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What Is the Best Method of Analysis for Forex Trading?
Forex analysis is used by retail forex day traders to determine to buy or sell decisions on currency pairs. It can be technical in nature, using resources such as charting tools. It can also be fundamental in nature, using economic indicators and/or newsbased events.
Types of Forex Market Analysis
Analysis can seem like an ambiguous concept to a new forex trader. But it actually falls into three basic types.
Fundamental Analysis
Fundamental analysis is often used to analyze changes in the forex market by monitoring figures, such as interest rates, unemployment rates, gross domestic product (GDP), and other types of economic data that come out of countries. For example, a trader conducting a fundamental analysis of the EUR/USD currency pair would find information on the interest rates in the Eurozone more useful than those in the U.S. Those traders would also want to be on top of any significant news releases coming out of each Eurozone country to gauge the relation to the health of their economies.
Technical Analysis
The technical analysis comes in the form of both manual and automated systems. A manual system typically means a trader is analyzing technical indicators and interpreting that data into a buy or sell decision. An automated trading analysis means that the trader is “teaching” the software to look for certain signals and interpret them into executing buy or sell decisions. Where automated analysis could have an advantage over its manual counterpart is that it is intended to take the behavioral economics out of trading decisions. Forex systems use past price movements to determine where a given currency may be headed.
Weekend Analysis
There are two basic reasons for doing a weekend analysis. The first reason is that you want to establish a “big picture” view of a particular market in which you are interested. Since the markets are closed and not in dynamic flux over the weekend, you don’t need to react to situations as they are unfolding, but can survey the landscape, so to speak.
Secondly, the weekend analysis will help you to set up your trading plans for the coming week, and establish the necessary mindset. A weekend analysis is akin to an architect preparing a blueprint to construct a building to ensure a smoother execution. Tempted to trade without a plan? Bad idea: Shooting from the hip can leave a hole in your pocket.
Applying Forex Market Analysis
It’s important to think critically about the tenets of forex market analysis. Here is a fourstep outline.
1. Understand the Drivers
The art of successful trading is partly due to an understanding of the current relationships between markets and the reasons that these relationships exist. It is important to get a sense of causation, remembering that these relationships can and do change over time.
For example, a stock market recovery could be explained by investors who are anticipating an economic recovery. These investors believe that companies will have improved earnings and, therefore, greater valuations in the future—and so it is a good time to buy. However, speculation, based on a flood of liquidity, could be fueling momentum and good old greed is pushing prices higher until larger players are on board so that the selling can begin.
Therefore the first questions to ask are: Why are these things happening? What are the drivers behind the market actions?
2. Chart the Indexes
It is helpful for a trader to chart the important indexes for each market for a longer time frame. This exercise can help a trader to determine relationships between markets and whether a movement in one market is inverse or in concert with the other.
For example, in 2009, gold was being driven to record highs. Was this move in response to the perception that paper money was decreasing in value so rapidly that there was a need to return to the hard metal or was this the result of cheap dollars fueling a commodities boom? The answer is that it could have been both, or as we discussed above, market movements driven by speculation.

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3. Look for a Consensus in Other Markets
We can gain a perspective of whether or not the markets are reaching a turning point consensus by charting other instruments on the same weekly or monthly basis. From there, we can take advantage of the consensus to enter a trade in an instrument that will be affected by the turn. For example, if the USD/JPY currency pair indicates an oversold position and that the Bank of Japan (BOJ) could intervene to weaken the yen, Japanese exports could be affected. However, a Japanese recovery is likely to be impaired without any weakening of the yen.
4. Time the Trades
There is a much higher chance of a successful trade if one can find turning points on the longer timeframes, then switch down to a shorter time period to finetune an entry. The first trade can be at the exact Fibonacci level or double bottom as indicated on the longerterm chart, and if this fails then a second opportunity will often occur on a pullback or test of the support level.
Patience, discipline, and preparation will set you apart from traders who simply trade on the fly without any preparation or analysis of multiple forex indicators.
