Your Investment Wealth Depends On Behavioral Analysis As Much As Fundamental Analysis

 |  Includes: UDOW
by: Peter F. Way, CFA

Maybe more, since Behavioral Analysis examines both the price you pay for investments, particularly equity investments, and the likely price you will ultimately get paid for them. Even if you are a confirmed "passive" investor, you should invest a bit of your time and mental energy in understanding the role being played by Behavioral Analysis [BA].

Fundamental analysis is essential, because it lays the foundation for why prices might be what they sometimes turn out to be. But it does little to tell when, or how likely such outcomes might occur. And as can be shown, both the "when" and the "if" in the challenge becomes a dominant factor in investors' wealth, and its rate of accumulation.

And the ability of fundamental analysis to provide helpful means of comparing the likelihood of one investment versus another reaching some price target before or beyond a given time is yet to be demonstrated. Without that, asset allocation choices or individual portfolio holdings selections become a product of only hopeful aspirations, rather than reasoned choices.

How can Behavioral Analysis Do Any Better, and Why Should It?

First, the why.

When Behavioral Analysis is directed to the actions of qualified, competent participants, to find what they do intelligently and productively, then very useful things can be learned. Unfortunately, most efforts in this field of study focus on the errors humans make, rather than on what they do right.

The equity investment markets provide a very usefully bounded structure for BA to address. That is, firstly, because investing in equities is a game, mankind's second most serious game, next to war. What makes it a game is that all of the actions that can be taken are dependent upon the actions of other players in the game. Every transaction must have an "other side of the trade."

As a game, investment markets provide a set of rules of play that must be followed if a transaction is to be cleared, or consummated. Players can be counted upon to follow the rules, with rare exceptions. (i.e. Madoff) Generally accepted scorekeeping practices - annual rates of return - provide a quantitative measure of player progress. Interruptions to that progress provide a qualitative measure of accomplishment, as well as reducing the rate of return.

Secondly, players in this game exercise their freedoms to set their own bounds of satisfaction, and their own styles of conduct (within the rules) to achieve their satisfactions. It is this freedom of choice that helps provide differences of opinion necessary to provide both a buyer and a seller at the same point in time for each transaction.

Equity markets in the U.S., and progressively, worldwide, are developed to the point where many players have assigned the investment task to professional organizations rather than undertaking the activity themselves. The size of assets under control of such organizations is typically vastly larger than that controlled by an average individual investor. Competition for assets to manage in this highly lucrative business encourages the organizations to seek to achieve attractive returns on the capital placed with them. Which in turn prompts them, from time to time, to make changes in the investments that they employ.

The large attempted trades which result from these decisions strain the capacity of markets. That makes it difficult to assemble sufficient numbers of shares from other investors to make up an "other side of the trade" and get the big-fund originator of the trade order "filled."

Efforts by the big-money funds to alleviate this persistent problem include breaking down their orders into "smaller" pieces (still many times the size of individual investor trade volumes), and seeking out other big-money funds. Funds willing to take the "other side" without publicly admitting the action, by doing direct fund-to-fund deals in what are known as "dark pools" rather than on public exchanges.

What makes these efforts limited is the biggest motivator for the trades to begin with, the price which the trade originator will accept to make the trade. Sell orders are usually motivated by a change in attitude about how attractive the subject's future prospects may be, and a desire to get as much for the item as they can before other funds learn what the seller now knows. Conversely, buy orders may be motivated by new insights or developments that are likely to turn into a "land rush" of acquisitions that will drive its price up beyond a point of attractiveness.

Either of those conditions makes trade actions a situation where "time is of the essence."

Working one's way out of or into a position may not be realistic. Many funds accumulate positions when following "conservative long-term investing" strategies, that could only be unwound over several months at average daily exchange volume levels. Acting in ways that raise the typical volume levels, by being a significant proportion of the total trading, is likely to accelerate the unwanted price change. Persistent actions over periods of weeks and months will alert the competition.

The answer to this dilemma is usually found in enlisting the aid of a "trusted" volume market-maker [MM] who will draw on its maintained knowledge of which funds own what stocks at cost prices that might encourage it to take the "other side" position at or very near to current prices. The "trust" dimension is earned by an implicit promise by the MM that the originator's identity and appetite to deal in the item will not be revealed to other street MMs, thus spooking the market. Funds maintain that trust by a continuing volume of such orders across a range of other securities; sometimes by "pairing" sell orders to be worked with volume buy orders to reinvest the capital.

These trust relationships develop over time and are valuable to the funds from a point of getting trades "filled" promptly at acceptable prices (bid-offer spreads). From the MM's perspective, there are incentives of both the trade spread and of a chance to engineer a hedge of its own temporary capital commitment that may produce or lock-in a gain even better than the trade spread, with no risk.

The fund knows what it wants to do and why, and has a sense of the value of what urgency may be involved. So it makes a value judgment of what it can afford to pay to get the trade done. The cost of the trade comes out of the capital being managed, and is typically believed to be in the best interest of that capital.

