|This essay by Robert R. Prechter, Jr. originally appeared in
The Elliott Wave Theorist in September 2004.
The Standard Social Science Model vs. Socionomics
Recent issues of The Elliott Wave Theorist along with the studies documented in Socionomics demonstrate that news financial, economic, political or cultural does not cause the stock market to go up and down. Such news, even if one could know it in advance, is no help in predicting stock market movement. The underlying idea of causality that the Standard Social Science Model simplistically borrows from physics that “external” social actions cause reactive changes in social mood is inappropriate for understanding the genesis of financial market action. I put the term external in quotation marks because actually there is no such thing as an external social action; everything in society is intertwined with everything else. A jump in interest rates or a change in economic performance is not an external shock but an intimate aspect of the social dynamic.
The socionomic hypothesis of social causality is that social mood, which is endogenous and self-regulating, determines the tenor and character of social actions. The difference between the socionomic and the standard view is fundamental. Here is an example of the difference: Economists typically argue that a strengthening economy causes consumers and business people to become optimistic. A socionomist understands that a change toward a more positive social mood means that consumers and business people both part of the larger herd are becoming more positive about their prospects, thereby inducing them on the one hand to buy more products and services and on the other to hire more people and expand output, all of which serves to cause a strengthening economy in the first place. Indeed, how could it be otherwise? An improvement in the economy is not an isolated event. It must arise from more optimistic decisions made by consumers and businessmen. Otherwise, optimism would have to result from actions taken for no reason. Social action is the eventual resultof social mood change, not the cause of social mood change. To get a feel for how a socionomist understands social causality in a variety of areas, consider the following list of examples:
|The Standard View||The Socionomic Hypothesis|
|(exogenous cause)||(endogenous cause)|
|Social events determine the tenor of
social mood. Examples
|Social mood determines the tenor of
social events. Examples
Unidirectional Causality: No Feedback Loop
Even when factoring in the idea of social-mood causality, chaos theorists typically presume a mutual causation between social actions and social mood, whereby actions affect mood affect actions, and so on, ad infinitum. However, this does not appear to be the case. Studies2 have shown that even the most dramatic social actions and events have no effect on the tenor or character of social mood, thus challenging the idea of a feedback loop between social mood and social action. I have concluded from these studies that social mood induces social action, period. The fact that manifestations of social mood fluctuate according to a patterned fractal called the Wave Principle is compatible with this conclusion.
Social action is nevertheless rich in the production of consequential actions. Chains of specific social events, stemming from the exercise of rational choices, may well follow other specific social events. For example, an economy in a particular region might contract so much due to the eventual effects of a negative social mood as to cause an exodus from the region, crowding in other areas, etc. Likewise, the assumption of power by authoritarians at a social-mood nadir might have local consequences with respect to the freedom of expression or travel or commerce for decades. Socionomists recognize that the ultimate effects of social mood trends and the social actions they induce are quite wide-ranging and probably chaotic. None of these subsequent events, however, feeds back to affect the endogenous pattern of social mood.
Toward a Science of Social Prediction
The idea that social events whether unidirectionally or as part of a feedback loop are a primary cause of social mood change has proven useless for predicting changes in its supposed result. Is the socionomic model of social mood causality useful for predicting its presumed result, social action? This paper will present a theoretical statement of socionomic utility to serve as the model for understanding our past and future empirical observations, correlations and predictions.
Social mood is the net emotional state of people in a society. Human’s impulses to herd in a context of uncertainty or arbitrariness create endogenous patterns of social mood. Social mood fluctuates at numerous degrees of trend between positive and negative poles, each of which comprises numerous related human emotions. Social mood motivates socionomic actions.
Socionomic actions are actions of social aggregations that express trends and changes in social mood. Socionomic actions result from emotionally impelled decision-making in a social context of significant uncertainty (such as in financial markets, business, and politics) or arbitrariness (such as with regard to fads and fashions). Investors are (despite the claims of the Efficient Market Hypothesis) highly uncertain about what any particular stock is actually worth, so an unconscious herding process takes over, producing the fractal pattern governed by the Wave Principle.
