Investment Analysis Using Scientific Method - Kind of

[DooDiligence]

OK, so after 1 classroom session of Intro to Biology, I find a correlation to the scientific method & investment analysis.

 

We develop hypotheses & since they're unprovable, we instead set out to disprove them.

 

Is it best to be a kind of perma-bear until we're unable to destroy the hypothesis?

[LC]

Probably more profitable to be a perma-bull unless proven otherwise.

[DooDiligence]

Probably more profitable to be a perma-bull unless proven otherwise.

 

You destroyed my hypothesis immediately.

[LC]

The scientific method works!  ;D

[Dynamic]

Where I see the major similarity is in the need for humility and necessity of being willing to give up our cherished ideas when evidence shows they're wrong and recognise our own errors. The need for rational skepticism.

 

I'd also agree that in general, a degree of optimism is rational.

 

For example, while I recognise that the market is quite richly priced in general and understand the bear case, I'm prepared to accept the drawdowns in market price that will eventually come by being fully invested in decent compounding companies purchased well below Intrinsic Value and currently selling at least moderately below Intrinsic Value.

 

I currently anticipate that the eventual crash in the US market has most likely been pushed out by the tax cuts to at least 12-18 months away, and could well still be a few years away, and that my holdings will continue to compound IV for a while more such that the eventual crash in their prices may well come after at least a similar amount of growth in their market value and their IV, while avoiding rational investments below IV for fear of an imminent crash. Keeping the cash I've added has no upside if the crash doesn't come soon enough and I could be missing out on a few years of valuable compounding of intrinsic value.

 

In other words I don't want to be one of those perma-bears who does great when the market does crash, but underperforms for year upon year by being far too early in acting on their pessimism and cannot make up for the time out of the market thanks to their attempt to time the market.

[scorpioncapital]

people and institutions have to make up their vast losses in terms of time from the crashes and mistakes of the past. This force is very strong but also blinding to risks and impossibilities.

 

 

[Dynamic]

You're quite right scorpioncapital. A balance has to be struck between being too pessimistic and too optimistic and nobody can expect to make the optimal decisions.

 

I don't want my previous post to be misinterpreted as excessive optimism, more as me trying to counter my instinctive concern to 'keep my powder dry' as trouble may be ahead, having read many articles about the dubious underpinnings of the recent market boom.

 

Some managers, when worried about lofty valuations, can still find deep value opportunities to deploy their capital and usually shouldn't turn them down because of short term broad market worries.

 

Some will be able to put significant amounts to work in areas such as merger arbitrage which they would usually consider market neutral but likely to achieve attractive IRR that depends almost entirely on the probability and timing of relevant events, regardless of whether the market rises or falls. I have not acquired skills in this area however.

 

In my case, deep value opportunities in my limited circle of competence have been lacking for about 18 months, but BRK.B at $196 in December 2017 with a tax cut almost inevitable seemed to me to offer a moderately well-protected downside and a healthy if not spectacular compound growth rate, making it preferable to holding cash. In such circumstances, the expected return more than meets my long-term needs and I feel suitably compensated for the short term downside risk.

[Cigarbutt]

Wise words.

Sir John Templeton had some words to say also about optimism and avoidance of excessive and unwarranted pessimism.

OK.

 

Analytical tools first came to me from a scientific background. I find too that there are similar principles to investment analysis but submit that the framework is vastly different.

At times, pure quantitative work can provide perhaps a sense a security that may not be always warranted.

In business analysis, much of the input has to be interpreted using subjective judgement, a degree of intuition and a fair bit of common sense.

 

The challenge is to try to understand human nature and that has to remain work in progress.

 

I understand that this Board is inhabited by out-performers and that's good but I continue to note that most investors (in the world in general) underperform.

This is a conundrum that science has not solved yet.

 

Quote from an article, Scientific Investment Analysis: Science or Fiction? Financial Analysts Journal, W. Scott Bauman, pp 93-97, 1967.

Last sentence of the conclusion:

"Evidence strongly suggests that the intelligent use of sophisticated quantitative techniques together with the use of discrete judgement offers fascinating rewards to the investors".