The MM has a specialized knowledge of current hedging markets, usually well beyond the desired involvement of the fund, as well as knowledge of where willing "other side" players are most likely to be found at acceptable prices. It utilizes these advantages to extract very attractive compensation from nearly every deal agreed to.

So how does Behavioral Analysis Figure In?

BA seeks a conclusion of the witness, a procedure denied in a court of law, unless the witness is an expert in the matter at hand. Like, in this case, the Market-Maker.

The MM community knows what likely price progressions are because they are constantly aware of the "order flow" from the fund management community. While their trust relationships require protection of client and trade specifics, awareness of an existing interest to buy or sell particular items becomes known in the MM community because it helps everyone involved to get deals filled. Order flow is a valuable resource.

Working from that specialized knowledge, the MMs build hedge protections in each case where they may need to put firm capital at risk to facilitate the deal's consummation. What they are willing to pay for such price change protection, and the way the hedge is structured, tells just how far they think prices may go, both up and down. And the up and down prospects are often not symmetrical.

So an analysis of the hedging markets produces implied (conclusion of the witness) forecasts of how far the fund community is likely to push prices. These forecasts are based on the self-protective interests of the MMs as they contemplate likely future market actions.

An understanding of how these implied forecasts are trending can be very helpful in keeping recent and current price moves in perspective. Here is an example:

Click to enlarge

(used with permission)

This picture of MM price range forecasts (the vertical bars, with contemporary market quotes as the heavy dot) differs enormously from conventional "technical analysis" charts. Those can only offer conjectures of future possibilities, based on artistic interpretations of what may have been present in past price movements, and the hope that they may recur.

With the MM forecasts the future is always the subject at hand, explicitly presented as prospects evolve.

What should be evident from this picture is that the balance between the upside prospect (from the current market to the top of the forecast range), and the converse (to the downside), logically should have some forecast value, as it seems to have here.

To make evaluations of that notion easier to explore, a measure called the Range Index [RI] tells what proportion of the full bottom-to-top span of the forecast lies below the current market price. The Range Index is not the downside price change prospect, but is a measure of the balance between the upside and downside: If the RI is 20, 80% of its forecast range is above the contemporary price, and there appears to be 4x as much upside as downside.

For any subject there will be an array of past RIs. The subsequent price actions following forecasts at various RI levels suggest how well a present RI may do in the near future as a guide to price prospects. We are usually most interested in the present RI, and its prior price change experiences. While there is no guarantee that future market conditions will duplicate the past, those priors may offer our best possible guide.

Measuring How Well the Forecasters Have Done

We devised, long ago, a simple standardized test to see how well a subject investment performed in actual price experiences following buys at specific RI levels. In it, the top of the forecast range is set as a sell target, and a holding time patience limit is set at 3 months from the date of the forecast. Performance is measured from an investment cost set at the first market-day end of day price following the forecast day.

The first occasion of an e.o.d. price at or above the target closes the buy position. Failing such an event, the position is closed at the time limit. At each RI level, geometric mean averages of the gains and losses thus incurred and averages of holding period times provide annual rates of return. A count of losing positions in the total number of experiences produces odds of winning positions, and notations of the worst price drawdowns below cost prior to closeouts allows their averaging into a measure of experienced risks.

Here is what those results looked like for the last date in the UDOW picture above:

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Its Range Index on October 31, 2013 was 63, and out of 920 market days of this ETF's existence (a bit short of 4 years) 95 of them had similar RIs. Put to the test just described, they produced average gains of +3.0% and took an average of 21 days to do it. That short a period (one market month) indicates that sell targets were reached in most cases rather promptly. The 3% earned, if compounded correctly expands into an annual rate of 42%.

In 86% of the 95 days an ending profit position occurred. During the course of those holdings an average worst-case price drawdown of - 6 ½% was experienced.

To give an illustration of the dynamics of price and expectations changes possible, here is what the same (3x leveraged) ETF's prospects looked like after the weekend:

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Note that its market price rose about 1½%, The forecast range also rose, by just a bit less, causing the Range Index to rise to 71 from 63. There are only 88 prior RIs at that level, and they produced test gains of +1.6% in average holding periods (a bit longer) of 23 market days for an annual return of only +19%, less than half of the earlier measure.

The win odds now have dropped to 81% from 86%, and the risk exposure has heightened from -6.5% to -7.1%. The upside price potential is squeezed down from +3.3% to only +2.3%. Now there is apparently more than 3 times as much risk as potential return, compared to the earlier 2 times.

A reasonable conclusion

While history suggests strong odds of reaching further small upsides, it is clear that the emotional cost of doing so may entail a discomfort disproportionate to the gain. Many thoughtful investors would shy away from such a proposition, and await a more favorable balance of prospects. Daily updates offer a means of tracking the situation, and confirmations from several issues with parallel objectives may help to provide perspective.

What does a fundamental analysis of the Dow-Jones Index as an investment now offer as guidance regarding market attractiveness in the near future? We don't see much currently for specifics from fundamental analysis.

Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.