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Narrative Economics
stories affect economics, look no further than the example of Bitcoin.
When the idea of Bitcoin was first introduced online in 2008 by a mysterious person under the name Satoshi Nakamoto, hype quickly grew around it. It was an entirely new system of money that had the ability to change everything we know about currency. From there, it became a global phenomenon, though partly not for the reason you’d think.
Sure, its innovation and complex mathematical theory is impressive, but what excited most people about it seemed to be the hype and mystery surrounding it. If you ask most Bitcoin investors about the actual theory that runs Bitcoin, they probably could only give you the very basics.
But ask them about what excites them about it and they’ll probably say it’s the idea of a new, revolutionary way of using currency. The way of the future. They feel that by investing in Bitcoin, they have a stake in the future, proving they are among the forward-thinkers of today.
Another narrative attached to Bitcoin is that it’s free of the control of governments and banks. This idea attracts those investors with an anarchic streak who view many modern institutions as corrupt. Because it isn’t attached to any one country, investors feel they are promoting internationalism.
In short, it is these futuristic narratives along with the mysterious founding of Bitcoin that have made it so attractive to investors, not the complex math behind it. Without the exciting story, it probably wouldn’t have succeeded as quickly as it has.
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Lesson 2: There is a lot in common with epidemics and economic narratives.
Two subjects people don’t usually compare are epidemiology, or the study of epidemics, and economics. This is a shame, because epidemiology and economics could learn a lot from each other. Epidemiologists study how diseases spread, and many of the patterns they see are similar to what economists observe.

For example, they study a disease like Ebola. They keep track of things like the rate of contagion and well as recovery and death rates. When an epidemic is quickly spreading, the contagion rate is much higher than death and recovery rates. When the epidemic starts to decline, the contagion rate falls while the recovery and death rate outnumbers new cases.

This idea can be applied to economic narratives that are contagious. The contagion of a narrative rapidly rises as people talk about it, whether through conversation in person or online. It also spreads through the news and other media. But just like an epidemic, eventually, the story slows down. People start to forget or they just lose interest and the story dies off.
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We can see this parallel when we look at the Bitcoin craze again. If you search how often news stories over the last decade said the word “Bitcoin” you can see this pattern. There was a sharp increase in 2014, and then there was another peak in 2018 before it fell again.

While this isn’t the end of the story for Bitcoin, we can see that the rapid increase and decline with secondary waves is strikingly similar to the shape of a graph of the contagion rate during an epidemic. So studying disease curves can give us a good idea of what a popular narrative might do to the market.

Lesson 3: We must understand the narratives of the past if we want to be ready for our economic future.
Clearly, narratives are important when we’re looking at the economy. This is why it’s essential that economists take these stories seriously, rather than just looking at the math, so they can more accurately predict what’s coming next.

Luckily for economists, now more than ever we are able to access data about these narratives. We can learn through market research, looking at social media, and gathering information about internet searches.

Technology can help economists to find patterns in the data. They can then use this information to predict what the prominent narratives will be and how they might affect the economy. Shiller makes a point to say it has to be done carefully and accurately if you are studying the effects of narratives on economic events.
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What good does this information do? By having a good understanding of narratives, policy-makers can help shape people’s behavior when there are times of stress.

An example of this is during the Great Depression, when President Roosevelt addressed the nation with “fireside chats.” He understood the people’s lack of confidence was part of what was keeping the economy down. In these chats, he asked people to set aside their fears and spend money. It seemed to work, too. Following each address, the markets stabilized.

If people in charge of making policy understand the narratives and take control of them, they can be active participants in what’s going on rather than just bystanders who have no control of the situation.
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Trading cycle
Once identified and understood, cycles can add significant value to the technical analysis toolbox. However, they are not perfect. Some will miss, some will disappear and some will provide a direct hit. This is why it is important to use cycles in conjunction with other aspects of technical analysis. Trend establishes direction, oscillators define momentum and cycles anticipate turning points. Look for confirmation with support or resistance on the price chart or a turn in a key momentum oscillator. It can also help to combine cycles. For example, the stock market is known to have 10-week, 20-week, and 40-week cycles. These cycles can be combined with the Six Month Cycle and Presidential Cycle for added value. Signals are enhanced when multiple cycles nest at a cycle low.

