Replies to post #375 on $THE CRYPTOCURRENCY FORUM

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Elliott Wave Principle and Basic Tenets
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The Wave Principle is governed by man’s social nature, and since he has such a nature, its expression generates forms. As the forms are repetitive, they have predictive value.

Sometimes the market appears to reflect outside conditions and events, but at other times it is entirely detached from what most people assume are causal conditions. The reason is that the market has a law of its own. It is not propelled by the external causality to which one becomes accustomed in the everyday experiences of life. The path of prices is not a product of news. Nor is the market the cyclically rhythmic machine that some declare it to be. Its movement reflects a repetition of forms that is independent both of presumed causal events and of periodicity.
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The market’s progression unfolds in waves. Waves are patterns of directional movement. More specifically, a wave is any one of the patterns that naturally occur, as described in the rest of this chapter.

The Five Wave Pattern
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In markets, progress ultimately takes the form of five waves of a specific structure. Three of these waves, which are labeled 1, 3 and 5, actually effect the directional movement. They are separated by two countertrend interruptions, which are labeled 2 and 4, as shown in Figure 1-1. The two interruptions are apparently a requisite for overall directional movement to occur.

Elliott noted three consistent aspects of the five-wave form. They are: Wave 2 never moves beyond the start of wave 1; wave 3 is never the shortest wave; wave 4 never enters the price territory of wave 1.

R.N. Elliott did not specifically say that there is only one overriding form, the “five-wave” pattern, but that is undeniably the case. At any time, the market may be identified as being somewhere in the basic five-wave pattern at the largest degree of trend. Because the five-wave pattern is the overriding form of market progress, all other patterns are subsumed by it.
1.3 Wave Mode
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There are two modes of wave development: motive and corrective. Motive waves have a five-wave structure, while corrective waves have a three-wave structure or a variation thereof. Motive mode is employed by both the five-wave pattern of Figure 1-1 and its same-directional components, i.e., waves 1, 3 and 5. Their structures are called “motive” because they powerfully impel the market. Corrective mode is employed by all countertrend interruptions, which include waves 2 and 4 in Figure 1-1. Their structures are called “corrective” because each one appears as a response to the preceding motive wave yet accomplishes only a partial retracement, or “correction,” of the progress it achieved. Thus, the two modes are fundamentally different, both in their roles and in their construction, as will be detailed throughout this chapter.
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Figure 1-1
The Complete Cycle
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One complete cycle consisting of eight waves, then, is made up of two distinct phases, the five-wave motive phase (also called a “five”), whose subwaves are denoted by numbers, and the threewave corrective phase (also called a “three”), whose subwaves are denoted by letters. Just as wave 2 corrects wave 1 in Figure 1-1, the sequence A, B, C corrects the sequence 1, 2, 3, 4, 5 in Figure 1-2.

Figure 1-2
Compound Construction
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When an initial eight-wave cycle such as shown in Figure 1-2 ends, a similar cycle ensues, which is then followed by another five-wave movement. This entire development produces a fivewave pattern of one degree (i.e., relative size) larger than the waves of which it is composed. The result is shown in Figure 1-3 up to the peak labeled (5). This five-wave pattern of larger degree is then corrected by a three-wave pattern of the same degree, completing a larger full cycle, depicted as Figure 1-3.
As Figure 1-3 illustrates, each same-direction component of a motive wave (i.e., wave 1, 3 and 5), and each full-cycle component (i.e., waves 1 + 2, or waves 3 + 4)of a cycle, is a smaller version of itself.
It is neccessary to understand a crucial point: Figure 1-3 not only illustrates a larger version of Figure 1-2, it also illustrates Figure 1-2 itself, in greater detail. In Figure 1-2, each subwave 1, 3 and 5 is a motive wave that must subdivide into a "five," and each subwave 2 and 4 is a corrective wave that must subdivide into a "three." Waves (1) and (2) in Figure 1-3, if examined under a "microscope," would take the same form as waves ? and ?. Regardless of degree, the form is constant. We can use Figure 1-3 to illustrate two waves, eight waves or thirty-four waves, depending upon the degree to which we are referring.
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Figure 1-3

