Investing is a battle between the past, present, and future.

The past tempts all to look and see what has happened, and extrapolate, or assume mean-reversion.  It tempts academics to use simplistic math, and calculate alphas, betas, standard deviations, R-squareds, and more.  They consider the past to be prologue.  They estimate assumptions for asset allocation off of averages of past returns, sometimes even making the error of arithmetic averages, rather than geometric averages.

But the past is the past.  It happened, and it usually has little bearing on the future, aside from momentum effects when few are following momentum.  Those who calculate models off of historical data describe the past in a stylized way.  The past is a historical accident; generalizing from it in precise terms is difficult.  In some ways I think that analogies from the more distant past have more validity, partly because they are less known by the average market participants.

Those who use the past for asset allocation are doomed for failure.  The past is the past.  Bonds returned well in the past, but the best estimate of a bond’s return over its maturity is the YTM now.

The present intrudes on the past that way. With stocks, the same thing happens measuring current P/Es, P/Bs, P/Ss, versus long term average returns.  It is far better to be a buyer when a stock is out of favor, but not dying.

In the present we can estimate implied volatilities from options, and even implied correlations in certain cases.  Real-time as those are, they give the knife-edge of the estimate of how things react presently.

But as for the future?

We have precious little in the way of clues.

Yes, value and momentum may give us some guidance when they are underfollowed, but they are poor and weak guides to the future.

The truth is that we just don’t know.  Our models are often regime-dependent, because data has been collected over a limited period of time.  I smiled at the Denver conference that I recently attended, as models were trotted out that were based on 20 years of data or fewer.

Now, I don’t blame the researchers, including myself, much.  We all look for the biggest, longest set of clean data we can find.  We realize there are things that we aren’t testing.  We should know that there are hidden variables that haven’t varied much during a regime, that might our results quite different when the regime shifts, but for the most part those are Rumsfeldian “unknown unknowns.”

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Excursus: I once did a seemingly hopeless project to try to estimate withdrawal sensitivity to interest rate movements on deferred annuities.  I completed it in 1998, with 16 years of data, on hundreds of thousands of policies.  Big known problem: interest rates had fallen over the whole period.  But the need for the project was evident, because interest rates had nowhere to go but up, right?  With a little clever modeling, though, I teased out the statistically significant result that a one percent rise in the difference between competing and our deferred annuity yields would lead to additional withdrawal of 2%/yr.

At first, I thought 2% was too small, but then I realized it was an option not efficiently exercised.  So I left padding  in my analysis, assuming that if the market ran away and we couldn’t keep up, that withdrawal levels would be far higher than a ratio of 2.  I built my asset-liability model, which had the capacity of running multiple scenarios developed from my multivariate mean-reverting lognormal interest rate model, built from my homegrown quasi-monte carlo multivariate random number generator.

I did not set the model to optimize investment policy.  Instead, I set it to do well on two criteria that I weighted: minimize losses in the lowest 5% of the tail, and best average result.  When I got the results, they looked wrong; but the more I looked at them, I realized they were right.  I did two versions, one that allowed for the use of interest rate options, and one that didn’t.  Knowing  that my investment department had no quants, I realized the options would be a tough sell — indeed, they chose the option without them.  But then they asked me, “Dave, these are deferred annuities; crediting rates vary annually.  You’re telling us to invest three years longer than we are currently in duration terms — that’s huge.  And why 20% in 30 year bonds?”

My answer was a simple one.  We were all concerned about rates rising and withdrawals that would occur from that.  We missed the other issue, because interest rates can only go up from here, right?  Floor guarantees.  If rates continued to fall, we would have no ability to lower rates further on an increasing amount of the policies; those policies also would have low lapse rates.  When I explained how close we were to the floor we were they caught on, and realized that we had a rare “free lunch.”  Limit risk and improve returns all at once.

Actually, it meant we had mismanaged the business previously, because it was the first withdrawal study in the history of that line of business, but at that point it increased the profits of the company significantly.  What’s more — rates didn’t rise as we all knew they would.  The change in investment policy saved the insurer that merged/acquired the company a lot of headaches.

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So, with whatever our results seem to be, we have to take caution and not overdo what our results seem to prove.  Risk control should be the order of the day.  Buffett said that all he wanted in life was an unfair advantage, but with our limited knowledge of how markets work, we have to realize that we probably have less advantage than we think.

I have more to say here, but I have to hit the publish button — too long already; more coming in part 2.

I have the fun of speaking at the Burridge Center Conference at the University of Colorado at Boulder this week on Friday.  The CFA Society of Colorado is co-sponsoring it.  As a guide, they have asked my panel to comment on this piece  by James Montier of GMO: Was It All Just A Bad Dream? Or, Ten Lessons Not Learnt.  I’m going to comment on each of the ten questions, and show where I agree and disagree.

Lesson 1: Markets aren’t efficient.

“As I have observed previously, the Efficient Market Hypothesis (EMH) is the financial equivalent of Monty Python’s Dead Parrot. No matter how many times you point out that it is dead, believers insist it is just resting.”

I partially disagree.  The EMH is valid as a limiting concept. The markets tend toward efficiency, but there are many disturbances in the market, and some of them are quite big.

The EMH properly understood only means that it is intensely difficult to beat the market, nothing more.  Market prices reveal the current expectations of the market as a knife edge — sharp but thin.  They might be the best estimate of values for the moment, but offer no infallible guide to the future. The crisis tells us nothing about the EMH.

Lesson 2: Relative performance is a dangerous game.

Definitely true.  Those chasing relative performance tend to destabilize markets to the degree that their time horizons are short.  Focusing on short term relative performance leads to an over-emphasis on momentum, and when too many focus on momentum, the markets tend to go nuts — overshooting and falling dramatically, until enough momentum players exit.

Lesson 3: The time is never different.

It’s never different, or it’s always different — which one you choose is a matter of semantics.  The main thing to remember is that human nature never changes.  In aggregate, we don’t learn from market behavior.  We follow trends — we arrive late to the party, and leave the hangover near the nadir.

Most professionals and nonprofessionals tend to chase performance — see lesson 2.  That is a large part of the boom-bust cycle, which no amount of government intervention can repeal.

Here’s some advice: read books on economic history, and avoid current books on how to beat the market.  Learning economic history will help inoculate an investor against greed and panic, and will help the investor understand the guts of the speculation cycle.

Lesson 4: Valuation matters.