Acquiring Forex Trading Systems and Strategies
A day trader’s currency trading system may be manually applied, or the trader may make use of automated forex trading strategies that incorporate technical and fundamental analysis. These are available for free, for a fee or can be developed by more techsavvy traders.
Both automated technical analysis and manual trading strategies are available for purchase through the internet. However, it is important to note that there is no such thing as the “holy grail” of trading systems in terms of success. If the system was a failproof money maker, then the seller would not want to share it. This is evidenced in how big financial firms keep their “black box” trading programs under lock and key.
The Bottom Line
There is no “best” method of analysis for forex trading between technical and fundamental analysis. The most viable option for traders is dependent on their time frame and access to information. For a shortterm trader with only delayed information to economic data, but realtime access to quotes, technical analysis may be the preferred method. Alternatively, traders that have access to uptotheminute news reports and economic data may prefer fundamental analysis. In either case, it does not hurt to conduct a weekend analysis when the markets are not in a constant state of fluctuation.
12 data analysis techniques for a trader
Statistical analysis has been used in financial markets for many decades to help take the guesswork out of – or, at least, firm up the “gut feelings” of – some of the top names in investment.
The history of statistics goes back centuries, even millennia – think of biblical censuses and the Domesday Book – the gathering of data for the study of population demographics.
The use of charts and historical data is commonplace in private investment but the use of statistical analysis is more typically associated with quantitative investment and active fund management techniques.
Warren Buffett
The socalled “Oracle of Omaha” Warren Buffett is perhaps best known for his “get greedy when everyone else is scared, and get scared when everyone else is being greedy” line.
But he was a pioneer of analysis – starting out with tips sheets on the racetrack.
He graduated to stock trading, and part of his approach is to work out what price is right for him, compared with what profits that company could be expected to be earning in 10 years.
And there are methods of extrapolating this from historical data using some, or a combination of the techniques listed below.
Buffett’s exdaughter in law, Mary Buffett, wrote in her book on his trading style: “Warren has found, if the company is one of sufficient earning power and earns high rates of return on shareholders’ equity, created by some kind of consumer monopoly, chances are good that accurate longterm projections of earnings can be made.”
Limitations to data analysis techniques
Statistical analysis has its limitations. There’s little room to account for “black swan” events – those sometimes catastrophic occurrences that no amount of number crunching can predict.
And during such periods – as in the volatile market conditions that followed events such as the dotcom bubble, 9/11 and the 2008 financial crisis – statistical analysis becomes something of a blunt tool, its predictive power neutered by unpredictability.
Statistical analysis tools
Below, then, are several techniques in the arsenal of statistical analysis.
We’ve removed most of the hard sums to leave you with just the ideas that make these tools useful.
Should these ideas prompt the desire for a deeper understanding of these types of investment methods, we’ve included further reading list at the end of the article
Measures of central value
There are three measures of central tendency in statistical analysis: the mean, median and mode. All three are summary measures that attempt to best describe a whole set of data in a single value that represents the core of that data set’s distribution.
1. Mode
This is the most commonly occurring value in a data set.
Consider the following data set of the ages of 10 children:
4, 5, 5, 6, 6, 6, 7, 8, 8 and 9
The mode here is 6, as this is the most commonly occurring value. The mode, however, won’t necessarily reflect the central value of a data set. Also, it is possible for there to be two or more modes in a data set or, indeed, no mode at all.
2. Arithmetic mean
The mean is the average value of a data set.
Consider the following data set:
The arithmetic mean is arrived at by adding all the numbers together and then dividing the total by the number of data points in the set.
So, by adding 2+4+5+8+9 = 28, which we then divide by 5 (the number of data points, or numbers, in that set) we arrive at 5.6.
Mean values are useful in many circumstances in business.
Internet shopping sites always ask for your age range when you set up an account. This is not only useful to them, but also to other retailers and manufacturers of goods for targeting advertising to certain age groups.
In investment, particularly for institutions, it’s becoming increasingly important to know the average buying prices at certain times of day to know whether your institution is arriving at best execution on its asset purchases.