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Wave Personality
The idea of wave personality is a substantial expansion of the Wave Principle. It has the advantage of bringing human behavior more personally into the equation.
free forex signals and The personality of each wave in the Elliott sequence is an integral part of the reflection of the mass psychology it embodies. The progression of mass emotions from pessimism to optimism and back again tends to follow a similar path each time around, producing similar circumstances at corresponding points in the wave structure. As the Wave Principle indicates, market history repeats but not exactly. Every wave has siblings (same-directional waves of the same degree within a larger wave) and cousins (samedegree and same-numbered waves within different larger waves) but no wave has a twin. Related waves — particularly cousins — have similar market and social characteristics. The personality of each wave type is manifest whether the wave is of Grand Supercycle degree or Subminuette. Waves’ properties not only forewarn what to expect in the next sequence but at times can help determine the market’s present location in the progression of waves, when for other reasons the count is unclear or open to differing interpretations. As waves are in the process of unfolding, there are times when several different wave counts are perfectly admissible under all known Elliott rules. It is at these junctures that a knowledge of wave personality can be invaluable. Recognizing the character of a single wave can often allow you to interpret correctly the complexities of the larger pattern. The following discussions relate to an underlying bull market picture, as illustrated in Figures 2-14 and 2-15. These observations apply in reverse when the actionary waves are downward and the reactionary waves are upward.
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1) First waves — As a rough estimate, about half of first waves are part of the "basing" process and thus tend to be heavily corrected by wave two. In contrast to the bear market rallies within the previous decline, however, this first wave rise is technically more constructive, often displaying a subtle increase in