You bet it matters.  Excellent long term results stem from buying cheap, among other factors, like margin of safety, earnings quality, and having a sense of the credit cycle, and industry pricing cycles.

Bubble language such as “This time is different,” often appears near the end of booms.  The truth is: it’s never different, or, it’s always different.  Human nature in individual and aggregate, does not change.  Watching valuation is a major way of avoiding getting whipped at extremes, and encourages willingness to invest in the depths of panic.

Lesson 5: Wait for the fat pitch

Also agreed.  One thing that I have focused on in my money management ideas, is to avoid thinking short-term.  There are too many hedge funds, day traders, swing traders, and high-frequency traders out there for me to compete against.  Even mutual funds turn over their positions too rapidly.

I aim to hold investments for three years, but I am not wedded to a time period.  If an investment still looks attractive after five years, compared to the other investments that I hold, I will keep it.  If I find a more  attractive investment than my median idea, I will buy it, and fund it with the proceeds from one of my investments scoring worse than my median idea.

Lesson 6: Sentiment Matters

Yes, sentiment matters, at least until too many people follow it.  I do this in an informal way by following the credit cycle — when risky yields are tight, only own safe stocks.  Volatile stocks rely on sentiment — it is almost a tautology.

Lesson 7: Leverage can’t make a bad investment good, but it can make a good investment bad!

Any investment can be overlevered, and die.  Think of Fannie and Freddie.  They ran on thin capital bases for years, thinking that they could never lose.  So long as housing prices continued to rise, they were right.  And for many, the idea of housing prices falling in aggregate was ridiculous.  Those who suggested that it would happen, like me, were roundly derided.

Yes, leverage can make a good investment bad.

Lesson 8: Over-quantification hides a real risk.

Just because you can quantify it does not mean you understand it.  The Society of Actuaries has a vapid motto quoting John Ruskin: The work of science is to substitute facts for appearances and demonstrations for impressions. Easy to say; hard to do.  Scientists are biased  like everyone else.

Mathematics applied to economics or finance serves to show where assumptions are inaccurate.  Mathematical risk controls are less important than changing the culture of a firm, and setting in place checks and balances.  Toss out VAR, and reduce incentives that would motivate people to take inordinate risks — instead, hire idealists that love the work because they would do it even if they weren’t paid.  That’s how I feel about investing; I just love the game, and wouldn’t want to do anything else.

Lesson 9: Macro matters.

Much as I admire Marty Whitman (and Peter Lynch), I am with Montier and Graham regarding the value of Macro.  Whitman, Pzena, Miller and some others rightfully got their heads handed to them when they neglected the key doctrine of value investing , which is “margin of safety.”  Most of my great mistakes have come from similar neglect.

Particularly when times are unusual, macro factors drive stocks.  But, how well can we predict that?  I’ve done okay over the years, but I am skeptical on being able to do that all of the time.

Lesson 10: Look for sources of cheap insurance.

Again, easy to say, hard to do.  I would like an infinite stream of patsies to soften the blow if I make bad decisions.  In the middle of the 2000s, I felt that shorting credit was nearly a free option, but will there always be bulls making stupid decisions during the bull phase of the market?

On second thought, yes, that should always be true, so where you find cheap insurance, like CDS 2003-2007, buy it.

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So, after all that, aside from point one, I agree with Montier almost entirely.  What a great article he wrote, and what a great article to stimulate the panel that I am on.

There is room for a new risk model based on the idea that risk is unique among individuals, and inversely related to the price paid for an asset.  If a risk control model has an asset becoming more risky when prices fall, it is wrong.

After doing my talk for the Society of Actuaries last Wednesday, I got inspired to write something about modern portfolio theory, the capital asset pricing model, the efficient markets hypothesis, etc.  This particular rule deals with two things:

• The same event can have different risk for different individuals.  Risk is unique to each individual.  It cannot be summarized by a single statistic for comparative purposes across individuals.
• In general, with a few exceptions, risk is inverse to price.  As the price gets higher, so does risk.  As the price gets lower, so does risk.  The major exception to this rule is when trends are underdiscounted, because estimates of intrinsic value are flawed.

Let’s deal with these issues one at a time.  Start with a simple question.  Why do academics want to have a single measure for risk?  It allows them to write papers, and it keeps the math simple.  That’s why we have concepts like beta and standard deviation of total return.  It’s why we have concepts like the Sharpe ratio and other ratios that purport to measure return versus risk.

If our total planning horizon was similar to the periods that these figures are calculated over, they might have some validity.  But most of the time are planning horizons are longer than the periods that these figures are calculated over.  Even worse, most of these statistics are not stable.  The value calculated today may likely have a statistically significant difference from the value calculated a year ago.

But what is worse still is the idea that by taking more risk you will get more return.  If anything, the empirical research that I’ve been reading, and the value investors that I have talked to, indicate that the less risk you take, the more you’ll make.  A good example of that would be Eric Falkenstein and his book Finding Alpha.  Minimum beta and minimum standard deviation portfolios tend to outperform the market.  Junk grade bonds tend to underperform investment-grade bonds.

If it hurts too much, don’t do what I’m about to say.  Think about Lenny Dykstra.  When he and I were writing at RealMoney.com at the same time, I would often ask him about what his method would be to control risk.  He never gave me a good answer; actually he never ever gave me an answer at all.

My concern was for small investors, dazzled by the celebrity, and the simple approach that he would take that seemingly yielded huge profits, would adopt the approach, and not know what to do when things went wrong.  For Dykstra, who seemingly had a lot of money, losing a little on a deep in the money call trade would not hurt him much.  But to an unfortunate average guy reading Dykstra’s work, a similar sized loss could be very painful.

That said, that greatest risk was in plain view, which Steve Smith, I, and a few others went after — Larry didn’t know what he was talking about.

Risk varies by differences in wealth; risk varies with age.  Risk varies with the level of fixed commitments you have in life.  To give you an example there, when I went to work for a hedge fund, the first thing I did was pay off my mortgage so that I would feel free to take big risks for the hedge fund.  It is far harder to take risk, the higher the level of fixed obligations that one must pay month after month.

To make it more practical, think of all the malarkey that has been spilled talking about “animal spirits.”  I don’t believe that businessmen are irrational; many Keynesian economists are irrational, but no, not businessmen.  Businessmen will not take risks when they are overleveraged, or, when a broad base of their customers is overleveraged.

