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(efeas, Egypt)
efeas, Egypt
Posts: 0
15 days ago
Jan 19, 2023 21:57
Understanding Risk Management
Risk management occurs everywhere in the realm
of finance. It occurs when an investor buys U.S.
Treasury bonds over corporate bonds,
when a fund manager hedges
his currency exposure with currency derivatives,
and when a bank performs a credit check on an individual
before issuing a personal line of credit.
Stockbrokers use financial instruments
like options and futures,
and money managers use strategies like portfolio diversification,
asset allocation and position sizing to mitigate or effectively manage risk.
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efeas, Egypt
Posts: 0
17 days ago
Jan 17, 2023 8:43
Understanding Risk Management
Risk management occurs everywhere in the realm of finance. It occurs when an investor buys U.S. Treasury bonds over corporate bonds, when a fund manager hedges his currency exposure with currency derivatives, and when a bank performs a credit check on an individual before issuing a personal line of credit. Stockbrokers use financial instruments like options and futures, and money managers use strategies like portfolio diversification, asset allocation and position sizing to mitigate or effectively manage risk.

Inadequate risk management can result in severe consequences for companies, individuals, and the economy. For example, the subprime mortgage meltdown in 2007 that helped trigger the Great Recession stemmed from bad risk-management decisions, such as lenders who extended mortgages to individuals with poor credit; investment firms who bought, packaged, and resold these mortgages; and funds that invested excessively in the repackaged, but still risky, mortgage-backed securities (MBSs).
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5 years ago
Good, Bad, and Necessary Risk
We tend to think of "risk" in predominantly negative terms. However, in the investment world, risk is necessary and inseparable from desirable performance.

A common definition of investment risk is a deviation from an expected outcome. We can express this deviation in absolute terms or relative to something else, like a market benchmark.
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While that deviation may be positive or negative, investment professionals generally accept the idea that such deviation implies some degree of the intended outcome for your investments. Thus to achieve higher returns one expects to accept the greater risk. It is also a generally accepted idea that increased risk comes in the form of increased volatility. While investment professionals constantly seek—and occasionally find—ways to reduce such volatility, there is no clear agreement among them on how it's best done.
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How much volatility an investor should accept depends entirely on the individual investor's tolerance for risk, or in the case of an investment professional, how much tolerance their investment objectives allow. One of the most commonly used absolute risk metrics is standard deviation, a statistical measure of dispersion around a central tendency. You look at the average return of an investment and then find its average standard deviation over the same time period. Normal distributions (the familiar bell-shaped curve) dictate that the expected return of the investment is likely to be one standard deviation from the average 67% of the time and two standard deviations from the average deviation 95% of the time. This helps investors evaluate risk numerically. If they believe that they can tolerate the risk, financially and emotionally, they invest.

Risk Management Example
For example, during a 15-year period from Aug. 1, 1992, to July 31, 2007, the average annualized total return of the S&P 500 was 10.7%. This number reveals what happened for the whole period, but it does not say what happened along the way. The average standard deviation of the S&P 500 for that same period was 13.5%. This is the difference between the average return and the real return at most given points throughout the 15-year period.

When applying the bell curve model, any given outcome should fall within one standard deviation of the mean about 67% of the time and within two standard deviations about 95% of the time. Thus, an S&P 500 investor could expect the return, at any given point during this period, to be 10.7% plus or minus the standard deviation of 13.5% about 67% of the time; he may also assume a 27% (two standard deviations) increase or decrease 95% of the time. If he can afford the loss, he invests.

Risk Management and Psychology
While that information may be helpful, it does not fully address an investor's risk concerns. The field of behavioral finance has contributed an important element to the risk equation, demonstrating asymmetry between how people view gains and losses. In the language of prospect theory, an area of behavioral finance introduced by Amos Tversky and Daniel Kahneman in 1979, investors exhibit loss aversion. Tversky and Kahneman documented that investors put roughly twice the weight on the pain associated with a loss than the good feeling associated with a profit.
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Often, what investors really want to know is not just how much an asset deviates from its expected outcome, but how bad things look way down on the left-hand tail of the distribution curve. Value at risk (VAR) attempts to provide an answer to this question
efeas, Egypt
Posts: 0
34 days ago
Dec 31, 2022 13:56
The word habit is pulled from the Latin words habere, which means "have, consist of," and habitus, which means "condition, or state of being." It also is derived from the French word habit (pronounced \ah-bee\), which means clothes.[11] In the 13th century, the word habit first just referred to clothing. The meaning then progressed to the more common use of the word, which is "acquired mode of behavior."[11]