Figure 2-14
volume and breadth. Plenty of short selling is in evidence as the majority has finally become convinced that the overall trend is down. Investors have finally gotten "one more rally to sell on," and they take advantage of it. The other fifty percent of first waves rise from either large bases formed by the previous correction, as in 1949, from downside failures, as in 1962, or from extreme compression, as in both 1962 and 1974. From such beginnings, first waves are dynamic and only moderately retraced.
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2) Second waves — Second waves often retrace so much of wave one that most of the profits gained up to that time are eroded away by the time it ends. This is especially true of call option purchases, as premiums sink drastically in the environment of 79 fear during second waves. At this point, investors are thoroughly convinced that the bear market is back to stay. Second waves often end on very low volume and volatility, indicating a drying up of selling pressure.
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3) Third waves — Third waves are wonders to behold. They are strong and broad, and the trend at this point is unmistakable. Increasingly favorable fundamentals enter the picture as confidence returns. Third waves usually generate the greatest volume and price movement and are most often the extended wave in a series. It follows, of course, that the third wave of a third wave, and so on, will be the most volatile point of strength in any wave sequence. Such points invariably produce breakouts, "continuation" gaps, volume expansions, exceptional breadth, major Dow Theory trend confirmations and runaway price movement, creating large hourly, daily, weekly, monthly or yearly gains in the market, depending on the degree of the wave. Virtually all stocks participate in third waves. Besides the personality of B waves, that of third waves produces the most valuable clues to the wave count as it unfolds.
4) Fourth waves — Fourth waves are predictable in both depth (see page 66) and form, because by alternation they should differ from the previous second wave of the same degree. More often than not they trend sideways, building the base for the final fifth wave move. Lagging stocks build their tops and begin declining during this wave, since only the strength of a third wave was able to generate any motion in them in the first place. This initial deterioration in the market sets the stage for non-confirmations and subtle signs of weakness during the fifth wave.
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5) Fifth waves — Fifth waves in stocks are always less dynamic than third waves in terms of breadth. They usually display a slower maximum speed of price change as well, although if a fifth wave is an extension, speed of price change in the third of the fifth can exceed that of the third wave. Similarly, while it is common for volume to increase through successive impulse waves at Cycle degree or larger, it usually happens in a fifth wave below Primary degree only if the fifth wave extends. Otherwise, look for lesser volume as a rule in a fifth wave as opposed to the third. Market dabblers sometimes call for "blowoffs" at the end of long trends, but the stock market has no history of reaching maximum acceleration at a peak. Even if a fifth wave extends, the fifth of the fifth will lack the dynamism that preceded it. During advancing fifth waves, optimism runs extremely high despite a narrowing of breadth. Nevertheless, market action does improve relative to prior corrective wave rallies. For example, the year-end rally in 1976 was unexciting in the Dow, but it was nevertheless a motive wave as opposed to the preceding corrective wave advances in April, July and September, which, by contrast, had even less influence on the secondary indexes and the cumulative advance-decline line. As a monument to the optimism that fifth waves can produce, the advisory services polled two weeks after the conclusion of that rally turned in the lowest percentage of "bears," 4.5%, in the history of the recorded figures despite that fifth wave’s failure to make a new high!
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6) A waves — During the A wave of a bear market, the investment world is generally convinced that this reaction is just a pullback pursuant to the next leg of advance. The public surges to the buy side despite the first really technically damaging cracks in individual stock patterns. The A wave sets the tone for the B wave to follow. A five-wave A indicates a zigzag for wave B, while a three-wave A indicates a flat or triangle.
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7) B waves — B waves are phonies. They are sucker plays, bull traps, speculators’ paradise, orgies of odd-lotter mentality or expressions of dumb institutional complacency (or both). They often involve a focus on a narrow list of stocks, are often "unconfirmed" (see Dow Theory discussion in Chapter 7) by other averages, are rarely technically strong, and are virtually always doomed to complete retracement by wave C. If the analyst can easily say to himself, "There is something wrong with this market," chances are it’s a B wave. X waves and D waves in expanding triangles, both of which are corrective wave advances, have the same characteristics. Several examples will suffice to illustrate the point.
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GBP USD
SELL from 1.2460
Take profit 1.2300
Stop loss 1.2540
type order Market Execution is entering this trade at any price from 1.2460
technical analysis and forex signals for GBP USD
waves in the same direction will tend toward equality SO GBPUSD WILL resume bearish wave to level 1.2130
Riding Wave C in a Zigzag
Trend continues till gives a reversal signal
on hourly chart the Last wave determine the end of the pattern and Consists of zigzag that generate sell GBPUSD forex signals
reversal candlestick pattern on daily chart is shooting star
The price behavior is the result of Environmental pattern
Current surrounding Repetitive pattern is zigzag Wave C = 1.618 Wave A
History Repeats Itself that the future is just a repetition of the past
The bearish movement from level 1.3510 to level 1.1410 appeared before on price chart at 19-6-2015 and followed with bullish movement equal the current bullish movement from level 1.2240 to 1.2520 that give forex trading signals to sell GBP USD and according to this movement GBP USD will decline to 1.0580
Also The bearish movement from level 1.2650 to level 1.2240 appeared before on price chart at 9-7-2018 and followed with bullish movement equal the current bullish movement from level 1.1410 to 1.2650 that give forex trading signals to sell GBP USD so the gbp usd will decline near to level 1.1970
surrounding Repetitive pattern before this movement expanded flat Wave C = 1.618 Wave A
We expect price will repeat the same movement again and gbp usd price will go down toward 1.1970
Maybe the correction equal only one wave of previous correction
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Asset Allocation and Diversification
The term "asset allocation" is often used to describe a money management strategy that defines how capital is distributed within an investment portfolio and Forex Signals . This usually includes specifying the amount of the portfolio that should be distributed to different asset classes, or broad types of investments such as stocks, bonds, commodities, and cash. The goal of asset allocation is to improve the mix of investments in different asset classes in order to maximize the return on the investment portfolio while minimizing potential risks, based on the investor’s time frame, risk tolerance, and long-term investment goals. There is evidence to suggest that certain classes of assets work better or worse depending on economic conditions, market forces, government policy, and political influence. The goal of an asset allocation strategy is to define these terms and allocate resources appropriately.
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The concept that is closely related to asset allocation is "diversification", and in practice these terms are often used interchangeably. However, asset allocation is primarily concerned with capital allocation in different asset classes. For example, a typical asset allocation strategy might dictate that your portfolio must invest 50% in stocks, 30% invest in bonds, 10% in commodities, and 10% in cash. Diversification is usually associated with capital allocation within these asset classes. For example, within allocating shares to the same portfolio, investments can be allocated to 50% of shares of large companies, 20% of shares of medium-sized companies, 10% of shares of small companies, 10% of international shares, and 10% of market shares Emerging. The concept of diversification involves the allocation of assets within individual asset classes - while risks are distributed among asset classes in the overall portfolio, diversification reduces the risk within each asset class.

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Asset distribution date
Using asset allocation strategies as a form of risk management is not a new concept. The idea of "not to put all your eggs in one basket" is something we learned when we were young and lived in for thousands of years. However, the term asset allocation was not present in the investment community until recently. Even before the emergence of modern financial markets, people understood that one's assets must be divided between different categories such as land, business ownership, and (cash) reserves. Until the mid-twentieth century, this concept of asset allocation as a fact of life remained relatively unchanged.
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So what has changed to create the asset allocation models that we know today? In 1952, an American economist named Harry Markowitz wrote a paper in the finance magazine called "Portfolio Selection," in which he developed the first mathematical model that emphasizes volatility in the portfolio by combining investments and different yield patterns. This paper was the basis for what would have become a standard in portfolio management known as "modern portfolio theory".