Risk is unique to everyone’s individual situation.  Any time you hear someone bring up risk factors that are generic, you can either ignore them, or, more charitably think that they have a proxy that might have something to do with risk, maybe.

Go back to Buffett’s dictum: far better to have a bumpy 15% return than a smooth 12% return.

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The second part of the rule says that risk models should reflect higher risk as prices rise and lower risks as prices fall.  The implicit idea behind this is that it is possible to calculate the intrinsic value of an asset.  Can I disagree with one of my own rules?  Well, since I do the writing here, I guess I get to make up the rules about the rules.

There are many assets that it is difficult calculate the intrinsic value thereof.  Examples would include commodities, growth stocks, and anything that is highly volatile.

Though I believe my rule is correct most the time, markets are subject to momentum effects.  Often when a stock is at its 52-week high, that’s a good time to buy, because people are slow to react to changes in information.  And, when stock is falling hard, and is at a 52-week low, that is often a good time to not buy the stock, because there are maybe bits of information about the stock, or its holders, that you don’t know.

In general, though, higher prices are more likely to be overpayment and lower prices are more likely to indicate bargains.  Why?  Because returns on equity tend to mean revert.  Companies with poor returns on equity tend to find ways to improve business.  Companies with high returns on equity tend to find increased competition.

Thus, as always, I counsel caution.  Don’t ignore momentum, but also don’t ignore valuation.  Ask yourself how much upside there could reasonably be, and how much downside.  Play where the downside is limited relative to the upside, because the key to investing is margin of safety.  Play to win, yes, but even more, play to survive, so that you can play longer.

Why does the stock market pay so much attention to earnings estimates?  Don’t earnings estimates embody the worst type of analysis of stocks on Wall Street?

There is some truth to the thought above.  After all, earnings estimates eliminate all one-time charges.  Now, that makes sense in the short run, but not in the long run.  In the short run we want to estimate the growth in value of the business on a continuing basis.  Thus, we eliminate one-time events.  In the long run we must see how a management team has grown the total value of the Corporation.  To do that, we must factor in all of the one-time events as well as the regular earnings in order to see how they have managed Corporation over time.  Would that one-time events were really one-time events.  And, would that one-time events averaged out to zero.  But truth, one-time events are on average highly negative.  And so, companies with a lot of one-time events typically have lousy earnings quality, and deserve a lower price earnings multiple as a result.

So if there is that much trouble with how we measure earnings as far as earnings estimates go, why do we use earnings estimates?  Most of the value of a Corporation on a going concern basis stems from the future earnings of the company.  Investors want to have an estimate of forward earnings so that they can gauge whether the company is growing at an appropriate rate.

Now, it wouldn’t matter if the system were set up by third-party sell side analysts, by buyside analysts, by companies themselves, or by a combination thereof.  The thing is investors are forward-looking, and they want a forward-looking estimate to allow them to estimate whether the companies are doing well with their current earnings or not.

So long as the earnings estimates are relied on a fair measure of likely future earnings of the company, they become an influence on the current price stock.  For example:

• If earnings estimates rise rapidly, so will stock prices.
• If actual earnings comes in above estimates the stock price will have one-time rise.
• And vice versa for when estimates fall , and when actual earnings are less than the estimate.

Now if earnings estimates were done right, together with growth estimates, by angels did not men, they would serve as cornerstones for estimating the value of corporations.  But our ability to see the future even collectively is poor.  Many things happen that we do not expect, whether from the government or the central bank or wars, you name it.

But even with all those flaws, earnings estimates provided useful function in being a feedback mechanism so that the market knows how to react in general, when earnings are released.

New Problem

But when beating earnings estimates become the be all and end all of the corporate management, we run into trouble.  Knowing that the estimate drives the stock price, makes some corporations fuddle the accounting.  They adjust revenue recognition, they differ recognition of expenses, enter into useless mergers and acquisitions, etc. Most accounting chicanery problems would not exist if beating the earnings estimates was not so important.

So what do we as investors do?  We look at the release of actual earnings with skepticism.  We carefully consider the adjustment of net earnings to operating earnings and asked whether the adjustments are truly reasonable or not.  We also don’t give full credibility to earnings estimates as if they were a sure thing.  Further, we review revenue recognition policies, and all other means to easily adjust operating earnings so we are not deceived by corporate managements.

And, if I can be so radical, we begin ignoring earnings and focus on growth tangible book value per share.  We look at growth cash flow per share net of maintenance capital expenditure.  We do all we can estimate free cash flow, and yet, take a step back and ask how the free cash flow is being used.

Free cash flow is not valuable if it’s being used to buy back stock at a high multiple.  It’s not valuable if it’s being used to do a scale acquisition.  Both of these are forms of dilution to common shareholders.

The key question is this: is the management building the net worth per share of the company?  That’s a lot harder question asking if the current earnings beat the estimate, but if this were easy, they would’ve brought someone else in to do it, not you or me.

PS – I leave aside the issue of intangibles here.  Usually intangibles are worthless.  But some are quite valuable, like the name Coca-Cola, or distribution network that is not easily replicated, or research and development is unique to the Corporation has not yet developed into a product.  All that said, for an intangible to have value, it must produce additional cash flow in the cash flow statement under operations, that do not reflect in the earnings statement.

One side benefit of deciding to start up Aleph Investments, LLC, is that it is forcing me to write out articles on my rules.  When I was writing for RealMoney.com, I wrote a number of articles about my eight rules, but I only wrote about four out of the eight rules.

Before I write about rule number three this evening, I would like to bring you up to date on what I am doing with Aleph Investments, LLC.  This past week I incorporated the business, and in this coming week.  I will be registering as an investment advisor.  I will be managing equity money, on both a long only and hedged basis.  I have yet to choose a custodian and clearing broker, but I am working on this.  Given the state that I am domiciled in, Maryland, there may be delays but I suspect I’ll be up and running by late November or early December.

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Let me give you a little history of how the eight rules came to be.  In 2000, I had an e-mail discussion with Kenneth Fisher.  I explained to him what I had been doing with small-cap value, and how I had done well with it in the 90s.  He told me to forget everything that I’ve learned, especially the CFA syllabus, and look for the things that I can do better than anyone else.  We exchanged about five or so e-mails; I appreciate the time he spent on me.

So I sat back and thought about what investments had worked best for me in the past.  I noticed that when I got the call right on cyclical industries, the results were spectacular.  I also noticed that I lost most when investing in companies that didn’t have good balance sheets, no matter how “cheap” they were in terms of valuation.

