More Than You Know

Mauboussin, M. J. (2007) More Than you Know: Finding Financial Wisdom in Unconventinal Places. New York: Columbia University Press

More than You Know

MT1:  Chapter 1

MT2:  Investing:  Profession or Business

MT3:  Babe Ruth Effect

MT4:  Circumstance Based Categorization.

MT5: Risky Business

MT6:  Experts and Markets

MT8:  Time is on My Side.

MT9:  No notes: Intro to Part II

MT10:  Linking Stresses to Suboptimal Portfolio Management

MT11:  Tupperware Parties

MT12:  Emotion and Intuition in Decision Making

MT13:  Role of Imitation in Markets

MT14:  Misuse of Behavioral Finance

MT15:  Long Term Expectations.

MT16:  Naturalistic Decision Making

MT17:  Weighting Information

MT18:  Innovation

MT19:  Boom and Bust, Staying Ahead of the Curve

MT20:  Impact of Accelerating Industry Change

MT21:  How to balance with the short term.

MT22:  Fitness Landscapes

MT23:  Folly of using Average P/Es

MT24:  Mean Reversion and Turnarounds

MT25:  Cooperation and Competition Through Game Theory

MT26:  On the Limits of Corporate Growth

MT27:  Thoughts on Organization for investing Success

MT28:  Wisdom and Whims of the Collective.

MT29:  Using the Collective to Find, Solve and Predict

MT30:  Discussion of Fractals and End Notes

MT1: Chapter 1

Thoughtful or poorly thought decisions can be successful or lead to failure.  However, over time, thoughtful decisions will emerge with better outcomes.  Better decisions emerge when we focus on how we made the decision, rather than evaluating the outcome.

We tend to assume good outcomes are the result of good decisions, and bad outcomes are the result of bad decisions.  Best long term performers in any probabilistic fields emphasize process over outcomes.  Over time, process dominates outcomes.

The goal of the investment process;

1.      Identify gaps between price and expected value.

2.     Expected value is the weighted average value for a distribution of possible outcomes.

3.     You calculate it my multiplying the payoff (stock price) for an outcome by the probability that the outcome materializes.

Goal:  To distinguish between the knowledge of a company’s fundamentals and the expectations implied by the market price.

Its not so much which horse will win, but which horse is offering odds that exceed their actual changes of winning.  Only the odds are in view, there is no liking a horse to win, only an attractive discrepancy between his chances and his price.

The idea is to get the positive expected value on your side.

Principles for decision making:

1.      The only certainty is there is no certainty.  Investors need to train themselves to consider a sufficiently wide range of outcomes.  Pay attention and prepare for inevitable surprises.

2.     Decisions are a matter of weighing probabilities.  Note:  Author indicates roughly 90% of option positions loose money.

3.     Despite uncertainty we must act.  Many decisions are made on imperfect or incomplete information.  More information does no necessarily mean someone will make better decisions.  However, their confidence in their decision will rise.

4.     Judge decisions not only on results, but also on how they were made.

Suggests focusing on expected values.  Value consisting of possible upside and downside in conjunction with risk.

Forming a range forces one to get past predictions on a scenario into forming possible scenarios.  Also mitigates the anchoring bias.  Can also remove the analyst from the confirmation tendency.  Also, by forecasting potential downsides, you know you’ll occasionally take a hit.  It allows you to be periodically wrong, without the stigma of failure.

The way decisions are evaluated affects the way decisions are made.

MT2:  investing: Profession or Business.

S&P 500 is used as a benchmark for how well money managers do.  The committee uses the following criteria for selecting index candidates.

1.      Liquidity:  Selecting stocks with sufficient liquidity (monthly trading volume divided by shares outstanding) and float.

2.     Fundamental analysis:  Four quarters of positive net income on an operating basis.

3.     Market Capitalization:  Must have excess of $4 Billion.

4.     Sector Representation:  Tries to weigh each sector in line with the sector’s weightings of the universe (of companies exceeding 4 billion).

5.     Lack of Representation:  If the index were created today, this company would not be included because it fails to meet one or more of the above criteria.

Also, the committee:

1.      Does no macroeconomic forecasting.

2.     Invests long term with low portfolio turnover.

3.     Unconstrained by sector or industry limitations, position weightings, investment style parameters or performance pressures.

4.     The fund tracks the S&P 500 at very low costs.

Common traits of money managers that beat the S&P 500 include:

1.      Portfolio Turnover:  This group had a turnover rate of 35%.  89% is average for all funds.  7% is average for S&P 500.

