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A Deep Dive Into Moving AveragesMoving averages are inherent in the world of technical analysis and are present in the core calculations of many technical indicators. In this post, we take a deep dive into 3 types of moving averages used every day by traders: the Simple Moving Average (SMA), Exponential Moving Average (EMA) and the Weighted Moving Average (WMA). The topics covered below can have practical applications while others are solely informative. 1. Introduction Moving averages are trend indicators commonly used to smooth the closing prices by removing or attenuating certain variations and are able to estimate underlying trends. Their usage can be recorded as early as 1829 by John Finlaison for smoothing mortality rates (1). In technical analysis moving averages are often essential for traders and can be found in every technical analysis software. However, they are not specific to this field as they often appear in Time Series Analysis and Digital Signal Processing (DSP). Moving averages possess a single user setting that generally determines the degree of smoothness. This setting is often referred to as the moving average "length", "period" or less commonly "window size". 2. Curiosities About The Simple Moving Average The Simple Moving Average abbreviated to "SMA", also known as the "Arithmetic Moving Average" or "Moving/Rolling Mean/Average" is certainly the most well-known moving average due to its simplicity and numerous applications in other domains. The SMA with period length is commonly calculated as follows: SMA = (SUM C )/length, for i = 0 to length-1 = (C + C + ... + C )/length Here all the weights w would be equal to 1/length (which is why we often state that a SMA has uniform weights). 2.1 Relationship With The Momentum Oscillator Changes in a simple moving average with period length are equal to a momentum oscillator of the same period divided by length , that is: SMA - SMA = (C - C )/length This can be explained from the calculations of the changes in a Simple Moving Average: change(SMA ) = SMA - SMA = (C + C + ... + C )/length - (C + C + ... + C )/length = (C - C )/length The closing prices with the same lag cancel each other out, leaving only C(t) and C(t-length) divided by length in the final calculation. As such you could tell whether a moving average of period length is rising or declining by simply comparing the current closing price to the closing price length bars ago. If the current closing price is higher; then the moving average is rising, else it is declining. This relationship allows us to efficiently compute the SMA, allowing us to obtain a computation time independent of the moving average period which is very important for real-time high-frequency applications of the SMA. 2.2 Lag Of The SMA Lag is defined as the effect moving averages have to return past price variations instead of new ones. For most moving averages this amount of lag can be quantified as the weighted sum between the moving average weights w(i) and the time lag associated with them. Higher weights given to more recent values would return a moving average with less lag. All the weights of a simple moving average are equal to 1/length . The lag of a Simple Moving Average is thus given by: Lag = SUM(1/length × i), for i = 1 to length-1 = 1/length + 1/length × 2 + ... + 1/length × (length-1) = (length-1)/2 As such, the lag (in bars) of a Simple Moving Average is equal to its period minus 1, divided by 2. Offsetting an SMA Lag bars in the past allows us to have it centered with the price. 2.3 Cascaded SMA's Using an SMA as input for another SMA would return a smoother output; this process is known as cascading. In the case of the Simple Moving Average, cascading many SMAs of the same period would converge toward a Gaussian function. The Irwin–Hall Probability Density Function can describe the result of cascading multiple SMAs using an impulse as input. 3. Curiosities About The Exponential Moving Average The Exponential Moving Average; abbreviated as "EMA", also known as an "Exponentially Weighted Moving Average" or "Exponential Average" is a recursive moving average. That is, it uses a previous output for its computation. This moving average is slightly more reactive than the Simple Moving Average due to its lower degree of filtering. An EMA of period length is calculated as follows: EMA = a × C + (1-a) × EMA or: EMA = EMA + a × (C - EMA ) with smoothing constant a = 2/(length+1) . 