge impact the last-second turnaround had on gamblers.  If Seattle’s desperation pass had correctly been ruled an interception, Green Bay – as 3½ point favorites — would have won by five, covering the spread.  Instead, the replacement officials’ call shifted the win from those who bet on the Packers to those who took the underdog Seahawks.  Remarkably, that result means that as much as $1 billion (that’s with a “b”) moved in one direction as opposed to the other.

Thus a clear win was eliminated due solely to the almost unbelievable incompetence of the replacement officials.  That’s just dumb luck for bettors, and why it can be so frustratingly difficult to wager successfully on both our favorite teams and our favorite stocks. It may seem like the system is gamed, but investing successfully is just really hard (like gambling), as Tadas Viskanta so eloquently points out and I regularly reiterate.

In all probabilistic fields, like investing and gambling, the best performers dwell on process. A great hitter focuses upon a good approach, his mechanics, being selective and hitting the ball hard. If he does that – maintains a good process – he will make outs sometimes (even when he hits the ball hard) but the hits will take care of themselves. That’s the Billy Walters process analogized to baseball. Maintaining good process is really hard to do psychologically, emotionally, and organizationally.  But it is absolutely imperative for investment success.  And for gambling success too.

Point Counterpoint (More on Math)

Josh, you ignorant, misguided slut!


Just kidding.

On Tuesday, Josh Brown wrote an interesting and engaging post called Math isn’t an Edge.  In it he reiterated an analyst/PM interaction he found instructive.  Here is the key assertion:  “Math isn’t an investing edge.  Go find something that doesn’t come out of a calculator.”  In Josh’s words, “tell me something I don’t know.” 

I replied (with trepidation) yesterday:  Math is a Major Edge.  To summarize: 

Math isn’t enough on its own.  But it is absolutely necessary for good investing. As the philosophers say, it is necessary but not sufficient. And since it is so often ignored and misinterpreted, it often provides a really big edge.

So, this morning we got Josh’s rebuttal, entitled Math is a Foundation, Not an Edge.  The best part, of course, is where Josh calls me one of his “fave financial bloggers.”  I’ll enjoy that all week-end and beyond.  Thanks, Josh.  I have stated my appreciation of him and his work (including his great blog and terrific book) many times and am pleased to do so again. May the record so reflect. 

But I still think he’s wrong here.  Please allow me to elaborate.  I’ll begin by emphasizing that our disagreements are relatively small yet significant.

Josh argues that enormous amounts of data are readily available to all.  Moreover, “[y]ou could say that the interpretation of how this data will affect a stock’s future price is your edge, but that is NOT MATH, it is ANALYSIS.  Not the same thing.”  I agree.  As my post was careful to state, “facts alone — without context and interpretation — aren’t worth much.” 

Josh continues (my emphasis):

The main reason so many of you have argued with me is based on a misunderstanding – I am not saying the math doesn’t matter, I am saying math is not an edge in and if itself because it is the starting point and the commonality between most experienced investors is that they all understand it.  Again, it is the foundation.

Here is a significant point of disagreement.  In a world where the vast majority of funds and managers underperform, there is little evidence that “experienced investors” really do understand math or the fundamentals of investing.  As I argued in my post, “all in all, we suck at math.  It isn’t just the ‘masses’ either — it’s the vast majority of us and often even alleged experts.  Thus an analyst who understands math and utilizes it correctly will have a major advantage.”

Josh seems to agree in principle because his final assertion makes a similar point (Josh’s emphasis): 

You know who was really good at math?  This fucking idiot [I don’t know if Josh means Meriwether, Merton, Scholes or someone else – I’d have used the plural, “idiots”].  Probably better at math than you are. Again, he has the foundation in that he knows all the calculations and ratios that everyone else knows.  But that was not his edge.

As Josh would have it, the investment world is full of experts that know the math but consistently underperform anyway.

Here is the (probably inevitable) juncture of the dispute where we may simply be arguing semantics.  What I see as knowing and using the math Josh sees as analysis.  In that context, math is not an edge per se, except as against the ignorant few.  Instead, being able to control oneself behaviorally so as to apply the math provides the edge. Or perhaps using the math to come up with a coherent investment approach is the edge.  In other words, essentially everybody agrees on the math but most experts do a lousy job applying it.  In that sense, per Josh, math isn’t an edge – it’s foundational. 

But I remain convinced that our disagreement is more than semantic.

To quote Tadas Viskanta yet again, investing successfully is hard – largely because of behavioral biases – but we can see generally what works and what doesn’t work.  That we see and don’t do (or try to do) what works is partly due to poor analysis and partly due to cognitive biases that limit our success, but it’s also partly a commercial judgment.  In the words of Upton Sinclair, “It is difficult to get a man to understand something, when his salary depends on his not understanding it.”

It is clear that high fees are a huge drag on returns and hurt consumers.  But they benefit us.  So we generally make our fees as high as we can get away with.  Closet indexing keeps assets sticky while doing right (value, small, concentration, low beta, momentum, etc.) risks underperformance for significant periods and thus losing assets. We want sticky asserts, so….

Ignoring the facts we know is practically and effectively no different from not knowing.  Ignoring the math we know isn’t an analytical problem.  It’s much worse than that.  It’s a moral problem.  Knowing and using the “math” (broadly interpreted to include basic investing principles) is thus a major edge.  Otherwise, how could such dreadful investment management performance be so commonplace?