Socionomic actions differ from social actions taken entirely for practical reasons, for example if the inhabitants of an area were concurrently to flee a volcanic eruption. When people possess undisputed facts and clear options in a context of certainty, they usually act rationally to meet a desirable end. This model is useful in utilitarian economics. When objectively valuable factors such as price and utility matter most, consumers typically exercise rational choice consciously according to the law of supply and demand, producing a global effect of price equilibrium, which differs dramatically from the dynamism of prices governed by social mood and therefore the Wave Principle. This difference is the essence of the financial/economic dichotomy postulated by socionomic theory.1
Social actions that are not primarily socionomic actions are rare. Social actions that most people think are rational responses to external stimuli are not so at all. Aggregate voting patterns, for example, are due primarily not to rational behavior but to socionomic behavior. Even macroeconomic activity ebbs and flows with social mood, not with some mechanistic criterion. (As mentioned, I would classify townsfolk fleeing an erupting volcano as a non-socionomic social action because endogenous mood is not the underlying cause of the action. Yet it makes a difference how far one goes to investigate underlying causes. The complacency that attended people’s original settling at the base of a volcano ignoring its dangers because other were doing so has socionomic aspects.)
Tenor and Character
Social mood and actions have two aspects: tenor and character. Tenor refers to polar direction, i.e., positive or negative, while character refers to the more specific traits of social mood toward each pole such as forbearance/anger, confidence/fear, optimism/pessimism, etc. (For a more extensive list of the polar attributes of social mood, see Chapter 14 of The Wave Principle of Human Social Behavior.) Predicting a trend in the negative direction is to forecast tenor; predicting an increase in expressions of anger or fear is to forecast character.
Sociometers and Sociometrics
A socionomist analyzes social mood by way of sociometers. A sociometer (so-she-om’-i-ter or so-see-om’-i-ter) is an indicator of the states and trends of social mood. The ideal sociometer would directly record aggregated mood changes in people’s minds, but such a tool is currently unavailable. All currently available sociometers are measures of socionomic actions taken in response to trends and changes in social mood. Therefore, all available sociometers lag actual changes in social mood.
The sociometer that most reliably measures the mood of the society or aggregation under study is termed abenchmark sociometer. A benchmark sociometer has, relative to all other available sociometers, the most data, the cleanest data and the most immediately reported data, is the most leading sociometer available (see discussion below) and covers the broadest subset of the society under study, making it the best sociometer for plotting, analysis and decision-making. The stock market is our benchmark sociometer for general social mood in the United States over the past two centuries and in the U.K. over the past three centuries because the data produced by this auction market on the value of human production satisfy the first four criteria far better than any other measure. As observed in The Wave Principle of Human Social Behavior (p.23.), the level of aggregate stock prices is a direct measure of the popular valuation of [a society’s] total productive capacity, there is voluminous, meticulously tabulated data on financial markets, and because stock market investors can respond almost immediately to their mood changes. The monthly report of the Gross Domestic Product may cover a broader subset of society than the stock market, better satisfying the fifth criterion, but it is not our benchmark sociometer because (1) it provides much less data (nothing weekly, daily or intraday), (2) it derives from contaminated data (the components are sometimes adjusted for political reasons, and the measure includes some bogus components, such as government spending), and (3) it is a seriously lagging sociometer (4) whose data is then reported late, extending the lag.
The science of applying sociometers to forecast or deduce the probable tenor and character of socionomic actions may be termed sociometrics.
Classes of Sociometers
There are two classes of sociometers: progressive and polar. These terms relate to their design.
Progressive sociometers incorporate potentially endless trends of growth or decay, hence the term progressive. Progressive sociometers that are immediately sensitive to social mood trace Elliott wave patterns. Examples are stock market averages, currency values and records of an area’s gross production. These data are unbounded by their composition and may fluctuate freely to ever-higher (or ever-lower, as in the case of a currency’s value) levels.
Polar sociometers are restricted by their construction to fluctuate between extremes, hence the term polar. Examples include certain measures of optimism and pessimism toward the future such as the Consumer Confidence Index, the percentage of advisors bullish or bearish on a financial market, put/call volume ratios, the percentage of commitment to the long or short side among various classes of futures traders, etc. Such indicators are common in the realm of technical market analysis, and some, such as the CCI, are popular among economists. (Conventional economists use such indicators improperly, in fact backwards, as they cite unanimously in my experience a high CCI reading as portending good times and vice versa, the opposite of their true implications. But I digress.)