I came to the conclusion that size and value/growth were not the major determinants of my investing success.  Instead, industry selection played a large role in what went right and wrong with my investment decisions.  So, I decided to formalize that.  I would rotate industries with a value bias.  But that would have other impacts on how I invested.  One of those impacts is rule number three.

I formalized the first seven of the rules in 2002, when the strategy was two years old and seemingly performing quite well.  I began doing what rule number eight states sometime in 2004, and reluctantly added it to the seven rules sometime in 2006.

With that, on to rule number three:

Stick with higher quality companies for a given industry.

There are three simple reasons for why rule number three works:

• First, companies with lower debt levels within a given industry tend to be more profitable than companies with higher debt levels that industry, contrary to what the Modigliani-Miller theorems state.
• Second, many investors, both retail and professional, have a bias toward what we might call “lottery ticket stocks.”  Many people swing for the fences in the stocks that they buy and accept high risks in order to achieve a high return.  On average, this strategy does not work.  In general, buying high beta, high volatility stocks is a recipe for disaster and buying low beta, low volatility stocks tends to earn money better than the market averages.
• Third, if you are rotating industries, there are two ways to do it.  These two ways are not mutually exclusive, you can have part of your portfolio in one strategy and part of your portfolio in the other.  Method one is to look for trends that are clearly going on, but that the market has not fully discounted.  In this case, one can buy companies with excellent or good balance sheets because the trend will carry you along.  Method two is to look for industries that are sick but not dead.  In that case, you only select companies with excellent balance sheets.  This is how it works: if the industry remains sick, weaker competitors will be destroyed, capacity will exit, and pricing power will return to the survivors.  If the industry’s pricing power suddenly improves, then all of the companies industry will do well.  The one with the excellent balance sheet will outperform the market as a whole.  That the ones with poor balance sheets do even better is not a concern.  The idea is to avoid losing money; don’t take the risk by buying the “lottery ticket stock.”

For what it is worth, this same idea not only works with stocks but it works with bonds as well.  If you read the book Finding Alpha, the author has an extensive discussion on why high quality bonds outperform low-quality bonds over the long haul.  In general, corporate bond investors underestimate the costs of default risk.  BBB bonds do best, followed by AAA bonds, and then other investment grade bonds.  After that, the lower the rating of the bond the worse they do.

The same is true of stocks, which is why it pays to look at where the market is in its liquidity cycle.  In November of 2008 through March of 2009, it made a lot of sense to buy junk bonds, and I did so for my church building fund.  Though I didn’t say it at the time and did not act on it, it was also in hindsight the right time to buy junk stocks.  Oh well, that’s water under the bridge.  I tend not to take the risk of buying junk stocks because I don’t want to lose money.  I did well enough by adding to more cyclical names that had strong balance sheets.

Two notes before I close: first, industries tend to have preferred habitats.  In other words, typically the difference between the company with the best balance sheet the industry and the company with the worst balance sheet industry is not all that great.  Why is that?  If you’re in the same industry, typically you have similar levels of fixed costs versus variable costs, and you face the same levels of variability in sales.  These two factors together will lead an industry to a preferred level of financial leverage.  But even though the difference might not be that much between the company with the best balance sheet and the worst balance sheet within the industry, when pricing power is weak that small difference is significant.

Second, I am a proponent of “good enough” investing.  What I am saying here is that it is very difficult to achieve optimal results, and that if you try too hard to achieve optimal results, it is likely that you will do worse than good enough results.  The demands of perfection kill.  Size your goals to what is humanly possible.  My methods allow me to sleep at night.  My methods allow me to step away from my computer, and spend time analyzing what really might matter.  I can go visit clients and not worry that something is going to blow up on me.

This is not laziness on my part.  It is my view that most investors can do well enough in investing at low to moderate levels of risk.  But at high levels of risk, you have to get too many things right too much of the time in order to succeed.

That’s all for now.  Back next week when I write about rule number four.

A little bit ago, I published Twenty Questions for the Author of Risk and the Smart Investor.  Well, David X. Martin got back to me, and here are his thoughtful answers.  I will have more commentary on this as I write the book review, which I am doing immediately after posting this.

1. Q: Imagine you are talking to a bright 12-year old girl.  How would you explain to her why and how the financial crisis happened?

A: Think of what happens when you blow up a balloon. First it expands, but eventually, if you continue to add more and more air, it bursts. The air going into the balloon in the years leading up to the recent financial crisis was either ‘borrowed’ air, that is air that was bought on credit, or air that was highly leveraged. In other words, only a small part of the air was paid for, and the rest was borrowed. And when the balloon burst most of those that had borrowed air, or had lent air to others, were left with nothing.

2. Q: I was fascinated with the structure of your book, which I found tedious and hokey at first, but I grew to like it.  The way I see it, you introduce the topic through your experience, then explain the theory, then show neglect of it led to failure, and then you give us the stories of Max and Rob.  How did you hit upon this intriguing and novel way to write your book?

A: I first thought about the decision process, and described the continuous process of risk management in relatively simple steps—i.e., assessment (know where you are and what you do not know); rules of the game (know your risk appetite, transparency, diversification, checks and balances); decision-making (alternatives, responsibilities, reputation and time frame); and finally, reevaluation (monitor and learn from your mistakes ). My goal was not to write a “how to book” but rather to help readers build frameworks to make good decisions, and it seemed it would be helpful, and entertaining, I hoped, to see the process in action through the fictional risk story.

3. Q: Why do you suppose so few people in risk management, and senior management at major financial firms, were unwilling to consider alternative views of the sustainability of the risks being taken as the risks got larger and larger relative to the equity of individual companies, the industry as a whole, and the economy as a whole?

A: People get lulled into seeing the world from a particular viewpoint, particularly if they have never been through the worse case scenario. I’ve been through many of them.

4. Q: As a risk manager, bosses would sometimes get frustrated with me when they wanted a simple answer to a complex question that had significant riskiness. They did not like answers like, “I don’t know, it could have six significant effects on our company.”  How can we convey the limits of our knowledge in a way that management can get the true uncertainty and riskiness of the environment that we work in?  How can we get management to consider scenarios that are reasonable, and could harm the company, but few others in similar situations are testing for?

A: Scenarios are a great way of thinking about the future in terms of the realm of possible outcomes. Thinking now about what you can/should be doing about those possible outcomes, is an excellent way to communicate risk potential to management. and engage their interest.