3.1 Traders Prefer The EMA Over The SMA The trading community seems to have developed a preference for the EMA over the SMA. This might be explained by the superior reactivity of the EMA over the SMA. The EMA is also more commonly used in the creation of technical indicators, sometimes for its superior reactivity, its computational efficiency, or sometimes simply by preference. Several studies attempted to indicate which moving average (between the EMA and SMA) provided better performances. The conclusion can vary depending on the markets and methodology used. Dzikevičius & Šaranda found superior results of the EMA over the SMA (2), while Predipbhai found better results from an EMA-based MACD over an SMA-based one (3). 3.2 The EMA Helps Avoiding Division By Zero In scenarios where we are required to perform a division with a moving average applied to a denominator, the EMA can help to avoid division by 0 as long as the smoothing factor is lower than 1 (EMA period superior to 1) For a < 1, the EMA has an exponentially decaying infinite impulse response. The impulse response converges towards 0 but never reaches it. This can be useful if we want to obtain the ratio between the average upward variations and average downward variations. In the event where there is a significant number of upward variations, an SMA of the downward variations might eventually be equal to 0; the EMA prevents this. 3.3 The EMA Has The Same Lag As An SMA We previously mentioned that the EMA is more reactive than the SMA, but quantifying the lag of an EMA from the weighted sum between the EMA weights and their associated lag gives the same results as the lag of an SMA. The weights of an EMA can be obtained from its impulse response, which is described as: h = a × (1-a)^n, n ∈ The lag is then calculated as follows: Lag = SUM i × (a × (1-a)^i), for i = 0 to infinity = (1 - a)/a = (1 - 2/(length+1))/(2/(length+1)) = 2/(length+1) 4. Curiosities About The Weighted Moving Average The Weighted Moving Average; abbreviated as "WMA", also known as a Linearly Weighted Moving Average (LWMA), is the most reactive moving average when compared to the SMA and EMA. The WMA uses linearly decaying weights for its calculations, giving higher weights to more recent prices. The WMA can be calculated as follows: WMA = (SUM (length-i) × C )/(length*(length+1)/2), for i = 0 to length-1 4.1 Relationship With The SMA It's interesting to observe how certain moving averages are related to each other. In the case of the WMA and SMA, the change of a WMA of period length can be given by the difference between the price and an SMA offset by 1 bar, divided by (length+1)/2 . This equality is described as follows: change(WMA ) = (1 - SMA )/((length+1)/2) This also shows that the changes in a WMA with a period length-1 can indicate if the price is above or below an SMA of period length . Like with the SMA, this relationship allows the calculation of the WMA efficiently allowing us to obtain a computation time independent of the moving average period. 4.2 Relationship With The Linear Regression It can seem extremely surprising, but it is indeed possible to compute a simple Linear Regression of the price using linear combinations between a WMA and an SMA (under certain conditions). The first point of a simple Linear Regression with coordinates (X1,Y1) fitted through the most recent length price observations can be obtained as follows: X1 = t - length + 1 Y1 = 4 × WMA - 3 × SMA While the last point with coordinates (X2,Y2) is given by: X2 = t Y2 = 3 × WMA - 2 × SMA The periods of the WMA and SMA are both equal to length . Drawing a line using the above coordinates would return the simple Linear Regression fitted to the most recent length price observations. The slope of the linear regression is equal to: m = ((3 × WMA - 2 × SMA ) - (4 × SMA - 3 × WMA ))/(length-1) = 6*(WMA - SMA )/(length-1) References (1) Hoem, J. M. (1984). A contribution to the statistical theory of linear graduation. Insurance: Mathematics and Economics, 3(1), 1-17. (2) Dzikevičius, A., & Šaranda, S. (2010). EMA Versus SMA usage to forecast stock markets: the case of S&P 500 and OMX Baltic Benchmark. Business: Theory and Practice, 11(3), 248-255. (3) Predipbhai, N. P. (2013). Comparison between exponential moving average based MACD with simple moving average based MACD of technical analysis. International Journal of Scientific Research, 2(12), 189-197.