2.     Portfolio concentration:  Tend to have 35% of assets in top ten holdings.  20% is average for S&P 500.

3.     Geographic Location:  Only small fraction are based in New York.

In summary, they tend to:

1.     Limited turnover.

2.     Spend limited time on macro forecasting.

3.     Hold higher concentrations of stocks.

4.     Sharp focus on price to value discrepancies.

Important to note that their success isn’t necessarily due to what they hold as much as how they make their decisions.

Author makes the distinction between profession and business.  Profession is building successful strategies, while business of investing relies on making money for the business at the expense of the profession.

The business of investing is growing rapidly.  People tend to chase returns which increase the cost to portfolios.

MT3:  Babe Ruth Effect

The frequency of correctness does not matter, the magnitude of the correction is what matters.

Back to Kahneman and Loss Aversion:  People like to be right….frequently.  Being right frequently doesn’t necessarily work with portfolio management.

Percentage change doesn’t determine how well the portfolio is doing, but the dollar change does.  Must constantly look at expected value.  A 70% chance of going up 1% does not compete with a 30% chance of loosing 1%.  Probability times outcome.

Investors tend to sell stocks too early, because they want to be right, and hold losers because they don’t want to be wrong.  Smarts and talent are great, but rationality gets you the most.

Long term success in probabilistic fields have some common traits:

1.      Focus:  The gambler focuses on one game, not on all the games.

2.     Lots of Situations:  They evaluate lots of examples. (Large sample size)

3.     Limited Opportunities:  Odds favor you less than 10% of the time.

4.     Ante:  In a casino you must pay to play.  With investing, you only pay when you want to or when the environment appears favorable.

Focus not on the frequency of correctness, but the magnitude of correctness.

MT4:  Circumstance Based Categorization

Three steps of Theory Building:

1.      Describe what you want to understand in words and numbers.  Observe, describe and measure phenomena.

2.     Classify the phenomena into categories based on similarities.  For investing, value, growth, high risk etc….are examples.

3.     Build a theory that explains the behavior.  Behavior of cause and effect.

After a theory is produced it can be used for predictions.  Anomalies may arise which causes researchers to reevaluate their theory.  Proper theory requires cycles.  The theory must be falseable.

Revisit of importance to actively look for ways to fail a theory rather than to seek confirmation.

Circumstance based categories tells us what to do in different situations.  Attributes based categories prescribe action based on the attributes of the phenomena.

Basing a decision on low P/E’s is an example of acting on attribute based category.  Probably not good to use only one attribute for investment decisios.

All investors use theory, either intentionally or unintentionally.  Building a sound theory requires context.  Point; Investors cling to attributes when markets turn and wring their hands when the market doesn’t perform the way they think it should.  A form of cognitive dissonance followed by the predictable responses while experiencing it.

MT5:  Risky Business

Risk:  Outcomes are unknown, but distributions are known.  Implies the possibility of harm or loss.

Uncertainty:  Outcomes and distributions are unknown.  Not known or established.  Uncertainty doesn’t imply losses only.

Point:  Try to change uncertainty to risk.  The range may be wide and unruly, but you will have an honest assessment of risk.

Investment is fundamentally an exercise in probability.  The process is translating investment opportunities into probabilities.  So, we need to think carefully about how we come up with probabilities and where the potential pitfalls lie.

Three ways to establish probabilities:

1.      Degree of Belief:  Subjective probabilities and are the most liberal means of translating uncertainty into probabilities.

2.     Propensity;  Reflect the properties of the object or the system.

3.     Frequencies:   Based on a large number of observations in an appropriate reference class.  Without an appropriate class, there can be no frequently based probability assessment.

Current forecasting is based on degrees of belief, with probabilities highly colored by recent experiences.  Have a large emotional component.

Stock prices are not normally distributed.  Has implications for risk and uncertainty.  They show a high kurtosis (the mean is higher with fatter tails.)

MT6:  Experts and Markets

Discussion on Experts

Functional Fixedness:  The idea that when we think about something a certain way, we have great difficulty in thinking about it in new ways.

Reductive Bias:  We tend to treat non-linear complex systems as if they are linear, simple systems.  Attribute evaluation versus circumstance based is a good example.

Experts are adept at problem solving in stable, linear systems.  But not so good in complex adaptive systems.  True experts understand when a problem falls out of their cognitive framework and face them to look at different models.  Reductive bias plays a significant role in determining an expert’s flexibility.  The less reduction done improves flexibility, more lessens flexibility. 

To mitigate reductive bias, the theory prescribes exploring abstractions across diverse cases to capture the significance of context dependence.