A Range of Scope
Sociometers range from broad to narrow in scope. The broadest sociometers measure such a large segment of society or such a commonly shared activity that they reflect the overall mood of a society. Examples are stock market averages, human conception rates, GDP and consumer sentiment polls.
The narrowest sociometers gauge a subset of social activity that may have a psychological structure of its own, substantially unrelated or only peripherally or temporarily related to general social mood. Examples are the total number of participants in a particular fad or fashion such as cigarette smoking or break-dancing. Socionomists may study narrow sociometers in an isolated fashion (plotting their waves, for instance) or as an aspect of the broader social mood. (The popularity of bubble-gum music, for example, is a narrow gauge of social mood, but the genre’s occasional strong popularity pertains to a broader analysis of the overall social mood.)
A Temporal Continuum of Socionomic Response: The Key to Sociometrics
Socionomic actions fall along an open-ended continuum of delay following the initial impetus from social mood, from immediate (for example, stock market trends) through intermediate (for example, styles of popular entertainment) to eventual (for example, climates of peace and war). This continuum makes earlier sociometers leading indicators of later ones, which is one source of their utility. It is acceptable to use the terms leading and lagging to define the relative temporal position of sociometers as long as the socionomist understands that there is no leading indicator of social mood itself. Sociometers that reveal social mood more rapidly are simply leading indicators of ones that reveal social mood more sluggishly. The term eventual does not mean final, as one might always be able to observe or postulate some social-action consequences of previous social action. The effects of specific social moods, however, dissipate with time.
An analogy from meteorology may clarify this point. A humidity reading of 100 percent is an immediate indicator of rain, while water runoff is an intermediately lagging indicator of rain, and a rising river level is an eventual lagging indicator of rain. Each of the first two indicators is a leading indicator of the next. (From a socionomic perspective, the conventional economist’s use of economic data to forecast the stock market is akin to a meteorologist using river fluctuations to predict rain.)
Why is it important to distinguish between leading and lagging sociometers and to use the term sociometer for any social-mood indicator along the entire continuum? Clearly, when various types of sociometric data are available, one would choose the most leading sociometer (other things being equal) as a benchmark to make socionomic assessments and predictions. To date, the best leading sociometer by far is the stock market, so why not just identify the stock market as the sociometer? The answer is that in some cases, not all desired data are available. To revisit our analogy, our meteorologist friend might be studying ancient civilizations and have only the record of rising and falling river levels with which to work. Those data are useful in being indicative of earlier rainfall. Likewise, a socionomist studying ancient civilizations may have limited data such as the dating of varying levels of production from a copper mine based upon the strata of scrap around its site or the levels of business activity in a pre-historic port city based upon layers of commercial debris in the sediment of the harbor. Since he understands that economic activity expands and contracts as a lagging indicator of social mood, he may be able to deduce all kinds of additional tentative presumptions about kindred social actions preceding, accompanying and following the known times of expansion and contraction in economic activity for those civilizations. He may have a lagging sociometer, but he has a sociometer nevertheless.
Categorizing Sociometers: Examples
The stock market is an immediate, broad, progressive sociometer.
The percentage of total votes cast for an incumbent leader is an immediate, broad, polar sociometer.
Gross Domestic Product is an eventual, broad, progressive sociometer.
The percentage of nations at war is an eventual, broad, polar sociometer.
The record of sales of cigarettes (see Fig 17-1 in HSB) is an immediate, narrow, progressive sociometer.
The audience share of westerns on television is an immediate, narrow, polar sociometer.
The total number of people dying from smoking is an eventual, narrow, progressive sociometer.
The percentage of Atlantans that buy season tickets to Braves baseball games is an eventual, narrow, polar sociometer.
We could compile a similar list of intermediate sociometers. For example, the tally of weekly sales, rentals, check-outs or downloads for a certain genre of entertainment (adventure or horror, for instance) would constitute an intermediate, broad, progressive sociometer. The Consumer Sentiment Index is an intermediate, broad, polar sociometer. (The intermediate nature of the CSI is due not to a necessary delay in initiating social action as in, say, making war, but rather to the delay in reporting the data and to a lesser degree to a possible reliance of consumer’s sentiment upon economic circumstance rather than strictly upon mood.)