Education
by LuxAlgo
11
Education Excerpt: Simple Moving AverageSimple Moving Average The origin of inventing the Simple Moving Average (MA) is not clear. Although, some of the first documented cases of its use date as far back as the early 20th century. Implementation of moving averages in technical analysis is one of the most successful methods of identifying trends. Moving averages are simply constant period averages - usually of prices, that are calculated for each successive period interval. The result of calculation is then plotted on the chart as a smooth line that represents successive average prices. Thus, the calculation of the moving average dampens fluctuations of price of an asset, making it easier to spot an underlying trend. Though use of the moving average goes beyond identifying trends. Support, resistance and price extremes can be anticipated by correct interpretation of the moving average. Crossover Generally, when the moving average with a lower period interval crosses above the moving average with a higher period interval it is considered a bullish signal. On the other hand, when the moving average with a longer period interval crosses above the moving average with a lower period interval it is considered a bearish signal. These crossovers can serve as specific buy and sell signals in markets that are trending. However, moving average crossovers tend to produce many false signals in non-trending markets. Furthermore, these same crossovers can act as support or resistance levels. Illustration 1.01 Picture above depicts daily graph of PepsiCo (Ticker:PEP) with 20-day SMA (blue) and 35-day SMA (red). With implementation of these two moving averages it is easily observable that prevailing trend is bullish. Crossovers between these two simple moving averages reveal where trend began (10th February 2017) and where it ended (7th July 2017). In addition to that analyst can identify price extremes when price deviates too far from its 20-day SMA. Length of the period Different lengths of moving average directly translate to the amount of data used in the calculation. Including more data in the calculation of the moving average makes each data per time interval relatively less important. Therefore, a large change in one particular data would not have as large an impact on the overall result of the calculation in comparison to if the moving average with a shorter period was employed. Hence, the longer moving average produces less false signals at the cost of revealing underlying trend sooner rather than later. Usually, the use of two moving averages with different period intervals is encouraged as opposed to use of a single moving average. This comes from the premise that when two moving averages with different period intervals are plotted on a chart, they tend to show two separate lines converging and diverging. Illustration 1.02 Picture above depicts daily graph of XAUUSD with 3-day SMA (blue) and 6-day SMA (red). Viewer can see that 3-day SMA copies price move more agressively than 6-day SMA. Illustration 1.03 Picture above depicts exactly same graph as is showed in Illustration 1.02. However, length of SMAs differs. Blue line represents 10-day SMA while red line represents 20-day SMA. It is clear that when length of SMAs was extended then SMAs produced less mechanical signals (crossovers) as opposed to SMAs used in Illustration 1.02. Calculation The calculation of the moving average usually involves use of the close price. Normally, 10, 20, 50, 100 or 200 periods are used and the calculation is conducted by creating the arithmetic mean of a dataset. SMA = (A1 + A2 + An) : n A = average in period n n = number of time periods Illustration 1.04 Picture above shows daily graph of Coca Cola (Ticker:KO). In this particular example trend was neutral and it is visible that crossovers between two simple averages produced many false signals. Disclaimer: This content is just excerpt from full paper that will be published later. It serves educational purpose only.
OANDA:XAUUSDEducation
by Tradersweekly
60
Education Excerpt: SMA, LWMA, GMA, TMA, EMAWe decided to publish second part of the paper on moving averages. The first part detailed Simple Moving Average. In the second part we decided to present: linearly weighted moving average (LWMA), geometric moving average (GMA), triangular moving average (TMA) and exponentially smoothed moving average (EMA). The first part can be read by clicking on chart below: Possible uses of the moving average • Identification of trends • Identification of price extremes • Identification of support and resistance levels • Identification of signals Identification of trend The moving average can be used as simple tool to determine prevailing trend. Simplest way to determine current trend using moving average is to compare current value of security to current value of moving average. If value of moving average is below price of the security, then trend is considered to be upward. Contrary to that when value of moving average is above price of the security then trend is considered to be downward. Another method of determining trend is to use two same moving averages but with different length (different number of hours or days, etc.). These two moving averages would be then plotted on graph as two simple lines occasionally crossing. Trend would be considered upward when shorter moving average would be above longer moving average. Opposite to that, if shorter moving average would be below longer moving average then trend would be regarded to be down. Illustration 1.01 Picture above depicts daily chart of XAUUSD. It is observable that price continued to rise most of the time when it was above 10-day SMA. It is also observable that when price dropped below 10-day SMA then it continued to decline further. Identification of price extremes Analyst can find another utilization of moving average in finding the price extremes. This is possible due to natural tendency of price to move back towards its moving average after it deviated too far from it. Illustration 1.02 Graph above depicts General Motors on daily time frame. It is visible that when price deviated too far from its 10-day SMA then retracement