5. Q: In your experience, how good are the managements of financial companies at establishing their risk tolerances?  Better, how good are they at enforcing those limits, such that they are never exceeded?

A: Not very good. Businesses have strategies, strategies entail risks, and risks require capital. Very few companies take a holistic view of risk, capital, and strategy.

6. Q: How do you create a transparent risk culture in a firm?  How do you get resisters to go along, even if it is management that does not see the full importance of the concept?

A: Cultures do not change rapidly, they migrate. Transparency starts at the top and it will never spread through a company if management doesn’t recognize its importance, and communicate its importance to everyone in the firm.

7. Q: Are most cases where a person or a company fails to diversify intentional or unintentional?  Do we put too many eggs in one basket more out of ignorance or greed?

A: Diversification is a strategy that requires discipline. Take the case where you start with a diversified portfolio, and then one position takes off and acquires a disproportionate weight in your portfolio. Regardless whether the cause is ignorance (you did not monitor your portfolio’s balance) or greed (you rode the stock up ), the root problem is a lack of discipline.

8. Q: Why do you suppose that checks and balances for risk management are not built into the cultures of many financial companies?

A: When does a problem exist? Even if it has always been there, it comes into existence only when you recognize that it is a problem. Many times checks and balances do not exist because no one recognizes the risk/problem and therefore no one evaluates the checks, and balances, and controls needed to manage it.

9. Q: I have a friend Pat Lewis who developed a risk management system for Bear that could have prevented the failure of the firm, but it was ignored because it got in the way of profit center manager goals.  Was it the same for you at Citigroup when your “Windows on Risk” got tossed out the window?

A: See pages 124-5 in my book. You never have to ask a portfolio manager what he or she thinks, just look at their portfolio. When I found out Citibank was no longer using Windows on Risk I sold my entire position that day. I recall it was at $51.75.

10. Q: Can culture and personal judgment work in risk management ever?  Take Berkshire Hathaway – risk control is embedded in the characters of a few people, notably Warren Buffett and Charlie Munger. If the culture is really, really good, and it comes from the top, can risk management work when it is seemingly informal?  (Remember, you don’t want to disappoint Warren.)

A: Risk management is all about culture and personal judgment. I remember pondering the question, “How high is up” at a Windows on Risk meeting at Citibank. The most senior management were sitting around the table. We came to our answer by asking the following question: What was the amount of loss we would be embarrassed to read about in the WSJ? That number, it turned out, was not very high, at least in the judgment of the people sitting around that table. News of that decision got around and had an impact on the company culture.

11. Q: How can you teach younger people in risk management intuition about risk that helps them have a healthy skepticism for the results of impressive complex modeling?

A: I co-wrote an article with Mike Powers from the London School of Economics titled “The End of Enterprise Risk Management.” Models are just one input; they are not a substitute for good judgment.

12. Q: Is it possible to do effective risk management in a financial firm if management is less than wholeheartedly committed to the goal?

A: I forgot where I first heard the expression, but it explains my feelings. “A fish starts to stink from its head first.”

13. Q: Aside from AIG, and other financial insurers, the insurance industry came through the crisis better than the banks because they focused on longer-term stress tests, and not on short-term measures like VAR.  Should the banking industry imitate the insurance industry, and focus on longer-term measures of risk, or continue to rely on VAR?

A: VaR is one measure. It has deficiencies. For example, the loss amounts predicted in the tails (that is, the extreme cases) are the best case scenarios, not the worse case. Institutionalizing this one measure, or relying on the measurement of “risk based capital,” has not worked.

14. Q: Seemingly the big complex banks did not analyze their liquidity risk, particularly with repo lines.  Why did they miss such an obvious area of risk management?

A: Liquidity is a very difficult concept. If you decide to sell your house in the suburbs at 2AM in the morning and put a “for sale” sign on your lawn at that hour, how quickly do you think it will sell. Liquidity, therefore, has to be thought of in terms of time. If, for instance, you see high average daily volume in a stock what is your real liquidity if the volume is the result of a nano second of high speed trading?.

15. Q: How much can risk management be shaped in financial firms by the compensation incentives that employees and managers receive?

I saw Walter Wriston six months before he died. He asked me how things were going. I said, nothing wrong with risk as long as you manage it. He smiled at me from ear to ear because those were his words, from his book Risk and other Four Letter Words. I think it is all about matching responsibility and authority, having the right culture, learning from errors, and promoting ethics. Incentives are on the list, but not at the top.

16. Q: I have often turned down shady deals in business, saying that you only get one reputation in this world.  How do you encourage an attitude like this in financial firms among staff?

A: If you go to sleep in s–t, you will most likely wake up covered with flies. I would start with an ethics committee, and make sure the most important people in the firm were on it.

17. Q: A lot of portfolio management and risk management is juggling different time frames.  Is there a good structure for balancing the demands of the short-, intermediate-, and long-terms?

A: A poor investment decision is still the same poor investment decision irrespective of the time frame. If you always try to do the right thing, time frames become less important.

I am not saying to forget about the timeframe, just that you shouldn’t let it lead you to a poor decision.

18. Q: Most developed country economic players assume that wars will have no impact on their portfolios.  Same for famine, plague, or environmental degradation.  What can you do to get investors to think about the broader risks that could materially harm their well-being?

A: Great question, but this one is outside my realm of expertise.

19. Q: Are Rob’s more common in the world than Max’s? That’s my experience; what do you think?

A: I purposely made Rob and Max pretty different in order to illustrate the principles in the book. I think we are all human and have a little bit of each.

20. Q: At the end of your book, one of your friends dies.  Did you mean to teach us that even if we manage our risks right, we still can’t overcome problems beyond our scope, or were you trying to say something else, like creating a system or family that can perform well after you die?

A: My first draft of the book began with what is now the concluding chapter—the one in which I discuss the courage necessary to face death. The developmental editor at McGraw-Hill, of course, didn’t like it up front, so I moved it to the end, where I wrote: “It is at that moment, when death is imminent, and there is no possibility of escape, that courage comes into the picture.”

My view is that this mindset can be useful long before we consider our mortality, by helping us understand that there are realities that must be faced and not avoided. In investing as in life, long term success results from thoughtful, timely preparation. Or in other words, the best decisions are made before we are forced to make them. The best decisions are made before certain inevitabilities, so long on the horizon, appear unexpectedly in front of us, and we no longer have the time to consider the alternatives; when we can still calmly and intelligently assess our circumstances, consider alternatives, and make informed decisions, monitoring the results as we go.