Discussion on collectives versus the one or the expert.

Humans are natural pattern seekers.  The hot hand is a prime example.  Someone who has a few successes believes that their chance of future success is higher.  Studies indicate the hot hand does not exist.  Note:  There is a difference between hot hands versus the development of skill.  Streaks and slumps lie within the domain of chance.

We see patterns where none exist because we’re wired to expect the characteristics of chance to show not in just the total, but also in small parts of the sequence “Belief in small numbers.”

The point is:  Streaks inform us about probabilities.  Long success streaks happen to the most skillful because their general chance of success is greater.  Because of skill probabilities of success are different for people.

MT8:  Time is on My Side

Loss Aversion:  Given a choice between risky outcomes we are about two times averse to losses than to comparable gains.

Expected Utility Theory:  Considers gains and losses I context of total wealth.

Prospect Theory:  Considers gains and losses versus isolated components of wealth.

Studies show investors use price or changes in price as a reference point when evaluating financial transactions.  They pay attention to narrow frames.

Expected utility:  generally applied to total wealth over a period of time.

Prospect Theory:  A sequence is not acceptable if each of its singal pays is not acceptable.

If prospect theory is accurate, then the probabilities of a stock (or portfolio rising and the investment evaluation period) becomes paramount.

1.      Loss aversion:  We regret losses two to two and half times more than similar size gains.

2.     Myopia:  The more frequently we evaluate our portfolios, the more likely we are to see losses and hence suffer from loss aversion.  The less we review portfolios the more likely we will see gains.

Utility = Probability of a price increase – ( probability of a decline  x 2 ).

Point:  Long term investors are willing to pay more for a risky asset than a short term investor.  Valuation depends on time horizon.

MT9:  No notes: Intro to Part II

No notes on the chapter.  Start introduction to Part II

It’s note enough to have your own views, but to consider what other people think.  We tend to see patterns, so well in fact, we see patterns where none exist.  We’re slow to deduce, but quick to fill in the gap.

Investing is interactive, probabilistic, and noisy.   Media provides the want of an expert, without the value of an expert.

MT10:  Linking Stresses to Suboptimal Portfolio Management

As the world and systems become more complex and move more rapidly the more humans become demonstrably less able to adapt.

 Humans deal with stressors that are primarily mental, which is not quite in line with our evolutionary make up.  The body’s physiological responses are well adapted for dealing with short term physical threats.  The problem’s humans have dealt with through most of our existence as a species.  The problem is mental stresses trigger the same responses as physical stress.  The source is different, but the reaction is the same.

Howe we think we handle stress tends to be short sighted and inefficient.  Stress stems from a loss of predictability and a loss of control.  Loss of control not only reflects actions within the portfolio, but also evaluation of the portfolio.

The average length of holding a mutual fund has gone from 15 years in the 1950’s to 4 years in 2006.

MT11:  Tupperware Parties

Six human tendencies that spur a positive response to a request:

1.     Reciprocation:  the obligation to reciprocate.

2.     Commitment and consistency:  Once we have made a decision, especially if we’ve made it public, we’re loathe to change our view.  Consistency allows us to stop thinking about the issue…a mental break.  And two, consistency allows us to avoid the consequences of reason.  The first allows us to avoid thinking, the second allows us to avoid action.

3.     Social validation:  We frequently make decisions based on the observations of how others make decisions.

4.     Liking:  We prefer to say yes to people we like.

5.     Authority:  People obey authority figures against their better judgment.

6.     Scarcity:  Scarce or perceived scarcity increases value.

These traits are powerful in and of themselves, but become more powerful with combinations.

Consistency, commitment, social value and scarcity are particularly important. 

After making a decision (buy or sell) we feel more confident in out position that just before the decision.  After making a decision we feel internal and external pressure to remain consistent to that view.  To the point of ignoring or dismissing new evidence to the contrary.  The confirmation bias also plays into this phenomena.

Investing is a social activity that can lead to people acting in concert.  Awareness of breakdowns in diversity can often help  in recognizing potential traps.  

Investors seek information scarcity, but knowing the difference between scarce information and what information is valuable is the real key.  Reverse engineering market expectations, or, figuring out what the market thinks helps determine what information is valuable.

MT12:  Emotion and intuition in Decisions Making

People base decisions not on what they think about it, but how they feel about it.  If they like an activity, they tend to appraise the risks lower and the gains higher.  If they dislike it, high risks, low rewards.  Impaired feelings and flawed decisions go hand in hand.