followed. However, it is not a rule that price will retrace full length back to moving average once it deviated too far from it. Identification of support and resistance levels Another possible use of moving averages lies in using them as specific support and resistance levels. In rising markets price has tendency to correct towards moving average before continuing to rise further. Similarly, in declining markets price tends to suddenly increase towards moving average and then drop and continue lower. Identification of signals Generally, when moving average with lower period interval crosses above moving average with longer period interval it is considered bullish signal. On the other hand, when moving average with longer period interval crosses above moving average with lower period interval it is considered bearish signal. These crossovers can serve as specific buy and sell signals in markets that are trending. Illustration 1.03 Picture above shows same graph of General motors as is depicted in Illustration 1.02. However, instead of one 10-day SMA this graph also includes 20-day SMA. It is easily identifiable where these two moving averages cross each other and by doing so generate specific buy and sell signals. However, we have to note that in non-trending markets this method lacks utility since moving averages tend to produce a lot of false signals. The Linearly Weighted Moving Average (LWMA) The Linearly Weighted Moving Average (LWMA) is very similar to the Simple Moving Average (SMA) we introduced in our previous education excerpt. But while SMA gives each time period involved in the calculation same weight LWMA differentiates between the weight linked to each time interval. Normally, 10-day SMA calculation would be conducted by summing up each value per time period and then dividing this result by total number of time intervals (which would be 10 in this particular example). In this calculation each time period (each day) would have 10% weight. However, as mentioned before, LWMA gives each time interval different weight. This unequal redistribution of weight can be achieved in two simple steps. In the first step analyst multiplies each day's value and sums up resulting values together. Then in the second step analyst divides resulting value (from the first step) by the sum of all multipliers. For example, in 10-day LWMA first day's value would be multiplied by 10. Then second day's value would be multiplied by 9; and third day's value would be multiplied by 8 (continuing up to 10 days where last day's value would be multiplied by 1). Resulting value for each time interval would be then summed up and divided by 55 (multipliers: 10+9+8+7+6+5+4+3+2+1 = 55). This simple change in formula would result in giving 10th (most recent day) day in the calculation twice the weight of 5th day and ten times the weight of the 1st day. Calculation of 10-day LWMA for 11th day would then involve weighting data from 2nd day up to 11th day while dropping the 1st day's value from data set being used in the calculation. Assigning different weight to each time interval helps to give more relevance to the most recent days as opposed to giving less importance to days before that. Formula LWMA = / summation of W P = price for the period n = period W = the assigned weight to each period (highest weight goes first and then it linearly declines) Illustration 1.04 Chart above depicts two different moving averages. First is 10-day SMA (blue) and second is 10-day LWMA (yellow). While these two moving averages have same length they are different in shape. This is because of unequal redistribution of weight. This allows LWMA to act in advance of SMA. Geometric Moving Average (GMA) The Geometric Moving Average (GMA) is another form of moving average. But rather than using price in its calculation GMA uses percentage changes between the previous time period and the current time period. This type of moving average distributes weight equally as SMA. In addition to that it suffers from lag. When SMA and GMA (with same length) are plotted on same graph they are not different in shape or dimensions. Therefore they would overlay each other. The Triangular Moving Average (TMA) The Triangular Moving Average (TMA) is another type of moving average that is different from previous types of moving averages in that it is double smoothed. Its calculation begins with taking SMA with predetermined number of bars. After that these results are being used to take SMA of former SMA. However, length of second SMA is only half of that used in calculation of original SMA. For example, 20-day SMA would be smoothed through calculation of 10-day SMA that would use data from 20-day SMA. The result can be then plotted on graph and it is depicted as smoothed line. TMA represents the trend better since it is double smoothed, however, at cost of sensitivity to trend changes. When TMA and SMA (with same length) are plotted on same graph they are different in shape and dimensions. Illustration 1.05 Picture above shows daily graph of PEP. Three moving averages are depicted: SMA, LWMA, TMA. They all observe same 10-days, however, each acts differently. The Exponentially Smoothed Moving Average (EMA) The Exponentially Smoothed Moving Average (EMA) is type of moving average that weights importance on the most recent data. Decrease in weight from one time interval (one day) to another is exponential; and unlike SMA and LWMA exponential moving average has ability to use information outside the length of the moving average. Result from calculation of EMA can be then plotted on graph similarly like result from SMA, LWMA or any other moving average. EMA is considered to be more responsive to trend changes and it can be used when analyst is concerned with effect of lag (which is stronger in SMA and LWMA). Formula EMA = Pricet x k + SMAy x (1-k) t = today k (multiplier) = 2/(number of days in period +1) SMA = simple moving average of closing price y = yesterday Illustration 1.06 Picture above depicts daily graph of Raytheon. It also depicts 10-day SMA and 20-day EMA. It is visible that many fake signals took place once market started to trade sideways. Disclaimer: This content is purely educational.
