Give & Take Economics produces a drastically different perspective on the nature of interaction, whether in markets or broader social interactions. As discussed, this distinction centres on the fact that the economizing trade-off shifts from one of price and quantity in the face of scarcity, to a trade-off between PTB and PTC. For the first time we have a comprehensive approach that builds market psychology ‘right into’ the model. Stock pickers and technical analysts take note, as the approaches that you know are profitable (but which have no place in the context of efficient markets theory), are now powerful predictions of economic theory.
In Give & Take Economics Theory, bids, offers and prices will not maintain steady equilibrium values. When interactions centre around direct ends (consumption or giving), with individuals seeking to demand/take and supply/give in exchange for compensation directly for that exchange, it is typical that the bids and offers of market participants will move toward cooperation to allow the completion of transactions and/or agreements.
This moving toward cooperation of bids and offers reflects the fact that individuals considering a transaction typically have less to gain and more to lose if a transaction/agreement is not secured. Moving to cooperation does not entail convergence to a single, recurrent market price, since bids and offers will still vary and testing will still occur in an attempt to pull prices up or to push prices down. As a result, these direct ends markets usually exhibit a white noise pattern (complete, uniform randomness), with some potential for random short oscillating trend and reversal patterns in bids, offers and prices.
In direct-ends markets relatively low levels of variability exist around actual transaction prices and it is very typical that bids and offers will vary more than actual transaction prices. Relative market power will determine the actual nature of testing in each market. For example, in the case of large-scale consumer goods markets, where many individual buyers demand from a smaller group of organized retailers, there will be little if any testing via bidding on the part of demanders, but there will be regular testing of offer prices by supplying retailers.
Disjoint interactions occur when individuals with indirect ends interact. These indirect ends can be driven by a desire to save or by a desire to speculate.
Individuals that are interested in mitigating risk and providing for future direct ends (consumption and/or giving), will engage in savings related transactions that reduce risk and provide for a relatively certain amount of future funds.
The observation of oscillating trending and reversal in economies and societies in general, such as business cycles and fads/counter-fads, results directly from the nature of speculation, which can be created and grow in disjoint interactions. Endogenous information and testing behaviour in the face of uncertainty are all that is required to produce speculation and an associated oscillating trend and reversal outcome dynamic. Speculation has been defined previously as coming to exist when an individual takes on risk in pursuit of a higher potential reward from taking on that risk, where they specifically expect both reward and risk possibilities in excess of the expected certain components of PTC and PTB.
Speculative situations occur whenever individuals feel that it is possible or likely that their prospects are better when participating in the speculation versus not participating in the speculation. This is fully reflective of perceived PTB and PTC, which may or may not accurately reflect actual outcome probabilities and magnitudes. An endogenous reversal occurs during speculation at the point when a number of individuals feel that their prospects are improved overall by giving up further potential gains in favour of lowering risk.
This dynamic reflects the reality that in a world of Cumulative Counter Agent Effects many outcomes are significantly beyond an individual’s control in the short to intermediate-term and exhibit a bell-shaped distribution centred around an observed trending average value. The number of individuals that start to bet against a trend eventually increases as the trend goes on. No matter how strong an up trend, perceived risk will eventually elevate as outcomes consistently push into the upper end of the bell curve.
As trends gain strength in their early stage, optimistic perceptions can quickly push the entire bell curve higher and even result in a heavily right skewed distribution, placing higher subjective probabilities and magnitudes on reward outcomes over risk outcomes. All it takes is a small number of individuals to begin to push in the direction against the trend due to a heightened perception of risk, and the masses may begin to move in tandem, creating an endogenous reversal.
Whereas the traditional statistical law of large numbers produces a relatively steady price (random walk) in non-speculative interactions (under the assumptions of efficient market theory) large numbers of individuals actually create amplification of the oscillating trend and reversal dynamic in speculative interactions (under the assumptions of Give & Take Economics). In essence more and more participants ‘jump on’ to the trend and add greater certainty to the developing moving average value. When risk levels increase to the threshold point of some individuals, these individuals start to feel that the counter trend is a better prospective situation.
Eventually, the actions of the individuals speculating on the counter trend push the existing trend in the opposite direction, even attracting on board many of the participants in the initial trend, as they now see high risk in sticking to the original trend, and want to exit their positions. Variance will typically increase with an increasing right (personal total benefit) skew as the trend advances and then increase greatly during the downtrend, with an increasing left (personal total cost) skew.