Within one area of inquiry, many types of sociometers exist. For example, the total number of conceptions in a society (had we the data nine months earlier than we do) would be an immediate, broad, progressive sociometer. The ratio of conceptions to total population would be an immediate, broad, polar sociometer. The birth rate is an eventual, broad, polar sociometer. The total number of births in a society is an eventual, broad, progressive sociometer.
Applying Sociometers to Forecasting
There are five rationales behind socionomic forecasting:
(1) Leading sociometers predict the tenor and character of lagging ones.
(2) Lagging sociometers, if they are the only sociometric data available, provide a basis for hypothesizing about the behavior of leading ones.
(3) Lagging sociometers can sometimes help confirm presumed changes in leading ones.
(4) A polar sociometer’s extremes can help predict its own changes.
(5) A progressive sociometer’s Elliott wave patterns can help predict its own changes.
All of these forecasting abilities are probabilistic.
Leading Sociometers Predict Lagging Ones
The most immediate consequence of mood is to induce initiating actions. Thereafter lies a continuum of durations relating to the eventual consequences of those initial actions.
At the nearest end of the spectrum are aggregations of almost instantaneous actions such as creating certain facial expressions, using a tone of voice, choosing the content of utterances, choosing a type of song to listen to, singing spontaneously, kicking the dog without provocation, calling a friend to chat, starting an argument, and buying or selling stocks, actions that express mood almost immediately. If a change in mood induces someone to buy or sell stocks, for example, he can so do in a matter of seconds (as long as the market is open, and many of today’s markets are open around the clock). Other imaginable leading sociometers are the frequency of human conceptions and the emotional quality (tone, content, length, speed, melody quotient, noise quotient, etc.) of popular songs. Unfortunately, the data for such measures are not easy to come by or compile.
Toward the far end of the delay spectrum are social actions such as expanding or contracting businesses, organizing labor strikes, creating TV pilots, getting married, planning protests, negotiating peace treaties, getting legislation passed and starting or ending wars. Political actions in particular significantly lag social mood trend.
Between these two extremes are social actions of every imaginable type. In the middle of the spectrum are aggregations of social actions such as adopting fashions, buying musical recordings, seeing movies, attending concerts, writing legislation, creating new business plans, etc.
Lagging social actions eventually result from decisions made earlier, coincidentally with people’s participation in the social mood. People decide to get married, but the marriages take place months later. People decide to have children, but birth statistics are affected months later. CEOs decide to expand or contract businesses, but the actual expansions and contractions take months to actualize. Writers conceive of ideas for films and TV shows, but it takes months to create them. Politicians decide to offer new legislation, but it takes months for Congress to pass or reject it. Leaders may initiate actions to go to war the very same day that others decide to sell stocks, but while the stock seller can act immediately, the warrior, for example, must gather his advisors, gain intelligence, accumulate supplies, and mobilize his forces. The full follow-through on his initial decision takes time. It may be months or years later that the planned action an attack takes place. In each set of cases, people make decisions when the mood strikes, but the eventual results take time to realize.3
The decisions behind social actions rarely make news. Actualizing those decisions often does, and their actualization takes varying amounts of time. This is why most news lags the stock market. This is why the stock market is an excellent predictor of the tenor of the news. This is why news is useless for predicting stock market trends.
Figure 1 is a diagram of the relative temporal relationship between immediate social actions, which can constitute sociometers, and lagging social actions, which often constitute news. The Elliott wave drawn with a solid line is an idealized depiction of immediate social actions, and the Elliott wave drawn with a dashed line is an idealized depiction of eventual social actions. I have positioned these sociometric waves to reflect a fact that Elliotticians often observe: The worst news appears up to one regressive wave past the stock market’s bottom (i.e., during waves 1 or 2) and the best news appears up to one progressive wave past the stock market’s top (i.e., during wave 1 or 2 of A, or during wave B). An example of the former is the occurrence of the greatest unemployment and lowest production of the Great Depression in early 1933, as stocks were making a higher low seven months after the bottom. An example of the latter is the historic achievement of the Apollo 11 moon landing in July 1969, seven months after the top in the Value Line index and the double top in the Dow.