NASDAQ:AAPLEducation
by Tradersweekly
47
FTM retested breakoutLooks like a successful retest of a breakout from this big ascending channel, and that's a very bullish sign. If you entered on my last FTM chart, now about 18% in profit so far. (link to it is below) Now under a small resistance level and we could see a small pullback (indicators on 1hr are relatively high, have more room for going up, so this pullback could happen also after we break up from this resistance level). Indicators on 4hr look bullish and could see the golden cross on MACD if the price continues up. I would really like this candle to close above 20sma (blue line) for further upside. One concern that I have is that if price go up more and indicators do not climb above the previous high levels, we might end up with multiple bear div-s. So we must keep an eye on this... Good luck traders
F
by PhilosophersStone
1
Classic Fibonacci Retracement to 0.382AUDCAD is at a unique level. When the market is unsure I tend to go back to the basics. Measuring this trend from the high to the low and snagging a quick trade to the 0.382 level is about as classic as it gets. This is a textbook fundamental trade, MACD (indicator on bottom) is telling me that the bears are losing steam and the price has the potential to reverse. EMA & SMA are showing a clear exhaustion of the trend on the 30 min timeframe (shown by the "BUY" flag)..... Trade this area with caution but a retracement to 0.382 is palatable. This is not financial advice.
Long
by diazfranj
1
SOL on crossroadsMy followers entered long in SOL by last idea (link is below) are about 14% in profit so far, if they didn't close the trade with larger gains... SOL will in few days run out of space, squeezed by resistance and support trendlines, but still a lot of space in this ascending triangle. Staying in this triangle longer than that would mean that it broke that resistance trendline, which is a good sign. Now is above 20sma which is acting as support for the time being. Got these 3 supports so near under and those 2 resistance levels above, could mean that we could see explosive breakout whatever the direction will be. SRSI printed golden cross but since RSI is near 50 it could go both ways. Well, our job is to catch it whatever it does. Set alarms since this could take few days to play out. Good luck traders
by PhilosophersStone
We talk about Moving Averages. 🖌Origin of moving averages: They are used to filter out market noise and clarify the direction of the trend, as they eliminate minor movements that could be hiding what the market is actually doing. The average price of a given period in the past is calculated, the result is plotted on a line chart next to the price chart. They are more suitable for detecting trends but are also useful for analyzing the evolution of the price in different periods of time. How are they calculated? The moving averages are the moving average and to calculate them the last periods that are parameterized for their calculation are taken. For instance; For a 10-period moving average, the last 10 price closing candles are taken and their average is taken. Remember that a moving average is always lagging because it is the result of making a calculation on the prices of the past, they do not predict the price, they only summarize more clearly what has happened in the price. Its usefulness, therefore, helps us to detect or see trends more clearly. And in technical analysis, it is considered that when there is a trend it is more likely to continue. The shorter the moving average calculation period, the less lag it will have, but it will include more volatility than longer period moving averages. The longer the moving average calculation average, the longer it will take to react to recent market changes. What is the best moving average? Surely you were waiting for me to tell you which is the best moving average because there is no better moving average than another, they are all worth it, they are all good, you just have to understand them well. Some are true that they are more used as 20, 50, 100 and 200. All the moving averages are showing you the line chart with the longest temporality (Except 1). So, a 5-period moving average is equivalent to the linear graph of multiplying that timeframe by 5. For example; If we were in 1-minute time frames it would be equivalent to the 5-minute line chart and if it were the 60 moving average it would be the 1-hour line chart. Moving averages and temporalities. If we take into account the moving average of 160 periods, it would be exactly equal to the moving average of 80 periods in 1 hour and of 20 periods in 4 hours. Types of moving averages. Since it is understood how the moving average works, we are going to talk about the 3 most used types of moving average. a) Simple moving average (MA): All the data of the period are weighted equally, all the candles have the same importance from the first to the last candle that is periodized, of which an average is taken. It is the most typical and the easiest to calculate, but also the slowest to adapt to the most recent price changes. b) Media móvil ponderada ( WMA ): Con este tipo de media móvil se le da diferente importancia a cada una de las velas, dando más prioridad a las primeras velas y dando menos importancia a las últimas velas a calcular, en su fórmula se asigna un coeficiente a cada uno de los valores. Esta media móvil reacciona más rápidamente a los últimos cambios de precios. c) Exponential moving average (EMA): Its calculation is more complicated but basically, an additional value is carried to the selected period, that is; for a 10-period exponential moving average, the last 11 candles are considered. These are done to minimize the sudden effect that occurs when eliminating the first data in the series, the most recent candle or price is weighted in greater percentages, while the rest of the candles all weigh equally. Arguably the "EMA" is equivalent to a simple moving average to which an additional period is added and the recent price is weighted much more. How to use them? Moving averages are considered to act as dynamic support and resistance, when the price is trending they act as a trend line that sets the guideline, but they also have the quality of "Attracting" the price, as they remain an average of the price. and by the statistical principle that everything returns to its average at some point. Another utility is that it also helps us to detect price highs, since all the data of distribution tend to group around its average, if a strong impulse moves the price away from the moving average, at some point the price will return to its average. half. and this will help us to detect extremes of the market For example; when the price is too far from its midpoint and you may be ready to make a correction. This is the beginning for which indicators like the MACD are created. If the price is far from its moving average it is very easy to detect it visually.