3. Median
The media is the middle number in a data set.
Consider the same data set as above:
The median is simply the number in the middle = 5. This is easily arrived at if the data set is an odd number, as above. But what if the data set were:
1, 2, 4, 5, 8 and 9
In the case of data set with an even number of data points, we take the average of the middle two numbers.
So, 4+5/2 gives us a median of 4.5.
Median values are useful in statistical analysis because they are less prone to be skewed by anomalies or other unusual appearances in a data set. Consider the following set:
2, 4, 5, 8 and 798
In reality, such an extraordinary thing isn’t likely to happen in such a small set, but the median of 5 is much more representative of the majority of that data set than the arithmetic mean of 163.4.
Imagine the example of salaries in a company. Let’s say there are three broad ranges of salary: 80% of those salaries are for semiskilled and unskilled workers, while 15% are for skilled workers and supervisors, while just 5% is represented by senior managers and executives.
That top 5% skews the average salary upward.
A semiskilled worker earning £30,000 a year isn’t likely to be impressed to learn that the mean salary where he works is £45,000 a year. He knows he earns more than an unskilled worker, but the mean salary makes his route up the corporate ladder seem a terribly long one.
His salary is likely to be more closely related to the median given the percentage of workers in that group of the data set.
Probability theory
4. Mathematical expectation
This is also called the expected value (EV), is the number in probability theory one may arrive at when a task with random variable outcomes is performed many times – such as rolling a single dice.
The data set here is 1, 2, 3, 4, 5 and 6 and probability of any of those numbers turning up on a single throw is 1 in 6, or 1/6 or, expressed as a decimal, 0.16666.
The mathematical expectation or EV is arrived at by multiplying each of the possible outcomes by the probability of it occurring and adding the sums of all those values. Hence, with a dice roll:
1×0.166666+2×0.16666 . . . +6×0.16666 = 3.5
Simply, the expected value is the arithmetic mean of all possible outcomes, so:
The law of large numbers dictates that the more often the dice is thrown, the nearer the mathematical mean value of those throws approaches EV. This is called convergence.
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In business and investment terms, expected value is used by risk managers in scenario analysis when calculating whether an investment is worth the appropriate level of risk the firm is willing to take on.
The quality and depth of statistical analysis now made possible by computing means EV can be calculated on data sets that were previously regarded as unworkably massive.
These can be of enormous value in helping investment professionals to arrive at forecasts for investment returns, particularly when used in conjunction with measures of variance and standard deviation (see below).
Distribution models
5. Normal distribution
Normal distribution is also called standard normal distribution or Gaussian distribution model.
Normal distribution can be charted along a single horizontal axis that represents the total spectrum of values within a given data set.
Half of that data set will have values that are higher than the mean and half will have values lower than the mean. Most data points will lie close to the mean and the rest will tail off in each direction.
The shape described by plotting this data will be a bell curve, as below.
Normal distribution patterns in historical returns don’t tell an investor that much, other than that the asset is apparently miraculously wellbehaved and that its returns mostly reflect the historical average.
6. Skewness
Skewness measures the symmetry, or asymmetry of distribution.
In a standard normal distribution, as above, the skewness will be zero.
Negative skewness will distort the bell curve to the left and positive skewness will have the opposite effect.
When examining an asset’s annual returns over a period of time, the professional investor will look for investments that show positive skewness – returns that are greater than the historical average.
This has, in some circumstances, proved disastrous for investors, however. When market bubbles form, an asset can show positive skewness, prompting investors to buy at the top of the market. Then, when the skew turns negative, they may be tempted to sell at a loss.
Statistical analysis is only as intuitive as the person using it.
7. Kurtosis
Kurtosis is another measure of deviation from normal distribution, but looks at the extremes. This introduces the wellknown investment term “tail risk”.
A distribution model that is said to have a fat tail is a sign of kurtosis. Tail risk arises when the possibility that an investment could move more than three standard deviations (see below) from the mean is greater than a normal distribution model.