By observing the swiftest consequences of social-mood impulsivity, a socionomist can predict the tenor, character and intensity of social actions that take longer to effect. He can do this because he knows that people have made decisions not only to buy or sell stocks but also to do other things whose tenor will reflect the same trend in mood. If people are buying stocks, reflecting an increasingly positive social mood, they are also deciding to expand businesses, fall in love, conceive children, buy happy music, exercise, dress with more color and less fabric, get along with their neighbors, free the marketplace for goods and services, cheer heroes, support leaders, and so on. If people are selling stocks, reflecting an increasingly negative social mood, they are also deciding to contract businesses, engage in conflict, delay conception, buy somber music, forego exercise, dress with less color and more fabric, attack their neighbors, restrict trade, denigrate heroes, withdraw support for leaders, etc. The consequences of these decisions will become manifest in ensuing months. Once a socionomist sees the direction that the immediate decisions are taking, he knows the trend of social mood and therefore the trend in the tenor and character of subsequent social actions. A socionomist can predict social actions that will express cooperation or conflict, economic expansion or contraction, political tolerance or repression and cultural ebullience or malaise, and so on.
The longer the average lag between Elliott waves of social mood and lagging subsequent actions, the looser the correlation will be between them. The reason is that a long average lag increases variance. Thus, while leading sociometers are quite precise in recording waves at small degree, lagging sociometers tend to be far less precisely delineated and therefore accurately reflect only the larger-degree trends. Figure 2 provides a visual depiction of this idea.
Lagging Sociometers Provide a Basis from which to Hypothesize about Leading Ones
When our archaeologist friend has only layers of harbor debris as his benchmark sociometer from which to speculate about the socionomic trends of an ancient civilization, he can work backwards from that data to hypothesize about earlier socionomic trends and conditions. For example, he might postulate that the tone of popular music probably became increasingly energetic and joyous before the peak of commercial activity or that a decline in local property values probably preceded its nadir. In this case, lagging data such as harbor debris may not constitute an ideal sociometer, it is nevertheless highly useful.
Lagging Sociometers Can Help Confirm Presumed Turns in Leading Ones
If a socionomist has been anticipating a bottom of Primary degree in the stock market, a majority consensus among economists (an eventual, broad, polar sociometer) that a recession is in force is a strong indication that the anticipated stock market bottom has occurred or is about to occur and that the recession is over or nearly so. Similarly, if a socionomist has been anticipating a top of Cycle degree in the stock market, a flurry of peace treaties and trade agreements (eventual, broad, polar sociometers) is a strong indication that the anticipated stock market top has occurred or is about to occur. Successful application of such lagging sociometers requires substantial study as to the typical lagging effects of social mood trends. It also requires an understanding of the socionomic effects of various Elliott wave aspects, particularly wave number and degree. Different wave numbers have different effects, and different degrees produce correspondingly larger or smaller effects. A negative mood trend of Primary degree will typically produce a recession; a negative mood trend of Millennium degree will produce a dark age.
When a polar sociometer approaches an extreme, a socionomist may begin to anticipate a trend reversal on the grounds that social mood continuously fluctuates and never achieves equilibrium. If, for example, polls reveal that 96 percent of futures traders interested in silver are bullish, one may anticipate that both the percentage reading of the sociometer and the price of silver will soon decline.
Because Elliott waves are hierarchical, the largest degrees of trend will produce longer durations of extreme readings in polar sociometers. Therefore, polar sociometers are best recorded and plotted over multiple durations (such as daily, weekly, monthly and annually). The adept socionomist can increase the odds of a successful forecast by integrating data of a polar sociometer with those of a progressive sociometer by using durations corresponding to the degrees of the relevant trend. An accomplished analyst desiring a comprehensive understanding of current and future states of social mood integrates into his analysis all durations from the largest applicable downward.
Even eventual sociometers have some predictive value for their own changes. When the best of times or worst of times appears to exist with respect to eventual sociometers (i.e., the economic and political climate), a socionomist can anticipate change based simply on the adage, This, too, shall pass. His anticipation, however, must be grounded in knowledge of the degree of trend in force, which regulates the duration and extremity of those good and bad times. Lacking knowledge of Elliott wave degree can make one’s judgment only on this basis early by months, years or even decades. The following discussion explains how to avoid this problem.