Habit formation is the process by which a behavior, through regular repetition, becomes automatic or habitual. This is modeled as an increase in automaticity with the number of repetitions up to an asymptote.[13][14][15] This process of habit formation can be slow. Lally et al. (2010) found the average time for participants to reach the asymptote of automaticity was 66 days with a range of 18–254
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There are 3 main components to habit formation: the context cue, behavioral repetition, and the reward.[16] The context cue can be a prior action, time of day, location, or anything that triggers the habitual behavior. This could be anything that one's mind associates with that habit, and one will automatically let a habit come to the surface. The behavior is the actual habit that one exhibits, and the reward, such as a positive feeling, therefore continues the "habit loop".[17] A habit may initially be triggered by a goal, but over time that goal becomes less necessary and the habit becomes more automatic. Intermittent or uncertain rewards have been found to be particularly effective in promoting habit learning.[18]

A variety of digital tools, online or mobile apps, have been introduced that are designed to support habit formation. For example, Habitica is a system that uses gamification, implementing strategies found in video games to real-life tasks by adding rewards such as experience and gold.[19] However, a review of such tools suggests most are poorly designed with respect to theory and fail to support the development of automaticity.[20][21]

Shopping habits are particularly vulnerable to change at "major life moments" like graduation, marriage, the birth of the first child, moving to a new home, and divorce. Some stores use purchase data to try to detect these events and take advantage of the marketing opportunity.[22]
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Some habits are known as "keystone habits," and these influence the formation of other habits. For example, identifying as the type of person who takes care of their body and is in the habit of exercising regularly, can also influence eating better and using credit cards less. In business, safety can be a keystone habit that influences other habits that result in greater productivity.[22]

A recent study by Adriaanse et al. (2014) found that habits mediate the relationship between self-control and unhealthy snack consumption.[23] The results of the study empirically demonstrate that high self-control may influence the formation of habits and in turn affect behavior.
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The habit–goal interface or interaction is constrained by the particular manner in which habits are learned and represented in memory. Specifically, the associative learning underlying habits is characterized by the slow, incremental accrual of information over time in procedural memory.[9] Habits can either benefit or hurt the goals a person sets for themselves.

Goals guide habits by providing the initial outcome-oriented motivation for response repetition. In this sense, habits are often a trace of past goal pursuit.[9] Although, when a habit forces one action, but a conscious goal pushes for another action, an oppositional context occurs.[24] When the habit prevails over the conscious goal, a capture error has taken place.

Behavior prediction is also derived from goals. Behavior prediction acknowledges the likelihood that a habit will form, but in order to form that habit, a goal must have been initially present. The influence of goals on habits is what makes a habit different from other automatic processes in the mind.[25]
The following is a description of a classic goal devaluation experiment (from a Scientific American MIND guest blog post called Should Habits or Goals Direct Your Life? It Depends) which demonstrates the difference between goal-directed and habitual behavior:

efeas, Egypt
Posts: 0
49 days ago
Dec 16, 2022 15:03
Why I Go To Investment Conferences

I’m off to a conference this week for the International Federation of Technical Analysts (IFTA). Why am I going? What do I hope to get out it? When you go to investment gatherings, what are your expectations? I’ve garnered essential benefits from a wide variety of seminars and conferences, and those benefits serve as an informal “goals list” for this week’s IFTA event.

1. I’m less interested in the speakers’ prognostications and future outlooks, and more interested in their systematic methods of analysis. If they offer up one without the other, I am not shy in challenging them for specifics.
2. I have a rule that I don’t read investment books unless they come recommended to me by at least two people I respect. There are just too many bad and misleading how-to books out there. I’m a little like that with new resources as well, such as advanced tools or websites. These conferences are a wonderful venue for learning about such items.
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4. In listening to other experienced investors talk about their tools and systems, one can’t help but review one’s own methodology. This enforced reflection is facilitated by metaphorically kicking the tires of other investors’ approaches. Most of the time, it reinforces my own methodology and builds self-confidence in my own system, and confidence does matter.
A corollary to objective #1 above is to remind attendees that the guy sitting next to you may have valuable knowledge and experience to share with you as well. I’ve found that these peer-to-peer, belly-to-belly networking ?????? ?????? ?????????
5. opportunities can yield both friendships as well as keen insights. In other words, don’t miss the lunch and dinner events. It’s half the fun, and you never know who you’ll get seated next to!
6. Call it the enthusiasm kick-start. I find I’m simply recharged as a trader when I get home. Let’s face it, these things are usually at pretty nice locations, and taking a break from normal office routines is always good for whatever ails you, even if you think nothing is ailing you.
7. Sometimes, I’ll take with me a specific element of my methodology or an indicator that I’d like some help demystifying an area of confusion. I recall just such a case some 20 years ago pertaining to stochastics. Lo and behold, I had dinner with George Lane, the creator of the stochastics oscillator. His advice was spot on, and I’ve been reaping the benefits for the past two decades. But I did pay for dinner!
8. With any speaker, I first try to ascertain his or her motive for being there as a presenter. This offers both a credibility check as well as helps me to focus on specific content rather than being mesmerized by the sizzle or the sales pitch. Keep an open mind, but in the end remember there is seldom a free lunch.
Finally, don’t get swept up into a totally new investment methodology or excited by a new system far outside of your comfort zone. Most investment conferences and seminars can offer something appropriate for every level of investor. You may have to actively dig for it, but that one trading gem which catapults you onto the next higher rung is there somewhere. Be patient. Be focused. But for gosh sake, be there. ?????? ?????