Most speculative trends consist of an upswing followed by a downswing but they can be ‘bearish’, first producing a downswing followed by an upswing. Individuals will perceive a distribution of potential duration and magnitude regarding both the upswing and downswing of a cycle. The upswing of trends is generally gradual as more and more people get on board and prepare themselves for increased risk, where the level of risk is still in the ‘middle’ of the bell curve. The downswing is typically very fast as fear and panic set in at the end of the upswing, reflected in an ever decreasing probability that outcomes push further and further out into the reward from risk tail of the distribution. This is a systematic cyclical outcome, a disequilibrium dynamic very different from a random walk around an ‘equilibrium’ outcome.
The existence of speculative bubbles (economic, sociological, political) flows from Give & Take Economics Theory with full rationality in the context of larger groups of participants, due to the testing dynamic and the endogenous nature of economic values. Speculative demand is a real demand and a recurrent, common demand. Booms and pullbacks occur when speculative demand naturally develops, with testing behaviour serving as the initiator, the enabler and the turning point. Speculation can begin to occur even when individuals do not have any perception of risk relative to reward from risk, since testing will drive some individuals to take on a small amount of risk in order to seek out potential reward from risk. This alone can be the starting point to actually introduce speculative value. As noted earlier, value can exist to facilitate either consumption, saving, altruism/giving or speculation.
Speculative value can exist solely based on the expectation that others will recognize the same value – there is no necessity for any underlying direct ends value. With any increase in perceived reward from risk relative to perceived risk, individuals will test more assertively, incrementally increasing the possibility of a speculative trend. A number of expected conditions contribute to an attractive environment for speculation:
- Variability (uncertainty)
- ‘Liquid’, actively traded markets
- Large populations
- Long time horizons
- Instruments with direct ends value and store of value properties
Expectations or observations of increases in any of these drivers may transform direct ends markets into boom/bust cycles and traditional negotiations may be transformed into fad/counter-fad cycles. Fad/counter-fad trends will be elaborated upon subsequently. Variability provides for the potential of personal total benefit through reward from risk. Liquid markets allow participants to easily buy and sell to speculate, giving confidence for additional, follow-on participants.
The liquidity of direct ends markets is what makes them particularly attractive as an environment in which speculation may form. Large populations mean that large numbers of individuals can participate and place bids and offers in support of the trend. An often used colloquial interpretation is that with large populations each individual can reasonably expect a ‘greater fool’ to come on board next. Due to differing perceptions of risk and reward from risk, many other individuals, not necessarily ‘fools’, do indeed often have reasonable grounds for coming on board within a cycle.
Longer time horizons mean that ongoing speculative value can be confirmed as some individuals forego direct ends transactions in order to speculate for the longer-term. Instruments imbued with direct ends value and store of value properties are ideal as speculative instruments, as they also provide an underlying direct ends ‘usage value’ as a fallback, in addition to the existence of consistently liquid markets. This serves as an ideal way to reduce risk relative to reward from risk. Gold, precious metals, commodities, and stocks and bonds fit this set of criteria very clearly. All of these factors can be measured in the speculation coefficient, introduced below. As an individual’s motivation to speculate grows, their speculation coefficient, Ф, increases.
Speculative value will be created whenever the speculation coefficient, Ф, which is equal to PTBR (Expected Reward from Risk) divided by PTCR (Expected Risk) is greater than one. As the level of speculation increases the value of Ф increases. When Ф > 1 for at least one individual, that individual will test and potentially create a speculative trend. The price change that occurs as a result may push Ф > 1 for a number of other individuals, adding momentum to a speculative trend and reversal process. Once overall PTC reaches the personal total cost threshold (PTCT) for one individual while their Ф meets the condition that Ф < 1, an endogenous reversal to a speculative trend may get underway as more and more individuals have potential to perceive Ф < 1.
Speculative testing will most often result in demanders bidding above current market price levels, and/or suppliers asking above current market price levels, each attempting to gain from reward from risk and prepared to take on some risk that the trend does not continue. In modern financial and commodity markets there is also a significant amount of speculation on the downside, whereby individuals drive a downward ‘bearish’ or ‘short’ trend by pulling down bids and offers.
The repeated existence of both bullish and bearish cycles is an observation that supports Give & Take Economics Theory very well, underpinning the reality that speculation is its own rational source of potential value to participating individuals. Even though both types of cycles do occur very regularly in real world economies, it is important to note that in most equity-based markets there is a long-term bias to the upside reflecting the profit generating activities of companies.
As noted previously, speculative testing and oscillating trending and reversal are amplified as the level of variability (which includes both risk and reward from risk) increases. Reward from risk provides the potential upside to speculation and risk provides the potential downside. As long as perceived reward from risk exists and that it is also perceived as sufficiently higher than perceived risk, testing will accelerate, which may also create or accelerate speculation.