Discussion on ‘Experiential system’ and the analytical system.  Notes taking during Think Twice and are similar to the reflective and reflexive model.

Experiential system:  uses perception and intuition to generate impressions of objects.  Involuntary and the person may not be aware of them.  System two consists of all judgments.  Intuition is a judgment that reflects impressions.

So…

1.      You can’t separate emotions from decisions and the trick is

2.     What influences our impressions and

3.     How do these impressions shape perceptions of risk and reward.

Affect:  The ‘goodness’ or ‘badness’ of how we feel about a stimuli.  Operates in the realm of system one.

Prospect Theory:  Investors are risk averse when facing gains and risk seeking when facing losses.  The ‘affect’ can amplify this bias, in terms of how we feel about a potential investment.

1.      The goal is to buy an investment at a lower price than its expected value.

2.     Expected value is the weighted average value for a distribution of possible outcomes.

3.     Expected value is calculated by multiplying the payoff of a given outcome by the probability it will occur.

Affect has two impacts on expected value:

1.      When outcomes don’t have a strong affective meaning we tend to over weight the probabilities.

2.     When the outcome does have strong affective meaning we tend to overweight the outcome.

When payoffs are vivid, people tend to focus on the outcomes and pay less attention to probabilities.

Bottom Line:  When investors feel good about an investment, they deem risks low and returns high irrespective of more objective possibilities.

Good investors aren’t swayed by affect.  Which may be an insight into how their systems are wired.

System one (experiential) can fail  when outside forces try to manipulate it.  Advertising, someone painting a vivid picture of an outcome are examples.   They also fail in non-linear systems.  As a result, outcomes can be very counter intuitive.

Individual versus the collective:  We’re all wired differently with varying experiences.  As such, we’re going to see and perceive things different.

The idea of separating emotion from rationality is foolish.  Both concepts are in play.  Not only is it not possible, it’s also undesirable.

MT13:  Role of Imitation in Markets

When people are free to do as they please, the usually imitate others.

Studies indicate that within the animal kingdom, imitation is clearly evident.  Imitation is a form of cultural transmission.

Fashion, fad, and traditions are a form of imitation.  As investing is a social activity, it is four to believe that imitation plays a role in the markets.

Discussion on positive and negative feedback.

People that think in herds go mad in herds, and recover their senses one by one.

Evidence suggests that positive feedback can dominate prices, if only for a short time.  It can cause investors to deviate from their fundamental approach when increases risk.

MT14:  Misuse of Behavioral Finance

Classic economic theory assumes:

1.      All people have the same preferences,

2.     Perfect knowledge of alternatives,

3.     Understanding of the consequences of their decision.  In short, people behave rationally.

Of course we know that classic economic theory and the reality of investing are two very different things.  The gap between theory and practice spawned behavioral finance.

Behavioral Finance:

1.      Can systems be developed to exploit irrational markets.

2.     How to avoid making suboptimal decisions.

Misusing behavioral finance can be as problematic as the general role of psychology in the markets.

A syllogism:

1.      Humans are irrational

2.     Markets are made up of humans, therefore

3.     Markets are irrational.

Behavioral finance assume that heuristic driven biases and framing effects cause market deviations.

Aggregation of irrational decisions leads to irrational markets.

However, due to a cancellation effect markets can still be rational with irrational investors.  As long as there are fairly equal parts of positive and negative irrationality (diversity).

The point is to find when investors are irrational in the same way at the same time.  Appreciation of the collective can be as important as establishing your own position.  It is not uncommon for behavioral finance experts to forget the collective part of the equation.

Question to Ponder:  Can days with little news help determine the direction of the market.  Contrarian view if volume is low.

Some elements of diversity:

1.      Technical versus fundamental.

2.     Value stocks versus growth.

3.     Short versus long term horizons.

The key to successful contrarian investing is to focus on the folly of the many, not the few.

MT15:  Long Term Expectations

Classic:  Something everybody wants to have read, but nobody wants to read.

Expectations:  Embedded in all the decisions we make.  But how and why are they formed.

Deductive process:  Move from general premises to specific conclusions.

Inductive:  Goes from specific facts to general principles.

Deductive rationality breaks down in the real world because human logical reasoning can’t handle situations that are too complex (bounded rationality).  Any deviation from rationality sparks speculation about how others will behave.

After an event occurs, humans tend to overestimate their previous knowledge of the outcome.  This hindsight bias erodes the quality of the feedback we need in order to sharpen our skills.

Expectation of future returns:  Two parts:

1.      Facts:  More or less certain.

2.     Forecasts:  Varying degree of confidence.

Forecasts include the magnitude and type of investment.