This is what I refer to as “de-risking,” and although the principles set out here are drawn from my experience as a risk manager at a number of leading investment firms, they apply not only to financial matters, but to almost every decision you’ll make over the course of your life.

So to my way of thinking,  when lightning strikes–the processes that you have put in place make courage less necessary. Put another way, if you embrace risk by following an orderly process you will have constructed a framework that will help you make the right decisions

Recently I got an e-mail from my friend Kid Dynamite.  He asked me an interesting question about pensions and long-duration bonds:

“back to the concept of century bonds.  I’m not sure if you read my recent pension post (http://fridayinvegas.blogspot.com/2010/09/problem-with-pensions.html) , but I’m having trouble with the concept of pensions investing in 100 year bonds at 6% while using an 8% portfolio return assumption. Does not compute…(and you can even pretend that pensions have 100 year obligations)

I just don’t get the concept of locking in long duration returns below your long term bogey. That just means that you have to do even better on the balance of your portfolio…which is nice to pretend about, but in reality, if you can do better on the balance, why bother with the 6% fixed income??”

It’s a great question and one that deserves more thought.  To do that, we have to separate the accounting from the economics.

When I was a young actuary, I was preparing to take the old Society of Actuaries test eight, which was the Investments exam.  An older British actuary made a comment in one of the study notes that I had to think about several times before I understood it: “Risk premiums must be taken as earned, and never capitalized.”

Sadly, the pension profession never got the memo on that idea.  The setting of investment assumptions accepts as a rule that risk margins will be earned without fail.  Therefore, when looking at a portfolio of common stocks in a pension trust, the actuary will assume that the equity premium will be earned over the long haul and build that into his discount rate assumptions and earned rate assumptions.  The same is true of bonds in the pension trust.  They may haircut the yield for potential default losses, but they will assume that much of the spread over Treasuries will be earned without fail and thus they capitalize the excess returns.

Let’s pretend that the 6% century bond that Kid Dynamite told me about is risk free.  Also, let’s pretend that the pension actually needs bonds as long as a century bond.  Defined benefit pension plans, if trying to match cash flows, need bonds longer than 30 years, but probably don’t need bonds longer than 75 years.  That said, given the lack of bonds that are longer than 30 years, a century bond will still prove useful in trying to immunize the tail cash flows of the defined benefit pension plan.

What that 6% century bond tells us is that the investment return assumption on an economic basis is too high.  And, given that the yields on safe debt shorter than a century is much less than 6%, it probably means that the investment earnings assumption rate is way too high at 8%, and should definitely be lower than 6%.

I know that’s not what GAAP accounting requires.  GAAP accounting allows you to choose whatever investment earnings rate you can justify using statistics.  That’s not the way GAAP accounting should work though.  GAAP accounting should work with discount rates derived from low risk fixed income securities, and use those to develop the investment earnings assumption.

If you earn more than the risk free investment earnings assumption, good.  Those excess earnings will reduce the pension plan deficit or increase its surplus.

Okay, then suppose we reset the investment earnings assumption at 4%, because that’s closer to where it should be economically.  My, what large pension deficits we see.  But now, all of a sudden, that 6% century bond looks pretty good, because it brings the cash flows of the plan into better balance, and earns a decent return in excess of the earnings assumption.

So, the problem isn’t with the century bond, it’s with the earnings assumption.  Now why does that earnings assumption exist?

• The US government wanted to encourage the creation of defined benefit pension plans, and so informally encouraged loose standards with respect to the earnings assumption.
• For years, it worked well, while we had bull markets going on, and interest rates were high, which decreased the value of the pension liabilities.
• The IRS took actions to prevent defined benefit plans from building up large surpluses, because it decreased their tax take.  Had companies been allowed to build up large surpluses, we wouldn’t be in the mess that we’re in today.
• There is the lazy acceptance of long-term historical figures in setting earnings assumptions, instead of building them from the ground up using a low risk yield curve, and conservative assumptions on how much risky assets can earn over the low risk yield curve.

So in an environment like this, where interest rates are low, and surpluses could not be built up in the past, pension funds are hurting.  The truth is, they are worse off than their stated deficits imply.  For economic and political reasons, the likely outcome resembles the riddle of how one eats an elephant: one bite at a time.

So we will see investment earnings assumptions and discount rates fall slowly, far too slowly to be the economic truth, but slowly recognizing funding gaps as corporations eat the loss one bite at a time, as they can afford to.

The investing implication is this: for any stock you own that sponsors the defined benefit pension plan, take a look at the earnings assumption and raise the value of the liabilities.  Also recognize that earnings will be lower than expected if the deficit is large and they need to make cash contributions in order to fund the pension plan.  That said, they could terminate the plan, and I suspect many current defined benefit plan sponsors will do so.

And given that, there is one more implication: if you are employed by, or are a beneficiary of a defined benefit pension plan, take a look at the form 5500, or at the company’s financial statements and look at the size of the deficit.  Take a look at what the PBGC will guarantee for you, and adjust your plans so that you are not relying on the continued well-being of the defined benefit pension plan.

I wish I could be the bearer of better news than this, but it is better to be aware of problems, then to learn that what you don’t know can hurt you.

1) Start with the big one from yesterday.  On of my favorite monetary heretics, Raghuram Rajan, whose excellent book I reviewed, Fault Lines, pointed out how he had gotten it right prior to the crisis, versus many at the Fed who blew it badly.  Rajan suggests that Fed Funds should be at 2-2.25%, which to me would be a neutral level for Fed Funds.  That’s a reasonable level.  The economy needs to work its way out of this crisis, even if it mean failures of enterprises relying on a low short rate.  Entities that can’t survive low positive rates that give savers something to chew on should die.  Mercilessly.  Monetary policy at present is a glorified form of stealing from savers, who deserve more for their sacrifice.

2) Peter Eavis, an old friend, echoes my points on QE, in his piece Government Clouds Value of Investments.  When the government is actively trying to destroy the willingness to hold short-term assets, and engages in QE, it makes all rational calculations on investments a farce.

3) I agree with John Hussman in a limited way.  QE artificially lowers interest rates, which lowers the forward value of the US Dollar.  That doesn’t mean it will generate a collapse; I don’t think it could do that unless the Fed began to do astounding things, like monetize a large fraction of all debt claims.