Education
by Ed_Ale
DASHBTC apparently developing a head and shoulders at resistanceI had mocked up these bands on the chart with the intent of looking for places to take profit on upside moves but it appears that Dash isn't going to make it through the orange zone just yet. There has been a downward channel with a slight broadening aspect to it since 2017 and seeing a head and shoulders at channel resistance does not make me confident that price will be able to break through at this time. The target on the head and shoulders is shown with a fib retracement that and the primary targets are going to be the 1.618 and 2 levels. That puts us within this half mast continuation pattern on the flagpole that began the multi-year consolidation that created the orange zone. My system for determining bias shows that there was some reason for hope on the weekly chart when DASHBTC hit the VSTOP MTF x3 but we have not followed through. And it also seems that we have slipped the 20 week (again). The MACD is below zero and it appears to be poised to cycle another bearish MACD-Signal cross. It seems that Dash is poised to drop around 55 to 66 percent against bitcoin. Linked ideas will show reasons to be bearish about crypto. I still think Dash has a lot of long term potential but it is certainly getting dogged right now. I am certainly going to keep a long term watch on DASHBTC and especially this trendline resistance. Dashusd has been great for swing trades for me for a long time but every time I look to hodl dash it betrays me.
Short
by This_Guhy
6
EURUSD: waiting for an extension of the pullbackHi Guys, the idea on this pair is to wait for an extension of the pullback to exceed 1.19088. This move was enbedded in the divergence between sentiment and price lows and stopped at July H in conjunction with NFP release on Sept.3rd. In this occasion the indicator didn't stop and exceeded it's July H forming a divergence also between latest two tops. Price: NFP H = July H RSI: NFP H > July H Today price has been hit by some near-term profit taking. However I still look for an extension above July H running possibly into 200SMA at 1.20029. To enter the market I am waiting for a bullish set up on LTF that may boost an attack to July H. Today's German Factory Order should be supportive for the EUR and also for EU GDP data to be released tomorrow. Important ECB meeting will take place on Thursday. The expected move may not take place before ECB meeting is finished. Be ready to take action only when right set up favours your objectives. If you have any queries please do not hesitate to ask. Good luck everybody! Disclaimer: Please note that I am not a professional trader and these are my personal ideas only. The information contained in this presentation is solely for educational purposes and does not constitute investment advice. The risk of trading in securities markets can be substantial. You should carefully consider if engaging in such activity is suitable to your own financial situation. Cozzamara is not responsible for any liabilities arising from the result of your market involvement or individual trade activities. Trading in foreign exchange (“Forex”) on margins entails high risk and is not suitable for all investors. Past performance is not an indication of future results. In this case, as well, the high degree of leverage can act both against you and for you. Before you decide to invest in foreign exchange, you should carefully assess your investment objectives, experience, financial possibilities and willingness to take risks. There is a possibility that you will lose your initial investment partially or completely. Therefore, you should not invest any funds that you cannot afford to completely lose in a worst-case scenario. You should also be aware of all the risks associated with foreign exchange trading and contact an independent financial advisor in case of doubt.
by cozzamara
BA: Watch for the bounce backAs we had more and more bad news and fast-growing covid cases there was a general downtrend beginning from March. Now we are getting to good levels of support to buy. That’s my trading setup 1. Buy: 204.83 Stop loss: 203.23 (-0.74%) First Target: 220.69 (+7.68%) Second Target: 230.49 (+14.49%) 2. Buy: 192.53 Stop loss: 191.07 (-0.70%) First Target: 204.83 (+7.09%) Second Target: 220.69 (+15.43%) I think it is more likely that we see a bounce back at 204$ range. We have the opportunity of a double bottom, have support of the 400 SMA (orange) where we often saw great support (green marked). Daily RSI is oversold (bullish), MACD is pretty neutral. At the second buy we reach the bottom of the parallel downtrend line to bounce up and double bottom with the strong support of 192.49$.