Divergence from the mean
8. Variance
Variance is used as a data analysis tool to examine how each individual value in a set of numbers differs from the arithmetic mean of that data set.
If you take the data set 2, 4, 5, 8 and 9, the arithmetic mean (adding all and dividing by number of data points, i.e. 5) is 5.6. If you simply take the deviation from the mean by subtracting it from each number, i.e.: 2 – 5.6, 4 – 5.6 etc, you get 3.6, 1.6, 0.6, 2.4 and 3.4.
The sum of all these numbers, and any other set of numbers will always be zero. To arrive at the variance, take the difference between each number in the data set and the arithmetic mean and square it. Hence:
3.6x3.6; 1.6x1.6 . . . etc, to arrive at the variance set of 12.96, 2.56, 0.36, 5.76 and 11.56 and then take a new arithmetic mean of this new set. The variance is therefore, 6.64.
Variance is also used in risk management to help determine the level of risk an investor might take when purchasing a certain asset, but usually as the square of standard deviation, which we’ll examine next.
9. Standard deviation
The standard deviation is simply the square root of variance, but is one of the most important measures in statistical analysis.
When applied to annual returns on an investment, standard deviation can help determine the historical volatility of that investment.
Once you have worked out the variance, it is simple. The variance of the set 2, 4, 5, 8 and 9 as above is 6.64. The standard deviation of this set is the square root of 6.64, which is 2.577.
Standard deviation is a fundamental risk measure in investment that most professional fund and portfolio managers use to help calculate likely returns from an investment.
Knowing the returns on an investment over several previous years, the mean or average return can be calculated, and from that the standard deviation tells the investment manager the likely volatility on the average return.
If the return each year has been within the standard deviation then it is a stable investment. If the return in some years is outside the standard deviation it is more volatile.
Measures of similitude
9. Covariance
Traders use statistical analysis to plot the returns on risky investments in a portfolio. When two or more risk assets move in tandem, they are said to have high, or positive covariance.
Positive covariance isn’t particularly welcome in an asset portfolio. One can expect a higher degree of returns from risk assets, but also a higher degree of losses when things go wrong – and you don’t want two or more risky assets going wrong at the same time.
Low, or negative covariance provides an asset portfolio with greater diversification, because when one risk asset is not performing well, other risk assets should be offsetting that poor performance.
10. Correlation coefficient
Simple correlations can be seen when comparing two charts side by side. The eye can spot simple matches between peaks and troughs.
For a more accurate gauge of correlation, however, the correlation coefficient can be worked out by dividing the sum of the covariance of the variables in question by the sum of their standard deviations.
The answer should come between the range of 1 and 1. A positive value means there is a positive correlation between the two variables. The closer to 1, the more highly correlated the two are. The opposite effect will be seen in a negative coefficient.
This type of statistical analysis is used by fund managers to determine how well their fund is performing compared to its benchmark index.
11. Regression
The bestknown regression model in finance is the capital asset pricing model (CAPM) which helps investors arrive at asset pricing and cost of capital.
Simply put, regression is the degree to which the price of an asset, or other variable, is influenced by another set of variables.
For example, it is possible using regression formula to work out the probable effect on an Australian gold miner’s shares from rising gold prices, rising domestic interest rates and a fall in the US dollar.
12. Rsquared
Rsquared is the statistical analysis of the relationship between a fund, particular asset or security and its benchmark index.
For example, an equity fund will have a firm relationship with the index it tracks – if the fund is sector based, then it should have a close resemblance to that sector’s subindex on a main stock index.
Rsquared values are measured in percentages, so an Rsquared relationship of 100% would mean that security, asset or fund had no other influence than its benchmark index, and that its performance matched that of the index.
An Rsquared value of less than 70% is usually said to indicate there is little relationship between the security and the index.
Conclusions and further reading
Remember that without some knowledge also of the market conditions in which certain assets and securities thrive, statistical analysis alone is of little reliable use.
If you’re only basing your investment decisions on hunches – you’re as much in the dark.