4) The US Government is so dysfunctional that the baseline budget has increased 4.4 Trillion over the next 10 years.  This is the beginning of the end of the supercycle, and the reduction of America to the influence level of Brazil.  Earnings levels will converge as well, but more slowly.

5) While we are thinking soggy, think of Japan.  Years of fiscal and monetary stimulus have availed little.  Overly low interest rates have fostered an economy satisfied  with low ROEs.  Low interest rates coddle laziness, and encourage stagnation.

6) There are limits to stimulus, whether monetary or fiscal.  There is no magic way to produce prosperity by government fiat.  Stimulus, by its nature, will run into constraints of default or inflation, if taken far enough.  If not, why doesn’t the Fed buy up all debt?  (leaving aside laws) Isn’t QE a free lunch?

7) Deflation is tough; it weighs upon cities, states and other municipalities, who hide their true obligations.

8 ) Hoisington, the best unknown bond manager.  Where do they think long rates are going?  2% or so on the 30-year.  Makes the current buyers of bond funds look like pikers.  That’s over a 35% gain from here.  If they are right, their fame will be legendary.  Now, that could explain the willingness to fund ultra-long duration debt, because the gains will be bigger still.  What a great confusing time to be a bond investor, until something fails.

9) Or consider the Norfolk Southern 100-year bond deal yesterday.  Quoting the WSJ:

In what bankers hope will be the first in a new round of 100-year bond sales, Norfolk Southern Corp. raised $250 million Monday by selling debt that it won’t have to repay until the next century.

—

Investor interest was strong enough that the company increased the size of the new sale from $100 million. Market participants said investors had expressed an interest in buying at least $75 million of the debt before the company decided to announce the $100 million deal.

—

The interest rate on Norfolk Southern’s new debt is 6% for a yield of 5.95%, about 0.90 percentage points more than where the company’s outstanding 30 year debt was trading Monday. It was the lowest yield for 100-year debt bankers could recall, breaking through the 6% yield on the company’s 100-year issue in 2005.

—

“There is no question, obviously, that you are giving up a bit of liquidity, but you’re getting a pickup of 90 basis points to move out of the 30-year,” said Jeff Coil, senior portfolio manager at Legal & General Investment Management America. “But you’re getting good income on a stable cash credit in a sector where there are only a handful of rails left.”

Mr. Coil said the firm had a “sizeable” order in the deal. There were approximately 20 investors overall.

Moody’s Investors Service rated the new senior fixed-rate bonds Baa1, and both Standard & Poor’s and Fitch Ratings rated them BBB+.

Is 0.90%/year enough to compensate from going from 30 to 100 years?  I think so. The difference in interest rate sensitivity of a 30 versus a 100 are small at a yield of 5-6%, and if you have a liability structure that can handle it, as a life insurer might, it makes a lot of sense.  After all, a life insurer can’t economically invest in equities because of capital restrictions. You could compare it to investing in long dated preferred stock or junior debt, but then if there is a default, the losses are more severe than with a senior unsecured bond.

10) I’ve never found the yield curve model for recession/recovery compelling.  Limited data set, not covering the Great Depression, etc.

More to come.

Illiquidity is an underrated risk.  Most financial company failures are due to illiquidity, which usually takes the form of too many illiquid assets and liquid liabilities.  Adding to the difficulty is that it is generally difficult to price illiquid assets, because they don’t trade often.

So where do we see failures due to illiquidity?

• Banks — too numerous to mention, though FDIC insurance restrains it now.
• Life insurers, particularly those that write a lot of deferred annuities.
• AIG and the GSEs — abominations all.
• Bear and Lehman — waiving the leverage limit was one of the stupidest regulatory decisions ever.
• Hedge funds – LTCM was the granddaddy of failures, but many have choked because redemptions forced liquidation of assets at unfavorable prices.
• No colleges, though those college that were too aggressive on illiquid assets got whupped in 2008.  Some were forced to raise liquidity in costly ways.  Same for many overly aggressive pension plans, many of whom came late to the game with Venture Capital, Hedge Funds, Timber, Commodities, etc.

Face it.  Most alternative asset classes involve additional illiquidity.  That is an additional risk, and when evaluating those investments, the expected rate of return must be greater than that for liquid investments.

As an aside, there is another factor to be considered with alternative investments.  That factor is strategy capacity.  Alternative investments do best when they are new.  Here is my version of the phases that they go through:

• New — few know about it except some business-minded investors.  Only the best deals get done.
• Growing — a modest number know about it, and a tiny number of consultants.  Only very good deals get done.
• Comes of age — many know about it, and most consultants pitch it to their clients as the way to go.  Good deals get done.
• Maturity — almost everyone knows about it, and it is a standard aspect of asset allocation for consultants, who have their means of differentiating between different providers, based on metrics that will later be revealed to be useless.  All reasonable deals get done.
• Post-maturity — Late bloomers make it to the party, and beg to get in, thinking that past is prologue, and do not realize that deal quality has eroded severely.
• Failure, which brings maturity — deals fail, leading the market to scrutinize all investments, leading to true risk-based pricing.  Later adopters abandon the market, and take losses.  Earlier adopters sharpen practices, and prepare for a more normal asset class.

So, when looking at illiquid assets, how do you determine how much to invest?  First determine how much of your funding base will never leave over the next 10 years.  When I was a corporate bond manager, that was 25% of the assets that I was managing, because of structured settlements and immediate annuities.

For a pension plan or endowment, forecast needed withdrawals over the next ten years, and calculate the present value at a conservative discount rate, no higher than 1% above the ten-year Treasury yield.  Invest that much in short to intermediate bond investments.  You can invest the rest in illiquid assets, because most illiquid assets become liquid over ten years.

But after that, there is an additional way of controlling illiquidity risk — time once again for the fusion solution! Money market funds run a ladder of maturities.  Stable value funds run a longer ladder, as should commodity ETFs, rather than floating at spot.  Then there are clever advisers who run municipal and other bond ladders for wealthy and semi-wealthy clients.  Running a ladder of maturities is one of the most robust management techniques as far as interest rate risk is concerned.  There is always money coming out and in every year, which slowly leads the portfolio yield in the direction of average rates.