efeas, Egypt
Posts: 0
2 months ago
Dec 2, 2022 7:09

Wall Street's Complexity versus Investors' Profits & Simplicity

“Any darn fool can make something complex; it takes a genius to make something simple.” -- Pete Seeger
As a long-time trader, I am living breathing proof that simplicity and profits are positively correlated while complexity and profits are inversely correlated. In other words, as my 25 year investing career has jettisoned multiple methodologies and numerous indicators, my profits have became more regular and predictable while my losing ratio has diminished. This is the absolute antithesis of what Wall Street wants you to believe.

Wall Street lives and breathes on complexity. They pitch derivatives of every variety and alternative funds for specific self-serving reasons.

1. They want to convince investors that it’s far too complicated for them to manage their own money – therefore, the wisest decision is for investors to just give it to Wall Street managers instead.

2. They try to assure you that with this complexity come “insider” rates of returns and big profits. But then can you explain to me why so many university endowments and retirement funds are closing out their hedge fund positions? Because the returns have not justified the risks, losses and complexity.

3. Wall Street loves to use the cliché, “you get what you pay for” as justification for higher fees. So then, can you explain to me again why so many academic studies have concluded that no load mutual funds outperform advisor-recommended loaded mutual funds? The fact is that investors often do not get what they pay for.
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The catalyst for this week’s rant is that I cleaned out a closet with my old trading binders from over 20 years ago and was stunned by two observations. The first thing I realized was that I had been so vulnerable to believing Wall Street’s siren song of complexity. The second thing was that it was obvious my trading methodology back then was unnecessarily complicated.

To most individual investors, it seems counterintuitive when I preach my doctrine of simplicity, but it is precisely this simplicity that empowers you to outperform the professional money managers. Layer on top of that my other sermon that no one will manage your money with the same passion and commitment as you yourself and you have the magic ingredients for achieving consistent success as a stock market investor.
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Wall Street is based on its own version of Yin & Yang as opposites and contrary forces are actually interconnected and interdependent. In simplest terms, the market is made up of buyers and sellers, load and no load funds, passive and managed strategies. The complexity and simplicity paradigm is just another example. Much like life, one must decide to embrace the light or the dark, the hot or the cold, the high or low. So too, as an investor, you must choose between the dichotomies that Wall Street offers you.

I am simply sharing the experiences of my own journey as an investor. As I embraced the mantra of simplification in my investment methodology and my trading tools, my net worth grew. My relatively small basket of 10 technical indicators and the Tensile Trading approach that I’ve written so much about are living testimonials to this mantra.

Albert Einstein famously said, “If I had one hour to save the world, I would spend 55 minutes defining the problem and five minutes implementing the solution.” If you were in a life threatening situation and had only one hour before it proved fatal, what would you do? Einstein said he’d spend his time wisely asking probing questions to understand the problem in depth. Having done that, he’d only need 5 minutes to address the issue.

Many new investors I meet in my classes totally flip around Dr. Einstein’s approach. They have an unstoppable inclination to jump right into the market, metaphorically speaking. They’ll trade impulsively for the first 55 minutes and then allocate the last 5 minutes trying to figure out what just happened.