But together with analysis of economic factors such as balance sheet and profit and loss, or historical returns, statistical analysis can help reassure investors on those hunches.
Use as much information as is readily available before making your investment decisions.
Please use this article, and any further reading on statistical analysis – of which we’ve provided some examples below – in conjunction with our courses on trading and other related features.
 Introduction to Statistical Methods for Financial Models – 11 Jul 2020 by Thomas A Severini
 Stock Market Probability: Using Statistics to Predict and Optimize Investment Outcomes Hardcover – 1 Apr 1994 by Joseph E. Murphy
 EvidenceBased Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals – 8 Dec 2006 by David Aronson
 Statistical Models and Methods for Financial Markets – 2008 by Tze Leung Lai, Haipeng Xing
Marketing Analysis Toolkit: Situation Analysis
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Six Essential Skills of Master Traders
Six Essential Skills of Master Traders
Just about anyone can become a trader, but to be one of the master traders takes more than investment capital Investing: A Beginner’s Guide CFI’s Investing for Beginners guide will teach you the basics of investing and how to get started. Learn about different strategies and techniques for trading, and about the different financial markets that you can invest in. and a threepiece suit. Keep in mind: there is a sea of individuals looking to join the ranks of master traders and bring home the kind of money that goes with that title. Very few of them make the grade or even come close to it. Consistent, winning traders are about as rare as multimillion dollar winning lottery tickets.
One of the prerequisites of becoming a master trader is an adequate education in fundamental economics, financial markets Types of Markets – Dealers, Brokers, Exchanges Markets include brokers, dealers, and exchange markets. Each market operates under different trading mechanisms, which affect liquidity and control. The different types of markets allow for different trading characteristics, outlined in this guide , and technical analysis Technical Analysis – A Beginner’s Guide Technical analysis is a form of investment valuation that analyses past prices to predict future price action. Technical analysts believe that the collective actions of all the participants in the market accurately reflect all relevant information, and therefore, continually assign a fair market value to securities. . But there are plenty of welleducated, wellinformed, very intelligent individuals who won’t qualify as master traders. The critical difference between winning traders and losing traders is more dependent on acquiring the six essential skills that master traders share. Master these skills and then you’ll get a genuine shot at being a trading master.
Skills #1 and #2 – Research and Analysis
The ability to do quality research and solid market analysis is fundamental to trading success. Master traders develop their skills in being able to thoroughly research all information relevant to the securities they trade – and then, more importantly, being able to accurately determine the likely impact of that information on a particular market.
Master traders learn and perfect utilizing market information – both fundamental economic information and market information in the form of trading and price action that occurs – to adapt and approach the market in the most effective ways possible. (By “effective,” we mean with favorable risk/reward ratios, high probabilities of success, and low levels of risk, just in case we get things wrong).
Analytical skills are vital because they enable a trader to better understand, identify, and use trends (or the lack thereof) – both as applied to price action on individual charts of various time frames, and in the market as a whole.
As you analyze a market and spot patterns and trends, it’s also necessary to determine what technical trading approaches are called for. We suggest that focusing less on the money to be made, and more on taking the right action at the right time, is a major attitude necessary for developing and perfecting your analytical skills. Focusing on the market, not on the money in your trading account, enables you to make the best, objective trading decisions in each situation – and doing THAT enables you to ultimately make the wisest and most profitable trades. Nearly all of the “Market Wizards” interviewed by Jack Schwager in his famous books on winning trading stated that they focus on the market and on their trades, not on their account balance. They’re solely concerned with trying to get the market right, regardless of whether doing so makes them a dollar or a million dollars.
Skill #3 – Adapting Your Market Analysis to Changing Market Conditions
Over time, master traders develop strategies and trading techniques that they use over and over again. Over time, every trader puts together his own personal toolkit of methods, maneuvers, strategies, and trading tactics. That’s a good thing. It’s important that you have your own individual trading style and trading edge, such as specific combinations of technical indicators that signal high probability trades.