  • As we are all well aware, managers generally fail to beat their benchmark indices.  In 2010, only about 25% of active managers outperformed.  2011 was even worse.  Among 4,100 funds that invest in large-cap stocks, only 17% beat the S&P 500 for the year.  Moreover, according to Bianco Research, 48% of equity mutual funds underperformed their benchmarks by more than 250 basis points. Those few managers that do outperform in any given year have a very hard time (more here) keeping up the good work.
  • Hedge funds – despite (and in part because of) enormous fees – have also badly underperformed.   Since 1998, the effective return to hedge-fund clients has only been 2.1% a year, half the return they could have achieved simply by investing in Treasury bills. Performance thus far in 2012 has lagged too. 
  • The Global Market Index (GMI) —a passive, unmanaged but well diversified mix of all the major asset classes weighted by market values — has outperformed nearly everything else over the past decade, providing a 6.0% annualized total return for the 10 years ending December 31, 2011. That puts GMI in the 89th percentile relative to the roughly 1,200 multi-asset class funds with at least 10 years of history (and thus makes it an even better performer overall than the 89th percentile suggests once survivorship bias is factored in). GMI’s rebalanced and equal-weighted counterparts did even better. 

Let these facts sink in for a bit.  

As I emphasized initially, the great Seth Klarman offers a terrific insight: “Value investing is at its core the marriage of a contrarian streak and a calculator.”  Being a contrarian is necessary because if virtually everyone else is doing it there can’t be an edge available.  But the calculator is necessary to prove what we think we know and to check our work.   Depending on (uh-hem) how you do the math, the overall investing failure rate approaches 90 percent.  Maybe, as Josh would have it, that level of failure merely evidences poor analysis.  But I think it’s more foundational than that.  We aren’t using Klarman’s calculator nearly enough and, when we do use it, we aren’t wielding it correctly.  Most fundamentally, the investment world ignores what it knows or should know to be true.

In any event, the real bottom line is this – whether the key problem vis-a-vis the math is foundational or analytical, our industry is failing consumers and failing them in a big way, over and over again.  That’s about as foundational as our business gets.

Reckoning with Risk (7): Widening Your Lens

Tadas Viskanta wrote a wonderful piece this week making the observation (as he had in his very fine book) that “the only low-hanging fruit for investors these days has to do with strategies and tactics that lie outside the realm of portfolio management. These include maximizing tax benefits through aggressive tax loss harvesting and optimal asset class location.”  He thus suggested that we invoke “a broader definition of alpha.”

If the goal of investing is to live a richer, fuller life and the opportunities by doing it through traditional investment techniques seems limited then it makes sense to look elsewhere. Beefing up our savings, more conscious consumption and investing in things, like education, that have the potential to generate returns in excess of financial markets all have the ability to increase our well-being without taking on more financial risk.

Within the investment context specifically, this approach means minimizing fees and expenses and tax efficiency (which is, of course, much more than tax loss harvesting).

I made a similar, if broader, recommendation in my 2012 Investment Outlook back at the beginning of the year.

Now is also a good time for individuals to guarantee value if not return by paying down debt, refinancing where possible, reducing consumption and reducing spending. They should consider giving more away too. While they are not investments per se, these actions will pay remarkable “dividends” immediately and will strengthen consumers’ financial position substantially so that when the next secular bull market comes around – as it inevitably will – they will be in a position to take advantage of it (emphasis in original).

What Tadas describes as “a broader definition of alpha,” I think of as widening one’s lens to see the bigger picture of opportunity and risk. Actively managing one’s life by “paying down debt, refinancing where possible, reducing consumption and reducing spending” – saving (much) more in general – is a fabulous risk management and mitigation strategy. 

The ideal approach in this regard can and should get even broader still.  I had dinner with Moshe Milevsky this week and he described a bit of his own investment process to me (besides being gracious and generally insightful).  One thing that stuck out was his 100% equity allocation.  He does that because he expects to work for at least 20 more years while his job (as a tenured professor) is very secure and provides a decent pension, but doesn’t have the upside potential of other choices he could make.  His life is thus very “bond-like” (even if  not “Bond-like”).  This concept is a key point of his forthcoming book (updated from an earlier edition).  Moshe argues that we need to be aware of the value, potential return and risks of our own “human capital” (job and career as opposed to investment choices) to plan a solid future. 

If your career is very secure you may be more aggressive with your investments.  But if your career is likely to suffer a good deal of volatility (perhaps you’re engaged with a speculative start-up or work at a hedge fund), your investment strategy should be adjusted accordingly.  Similarly, if you work in real estate or own your own home, your asset allocation ought to be reflective of that.  Your financial planning should also reflect where you are in the life-cycle, mortality risks (do early heart attacks run in your family?) and any social capital you may have. 

Dealing with investment risk is insufficient if you don’t deal effectively with the broader risks you face in life.  When reckoning with risk, widen your lens to see the bigger picture.  Once you have evaluated it, actively manage your life so as to take advantage of the opportunities you see and to protect against the risks you face.  After all, risk is always risky.


My Reckoning with Risk series:

A Very Nice Honor

Michael Kitces published a piece in Investment News today recommending 11 investment blogs for financial professionals, including Above the Market in the 11.  I’m in very good company with Michael’s Nerd’s Eye View, Tadas Viskanta’s Abnormal Returns, Wade Pfau’s Retirement Researcher Blog, and Josh Brown’s The Reformed Broker, You should read them all regularly.