 

Will ponder about the issues mentioned above as I'm about to go on my long solo cross-country ski ride. That's when I do my best quantitative work, far from my financial calculator.

 

[clutch]

The problem in this comparison is that many of the investment hypotheses / methods can not be validated or disapproved in the same manner that scientific falsification can.

 

Think of a typical hypothesis we make: "Company X has intrinsic value of Y", so when Y is higher than price P, we buy the company.

 

How can you ever prove or disapprove this hypothesis? We can never measure and confirm the intrinsic value in reality. All we can "measure" is the price people pay for the company, which by the value investor's definition is not equal to the intrinsic value. Even if the price has converged to your estimated intrinsic value, that does not prove that your intrinsic value was right!

 

In contrast, scientific hypotheses involve physical quantities that are measurable, e.g., "Blood cells will rise by X amount if condition Y is applied". We can measure X before and after the application of Y, to test whether our hypothesis is true or false.

 

In investing, you can go out to disapprove your hypotheses, but you wouldn't know what it takes or how much evidence you'd need to disapprove them, and in the end you have to make conclusions based on some subjective decisions anyways. So, I don't think it fits well with the method of scientific falsification.

 

[Dynamic]

I'd agree, clutch, that it's difficult to prove or disprove a hypothesis. Back-testing gives some indication for certain mechanical strategies but can be prone to finding false positives by data mining numerous approaches until you find things that appear to offer a statistically significant advantage. Then when applied to future data one might find they don't work and it was probably being fooled by randomness.

 

I think the Margin of Safety approach reduces the number of decision thresholds that occur and provides hysteresis against selling on the upside to stop excessive trading, but may skew the distribution in the investor's favour. I'd suggest that a consistent record of beating the market under various conditions and over at least one economic cycle adds a good deal of evidence to support the hypothesis.

 

The Superinvestors of Graham and Doddsville cited in Buffett's essay were pre-selected as people who learned from Graham and Dodd and people who:

• applied the margin of safety principle to their investments and

• considered the ownership of shares as ownership of the business and

• appreciated Mr Market as a source of opportunity rather than wisdom.

They invested in very different areas of the economy, from cigar-butts to quality businesses. Their returns as published showed that as a group, they all beat the market in the long run, with varying stocks held, varying volatility and varying total returns.

This evidence lends a lot of support (but not conclusive proof) to the idea that Margin of Safety is a useful concept to employ.

 

Going back to why most investors underperform:

 

It seems that a reasonable hypothesis (one I'll run with for the sake of argument) could be that the underperformance of the majority of investors is because:

• they have a tendency to buy high and sell low

• presumably they believe that recent past performance and returns, and the illusion of movement of the stock price (as if it possesses inertial mass and will continue trending in the same direction unless a force acts upon it) are positively correlated with future returns, often with a short-term time horizon.

• While these investors may wish to buy low and sell high, I surmise that they don't have any concept of intrinsic value other than "the stock is worth what someone will pay for it".

• In Buffett's essay The Superinvestors of Graham and Doddsville, I imagine them as the majority of people for whom "price is what you pay and value is what you receive" doesn't gel in their minds, and nor does the idea of margin of safety.

• If they do have a concept of intrinsic value, perhaps it seems too much like hard work to learn enough accounting and perhaps they're unwilling to put companies they can't value into the 'too hard' pile and move onto something else. Intellectual short-cuts may be used instead, such as analyst reports, newsflow and tipsheets.

• So they too often buy stocks that have recently increased in price substantially and they sell after a recent decline.

• Many only start investing when the markets have risen consistently for a few years and sell out after they make a loss, waiting for conditions to look rosy again before they risk investing again.

• If they don't have an idea of intrinsic value a stock that was absurdly overpriced and has since declined 50% may look cheap to them when in fact it's just greatly overpriced and still likely to offer poor returns.

• Many consider investing to be gambling. While it's fortunately a positive-sum game, that mentality tends to cause bad judgement.

• They probably have too little regard for frictional costs in trading (fees and taxes) and how they eat into compound returns over time.