Convention:  Start with the current situation and modify it when they have reasons to expect a change.

Magnitude of modification reflects the state of confidence.  No way to anticipate confidence because it requires feedback.  Markets affect psychology, psychology affects markets.

Conventions are inherently precarious.  Investors tend to focus on short term )speculative) rather than long term (enterprise).  Speculation is basing decisions based on market psychology.  Your trying to decipher what the average opinion thinks of the average opinion.

Hindsight bias:  Once an event has passed we tend to believe that we had better knowledge of the outcome before the fact that we really did.  Indicates people are not good at remembering the level of uncertainty before the event.

MT16:  Investing with Naturalistic Decision making

People don’t necessarily make the best possible decision, but merely ‘what is good enough’.

Naturalistic tasks  - five conditions.

1.     Ill-structured and complex tasks.  No obvious best procedure exists to solve the problem.

2.     Information is incomplete, ambiguous and changing.

3.     Ill defined shifting and competing goals.  Goals can change over the short term.

4.     Mistakes due to stress (time constraints and high stakes).

5.     Decision may involve multiple participants.

Three behaviors of naturalistic decision makers:

1.      The ability to rely on mental imagery and simulation in order to assess a situation and possible alternatives.

2.     Ability to recognize problems based on pattern matching.

3.     Reason through analogy.

Tend to make decisions with very little conscious behavior.

It is suggested that our sensory band width is around 11 megabytes per second, while our conscious bandwidth is 16 bits per second.  The implication is our sensory unconscious ability to process information is dramatically higher than our conscious ability to process it.  Note-automated systems may have more elementary data to process – eye example, peripheral vision – low resolution, black and white versus central, color, high resolution.

Creating story based on facts is important to successful investing, based on naturalistic decisions.

It is common for investors to weigh negative outcomes higher as uncertainty grows.  They also tend to ignore unlikely outcomes and collapse similar categories.

Naturalistic decision making is most relevant in complex environments.  Successful experts seem to be those who can mentally represent a complex system in their head.

The best investors tend to have innate ability (hardwiring) with hard work (diverse information input.)  Naturalistic thinking may be non-transferable.  You either have or you don’t.

MT17:  Weighting Information

Author describes how technology has made vast amounts of information available to individual traders.  Describes want or reliance on proprietary information.

Author lists three sources of skepticism regarding proprietary information:

1.      Can investors properly weigh information.

2.     Are sampling techniques valid.

3.     Does today’s proprietary information lead to superior performance.

Our belief in a hypothesis integrates two kinds of evidence:

1.      The strength or extremeness of the evidence.

2.     Weight of predictive validity.

3.      

Most people ascribe more relevancy to the strength of the evidence rather than the weight of the probabilities.

This tendency leads to an over or under confidence bias.  When the strength of the evidence outweighs the weight and overconfidence bias comes into play.  When strength is low and weighting is high, people become under confident.

Winner’s curse:  in an auction the highest bidder wins the item, but is cursed by overpayment needed to win the auction.   Premiums in mergers are an example.  During appraisal, analysts tend to dwell on the average value, rather than the final value.

Information weighting underscores that not all information os of equal value.

Surveys can be misleading if weighting isn’t accounted for.  If purchasing index is directed toward fortune 500 companies. Then small business may not be included.  Or, one or two large companies may have significantly higher dollar values that don’t necessarily represent the collective.

Over confidence from strong evidence, yet weak predictive validity seems prominent in today’s markets.  Author suggests that information from surveys does not provide superior gains.

The rational is as follows:

1.      Market reacts quickly to information.

2.     Difficult to move as fast as the market.

3.     Survey information collected today is outdated tomorrow by new news.

There is a difference between understanding the fundamentals (or change in fundamental) and grasp of the expectations built into the current stock price.  Prices reflect collective information more than any one person can claim knowledge of.

So, the question is…is the information new or new to the market.

People tend to overestimate the likely hood of two events occurring.

MT18:  Innovation

Any predictions about the future are likely to be wildly off the mark.  Innovation is the only certainty toward the future.  How to think about and cope with innovation is the theme of this section.  Innovation is the primary mechanism shaping companies and determining winners from losers.  Innovation tends to occur in small incremental steps.  It’s the cumulative effect that we need to be concerned about.

Innovation breaks from the past and builds from the past.  Innovation is also at the heart of creative destruction.  More rapid innovation means more success and failure for companies.

Physical control of resources was the primary source of wealth a hundred years ago.  Today, ideas and formulas to manipulate raw materials is the engine of wealth creation.