NYSE:BALong
by Chrlstlan
Properly trade EURUSD 1H SwingsHi! For my first post here on TV, I will show my way of trading the trends on EURUSD on the 1H time frame. For that I use my own SMA-96 indicator which does 80% of the job and other private techniques to close the trade. From the chart, you can see my last 4 trades, 23, 24, 25 and 26 still open, taken in the last 30 days, I think that they are easy to understand. My expectation for my current open trade is that either the down trend will resume allowing me to keep trade 26 open or some recent high will be violated with the price going to the other side of the SMA which will force me to close trade 26 and open a long position 27.
by AL26
MATCH THAT MONEYToday I will be analyzing Match Group. For everyone who doesn’t know this company, they are creating and managing many dating platforms one of their well-known is Tinder. Cash flow comes from subscriptions (like Tinder Plus) and other services. Buy Signal -support at 129.46$ (3 times) -daily RSI oversold area -daily MACD indicates slowing selling pressure -current price is below analyst estimates ->>> TipRanks: „The average price target is 175$ with a high estimate of 190$ and a low estimate of 148$. -Bumble (same industry) reported a good quarter a few days ago-> positive momentum Sell Signal -under the SMAs -RSI/MACD weekly+monthly indicate a downtrend!! -misled earnings by -15% -potentially Delta-Virus results in new lockdowns Conclusion I think this is a great company with a nice discount, in addition, the Wall Street/analysts like the stock too if we look at what %-rates the stock recovered from the March Lows that makes total sense. So, I would be willing to buy at the support of 129.46$ (109,90€) with a tight stop loss of 122.18$ (108.82€) and a price target of 145$ (123.06€) which would be a +11.79% return. This number is approximately the mid of the parallel channel but at the same time I took it because of the past reaction contacted support line where it every time bounced 11.79% up in just 3-4 days which indicates the importance of this line.
NASDAQ:MTCHLong
by Chrlstlan
2
Polkadot Descending Channel Breakout PlayPolkadot's (DOT) price has broken above a descending channel that can suggest a potential trend reversal. Another confluence factor that adds more weight to the bullish case scenario is the MACD regular bullish divergence. Descending Channel Before Polkadot emerged higher out of the descending channel, it reached a new low of $10.37, which is a key support level. The short-term support level also comes in at $16.70, which needs to hold for the current rally to continue. On the flip side, the bulls are eyeing the considerable psychological number of $20.0. A daily break and close above the considerable round number $20 can open the door for a retest of the next critical resistance found at the $27.90 level. However, the 100-day simple moving average, which currently stands at $22.81, is another obstacle the bulls need to overcome. MACD Divergence The MACD divergence also signals that the bottom might be settled, even if it is only temporary. This adds more confluence to the reversal signal, but at the same time, traders need to be aware that this rally may also just be a minor retracement in the grand scheme of things. In this regard, traders need to keep an open mind and simply go with the market flow.
KRAKEN:DOTUSDLong
by cryptohopper
Quick analysis on the 4H chart - BTCUSD*** Always trade your own charts. These charts are for simple analysis from my point of view. This is NOT trading advice. *** A simple look at the 4H chart versus the 200 smoothed moving average (green line) and the 200 simple moving average (blue / orange line). Trending well below the 200 SMMA - Sign of weakness. Trending below the 200 SMA - Sign of weakness. Arrows point to continuously weakening buy pressure and eventual failure to surpass back above the 200 SMA - Major sign of weakness. Short term, this is still very much in a downwards trajectory. How low can we go? I'm still sticking to my original projection of 25-26K before any sort of major trend reversal. Could we go lower? Certainly. Could this entire structure be invalidated? You bet. Whales can do it if they want to. It's hard to tell at this point in time. Just keep a larger perspective on what kind of trend we're in. Don't try to crystal ball your trading, just trade the trend. If you're a day trader or scalper, there's money to be made here. If you're holding, that's up to your comfort level on if you want to hold and wait until a final rebound or get out and buy lower. It all depends on your risk management and trading style. I'm just here to make a non-biased analysis of what kind of trend we're still in. I see more downwards pressure coming. Hold on to your butts!
COINBASE:BTCUSDShort
by DashingSixty
3