Before Markowitz contributed to asset allocation to equity portfolios, diversification was a process that focused on the yield and risk characteristics of individual securities regardless of how the returns relate to each other. After Markowitz invented his mathematical models for wallet construction, his ideas soon became accepted in academia. A large number of research papers have been published to verify the benefits of asset allocation and have quickly become popular with financial professionals as well.
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In 1974, the Employees Retirement Income Guarantee Act (ERISA) was enacted as a federal law setting minimum standards for investment allocations in pension plans. After ERISA became law, asset allocation and modern portfolio theory became standard practices for portfolio managers required to comply with the law when allocating invested capital in pension plans.
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Modern Portfolio Theory and Concepts (MPT)
The modern portfolio theory (MPT) has greatly influenced the way investment portfolio managers create portfolios. The concept of MPT is fairly straightforward. However, it requires the investor to make several assumptions about the financial markets; In addition, the mathematical equations used to calculate correlation and risk can be somewhat complicated.
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The basic premise of MPT is simple: by bringing together securities of different asset classes that are not closely related, one can reduce portfolio volatility and increase risk-adjusted performance. In other words, a combination of unrelated assets will lead to the most efficient portfolio - the portfolio that yields the greatest return for a given amount of risk.
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Returns of assets do not have to be passively or even disconnected to provide diversification benefits, as they cannot be fully correlated. For example, in the chart below, international stocks (as represented by the EAFE index) are compared to US domestic shares (as represented by the S&P 500). Using the correlation coefficient, you can see that the relationship is positive for most of the five-year period. However, it is not completely correlated (i.e. a correlation coefficient of 1.0).


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There are periods of low to negative correlation received during this time period. By investing in both US domestic stocks and international stocks, general volatility can be reduced as the correlation varies enough between the two asset classes to provide meaningful diversification. The MPT concept demonstrates that adding a volatile asset to a portfolio can reduce overall volatility if returns have differences in correlation. This is an intriguing concept - portfolio volatility can generally be minimized by bringing together asset classes together which, in themselves, have returns with higher volatility.
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The assumption is that by combining asset classes that are not fully correlated when one asset’s value declines, the value of another asset in the portfolio increases over the same time period. So even if all asset classes themselves are very volatile, when combined into one portfolio, volatility is reduced.
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The extreme example of negative correlation is shown in the following chart of the US dollar compared to the price of gold over the past five years. If the investor had invested in these two volatile assets together, the overall volatility of the portfolio would have decreased significantly due to the negative correlation.

As mentioned earlier, the MPT requires that the investor make some assumptions about financial markets in order to calculate the potential benefits of the theory. The main assumptions are that ...

Financial markets are efficient.
Market returns are distributed randomly.
Investors are rational.
These assumptions are necessary to accurately calculate standard deviation and correlation using the normal distribution or bell curve.

By using the normal distribution function (which determines risk as the standard deviation of return), the risk and the correlation can be calculated mathematically for individual assets as well as portfolios. However, if the markets are in fact not fully effective, the returns to the assets do not necessarily follow the normal distribution and the correlation accounts and risks used in the MPT may be flawed. With the extreme market volatility seen during the dot com bubble in the early 2000s and the 2008-2009 financial crisis, the assumptions used in the MPT have been largely examined.