Innovations is accelerating because:

1.      There are more blocks to break and build from.

2.     Move to instructions (software) and looking for better ways of manipulating resources.

3.     Scientific advances, information storage, and computer power.

MT19:  Boom and Bust and Staying Ahead of the Curve

Brain development and innovation analogy.

Boom and Bust cycles:

1.      Appreciate the cycle

2.     When the environment is uncertain, it helps by starting with lots of alternatives (increased synaptic connections) and then become selective (via pruning).  The ones that remain are the ones that are best for the environment.

3.     As prices bid up, people want to participate.

Markets and businesses are social constructions and exhibit parallels in nature.

Staying Ahead of the Curve:

Success in nature means passing your genes to the next generation.  Success in business means generating higher returns than your competitors.  There appears to be a discernable pattern of investor reaction to innovation.  Investors tend to understate or overstate growth prospects.

Investors use a myriad of means to determine a current price of a company’s future (present value on future cash flows).  Investors must asses how the market will consider innovation.

Growth starts slowly, then increases at an increasing pace, then flattens out.  Humans tend to think linearly, which, when overlaid on the growth curve, describes the difference between prediction and growth.

As described by the author:

1.      Investors do not anticipate growth.  They extrapolate future growth from current earnings.  There extrapolations tend to be low.

2.     As growth occurs, they extrapolate the growth indefinitely into the future.  Expectations then become too high.

3.     As growth flattens, expectations are reigned in and stocks tend to get adjusted to more reasonable growth.

In summary, analysts tend to look at current earnings as their base level, then make minor adjustments for expected growth.   As growth increases, analysts take the higher earnings and extrapolate further out in the future than what is realistic.

Transitions form point A to point B present the best opportunities for investors.  B to C, not so good.  As innovation accelerates, there will be more A to B opportunities.

Researchers indicates that challengers have the advantage and incumbent’s don’t innovate enough to sustain leadership prices.   Expectations for challengers tend to be initially to low, then become to high.

MT20:  Impact of Accelerating Industry Change

Product clock speed:  how quickly an industry launches new products and how long products live.

Process clock speed:  Process for creating are delivering a good or service.

Three hypothesis with scientific support.

1.      Periods of persistent superior economic performance are decreasing in duration over time.

2.     Hypercompetition resides in all industries, not just technology.

3.     Firms are increasingly seeking to sustain  the competitive advantage by concentrating a series of short term competitive advantages.

Impact to investors:

1.      Shorter life cycles undermine the usefulness of historical multiples.  Simplistic valuations invite danger.

2.     Discounted cash flows are extended too far out in the future.  The expectation of growth exceeds the top of the S curve.  Any value incorrectly attributed to extended valuations will adversely affect today’s discounted price.

3.     Implies higher portfolio turnover may be needed to be flexible.

4.     Need for greater diversification .  Need to cast a wider net.

MT21:  How to balance with the short term.

When developing strategies, ensure options (plans b, c  and d) are part of them. 

The notion of the long term being the focus of business leaders is nonsensical.  The long term is the aggregation of the short term.  Due to the complexity of business and the market, it’s impossible to understand all future positions.  The key is to develop long term goals.

How to develop short versus long term goals:

1.      Don’t look too far ahead.  Looking too far ahead is useless as the amount of uncertainty is high.

2.     Develop options and continually revise them based on changing conditions.  Don’t play your first move, consider it and then ask what are other options.

3.     Know your competition.

4.     Seek small advantages:  Play for advantages your opponent doesn’t see.

Your greatest advantage is the ability to read other people and to know yourself as they are the only intelligences you need.

Highly variable outcomes emerge from simple rules which is a characteristic of a complex system.

Author suggests developing long term decision rules that allow for the right decisions in the short term.  No company knows how the future will develop, but decision rules provide action guidelines no matter what happens.

Five types of rules:

1.      How to rules:  Spells out how a company should execute a process.

2.     Boundary rules:  Focus managers on which opportunities they should pursue and which not to.

3.     Priority rules:  Help managers rank the opportunities they accept.

4.     Timing rules:  Synchronizing managers with the pace of opportunities that emerge in other parts of the company.

5.     Exit rules:  how to pull out of yesterdays opportunities.

Strategy of simple rules “resonates with complex adaptive systems.”

MT22:  Fitness Landscapes

Improving fitness means becoming more suited to your environment.  Better fitness means generating options and choosing the best ones.  It may be necessary to reduce the peak performance in the short term to achieve higher levels of fitness.