A Progressive Sociometer’s Elliott Wave Patterns Can Help Predict Its Own Changes
No indicator leads social mood. Social mood is endogenous and self-regulating, so it has no preceding mechanistic cause. There is, nevertheless, a way to anticipate changes in social mood, with the most leading indicator of all. The primary cause of socionomic action is Elliott waves of social mood. Because actions deriving from social mood trends trace out Elliott waves and because Elliott waves are specifically patterned, a careful analysis of developing wave patterns in an immediate, progressive sociometer offers a probabilistic knowledge of its likely future path. Thus, progressive sociometers with clear Elliott wave patterns announce their own reversals. When a progressive sociometer completes an Elliott wave, an Elliottician may anticipate a reversal at the largest corresponding degree. For example, at the end of the fifth Minor wave of a fifth Intermediate wave of any (except a final) Primary wave, he may anticipate a reversal of Primary degree. If it is a final Primary wave, such as wave five, C, Y or Z, the turn will be of Cycle degree or higher, corresponding to the degree of the largest completed wave, knowledge of such degree being limited only by the availability of data and the clarity of the waves.
A prediction of wave form not only indicates simultaneous changes in social mood but also forecasts the character of immediate, intermediate and eventual social actions, which register in corresponding sociometers. A good Elliottician can analyze wave structures to predict likely changes in wave form and therefore of social mood and therefore of social events, well in advance of a sociometer’s trends. Thus, while knowledge of socionomic causality is extremely useful, knowledge of the Wave Principle can compound that utility immeasurably. As the eventual practical goal of a socionomist is to forecast social change, the best socionomists are also good Elliotticians.
Given adequate data, the immense utility of Elliott wave analysis thereafter is bounded only by the probabilistic nature of potential Elliott wave trends and impeded only by one’s own impulses to herd when confronted with such uncertainty. Although that sentence contains the word only, it is a quantitative reference, not a qualitative one. While there are only two difficulties with which to deal, it takes immense effort to deal with them effectively. Most people don’t do it well, and many people can’t do it at all. Hardly anyone does it well all the time, including me.
Levels of Certainty
To return to our analogy to meteorology, the sociometric forecasting value of Elliott wave formations is similar to the rain-forecasting value of cloud formations. Each is a potential indicator of the future that allows probabilistic forecasting. The further along the temporal spectrum of socionomic expression one goes, the more certainty one may attach to forecasts. While clouds are highly probabilistic forecasters of rain, runoff is a morecertain forecaster of river levels. Similarly, while the apparent positions of Elliott wave patterns are highly probabilistic forecasters of sociometric behavior, the manifest trends of leading sociometers are more certain forecasters of the tenor and character of eventual sociometers.
Why News Fools Investors
Figure 1 illlustrates that the tenor of news, since it comprises mostly reports of eventual socionomic actions, lags the social mood trend that created it. This offset fools investors two ways.
First, news fools investors in a subtle and fundamental way. From Figure 1, you can see why it is so easy for investors to be fooled into thinking that news causes stock market trends. For most of a social mood trend, the tenor of the news is parallel to that of the stock market. News of eventual socionomic actions is not disassociated from stock trends; it simply lags them. The conjunction of the tenor of the news with the stock market is particularly strong in waves 3, 5 and C. During those waves, stocks are rising and news is good, or stocks are falling and news is bad. At such times, economists, investors and the media are flush with certainty about the new’s causality of market trends.