A cycle is an event, such as a price high or low, which repeats itself on a regular basis. Cycles exist in the economy, in nature and in financial markets. The basic business cycle encompasses an economic downturn, bottom, economic upturn, and top. Cycles in nature include the four seasons and solar activity (11 years). Cycles are also part of technical analysis of the financial markets. Cycle theory asserts that cyclical forces, both long and short, drive price movements in the financial markets.

Price and time cycles are used to anticipate turning points. Lows are normally used to define cycle length and then project future cycle lows. Even though there is evidence that cycles do indeed exist, they tend to change over time and can even disappear for a while. While this may sound discouraging, trend is the same way. There is indeed evidence that markets trend, but not all the time. Trend disappears when markets move into a trading range and reverses when prices change direction. Cycles can also disappear and even invert. Do not expect cycle analysis to pinpoint reaction highs or lows. Instead, cycle analysis should be used in conjunction with other aspects of technical analysis to anticipate turning points.

The Perfect Cycle and stock signals
The image below shows a perfect cycle with a length of 100 days. The first peak is at 25 days and the second peak is at 125 days (125 - 25 = 100). The first cycle low is at 75 days and the second cycle low is at 175 days (also 100 days later). Notice that the cycle crosses the X-axis at 50, 100 and 150, which is every 50 points or half a cycle.

Chart 1 - Cycles

Crest: Cycle high
Trough: Cycle low
Phase: Position of the cycle at a particular point in time (the example cycle is at .95 on day 20)
Inflection Point: This is where the cycle line crosses the X-axis
Amplitude: Height of the cycle from X-axis to peak or trough
Length: Distance between cycle highs or cycle lows
Observe that this is merely a blueprint for the ideal cycle; most cycles are not this well-defined.

Cycle Characteristics

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Cycle Length: Lows are usually used to define the length of a cycle and project the cycle into the future. A cycle high can be expected somewhere between the cycle lows.

Translation: Cycles almost never peak at the exact midpoint nor trough at the expected cycle low. Most often, peaks occur before or after the midpoint of the cycle. Right translation is the tendency of prices to peak in the latter part of the cycle during bull markets. Conversely, left translation is the tendency of prices to peak in the front half of the cycle during bear markets. Prices tend to peak later in bull markets and earlier in bear markets.

Harmonics: Larger cycles can be broken down into smaller, and equal, cycles. A 40-week cycle divides into two 20-week cycles. A 20-week cycle divides into two 10-week cycles. Sometimes a larger cycle can divide into three or more parts. The inverse is also true. Small cycles can multiply into larger cycles. A 10-week cycle can be part of a larger 20-week cycle and an even larger 40-week cycle.

Nesting: forex signals A cycle low is reinforced when several cycles signal a trough at the same time. The 10-week, 20-week, and 40-week cycles are nesting when they all trough at the same time.

Inversions: Sometimes a cycle high occurs when there should be a cycle low and vice versa. This can happen when a cycle high or low is skipped or is minimal. A cycle low may be short or almost non-existent in a strong uptrend. Similarly, markets can fall fast and skip a cycle high during sharp declines. Inversions are more prominent with shorter cycles and less common with longer cycles. For instance, one could expect more inversions with a 10-week cycle than a 40-week cycle. Read more onhttps://www.gold-pattern.com/en