Fitness landscapes are a good way to look at businesses.  Can also apply to markets.

1.      How does the company view itself.  Their own perception helps form fitness decisions.

2.     Is the company pursuing the right strategies to improve its fitness.

Nothing happens in a void.  Actions trigger reactions.

Three types of landscapes:

1.      Stable:  landscape is relatively flat.  Companies generate excess economic returns when cyclical forces are favorable.  Utilities, commodities, real estate and consumer non-durables.  Limited opportunities for growth.

2.     Coarse:  landscape is in flux, but changes have some predictability.  Financial, retail, and health care and more established parts of technology, can be unseated.

3.     Roiling:  dynamic businesses.  Evolving business models and substantial uncertainty.  Software, genomics, fashion related, and most start ups.

Accelerating innovation, deregulation, and globalization is causing fitness to contort more than in the past.

Once you know the fitness level of a company, then you can consider the appropriate strategies for determining long term value.

Two general strategies for improving fitness:

1.      Short jumps:  Small incremental steps toward a peak.  Usually consists of small changes to internal processes.

2.     Long Jumps:  discontinuous jumps.  Large jumps outside of the normal realm of business.  Mergers of an unrelated company.

Small jumps, incremental change is usually the focus of businesses with a stable landscape.  Long jumps tend to be potentially distracting and costly.  Roiling landscapes work primarily on long jumps.

Traditional discounted cash flow analysis is well suited for businesses that compete in stable fitness landscapes.

Coarse fitness landscapes requires a blend of traditional cash flow models and strategic options.  Strategic options are the right, but not the obligation to pursue potentially value crating business opportunities.

Roiling industries rely mostly on strategic options.

The point of fitness landscapes is to help you determine if the business is following the right mix of financial tools (blend of discounted cash flows and strategic options).  Their strategy needs to fit their fitness landscape if they are to survive.

MT23:  Folly of using Average P/Es

You can’t draw conclusions from past averages, when the underlying data is changing.  Because, they don’t accurately represent today’s averages. 

Price to earnings ratios fall within the category of money underlying data.  They only capture what was meaningful of the time.

Non-stationary is critical to any time series analysis for averages to be comparable over time.  Over time, the statistical properties of the data must remain the same.  Research indicates there is no statistically significant relationship between a P/E ratio at the beginning of a year and the end of the year.

Why P/E ratios are non-stationary is important.  Three large drivers include:

1.      Taxes and inflation.

2.     Changes in composition of the economy

3.     Shifts in equity risk premium.

Tax rates have a material impact on equities.  Higher taxes means lower multiples, and lower taxes mean higher multiples.  Adjustments ar also made for inflation.  Higher inflation, less real growth, lower multiples.

Composition of tangible and intangible benefits play a role.  Capital investments are depreciated over years, non tangible assets (R&D, Advertising) are immediately expenses.

So, the composition of the companies assets play a significant role.  Companies with higher intangible reliant assets tend to have higher cash flow to net income rations.

Ebb and flow of investor’s risk appetite also affect capital inflows and outflows.  Cautious environments lower multiples, optimistic environments increase multiples.

MT24: Mean Reversion and Turnarounds

A company’s value is a function of the markets expectations for its growth rate and its economic returns.  First, you need to have a clear understanding of whether a company is earning appropriate returns before you can judge the effect of growth.

Goal of strategic analysis is to address three fundamental questions.

1.      Are returns greater than the cost of capital, or, is there good reason they will in the future.

2.     If yes to 1, how long can the company sustain its excess returns.

3.     If returns fall below the cost of capital.  What’s the probability it can recover.

The notion that a company’s return on investment reverts to the cost of capital over time is well documented.  Companies that generating high returns draws competition.  Companies that generate low returns lose capital as investors leave.

MT25:  Cooperation and Competition Through Game Theory

Discussion on the parallels of cooperation between business and game theory.  Example of adding capacity.  A company’s choice to add capacity is not executed in a vacuum.  As a competitor will most likely add capacity as well.  Using prisoners dilemma, if you think a competitor may add capacity, it’s in your interest to add capacity.  Although its in both of their interests not to add capacity.  Good for consumers, not so much for the companies.

Interaction is not a one time event, it’s continual.  Companies effectively play it over and over.  Cooperation may slowly build in numerous iterations as companies learn to cooperate with each other.

Be wary of companies adding capacity at peaks levels.  Be aware the competition between businesses need not be zero sum games.