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The Framing Effect and Confirmation Bias
The framing effect describes our tendency to react to, judge, or interpret the exact same information in distinctly different ways depending on how it is presented to us, or “framed” (most commonly, whether the information is framed as a loss or as a gain). Building off of the previously discussed concepts of loss aversion and Prospect Theory, people tend to avoid risk when information is presented in a positive frame but seek risk when information is presented in a negative frame.
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The most commonly cited example of this is a 1981 Tversky and Kahneman study that asked participants to choose between two treatments, A and B, for 600 people affected by a deadly disease. Treatment A was predicted to result in a guaranteed total of 400 deaths, while treatment B had a 33% chance that no one would die but a 66% chance that everyone would die. The same two alternatives were then presented to the study's participants either under a positive frame (how many peoples' lives would be saved) or under a negative frame (how many people would die).
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When the alternatives were framed positively, 72% of participants chose Treatment A (“saves 200 lives”). When the exact same alternatives were framed negatively, however, only 22% of participants chose Treatment A (now presented as “400 people will die”). Saving 200 of the 600 lives is the exact same outcome as letting 400 of the 600 die, but the manner in which this identical treatment option was framed resulted in a massive decrease in the number of participants who chose it. Under the positive frame, the majority of participants avoided risk by choosing the treatment that resulted in a sure saving of 200 lives. Under the negative frame, however, the majority of participants sought the riskier alternative treatment that offered a 33% chance of saving all 600 lives.
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Another famous example that demonstrates the impact of framing is a study that found 93% of PhD students registered for classes early when a penalty fee for late registration was emphasized, but only 67% did so when the same number was presented as a discount for early registration.
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It is no secret that investors in the financial markets are under a constant barrage of information from all different sides - bullish, bearish, and everything in between. The exact same information can be framed by multiple sources in many different ways, biasing your interpretation of it. As you filter the stream of news and financial data that comes your way, consider the manner in which those numbers, statistics or reports are framed and think about the impact that their presentation has on the opinions they lead you to form.
Confirmation Bias and Forex Signals
Confirmation bias is the tendency to overweight, favor, seek out, exaggerate or more readily recall information or alternatives in a way that confirms our preconceived beliefs, hypotheses or desires, while simultaneously undervaluing, ignoring or otherwise giving disproportionately less consideration to information or alternatives that do not confirm our preconceived beliefs, hypotheses or desires. This inherent flaw in our cognitive reasoning leads to misconstrued interpretations of information, errors in judgment, and poor decision making. The effects of confirmation bias have been shown to be much stronger for emotionally-charged issues or beliefs that are deeply entrenched. In addition to overvaluing information that confirms our preexisting beliefs, confirmation bias also includes our tendency to interpret ambiguous evidence as supporting existing positions, even if no true relationship exists. In short, this concept says that individuals are biased towards information that confirms their existing beliefs and biased against information that disproves their existing beliefs, leading to overconfidence in our opinions and our decisions even in the face of strong contrary evidence.
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As an investor in the financial markets, it can be difficult to maintain a separation between informed estimates or expectations and emotional judgments based on hopes or desires. By causing us to overweight information that confirms such hopes or desires, confirmation bias can affect our abilities to make sound assessments and form well-reasoned opinions about, for example, a stock's upside potential. Awareness of our natural biases towards confirming information and, perhaps more importantly, our biases against disproving information is the first step in combating the unwanted effects of confirmation bias.
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Hindsight Bias and the Availability Heuristic
Hindsight bias describes our inclination, after an event has occurred, to see the event as having been predictable, even if there had been little to no objective basis for predicting it. This is the psychological tendency that causes us, after witnessing or experiencing the outcome of even an entirely unforeseeable event, to exclaim “I knew it all along!”