Behaviorist
Main articles: Behaviorism, Psychological behaviorism, and Radical behaviorism
Skinner's teaching machine, a mechanical invention to automate the task of programmed instruction
A tenet of behavioral research is that a large part of both human and lower-animal behavior is learned. A principle associated with behavioral research is that the mechanisms involved in learning apply to humans and non-human animals. Behavioral researchers have developed a treatment known as behavior modification, which is used to help individuals replace undesirable behaviors with desirable ones.
The film of the Little Albert experiment
Early behavioral researchers studied stimulus–response pairings, now known as classical conditioning. They demonstrated that when a biologically potent stimulus (e.g., food that elicits salivation) is paired with a previously neutral stimulus (e.g., a bell) over several learning trials, the neutral stimulus by itself can come to elicit the response the biologically potent stimulus elicits. Ivan Pavlov—known best for inducing dogs to salivate in the presence of a stimulus previously linked with food—became a leading figure in the Soviet Union and inspired followers to use his methods on humans.[35] In the United States, Edward Lee Thorndike initiated "connectionist" studies by trapping animals in "puzzle boxes" and rewarding them for escaping. Thorndike wrote in 1911, "There can be no moral warrant for studying man's nature unless the study will enable us to control his acts."[27]:?212–5? From 1910 to 1913 the American Psychological Association went through a sea change of opinion, away from mentalism and towards "behavioralism." In 1913, John B. Watson coined the term behaviorism for this school of thought.[27]:?218–27? Watson's famous Little Albert experiment in 1920 was at first thought to demonstrate that repeated use of upsetting loud noises could instill phobias (aversions to other stimuli) in an infant human,[12][75] although such a conclusion was likely an exaggeration.[76] Karl Lashley, a close collaborator with Watson, examined biological manifestations of learning in the brain.[67]

Clark L. Hull, Edwin Guthrie, and others did much to help behaviorism become a widely used paradigm.[33] A new method of "instrumental" or "operant" conditioning added the concepts of reinforcement and punishment to the model of behavior change. Radical behaviorists avoided discussing the inner workings of the mind, especially the unconscious mind, which they considered impossible to assess scientifically.[77] Operant conditioning was first described by Miller and Kanorski and popularized in the U.S. by B.F. Skinner, who emerged as a leading intellectual of the behaviorist movement.
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Noam Chomsky published an influential critique of radical behaviorism on the grounds that behaviorist principles could not adequately explain the complex mental process of language acquisition and language use.[80][81] The review, which was scathing, did much to reduce the status of behaviorism within psychology.[27]:?282–5? Martin Seligman and his colleagues discovered that they could condition in dogs a state of "learned helplessness", which was not predicted by the behaviorist approach to psychology.[82][83] Edward C. Tolman advanced a hybrid "cognitive behavioral" model, most notably with his 1948 publication discussing the cognitive maps used by rats to guess at the location of food at the end of a maze.[84] Skinner's behaviorism did not die, in part because it generated successful practical applications.
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The Association for Behavior Analysis International was founded in 1974 and by 2003 had members from 42 countries. The field has gained a foothold in Latin America and Japan.[85] Applied behavior analysis is the term used for the application of the principles of operant conditioning to change socially significant behavior (it supersedes the term, "behavior modification").
Boundaries
Early practitioners of experimental psychology distinguished themselves from parapsychology, which in the late nineteenth century enjoyed popularity (including the interest of scholars such as William James). Some people considered parapsychology to be part of "psychology." Parapsychology, hypnotism, and psychism were major topics at the early International Congresses. But students of these fields were eventually ostracized, and more or less banished from the Congress in 1900–1905.[31] Parapsychology persisted for a time at Imperial University in Japan, with publications such as Clairvoyance and Thoughtography by Tomokichi Fukurai, but it was mostly shunned by 1913.[32]
As a discipline, psychology has long sought to fend off accusations that it is a "soft" science. Philosopher of science Thomas Kuhn's 1962 critique implied psychology overall was in a pre-paradigm state, lacking agreement on the type of overarching theory found in mature sciences such as chemistry and physics.[61] Because some areas of psychology rely on research methods such as surveys and questionnaires, critics asserted that psychology is not an objective science. Skeptics have suggested that personality, thinking, and emotion cannot be directly measured and are often inferred from subjective self-reports, which may be problematic. Experimental psychologists have devised a variety of ways to indirectly measure these elusive phenomenological entities.
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Divisions still exist within the field, with some psychologists more oriented towards the unique experiences of individual humans, which cannot be understood only as data points within a larger population. Critics inside and outside the field have argued that mainstream psychology has become increasingly dominated by a "cult of empiricism," which limits the scope of research because investigators restrict themselves to methods derived from the physical sciences.[65]:?36–7? Feminist critiques have argued that claims to scientific objectivity obscure the values and agenda of (historically) mostly male researchers.[37] Jean Grimshaw, for example, argues that mainstream psychological research has advanced a patriarchal agenda through its efforts to control behavior
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Psychological Traps