Having your own tried and true trading tricks is a good thing. A better thing, a master trader sort of thing, is having your most ingrained habit be the habit of continually monitoring the market for signs and indications that the market is changing or forming a new pattern, thereby signaling to you that you need to adapt to those changing conditions by adjusting your trading strategy accordingly.
Skill #4 – Staying in the Game
Regardless of the industry, company, or particular profession, everyone faces peaks and valleys in their career. If you are a fulltime trader, you will inevitably be met with considerable gains and, at other times, significant losses. Sticking with it – staying in the trading game – is an irreplaceable and vital skill that every master trader possesses.
Of course, it’s easy to become excited and overly eager to make hasty trades when favorable price movements benefit your bank account. Human nature bids us to continue acting in certain ways when the outcomes are good. But there will also be days when the market all but completely turns against you. Rather than being filled with excitement about trading, at times like those you just want to turn off your computer monitor or close out your trading platform and slink away and lick your financial wounds.
A master trader understands that neither extreme will last forever, and, that sticking it out – through the good and the bad – is a skill that enables you to learn, grow, and profit.
A significant part of being able to stay in the game is practicing good risk management and money management. Always use stoploss orders and never risk too much on any one trade. Don’t take trades unless they have positive risk/reward ratios, in other words, if what you’ll make if you’re right is significantly more than what you’ll lose if you’re wrong. Why risk a possible $500 loss if the most you’ll likely make even if your market analysis is perfectly correct is only $100? Those numbers are not in your favor. Instead, only take trades when being right stands to make you a lot more than being wrong can cost you. Even when there seems to be a good trade opportunity, such as a major market reversal, if you can’t get a favorable lowrisk entry point, just let that opportunity go by, and instead wait for one to materialize where you can get a good, lowrisk entry.
Skills #5 and #6 – Discipline and Patience
Discipline and patience are two very closely related skills that every master trader needs – in abundance. As we mentioned above, staying in the game is important because it allows you to experience both the highs and the lows, learning from them and making the necessary adjustments to your trading. A master trader must be both patient and disciplined in order to stick with it, especially on days when profit is nonexistent.
A patient and disciplined trader knows, for example, that quite often the very worst trading sessions or days are followed by significantly better ones. Keep in mind that a fundamental part of market behavior is its upanddown, giveandtake fluctuations. Sessions that run flat and see very little volume may continue for several days, but the disciplined trader understands that patience will be rewarded, so he waits until the market begins to make a truly significant move before entering and risking his hardearned money.
One of the most common mistakes of losing traders is trading when the market isn’t presenting any genuine profit opportunities. Many traders just put on a trade out of sheer boredom. Such actions nearly always cost you money.
A master trader simply takes it in stride if an entire trading session passes by in which no good, lowrisk profit opportunities arise. Master traders know that the market will be open again tomorrow and that there will always be new trading opportunities.
Don’t let markets that are going basically nowhere trick you into abandoning good trading discipline and strategy. Be patient, wait, and when an opportunity does present itself, don’t hesitate – pull the trigger and enter the market, with confidence in your trading ability.
Bonus Skill #7 – Record Keeping
Master traders learn from their trading mistakes. Losing traders rarely do. One of the critical habits that creates winning traders is that of keeping a trading journal. Your trading journal keeps a record of each trade as it happens: your entry point and your reason for buying or selling; where you put your stoploss order and your takeprofit order; what happened in the market after you initiated your trade and how you reacted to the market action; finally, the amount of your win/loss.
Keeping a trading journal and regularly reading back through it provides one of the quickest and easiest ways to identify both what you’re doing right and what you’re doing wrong.
In the End
The primary message we hope you take away from this piece is that every master trader needs to develop the essential skills for successful (i.e., profitable) trading. Make the necessary effort to become a genuinely skilled trader, and the market will reward you for your diligent efforts.
Becoming a master trader isn’t easy, but it is possible and well worth the effort. If you start working in that direction today, rather than putting it off until tomorrow, then you’re one day closer to making your financial dreams a reality.

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