The discovery of hindsight bias emerged during the early 1970s as the field of psychology witnessed an expansion of investigations into heuristics and biases, largely led by Amos Tversky and Daniel Kahneman. Along with the uncovering of tendencies such as the hindsight bias came the discovery of the availability heuristic, a common mental shortcut that causes individuals to rely on immediate information or examples that come to mind first when evaluating a specific topic, concept, method or decision. According to the cognitive reasoning behind the availability heuristic, if something can be recalled, it must be important, or at least more so than alternatives that are not as readily recalled. As a result, individuals tend to more heavily weight recent or immediately-recalled information, creating a bias towards the latest news, events, experiences or memories.
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The Sunk Cost Fallacy
The sunk cost fallacy rests on the economic concept of a sunk cost: a cost that has already been incurred and cannot be recovered. While theoretical economics says that only future (prospective) costs are relevant to an investment decision and that rational economic actors therefore should not let sunk costs influence their decisions, the findings of psychological and behavioral finance research show that sunk costs do in fact affect real-world human decision making. Because of our tendencies towards Loss Aversion and other cognitive biases, we fall victim to the sunk cost fallacy, which describes our irrational belief that sunk costs should be considered a legitimate factor in our forward decision making when, in fact, their consideration often leads us towards inefficient outcomes.
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For example, let's say a gentleman named Fred is concerned about his weight and decides to go on a diet. As part of his cleanse, he empties his fridge of all tasty temptations. When he comes across an unopened tub of ice cream, however, he falls victim to the Sunk Cost Fallacy. Even though the $15.00 Fred spent on the ice cream is a sunk cost that has already been incurred and cannot be recovered, Fred convinces himself that he cannot let the ice cream go to waste because he previously spent his hard-earned dollars to buy it. Eating a full tub of ice cream is in no way in line with his current weight-loss objectives, as the calories he will take in by consuming it are many times the daily total target of his new diet. Still, despite the adverse consequences for his health goals, Fred is swayed into eating the ice cream because of the Sunk Cost Fallacy.
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In an investment setting, the consequences of the sunk cost fallacy can be much more severe than some unwanted calories. As the share price of a security falls, investors often begin to employ the logic that “I've already lost $XXX, it's too late to sell now.” As prices keep falling further and losses grow, the investor's commitment to the sunk cost continues to escalate. “Now I’ve lost $XXXXX, there's no way I can sell now. It has to come back eventually. I'll just hold on to it.” Improper or irrational considerations of sunk costs can lead to poor decisions that continue to spiral out of control, simply because of an incorrect perception of an expense that is irrecoverable.
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The Gambler's Fallacy
The gambler's fallacy, also known as the Monte Carlo Fallacy, is the mistaken tendency to believe that, if something happens more frequently than “normal” during a period of time, it must happen less frequently in the future, or that, if something happens less frequently than “normal” during a period of time, it must happen more frequently in the future. This tendency presumably arises out of an ingrained human desire for nature to be constantly balanced or averaged. In situations where the event being observed or measured is truly random (such as the flip of a coin), this belief, although appealing to the human mind, is false.
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The gambler's fallacy is, rather obviously, most strongly associated with gambling, where such errors in judgment and decision making are common. It can, however, arise in many practical situations, including investing. Winning and losing trades are in many ways similar to the flip of a coin and thus subject to the same psychological biases. If an investor has a series of losing trades, for example, he or she can begin to erroneously believe that, since the statistics feel unbalanced, his or her probability of making a profitable trade increases. In reality, the probability of his or her next trade being profitable is unaffected by previous losses.
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Over 2.4 million people track their finances using personal capital, which includes more than 22,000 investment clients in all US states (as of December 2019). 1 Sync almost any investment account, including retirement and taxable accounts, then track Performance and customization, and graphics with easy-to-read graphs and charts. Track investments by account, asset class, or individual security. The You Index tracks your holdings and measures their performance against major market indices, so you can see your progress in stocks, cash, ETFs and mutual funds positions.

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The portfolio check feature determines whether you can save money on mutual fund fees, and the asset allocation review reveals diversification opportunities. Work with a personal wealth management advisor to discuss your investment needs via FaceTime, email or phone. Bank-wide app security uses a two-step remote authentication process.
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Mobile portfolio management apps can provide information on your investments from 401K (s) to IRAs.
Some wallet management apps can sync with your existing accounts, and most are free.
Some of the more popular apps include SigFig Wealth Management, Personal Capital, and Stocks Portfolio Manager.
SigFig Wealth Management
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Use the wealth management app of investment company SigFig to track all of your investment accounts for free. SigFig automatically pulls your investment accounts from more than 50 leading brokers into a single dashboard to provide you with a real-time view of every stock, mutual fund, ETF, and option you own. 2 In addition, it provides snapshots of the 401 (k)) plan. And IRAs. You'll get weekly email summaries of account performance, news affecting your portfolio, and alerts focused on the top gainers and losers.

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The app automatically analyzes your portfolio to find hidden charts and overexposures for a single stock / industry. For a fee, users can improve their returns through automated investing. SigFig will optimize your portfolio and provide daily monitoring to keep it on track through rebalancing, profit reinvestment and tax-efficient strategies.
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Tape: a stock portfolio manager
Platform: iOS, cost: free
Ticker lets you manage multiple equity portfolios - think growth, technology, and retirement portfolios - from one dashboard. Color charts, graphs, and detailed analyzes display real-time account values, daily profit / loss, daily profit / loss, customization, money weighted return rate (MWRR), time-weighted rate of return (TWRR), plus news related to symbols. Manually enter trading information for stocks and currency pairs such as EUR / USD, mutual funds and ETFs, including dividends, splits, buy / sell orders, indicator symbol, trading volume, price, date, and brokerage fees. Track stocks with multiple watchlists, and create alerts to notify you if a stock is trading above or below the stimulus level you selected, based on price, volume, and percentage of changes.