Humor me, please. Just go with this. Place your hands on the table, turn down the lights and let’s invite Albert Einstein to our séance to give us his advice. If it was indeed possible to “channel” him, I suspect he would suggest approaching the market’s first 55 minutes more like this:
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You have accumulated certain assets. Ask yourself if they are safe. Dr. Einstein would challenge you to address asset protection, first and foremost. Issues such as insurance, estate planning, identification theft, tax planning, record keeping and the like. You have to secure what you’ve got.
Next, he would ask if you had thought through personal money management questions and committed yourself to a personal trading plan in writing. It’s shocking how few investors actually do this. Einstein’s objective here would be to make certain you grasp the full scope of the problem.

efeas, Egypt
Posts: 0
2 months ago
Nov 11, 2022 14:01
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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efeas, Egypt
Posts: 0
3 months ago
Oct 28, 2022 16:08
Avoid emotional trading
Trading psychology describes how a trader handles generating gains and handling losses. It represents their ability to deal with risks and not deviate from their trading plan. The emotional aspects of investing will attempt to dictate your every transaction, and your ability to handle your emotions is part of your trading psychology.
It is impossible to eliminate emotions in trading, but this should not be the goal in the first place. Instead, traders should understand how certain biases or emotions can affect their trading and use this information to their advantage. Every trader is different, and there is no simple rulebook that everyone should follow.
Identify your personality traits
Develop and follow a trading plan
Have patience
Be adaptive
Take a break after a loss
Accept your winnings
Keep a trading log
Identify your personality traits
One of the keys to developing successful trading psychology is identifying your personality traits early on. You will need to be honest with yourself and say if you have impulsive tendencies or if you are prone to acting out of anger or frustration.
If this is the case, it is important to keep these traits in check while you are actively trading because they can lead you to make rash and ill-advised decisions that have little analytical backing. However, it is also important to play to your personal strengths. For instance, if you are naturally calm and calculated, you can take advantage of these personality traits during your time on the markets.
Equally as important as identifying and being aware of your personality traits and emotions is recognising your biases, as listed above. Biases are an innate aspect of human nature, but you should be aware of what your individual biases are before opening or closing any trades.
Develop and follow a trading plan
Having a trading plan is paramount to ensuring that you achieve your goals. A trading plan acts as the blueprint to your trading, and it should highlight your time commitments, your available trading funds, your risk-reward ratio and a trading strategy that you feel comfortable with.
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For instance, a trading plan could say that you were going to commit one hour every morning and evening to trading, and that you will never commit more than 2% of the total value of your portfolio to any one trade. This can help minimise losses and limit the effect of emotions on your trading as the rules for opening or closing a position are already highlighted for you.
Trading plans should also take into account individual factors that could affect your trading discipline such as your emotions, biases and personality traits. If you make clear what your biases are before you start trading, you might be less inclined to act on them.
Have patience
Patience is integral to discipline and it is crucial that you have patience with your positions. Acting on emotions like fear can lead you to miss out on a profit by closing a position too early. Trust your analysis and remain patient and disciplined. Equally, when looking to enter a trade, it is important to be patient and wait for the opportune moment rather than just jumping into a trade right then and there.
For instance, if you were wanting to speculate on some GBP currency pairs like EUR/GBP or GBP/USD, you may want to wait until just before a Bank of England (BoE) announcement as there tends to be increased volatility at this time.
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Be adaptive
While it is important to have a trading plan, remember that no two days on the markets are the same, and winning streaks don’t exist in trading. With this in mind, you should become comfortable in assessing how the markets are different from day to day and adapt accordingly.
If there is more volatility on one day compared to the day before and the markets are moving particularly unpredictably, you may decide to put your trading activity on hold until you’re sure you understand what is happening. Being adaptive can help to limit your emotions and rule out representative and status quo biases, enabling you to assess each situation on its own merits – ensuring that you are pragmatic during your time on the markets.
Take a break after a loss
Sometimes after a loss, the best thing you can do is walk away from your trading account for a short while to gather your thoughts and compose yourself – rather than rushing into another trade in an attempt to regain some of your losses.
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The best traders are those that take their losses and use them as learning opportunities. They will typically take a few minutes to themselves before going back to their platform, using this time to assess what went wrong for that particular trade in the hope that they might avoid making the same mistake in the future.
In doing so, they keep emotions like pride or fear in check by letting themselves cool off before approaching the next trade with a clear head and sound judgment.

efeas, Egypt
Posts: 0
3 months ago
Oct 16, 2022 18:22
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 on

efeas, Egypt
Posts: 0
4 months ago
Sep 20, 2022 12:39

S&P 500 Inclusion Criteria
The S&P 500 was created in 1957 and is one of the most widely quoted stock market indexes. S&P 500 stocks represent the largest publicly-traded companies in the U.S. The S&P 500 focuses on the U.S. market's large-cap sector.
An S&P 500 company must meet a broad set of criteria to be added to the index, including the following:

A total market capitalization of at least $14.6 billion
Must be a U.S. company
Must have a public float of at least 10% of its equity shares outstanding
A positive sum of the most recent four consecutive quarters of trailing earnings
Positive earnings for its most recent quarter
Must meet certain liquidity requirements

Companies may be removed from the S&P 500 if they deviate substantially from these standards.