1. Anchoring Trap
First, there is the so-called anchoring trap, which refers to an over-reliance on what one originally thinks. Imagine betting on a boxing match and choosing the fighter purely by who has thrown the most punches in their last five fights. You may come out all right by picking the statistically more-active fighter, but the fighter with the least punches may have won five bouts by first-round knockouts. Clearly, any metric can become meaningless when it is taken out of context.
For instance, if you think of a certain company as successful, you may be too confident that its stocks are a good bet. This preconception may be totally incorrect in the prevailing situation or at some point in the future.
Take, for example, electronics retailer Radio Shack. Once a thriving seller of personal electronics and gadgets in the 1980s and 1990s, the chain was crushed by online retailers such as Amazon (AMZN). Those trapped in the perception that Radio Shack was there to stay lost a lot of money as the company filed for bankruptcy multiple times and shrinking from its heyday size of 7,300 stores to 70 outlets by the end of 2017.1
In order to avoid this trap, you need to remain flexible in your thinking and open to new sources of information, while understanding the reality that any company can be here today and gone tomorrow. Any manager can disappear too, for that matter.
#2. Sunk Cost Trap
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The sunk cost trap is just as dangerous. This is about psychologically (but not in reality) protecting your previous choices or decisions — which is often disastrous for your investments. It is truly hard to take a loss and/or accept that you made the wrong choices or allowed someone else to make them for you. But if your investment is no good, or sinking fast, the sooner you get out of it and into something more promising, the better.
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If you clung to stocks that you bought in 1999 at the height of the dot.com boom, you would have had to wait a decade to break even, and that is for non-technology stocks.2 It's far better not to cling to the sunk cost and to get into other assets classes that are moving up fast. Emotional commitment to bad investments just makes things worse.