Second, news fools investors in a dramatic and practical way. The decoupling of waves and news comes at the turns. Events that most investors deem newsworthy fool them in terms of their current opinions: News of eventual socionomic actions stays very good or gets better after a stock market peak has passed and stays very bad or gets worse after a stock market low has passed. Thus, the opposition of news to market action in waves 1 and A kills investors in current time. The dramatic crashes of 1929 and 1987 were A waves (the initial wave of a corrective Elliott wave pattern), which took place amidst a strong economy and rosy forecasts, and to this day, economists and academics who use the external causality model cannot explain what caused them. The explosive stock market rises of 1932-1933 and August-October 1982 were 1 waves (the initial wave of a bull market), which took place during a depression and recession respectively, taking economists and the investing public by surprise. More recently, the downturn of 2000-2002, another A wave, and the recession of 2001 similarly arrived with (once again) nary a hint of warning from conventional economists, who use the model of exogenous cause to attempt predictions. Whenever the stock market and the tenor of the news diverge, conventional theorists are lost and expend much effort searching the archives for hints of some external cause that they can use to explain the stock market’s action. When the news finally catches up with the trend, some of them conclude that the stock market magically knew what was coming, a concept called discounting, a time-honored but fantastical idea that socionomists reject.4
Now consider the fact that news’ opposition to initial waves comes at turns of every degree. Because news of eventual social actions is always lagging the market, most investors see many news-related reasons to take the wrong action and few news-related reasons to take the right one. When multiple degrees of trend are culminating together, a general conviction of trend continuation reaches its zenith, which means that it happens at precisely the wrong time, over and over. Of course, someone must be selling on the first day off a top, and someone must be buying on the first day off a bottom. But as trends progress, only the subtlest mood changes of the herd induce buying and selling at the margin, creating the trends we see on the graph. Each participating investor, depending upon his sensitivity to social-mood signals and his proclivity to herd, takes his turn ignoring, resisting or capitulating to the evolving trend. In doing so, the bulk of investors is always late.
No sociometer enjoys purely socionomic data. Any particular individual action included in the makeup of a sociometer may have an entirely rational motive disconnected from mood. For instance, a D.J. might choose a song to play because he’s paid to do it, a criminal might kick his dog without provocation because he thinks it will impress his sadistic companion, a clown might use certain facial expressions to generate a response in his audience, and a non-citizen might get married in order to obtain a green card.
The data impurity, though, goes both ways: Trends in payola, sadism, entertainment and citizenship restriction all ebb and flow with social mood, so even these actions are related to socionomic forces and are not rationally pristine. Just as few social actions result entirely from rationality, few sociometers derive entirely from socionomic causality. When the primary motivation for social action is socionomic, however, individual rational as opposed to rationalized actions within a socionomic context are often countervailing to others so that they mostly cancel each other out. The net influence is therefore negligible, leaving socionomic trends and patterns intact. Indeed, rational investment decisions that also derive from the proper premises take crowd behavior into account, demonstrating that the herd is always in charge. Conventional economists have no such comfort. When socionomic forces enter their realm, all their equations go out the window.
Data Inexactness and Relativity
Sociometers are selective measures of certain types of social actions, not mood itself, and probably always will be. Therefore, unlike a thermometer, they are not perfect gauges of what they attempt to measure, which is the underlying social mood.
Some socionometers are expressed as ratios. The DJIA, for instance, is commonly quoted in terms of dollars. One may also quote it in terms of gold or the PPI (which I often do) or anything else. Sometimes using multiple ratios provides more information. I am impressed, for example, how well the constant-dollar Dow has matched other expressions of social mood over the past half-century. In other historical times, money and gold were equal or the money supply was constant, making choices among such graphs moot.
There are also multiple measures of stock market values. There is the Dow Jones Industrial Average, the Dow Jones Transportation Average, the Dow Jones Utility Average, the Dow Jones Composite Average, the S&P 500 Composite, the S&P 400 Industrials, the S&P 100 big cap stocks, the Value Line geometric average, the Value Line arithmetic average, the Wilshire 5000 index, the NASDAQ Composite index, the NASDAQ 100 blue chip index and others, not to mention sectors and groups. Many of these measures are constructed in ways that differ mathematically. Some are price averages, some are capitalization weighted, and others are based upon the daily percentage moves of their components. This panoply of indicators is a fact of sociology; we have no measure of stock market value that is as apt to the task of valuing the stock market as a thermometer is to gauging the temperature. On the other hand, multiple gauges provide useful insights. When they act in concert, the trend of social mood is quite certain. When they diverge, the trend is correcting or maturing. Activity in one index can help explain related social phenomena. For example, Ronald Reagan’s landslide re-election in 1984 came on the heels of only a moderate gain in the DJIA for his first term, but the Value Line geometric average was soaring throughout, so a waxing positive mood was showing up in a broad list of stocks. Likewise, the downtrend in the Value Line index beginning in April 1998 explains why a Republican (barely) beat a Democrat for the presidency in 2000. Although the Dow was up in Clinton’s last term, the Value Line index revealed a broad underlying negative mood trend for over two and a half years leading up to that election.