• Many also anchor too much on the price they paid for each stock, rather than reassessing their best options available at any point in time. Sometimes it's sensible to sell out of a position showing a loss (or having retreated from its highs) and take advantage of an alternative with an even bigger margin of safety and prospective return.

• Many have no quality thresholds and buy companies with questionable economics or excessive debt and wonder why lose money.

• I think this period is almost the inversion of the early 20th century and before, when most people almost entirely focused on dividend yields or tangible book value to the exclusion of the growth component of value or qualitative business factors.

• Most people know about P/E ratios but don't see how the inverse, earnings yields (E/P), are somehow commensurate with interest rates and offer at least a crude way of comparing alternative places to put your money. At least dividend yields are recognised better so high yield investors tend to avoid overpaying for growth and can remain patient.

• Most people understand only superficially what things do. For example the word 'stop loss order' sounds beneficial, but it can crystallise temporary paper losses into real losses. Likewise a 'sell limit order' can take profits when available, but can prevent you realising even greater profits if the stock keeps rising. Value Investors who have a feeling for the Intrinsic Value and its long term compounding rate can be confident to hold a stock that falls further after they buy (and perhaps buy more) and to hold a stock that has risen considerably.

• Many day traders get small repeated successes that really seem to work, until they don't work and they lose all their accumulated gains and more thanks to a fundamental shift, or they miss out on most of the compounding by being out of the market for those short periods when fundamental value becomes recognised.

 

I'm sure there are many other types of folly out there that I haven't covered.

 

It's certainly plausible to have a skewed distribution where the majority of participants greatly underperform, and it seems to roughly match the distribution of active fund returns, whereby most lag the market in the long term, index funds kept invested achieve something like 90th to 95th percentile returns (depending on time period) and the upper 5% earns returns in excess of the market.

 

The 'kept invested' is crucial. As I understand it, many market participants including index fund investors sell out after a market crash and don't return until it's far too late, so they tend to underperform despite choosing a sound investment vehicle in the first place. Their emotional reaction to the negative numbers relative to the year before on their annual statement work against their best interests and make them sell low just when prospective returns have actually increased.

[KJP]

 

Think of a typical hypothesis we make: "Company X has intrinsic value of Y", so when Y is higher than price P, we buy the company.

 

 

Is that really a typical hypothesis?  Or is a typical hypothesis something like:  "Company X has competitive advantage Y, which should lead to measureable good operating outcome Z," e.g., circa 1980 a hypothesis might be "Walmart has strong local economies of scale, which should lead to increasing net margins and returns on capital far in excess of its cost capital as it expands into geographically adjacent markets."  Or the typical value-investor regression-to-the-mean hypothesis:  "Company X is in Industry Y.  Companies in Industry Y typically earn Z margins.  Company X has been earning .5(Z) margins because of Fixable Issue 1.  Fixable Issue 1 will be fixed, leading Company X's margins to increase to Z."

 

The difficulty is that these are statements about the future, but all we have is data about the past, so we can't test it today. 

[clutch]

 

Think of a typical hypothesis we make: "Company X has intrinsic value of Y", so when Y is higher than price P, we buy the company.

 

 

Is that really a typical hypothesis?  Or is a typical hypothesis something like:  "Company X has competitive advantage Y, which should lead to measureable good operating outcome Z," e.g., circa 1980 a hypothesis might be "Walmart has strong local economies of scale, which should lead to increasing net margins and returns on capital far in excess of its cost capital as it expands into geographically adjacent markets."  Or the typical value-investor regression-to-the-mean hypothesis:  "Company X is in Industry Y.  Companies in Industry Y typically earn Z margins.  Company X has been earning .5(Z) margins because of Fixable Issue 1.  Fixable Issue 1 will be fixed, leading Company X's margins to increase to Z."

 

The difficulty is that these are statements about the future, but all we have is data about the past, so we can't test it today.

 

Perhaps not typical, but an essential hypothesis for value investing IMO.

 

You bring another good point though. Even if the hypothesis is testable, you need time to test it, and you have to commit to your hypothesis before you can test them.