#3. Confirmation Trap
Similarly, in the confirmation trap, people often seek out others who have made and are still making, the same mistake. Make sure you get objective advice from fresh sources, rather than consulting the person who gave you the bad advice in the first place. If you find yourself saying something like, "Our stocks have dropped by 30 percent, but it’s surely best just to hang onto them, isn’t it?" then you are seeking confirmation from some other unfortunate investor in the same situation. You can comfort each other in the short run, but it’s just self-delusion.
#4. Blindness Trap
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Situational blindness can exacerbate the situation. Even people who are not specifically seeking confirmation often just shut out the prevailing market realities in order to do nothing and postpone the evil day when the losses just have to be confronted.
If you know deep down that there is a problem with your investments, such as a major scandal at the company or market warnings, but you read everything online except for the financial headlines, then you are probably suffering from this blinder effect.
#5. Relativity Trap
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The relativity trap is also there waiting to lead you astray. Everyone has a different psychological make-up, combined with a unique set of circumstances extending to work, family, career prospects and likely inheritances. This means that although you need to be aware of what others are doing and saying, their situation and views are not necessarily relevant outside their own context.
"I think a lot of people tend to equate their self worth with their income, or they think that social media, these days puts pressure on people to make it look like they're doing better than they are. And because of that, people feel bad," said Amy Morin, Verywell Mind’s editor-in-chief. "We look at somebody else who has a new car or somebody else whose house looks beautiful and think, 'Oh, why don't I have that?' And those emotions that get stirred up, I think for a lot of people are really difficult. Then how do you decide what you really value in life and what's most important?"
Be aware, but beware too! You must invest for yourself and only in your own context. Your friends may have both the money and the risk-friendliness to speculate in pork belly futures (as in the movie Trading Places), but if you are a modest earning and nervy person, this is not for you.
#6. Irrational Exuberance Trap
When investors start believing that the past equals the future, they are acting as if there is no uncertainty in the market. Unfortunately, uncertainty never vanishes.
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What Is a Technical Indicator?
A technical indicator is a series of data points that are derived by applying a formula to the price data of a security. Price data includes any combination of the open, high, low or close over a period of time. Some indicators may use only the closing prices, while others incorporate volume and open interest into their formulas. The price data is entered into the formula and a data point is produced. For example, the average of 3 closing prices is one data point [ (41+43+43) / 3 = 42.33 ].
However, one data point does not offer much information and does not make for a useful indicator. A series of data points over a period of time is required to create valid reference points to enable analysis. By creating a time series of data points, a comparison can be made between present and past levels. For analysis purposes, technical indicators are usually shown in a graphical form above or below a security's price chart. Once shown in graphical form, an indicator can then be compared with the corresponding price chart of the security. Sometimes indicators are plotted on top of the price plot for a more direct comparison.
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What Does a Technical Indicator Offer?
A technical indicator offers a different perspective from which to analyze the price action. Some, such as moving averages, are derived from simple formulas and the mechanics are relatively easy to understand. Others, such as Stochastics, have complex formulas and require more study to fully understand and appreciate. Regardless of the complexity of the formula, technical indicators can provide a unique perspective on the strength and direction of the underlying price action.
A simple moving average is an indicator that calculates the average price of a security over a specified number of periods. If a security is exceptionally volatile, then a moving average will help to smooth the data. A moving average filters out random noise and offers a smoother perspective of the price action. Veritas (VRTSE) displays a lot of volatility and an analyst may have difficulty discerning a trend. By applying a 10-day simple moving average to the price action, random fluctuations are smoothed to make it easier to identify a trend.
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Why Use Indicators?
Indicators serve three broad functions: to alert, to confirm and to predict.
An indicator can act as an alert to study price action a little more closely. If momentum is waning, it may be a signal to watch for a break of support. Alternatively, if there is a large positive divergence building, it may serve as an alert to watch for a resistance breakout.
Indicators can be used to confirm other technical analysis tools. If there is a breakout on the price chart, a corresponding moving average crossover could serve to confirm the breakout. If a stock breaks support, a corresponding low in the On-Balance-Volume (OBV) could serve to confirm the weakness.

According to some investors and traders, indicators can be used to predict the direction of future prices.
Tips for Using Indicators
Indicators indicate. This may sound straightforward, but sometimes traders ignore the price action of a security and focus solely on an indicator. Indicators filter price action with formulas. As such, they are derivatives and not direct reflections of the price action. This should be taken into consideration when applying analysis. Any analysis of an indicator should be taken with the price action in mind. What is the indicator saying about the price action of a security? Is the price action getting stronger? Weaker?

Even though it may be obvious when indicators generate buy and sell signals, the signals should be taken in context with other technical analysis tools. An indicator may flash a buy signal, but if the chart pattern shows a descending triangle with a series of declining peaks, it may be a false signal.

On the Rambus (RMBS) chart, MACD improved from November to March, forming a positive divergence. All the earmarks of a MACD buying opportunity were present, but the stock failed to break above the resistance and exceed its previous reaction high. This non-confirmation from the stock should have served as a warning sign against a long position. For the record, a sell signal occurred when the stock broke support from the descending triangle in March-01.
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As always in technical analysis, learning how to read indicators is more of an art than a science. The same indicator may exhibit different behavioral patterns when applied to different stocks. Indicators that work well for IBM might not work the same for Delta Airlines. Through careful study and analysis, expertise with the various indicators will develop over time. As this expertise develops, certain nuances, as well as favorite setups, will become clear.


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