Now, if these bonds are less liquid muni bonds, but the credit risk is low, you don’t care as much about the illiquidity, because the ladder produces its own liquidity as bonds mature.  The key question is sizing the length of the ladder, which comes down to a question of analyzing the liquidity/income needs of the client, combined with a forecast on the secular direction of rates.  The forecast is the least important item, because it is the toughest to get right.  (An aside: who has been right on bond yields consistently for the last 20+ years?  Hoisington, my favorite deflationists.  Wish I had listened more closely.)

The same principle applies to pension funds, endowments, life insurers with a few twists.  Divide your liabilities in two.  What obligations do you know cannot be changed, except at your discretion?  That group of liabilities can have illiquid assets to fund them.  Try to match the payout streams, but if not, try to match them in broad with a ladder, keeping in mind what mismatches you will likely face over the next 1-2 years in order to properly size your cash position.

The rest of the liabilities need more intensive modeling, analyzing what could make them change.  You can try to buy assets that change along with the liabilities, but in practice that is hard to do.  (That said, there are no end of clever derivative instruments available to solve the problem in theory.  Caveat emptor.)  The assets have to be liquid for this portfolio.  Other aspects of portfolio choice will depend on valuation parameters, credit spreads, yield curve shape, market volatilities, as well as macroeconomic factors.

Three Closing Notes

1) Now, all that said, just because you can take on illiquidity doesn’t mean that you should.  A good manager has a feel from history for what the proper liquidity give up is in valuations for stocks and other risk assets, and credit spreads for fixed income assets of all sorts.

Was it worth moving from the:

• Relatively liquid AAA tranche to the illiquid AA, A or BBB tranche for 0.10%, 0.20%, 0.40%/year respectively?  As a bond manager at much larger insurance company said back in 2000 — “It’s free money.”  (That is almost always a dangerous phrase.) My view was there was more illiquidity and credit risk than we could consider.
• Relatively liquid large-issue BBB bank bond to the relatively illiquid small-issue BBB bank bond for 1% more in yield?  Hard to say.  There are a lot of factors involved here, and your credit analyst will have to be at the top of his game.  It also depends on where you are in the speculation cycle.
• Liquid public equities to private equity or hedge funds with lockups?  Tough question.  Try to figure out what the unlevered returns are for comparative purposes.  Analyze long-term competitive advantage.  Look at current deal quality and valuation metrics.  For hedge funds, look at how credit spreads moved over their performance horizon.  Anyone can make money when spreads are tightening, but who makes money when spreads are blowing out?  Analyze them over a full credit cycle.

2) Institutions that did not previously do more liquidity analysis because we had been in near-boom conditions for decades need to at least do scenario testing to assure that they aren’t overplaying their hands, such that they might be forced to make bad decisions if liquidity gets tight.  Safety first.  (This applies to governments and industrial corporations too, as we will experience over the next three years.)

3) Finally, if you decide to make a large illiquid purchase like Mr. Buffett did last year, make triple-sure of your logic and your liquidity positioning.  Nothing lives forever, but you can prolong the life of the institutions you serve by careful reasoning and planning, particularly regarding liquidity.  Get financing when you can, not when you need it. It takes humility to do so, but it yields the quiet reward of continued existence at a modest price.

These three book reviews are for books that I scanned, and did not read in depth.

Quantitative Equity Investing

The first book: Quantitative Equity Investing, is a book for practitioners with strong math skills, not average investors.  It reviews basic econometrics and factor analysis, and then applies these tools in an effort to sort out anomalies in investment markets, tease out important factors driving markets, and find workable trading strategies, considering execution costs, slippage, etc.  It has a brief section on algorithmic and high frequency trading.

On the whole, I didn’t find anything that new or amazing in the book.  Though there were a few things in the book that I hadn’t seen before, they were trivial things that I looked at and said, “Oh, yeah, of course.”

The book is generic in the way that it deals with the topic.  It is no going to give you ideas to pursue, but only tools that you can use if you have ideas tht you want to analyze, and turn into strategies.

Who would benefit from this book?

You have to have a very strong math background, including the type of Matrix Algebra that one would use in graduate-level Econometrics.  To that end, this book would be most useful to grad students wanting an introduction to how to apply their math skills to the markets.

The book is available here: Quantitative Equity Investing: Techniques and Strategies (The Frank J. Fabozzi Series)

The New Science of Asset Allocation

This book uses Modern Portfolio Theory in order to analyze asset allocation decisions.  Those that have read me for a while know that I think that is a flawed paradigm, in need of replacement.  For those that want a reasonable understanding of that paradigm in a short space, the book does that very well.

That said, the book has its virtues.  The chapter on the “Myths of Asset Allocation” shows that the authors have some depth of insight into the foibles and misunderstandings that surround asset allocation.  The book also goes into the importance of qualitative analysis of managers, looking up from the numbers so that you can avoid allocating money to the next Madoff.  It also describes the use of derivatives in order to control risk exposures.

Each chapter ends with a short summary of the takeaways from the chapter, which serves to reinforce the points of the book.

Though the book has the word “new” in the title, I did not find much new in it.  If one is looking for novel implementation methods for asset allocation, best to look elsewhere.

Who would benefit from this book?

This is not a book for average investors.  It is for professionals who want to brush up their asset allocation skills, and young professionals wanting insight into asset allocation.

The book is available here: The New Science of Asset Allocation: Risk Management in a Multi-Asset World (Wiley Finance)

The Economics of Food: How Feeding and Fueling the Planet Affects Food Prices

To me, this was the most interesting book of the three, but I feel it was mistitled.  A better title would have been: “Fueled: The Effects of  Using Food for Fuel” or something like that, because the central question of the book is to what degree has using crops to produce biomass for fuel production (usually ethanol) affected the costs of food and fuel.

I found the book is very even-handed, to a fault.  It argues that the use of crops for fuel production had little impact on food costs, and that there were many other factors that made food prices rise when ethanol production was going gangbusters.  Weather, domestic and foreign demand and many other factors had a role in moving food prices, not just ethanol.

After reviewing the book, I have a better sense of the complexity of the question, and that it will not admit easy answers.

Who would benefit from this book?

Anyone who wants a basic understanding of food economics, and how that is impacted by a wide number of factors including using crops for the production of fuel would benefit from this book.  The book is well written, and seemingly balanced.

The book is available here: The Economics of Food: How Feeding and Fueling the Planet Affects Food Prices

Full disclosure: The publishers sent me copies of these books, hoping that I would review them.  I review about 80% of the books that get sent to me.

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