Some sociometers appear to provide an absolute reading on their levels, for example, the annual number of births in a nation. One can ask, however, whether such a measure would be more meaningful as a percentage of the population. Only substantial study can answer that question. This is not the case with a thermometer.
Available sociometers also suffer from a lack of universal applicability. We have stock market data, but not all societies in history had a stock market. We have birth data for nations, but nations arise, change boundaries and occasionally disappear. We have the annual number of nuclear bomb tests worldwide, but those data extend back only to the 1940s.
In every case, then, socionomic data are impure, inexact, relative and/or limited. (Of course, economists have the same problems with their data, too; they just don’t often admit it.)5 In this matter, we may envy our friends in the field of physics, in which such problems, while certainly present, are not quite as universal.
The Point of the Exercise
The potential rewards of socionomic analysis are worth the effort. Predicting the tenor of financial, economic, cultural and political news can be highly rewarding to planning the course of one’s life or an enterprise in order to survive and thrive. If you can anticipate changes in stock market trends, you can take advantage of opportunities and avoid disastrous losses. If you can anticipate changes in the economy, you can expand your business at the right time, choose a good time to buy house, know when to ask for a long term business contract or know when to sell your land or business. If you can anticipate changes in the culture, you can choose the right film to produce, know when your band is likely to succeed and put your firm on the cutting edge of fashion trends. If you can anticipate changes in the political climate, you can choose the best time to run for office, know when to put the most money and effort behind your candidate of choice or decide when to think of leaving a country before the borders close. Inexact though it may be, there is no science of social prediction outside socionomics. If you wish to forecast the social future, you must begin here.■
1. See April 16, 2004 Elliott Wave Theorist
2. Please see Prechter, Robert, The Socionomic Insight vs. the Assumption of Event Causality and Challenging the Conventional Assumption about the Presumed Sociological Effect of Terrorist News in Pioneering Studies in Socionomics (2003), pp. 198-218. Also see The Stock Market Is Not Physics in the May and June issues of The Elliott Wave Theorist and A Socionomist Looks at the Blackout (The Elliott Wave Theorist, September 11, 2003), which demonstrates that the occurrence of a major blackout per se has no effect on the peoples mood, but that peoples mood dictates their aggregate actions in such a setting.
3. Recent events provide a classic example. After two and a half years of increasingly negative social mood and months of war talk, the U.S. Congress passed a resolution to attack Iraq on October 10, 2002, the very day of a multi-year low in the Dow Jones Industrial Average. The actual attack took place on March 19, 2003, just 7 days after a multi-year low in the World Stock Index and a test of the earlier low in the Dow.
4. See the discussion under the subhead A Parallel Error in Finance within the article, Parallel Revolutions in the Physical and Social Sciences, in Pioneering Studies in Socionomics, pp. 379-383.
5. For example, rather then bemoaning the lack of data prior to 1950, economists assert that data pre-dating the end of World War II are irrelevant to a modern Fed-managed economy.
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Most economists, historians and sociologists
presume that events determine society’s mood. But socionomics hypothesizes
the opposite: that social mood regulates the character of social events. The
events of history—such as investment booms and busts, political events,
macroeconomic trends and even peace and war—are the products of a naturally
occurring pattern of social-mood fluctuation. Such events, therefore, are not
randomly distributed, as is commonly believed, but are in fact probabilistically
predictable. Socionomics also posits that the stock market is the best available
meter of a society’s aggregate mood, that news is irrelevant to social
mood, and that financial and economic decision-making are fundamentally different
in that financial decisions are motivated by the herding impulse while economic
choices are guided by supply and demand. For more information about socionomic
theory, see (1) the text, The
Wave Principle of Human Social Behavior © 1999, by Robert Prechter;
(2) the introductory documentary History's
Hidden Engine; (3) the video Toward
a New Science of Social Prediction, Prechter’s 2004 speech before
the London School of Economics in which he presents evidence to support his
socionomic hypothesis; and (4) the Socionomics Institute’s website, www.socionomics.net.
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