EUR-USD Shows Strong Uptrend Characteristics

By Glenford S. Robinson, BS, MLT, CLS (ASCP).

The EUR/USD average closing price as of 2/11/18 at about 22:00, UTC was 1.2248. Since then, however, the Market Genie has held the market above that level for a considerable amount of time, only going below the 1.2248 level once, when the market temporarily pulled back to 1.2234 on February 12, 2018 at 13:00 UTC.

The Market Genie pushed the market up to the 1.2259 to 1.2260 levels, establishing support at the 1.2260 level. After establishing support at the 1.2260 level, the market continued to advance upward, hitting resistance at the 1.2295 area, where it had visited earlier in the morning at about 4am, UTC.

Therefore, the revisiting or retesting of the 1.2295 area should be taken seriously because this is telling us that the Market Genie has decided to build bullish momentum to eventually push the market to higher levels, and indeed that was what happened because the market made a bullish push upward, ending up at the 1.2305 level at 23:00 UTC on Feb 12,2018. It has since regressed back to its current area of oscillation, the 1.2286-1.2290 area.

Based on our statistical inferences using data points available on February 11,2018, we were able to hypothesize that the Market Genie could eventually push the market to a level close to the 1.2356 area before it is all said and done. We also concluded that if the market spend considerable time closer to our statistical range of 1.2140, say for example, spending considerable time at the 1.2205 level, this would give us the clue that the Market Genie was building up bearish momentum and is getting ready to drag the market down to an area close to the lower limit of our hypothetical range 1.2140 levels.

However, as we can see on the one-hour chart, that did not happen, the opposite scenario happened instead, where the market spent a considerable amount of time closer to the upper limit of our hypothetical range of 1.2356, with our range being 1.2140 to 1.2356. Based on using the empirical formula's normal distribution concepts or three-sigma rule, we were able to conclude that at one standard deviation below or above the mean or average of the closing prices, 68% of closing prices will fall within one standard deviation of the mean or average.

This left us with a probability of (32% divided by 2) 16%, which means that there is a 16% chance or a 16% probability that the Market Genie will probably push the market to an area above 1.2356 from our closing price mean or average of 1.2248, keeping in mind that the clue of this happening will be evident if the market hangs out or spends a considerable amount of time at a price point that is close to the upper limit of our range 1.2356, with 1.2140 to 1.2356 being our range derived from analyzing our data set. On the other side of the bell curve, there is a probability of (32% divided by 2) 16% or a 16% chance that the Market Genie will drag the market to a price point below our range's low limit of 1.2140.

When we analyzed our data on closing prices using descriptive statistics, we identified the mean of 1.2248 which we have mentioned earlier and we identified the median of the data of closing prices that we did not mention earlier, until now. The median happens to be 1.2264 based on the data set we have chosen. Our data set did not consist of any mode specific data point, so we did not include the mode in our analysis.

Therefore, moving forward, we are expecting to see the median closing price play a role in the price action of the minor trend that has begun to develop. We are calling this trend a minor trend because we do not have sufficient evidence to support the idea that this minor trend will manifest itself into a major trend. It is possible, however, that the median price of 1.2264 could evolve into a secondary average or new mean location where frequent "bounces" and mean regression or reversion could soon occur. At this point of writing this article, the market found itself at the 1.2290 price point after a temporary spike to 1.2305. The pullback to 1.2290 has been met with buyers buying in the area, and as a result of the struggle for supremacy, the market is at a standstill; when this happens, the market often moves sideways for a while before continuing on its journey up or down. But, based on what we have seen so far, we are expecting another pullback to an area close to the 1.2264 level or even an area close to the 1.2248 level, which was the original area of the original closing price average or mean. There is a 16% chance of this happening.

There is also a 16% chance of the market pulling back to an area below the 1.2140 level. Again, this is highly unlikely because of the market hovering around the 1.2290 level, which is closer to the 16% chance of the market heading to an area above the upper limit of our hypothetical range of 1.2140 - 1.2356, simply because the market has spent a considerable amount of time above the original closing price mean of 1.2248.

Therefore, we are expecting the minor uptrend to continue toward our range's upper limit of 1.2356. Above this limit, the probability dwindles to (5% divide by 2) 2.5% that the market will continue to push upward because in a normal distribution system or a dispersion scenario expressed by the bell curve of the three-sigma rule, 95% of the data will fall within 2 standard deviations of the mean or average. In fact, it is expected that the Market Genie will become hungry at this point and begins to eat the king fish traders for dinner, and as a result the market will decline a little bit back to the closest and most reliable support line, which is around the 1.2233 mark. Any movement lower than that will head toward the lower limit of our range of 1.2140 to 1.2356. There is a (5% divided by 2) 2.5% chance of this happening. If this happens, a massive upswing or bullish reversion will ensue taking the market back to our original average price level of 1.2248, then to 1.2264 or median closing price level and then back to the high 1.2286s to 1.2290s.

Within the normal distribution realm of our three-sigma rule or a bell curve, 99.7% of the closing prices will fall within 3 standard deviations of the mean or average, which means that there is a (0.3% divided by2) 0.15% probability or 0.15% chance that the Market Genie will push the market to an area above 1.2356 or to an area below our range's low limit of 1.2140. However, these events would be "black swan" events that are unlikely and would incur large gains, or large losses if the proper risk management tools are not put in place. If any of these events were to happen, their probabilities would lie in the tail of the normal distribution bell curve.

The tail of the bell curve housed the probabilities of events that are unlikely but possible to occur. Some investors are black swan investors that invest based on the occurrence of unlikely events. So, when they win, they win big. These successful swan investors limit their losses by using proper risk management techniques. So, even though they lose many times, their losses are kept to a minimum.

We should mention that upon calculating and evaluating the volatility of the EUR/USD currency pair, we determine that the currency pair has a very low level of volatility based on the time frame analyzed. Standard deviation is synonymous with volatility and with a small standard deviation value, we conclude that the volatility is also low. This is telling us that it will be difficult to make money in a market that exhibits low volatility. So, in the case of the EUR/USD pair, opportunities to profit only comes sometimes. Sideways movements or ranging of the market is a regular occurrence in low volatile markets. Traders must employ different trading strategies for ranging markets and trending markets. Using the wrong trading strategy for the wrong market condition could be disastrous for traders' accounts.

If the historic volatility of the S&P was to be placed under the microscope and analyze, it would reveal that the index is only profitable when a trader or an investor holds onto a position over an extended period. This is the reason why day traders lose money 95% of the time and are the poorest of all the categories of traders. While on the other hand, long term investors or traders make the most money in the financial markets. Warren buffet is a prime example of an investor that holds on to stocks for an eternity and he is one of the most successful stock investors of all time.

Always remember to think risk management first and what better way to do this, but to utilize the trailing stop.

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