Variability is most often the result of longer time horizons and larger populations of interacting individuals, because these conditions provide greater opportunity for speculative testing to exist and to build on itself. Longer time horizons allow speculative value to be created either in fully speculative instruments or as an additional component of value in direct ends products/services. With longer time horizons more individuals can direct funds and/or effort from direct ends activities in the current time period toward speculative activities that are expected to yield reward from risk in future periods. Each individual that speculates produces a slightly higher chance that others jump on board through an increase in perceived likelihood of the cycle gaining momentum.
Speculative demand is often highly emotional, and as a speculative cycle gets underway, it is commonplace that participants begin to systematically overestimate the certain component of PTB and the expected reward from risk as well as to systematically underestimate the certain component of PTC and the expected level of risk. This reflects a fully rational optimistic bias. It is also commonplace that during the downside ‘correction’ of an oscillating trend and reversal, the certain component of PTC and risk will each be overestimated and the certain component of PTB and expected reward from risk will also each be underestimated.
This dynamic reflects a fully rational pessimistic bias. Repeated cycles of upward trending and subsequent reversal of market activity are a common observation in real world economies and social movements. The existence of these cycles is an inconvenient deviation in equilibrium models. Mainstream economic theory would suggest that all new information revealed helps to clarify and move all individuals toward equilibrium levels rather than producing recurrent cycles. By contrast, market cycles and broad social cycles are a core theoretical implication of Give & Take Economics Theory.
Therefore, testing, which seems like a trivial distinction in direct ends markets, becomes a vital trigger of a very different dynamic in indirect ends markets that become speculative. As previously discussed, when speculative demand is created by some individuals, it can feed on itself as other individuals adopt a similar perspective. Speculative demand can form in many areas, such as stocks, bonds, real estate, art, commodities, currencies, fashion trends, political views, tastes in music and even tulips, as the famous historical ‘tulip bubble’ example illustrates.
As long as an economic or social factor faces variability, which basically every one does in a world of uncertainty, there is some chance that speculation can begin. Whenever expected reward from risk exceeds expected risk it is completely rational and likely beneficial for an individual to start or participate in a speculative ‘bubble’, attempting to get in early and to get out at or near the perceived peak.
Rational Expectations Theory suggests that each individual will know that such an action is futile and hence not pursue it. This conclusion does not align with observed reality. If even one individual manages to start a speculative cycle, by testing, it is possible and rational for other individuals to similarly test and jump on board as they may personally benefit overall. This dynamic has repeated itself over and over again in real estate, equities and other markets, as those that participate early profit at the expense of those who participate late, based on differing perceptions of when ‘early’ and ‘late’ may be. Rational Expectations does not explain observed outcomes in reality.
Booms/Busts and more muted business cycles are each a fundamental and ‘built-in’ element of the market dynamic in Give & Take Economics Theory. Considering that testing behaviour can easily generate crowd psychology/herd behaviour, speculation and ‘bubbles’ become very commonplace events in modern societies with rapid communication infrastructure. This conclusion is based on the same psychological drivers that make gambling a mainstay in our society, even with widespread knowledge that the odds are strictly managed for the profit of the gambling establishments.
Give & Take Economics Theory explains the full range of market moves and provides a fully rational motivation for pure speculation, however it does not suggest that underlying drivers, such as profit growth, do not serve as some of the most important and consistent inputs to the determination of value. Speculative value can be extremely short-lived and is very often built upon a base of underlying non-speculative elements, such as strong corporate earnings, which is then imbued into direct ends goods/services or financial instruments.
Very little additional discussion is required to illustrate how Give & Take Economics Theory applies to describe business cycles. The oscillating trend and reversal dynamic inherent to Give and Take economics means that business cycles can be triggered by any factor that stimulates a speculative cycle. This means that a business cycle can be triggered by technological changes, changes in tastes, or as is typical in modern economies, by manipulation of the money supply and interest rates.
Business cycles are a natural phenomenon based on natural speculation. They will always occur to some degree but are best minimized by providing coupled social structures and policies that don’t provide PTB to intermediaries with socialized costs (PTC borne by society). Active monetary and fiscal policies are simply tools that further decouple PTB and PTC. In the short-term, monetary and fiscal policy can appear to have positive impact as they counteract voluntary market and political trends, however they actually further decouple PTB and PTC and put in place the conditions for further subsequent instability. Reliable and steadily evolving social infrastructure will generally result in a steady growth trajectory without sizeable business cycles.