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Hey ho! Financial
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Hey ho! Finance has an easy-to-use design, so you can easily track your stocks, commodities, bonds, and currencies.4 Get personalized news and alerts and follow market movements in real time. Set watchlists and get live quotes while monitoring your portfolio performance.

Hey ho! Finance is one of the largest business news sites in the United States with data, comments, and press releases within its daily content. Of course, Yahoo! Finance app users also have quick access to this urgent information at a glance.

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Portfolio management apps easily track your investments from anywhere, anytime. Some apps sync with your existing accounts, while others require you to manually enter information about your assets. Either way, these apps provide the most up-to-date information - so you know where you stand now - as well as provide tools to help you get where you want to be in the future.

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Understanding Fundamentals
In business and economics, fundamentals represent the primary characteristics and financial data necessary to determine the stability and health of an asset. This data can include macroeconomic, or large-scale factors, and microeconomic, or small-scale factors to set a value on securities or businesses.
Analysts and investors examine these fundamentals to develop an estimate as to whether the underlying asset is considered a worthwhile investment, and if there is fair valuation in the market. For businesses, information such as profitability, revenue, assets, liabilities, and growth potential are considered fundamentals. Through the use of fundamental analysis, you may calculate a company's financial ratios to determine the feasibility of the investment.
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While fundamentals are most often considered factors that relate to particular businesses or securities, national economies, and their currencies also have a set of fundamentals that can be analyzed. For example, interest rates, gross domestic product (GDP) growth, trade balance surplus/deficits, and inflation levels are some factors that are considered to be fundamentals of a nation's value.
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Macroeconomic and Microeconomic Fundamentals
Macroeconomic fundamentals are topics that affect an economy at-large, including statistics regarding unemployment, supply and demand, growth, and inflation, as well as considerations for monetary or fiscal policy and international trade. These categories can be applied to the analysis of a large-scale economy as a whole or can be related to individual business activity to make changes based on macroeconomic influences. Large scale, macroeconomic fundamentals are also part of the top-down analysis of individual companies.
Microeconomic fundamentals focus on the activities within smaller segments of the economy, such as a particular market or sector. This small-scale focus can include issues of supply and demand within the specified segment, labor, and both consumer and firm theories. Consumer theory investigates how people spend within their particular budget restraints. The theory of the firm states that a business exists and makes decisions to earn profits.
Fundamentals in Business
By looking at the economics of a business, including the overall management and the financial statements, investors are looking at a company's fundamentals. Not only do these data points show the health of the business, but they also indicate the probability of further growth. A company with little debt and sufficient cash is considered to have strong fundamentals.
Strong fundamentals suggest that a business has a viable framework or financial structure. Conversely, those with weak fundamentals may have issues in the areas of debt obligation management, cost control, or overall organizational management. A business with strong fundamentals may be more likely to survive adverse events, like economic recessions or depressions, than one with weaker fundamentals. Also, strength may indicate less risk should an investor consider purchasing securities associated with the businesses mentioned.
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Fundamental Analysis
Investors and financial analysts are interested in evaluating the fundamentals of a company to compare its economic position relative to its industry peers, to the broader market, or to itself over time. Fundamental analysis involves digging deep into a company's financial statements to extract its profit and growth potential, relative riskiness, and to ultimately decide if its shares are over, under, or fairly valued in the market.
Often fundamental analysis involves computing and analyzing ratios to make apples-to-apples comparisons. Some common fundamental analysis ratios are listed below.
The debt-to-equity ratio (DE) measures how a company is financing its operations.
The quick ratio measures the company’s ability to meet its short-term obligations.
The degree of financial leverage (DFL) measures the stability or volatility of the earnings per share (EPS).
The price-to-earnings (P/E) ratio compares investment to earnings dollars.
The DuPont analysis looks at return on equity (ROE) by looking at asset use efficiency, operating efficiency, and financial leverage.
Fundamental analysis should be carried out with a holistic approach, utilizing several ratios and including a bottom-up as well as a top-down analysis to come to specific conclusions and actions.
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Real World Example
In the fourth quarter of 2018, according to Market Watch, large-cap tech companies Microsoft and Apple had similar market caps for the first time since 2010. Although the two companies had similar market caps of about $850 billion, they had very different fundamentals. For example, Microsoft was trading at 45X earnings while Apple was trading at 15X earnings.1