$40.3 trillion
The total combined market cap of the 500 companies in the S&P 500 as of March 31, 2022.
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S&P 500 Calculation
The S&P 500 is a free-float market capitalization-weighted index. Market capitalization (or market cap) represents the total dollar market value of a company's outstanding equity shares. Market cap is calculated by multiplying the total number of outstanding shares of stock by the company's current stock price.
For example, a company with 20 million shares outstanding in which its stock is selling for $100 per share would have a market cap of $2 billion.

As a result, the more valuable an individual company's stock becomes, the more it contributes to the S&P 500's overall return. It is not uncommon for three-quarters of the index's return to be linked to only 50 to 75 stocks.

Therefore, the addition or subtraction of smaller companies from the index will not have a noticeable impact on the overall return of the index. However, the removal or addition of even just one of the largest stocks can have a major impact.

S&P 500 Sector Breakdown
Below are the top sectors and their weightings within the S&P 500 index as of March 31, 2022.

S&P 500 Sector Weighting
Sector Index Weighting
Information Technology 28.0%
Health Care 13.6%
Consumer Discretionary 12.0%
Financials 11.1%
Communication Services 9.4%
Industrials 7.9%
Consumer Staples 6.1%
Energy 3.9%
Utilities 2.7%
Real Estate 2.7%
Materials 2.6%
Source: S&P Dow Jones Indices
Being aware of the S&P's sector weighting is important because sectors with a smaller weighting may not have a material impact on the value of the overall index—even if they're outperforming or underperforming the market.

For example, if oil prices are rising, leading to increased profits for the energy sector, those stocks represent only 3.9% of the S&P 500. As a result, oil stocks may not lead to a higher S&P if, for example, the more heavily weighted information technology sector is underperforming.

S&P 500 components are weighted by free-float market capitalization, which means that larger companies can affect the value of the index to a greater degree.
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Top 25 Components by Market Cap
Because the exact weightings of the top 25 components are not available from S&P directly, the weightings below are from the SPDR S&P 500 Trust ETF (SPY). SPY is the oldest exchange traded fund (ETF) that tracks the S&P 500 and holds over $419 million in assets under management (AUM) and is highly traded.

As a result, the SPY's portfolio weightings provide a good proxy for investing in the underlying S&P 500 index, although the two may not be exactly the same. As of April 1, 2022, the following are the 25 largest S&P 500 index constituents by weight:

Apple (AAPL): 7.14%
Microsoft (MSFT): 6.1%
Amazon (AMZN): 3.8%
Tesla (TSLA): 2.5%
Alphabet Class A (GOOGL): 2.2%
Alphabet Class C (GOOG): 2.1%
NVIDIA Corporation (NVDA): 1.8%
Berkshire Hathaway Class B (BRK.B): 1.7%
Meta (META), formerly Facebook, Class A: 1.4%
UnitedHealth Group (UNH): 1.2%
Johnson & Johnson (JNJ): 1.2%
JPMorgan Chase (JPM): 1.0%
Visa Class A (V): 1.0%
Procter & Gamble (PG): 1.0%
Exxon Mobil (XOM): 0.90%
Home Depot (HD): 0.8%
Chevron Corporation (CVX): 0.80%
Mastercard Inc. Class A (MA): 0.8%
Bank of America (BAC): 0.8%
AbbVie Inc. (ABBV): 0.7%
Pfizer (PFE): 0.7%
Broadcom Inc. (AVGO): 0.7%
Costco (COST): 0.7%
Walt Disney (DIS): 0.7%
Coca-Cola Company (KO): 0.6%
How Many Companies Are in the S&P 500?
There are 500 companies within the S&P 500 index. However, there are 505 stocks since some companies have multiple classes of equity shares, such as Alphabet and Berkshire Hathaway.

What Are the Top 10 Holdings in the S&P 500?
As of April 1, 2022, the top ten holdings and their weighting in the index are:

Apple (AAPL): 7.14%
Microsoft (MSFT): 6.1%
Amazon (AMZN): 3.8%
Tesla (TSLA): 2.5%
Alphabet Class A (GOOGL): 2.2%
Alphabet Class C (GOOG): 2.1%
NVIDIA Corporation (NVDA): 1.8%
Berkshire Hathaway Class B (BRK.B): 1.6%
Meta (META), formerly Facebook, Class A: 1.4%
UnitedHealth Group (UNH): 1.2%
How Are Companies Selected for the S&P 500?
efeas, Egypt
Posts: 0
4 months ago
Sep 12, 2022 21:29
In Thread: EUR
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").
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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