MT26:  On the Limits of Corporate Growth

Most managers and investors focus on growth.  People do not intuitively understand compounding.  Growth rate variance declines with size.  This isn’t to say large companies are poor investments.  Some large companies will grow and increase shareholder returns.  We just don’t have a systematic way to identify them.  Herein lies the opportunity.

Remember that there is a difference between the average P/E and individual P/E ratios.  Poor performers, that are solid companies, will normally revert back to the mean.

Although growth stocks tend to have higher returns, we don’t know which ones will grow.  Focus needs to be on expected value, where upside opportunity outstrips the downside risk.

MT27:  Thoughts on Organization for investing Success

Diverse information and perspectives can help improve investment performance.

Point:  When searching for a solution, especially a random problem, a bunch of people going down random paths increases the efficiency of finding the solution.

There is a theme of brute force in numbers, incredible wasted energy seems, random paths, and pruning then to find the best answer.

Ant example, although ants tend to follow one another, enough will break off to explore new trails.  The analogy applies to human learning.  Exploring a wild hair may lead to new and insightful information.

Intelligence:  Making a guess that discovers a new underlying order.

You need two features to cussed in a complex system.

1.      The ability to create a simulation in your head that allows you to select among varying strategies.

2.     Being able to populate your mind with information from diverse sources.

Idea diversity allows you to find weak signals.  A weak signal may be the start of a new trend.

Creative people are:

-         Intellectually curious

-        Flexible and open to new information

-        Able to identify and clearly define problems.

-        Ability to put information together.  In different ways to reach a solution.

-        Anti authority and unorthodox

-        Mentally restless, intense and highly motivated.

-        Highly Intelligent.

-        Goal oriented.

MT28:  Wisdom and Whims of the Collective.

Discussion on the collectives analogous with ants and bees. 

Three systems that depend on collective behavior:

1.      Social insects

2.     Decision markets

3.     Stock markets

Features of colony of honey bees.

1.      Discussion of labor based on temporary specialization.

2.     Absence of physical connections between workers.

3.     Diverse pathways of information flow.

4.     High economy on communication.

5.     Negative feedback.

6.     Coordination without central planning.

Review of experts and the wisdom of collectives

Decision Markets aggregate information across traders, allowing them to solve hard problems more effectively than any individual can.

MT29:  Using the Collective to Find, Solve and Predict

Accuracy of Crowds:

1.      Information aggregation is at the heart of market efficiency.

2.     Companies that take advantage of embedded information may be able to get a competitive edge.

To Ponder:  How do we know if the market is efficient.  Feedback tends to be in prices and susceptible to new news.

Author states there is no answer as the stock market has no specified time or value.  As a result investors are susceptible to imitation.  Understanding why the markets are efficient may help determine when they are being inefficient.

MT30:  Fat Tails and Investing

Much of the world is controlled as much by tails, rather than the averages.  By catastrophe, rather than drip by drip, rather by the rich, not the middle class.  We need to free ourselves from average thinking.

Experience:  Looks to the past and considers future outcomes.

Exposure:  considers the likelihood of a potential risk, of an event that history may not reveal.

Review of Fat Tails:

Figures Show:

1.      Small changes appear more frequently than the normal distribution predicts.

2.     Fewer medium changes than models predict.

3.     Fatter tails than what standard models predict.

Fat tails:  ends of distribution curves, indicates extreme events happen more frequently than an average bell curve.

MT30:  Discussion of Fractals and End Notes

Order is often hidden.  Fractals appear frequently in nature and also in the markets.  Stock prices look fractal.  After adjustments, day to day, week to week, and month to month data looks the same.

Not a lot of useful information on fractals other than it’s an interesting area to look into.

Implications:

1.      Consider why returns are less than the cost of capital>  Economic future may be bright if the company is heavily investing early in the business cycle.

2.     Look for changes in returns that were not anticipated by the markets.

3.     Judge the longevity of excess returns.  Reversion to the mean is a powerful force.

4.     Strategy matters.

The trick is to find order within disorder, the linear pattern seeking, but to locate data within self organizing systems.  

Understanding of the markets come from:

1.      Having a broad range of information.

2.     Ability to form mental models

3.     Ability to develop strategies and count strategies

4.     Ability to understand your own biases

5.     Ability to objectively compile and evaluate data, and

6.     The ability to be flexible and to act with new information.

In other words, overcoming most of our natural traits.

Author suggests learning more by crossing disciplines.

Areas of interest include:

1.      Decision making and neuroscience.

2.     Statistical properties of markets, from description to prediction.  Remember that distributions are not normal within a market.

3.     Agent based models

4.     Network theory and information.

5.     Growth and size distributions

6.     Simulators for the mind