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Looking down the road for a NKE reversalI hate talking about water under the bridge, but this time I will bring up the case of NKE. What I am disgruntled about is that I I didn't head my own (documented) thoughts on NKE that I had posted on Jan 19: Depending on how you look at it, there has been 4 times that puts below 144 would have worked out wonderfully. The time, I thought I push to 135 would hold as support but that has proved wrong. I hate to chase so I am looking forward to a reversal. I do want to point out a possible future long.... **__Price History: __** **YTD** -24% **1 Month** -14% **3 Month** -26% **6 Month** -23.5% **1 Year** -7% **5 Year** +121% +01% off 52 week low -30% off 52 week high Recently a gap was filled - previously created in June 21' and fully filled Feb 21' Dividends are here! Historically over the past year NKE has seen a sell off proceeding ex-dividend periods. I won't speak too much on this outside this isolated observation - MM hedging around this period can make the options chain hard to read. Ex-Div. Date Amount Type Yield Change Rec. Date Pay. Date 3/4/2022 $0.305 Quarter 0.9% N/A 3/7/2022 4/1/2022 **__Indicators__** - 3 Day Chart **Moving Averages** Easily summed up as trading below all MA's, the 12/26 EMA, 50/200 SMA, and 9 HMA The most import to note is the break of the current 3 Day candle below the 200 SMA. A failure to recapture the 200 SMA by the close of this candle could set up NKE for further selling pressure before earnings. **RSI** Showing signs of being oversold on its current candle and has been hovering right above oversold for over 30 days now - no divergence present currently **SO** Shows oversold conditions since early Jan 21' and the break below its 50 SMA. The SO remained relatively the same since. **QQE** Shows momentum to the downside. When compared to the ATR and RSI, the QQE makes sense in this case. There are very little signs of a momentum shift that is imminent. **ATR** Specifically the decomposed ATR we see that the stock (recently) has had increasingly bearish range with decreasing bullish range - there is no divergence apparent (yet). 1 year ago NKE was trading at SIMILIAR price levels with about less $2 of bearish price movement as compared to today. The important thing to note here is that there seems to be compounded bearish pressure present causing additional volatility on red days. **OBV** Tracking price closely with no signs of major divergence, although the OBV is declining telling us that volume on down days is getting stronger - thus influencing the ATR (IMO) **__Thoughts on Price Momentum and Direction__** **Candles** The 1 month chart shows a current candle that has opened below and trading below the open of the June 2021 monthly candle - I would look for 122.44 to act as support if bearish momentum continues. This is a level that a reversal could be looked for. Any CLOSE of the March monthly candle below 122 would make me feel like the selling pressure would continue. The 50 MA on the monthly chart could also be used as a level of (possible) support. $122(+- The 3 day chart shows a current candle with 1 more trading day left - Bulls would want this to close above 128 ( Local Support from 1 year ago) and bears would obviously want to close the candle below - again, closing below $122 would indicate continued selling pressure. Since the gap is filled, the biggest highlight here is holding support (122) or not. **Earnings** Historically, NKE has had a beat on earnings for the past 6 reporting periods. EPS reporting turned $0.90, $0.93, $1.16, $0.83 were reported period ending Feb 21, May 21', Aug 21', and Nov 21' respectively. Although the Nov 21' earnings beat, it was down from Aug 21. Estimates now show $0.72, a slightly higher bar than Novembers' expectations but down from what was reported. This to me just says that analysts are expecting the effects of COVID, the labor market, and overall transportation costs to weigh heavily on NKE's earnings. It is also important to note that no dilution has occurred in the last year. **Insiders** According to **__Fintel: __** Shares Outstanding 1,581,295,273 shares Insider Shares 251,328,587 shares Insider Ownership 15.89% Total Insiders 48 "**Insider Accumulation Score** According to Fintel: "The Insider Accumulation Score is the result of a sophisticated, multi-factor quantitative model that identifies companies with the highest levels of insider accumulation. The scoring model uses a combination of the the net number of insiders buying the prior 90 days, the total shares bought as a percentage of float, and the total shares owned by insiders. The number ranges from 0 to 100, with higher numbers indicating a higher level of accumulation to its peers, and 50 being the average." Score: 8.88 (12942 of 13931) - as reference the top rated ticker REFI has a score of 99%+ Although higher insider ownership typically signals more confidence in a company's outlook and ownership in its shares. The more insiders that hold shares the more they would be (in theory) incentivized to do good for the company and help increase its profitability and shareholder value. **Net Number of Insiders Buying (Rank)** -3 (3.38%) 13784 out of 14266 Net Number of Insiders Buying is the total number of insiders buying minus the total number of insiders selling in the last 90 days. The percentile rank is shown here (range from 0 to 100%). **Options** TOTAL OI -527K Call 272K Put 255K P/C RATIO - 0.94 Most significant chain activity on 3/7/22 : The 3/25/2022 strike P $135.00 had a previous day volume of 930, OI of 1,583 and a current OI of 2,243 for a overall charge of +660 (+41.69%) The 3/18/2022 strike P $125.00 had a previous day volume of 1,376, OI of 3,655, and a current OI of 4,309 for an overall change of +654 (+17.89%) Top 10 chains by OI **Chain Bid-Ask Low-High Vol OI** 3/18/2022 C $160.00 $0.00-$0.03 $0.02-$0.06 24 23,946 3/18/2022 P $160.00 $35.25-$35.90 $34.90-$35.70 25 18,805 1/20/2023 C $180.00 $2.35-$2.73 $2.40-$3.25 108 11,596 3/18/2022 C $150.00 $0.03-$0.04 $0.03-$0.15 1,220 11,313 1/20/2023 C $165.00 $4.10-$4.40 $4.10-$5.00 17 11,107 3/18/2022 C $140.00 $0.14-$0.21 $0.19-$0.72 267 10,462 6/17/2022 C $125.00 $10.00-$10.40 $9.85-$10.40 217 10,433 3/18/2022 P $140.00 $15.40-$15.90 $9.60-$16.02 123 10,040 3/18/2022 C $155.00 $0.01-$0.02 $0.02-$0.08 58 8,876 3/18/2022 P $150.00 $25.00-$25.95 $21.07-$25.30 22 7,218 What is important to note here is the $160 Puts and Calls holding the highest OI - premium heavily favoring the Put side. **__Further Observations__** I see NKE continuing its downward trend to test 122. This is a critical level that could start to form support in order for a reversal. An official reversal to me would come with a 3Day candle closing opening above 122 and a close above 135-137. On the monthly, to be more conservative, confirmation would come with a candle close above $150. The QQE on the monthly chart has just flipped (negative) showing (again) bearish momentum - this I do not like if I were to look for a long position too close to the (assumed) $122 support level. I do think, with the right patience, a comfortable long could be taken at confirmation of reversal (early at 135, late at 150) to test ATH's again (179.10). This could equate to a 20-30% gain in full - this is what I will be targeting. **__NFA Disclaimer__** This is NOT FINANCIAL ADVISE. These are my own unique opinions based on MY observations and MY experience. I only wish to document and share my thoughts on NKE. DO NOT take this is as a buy or sell signal, you must manage and take responsibility for 100% of your own trades.
NYSE:NKELong
by OccamsPhazer
1
LINKBTC - close to the bottomLINKBTC is near the tip of a falling wedge which have a bullish bias and it's very close to the daily 200 SMA. We can see bullish divergence on almost all timeframes and the 23500 - 25000 range is a zone of major support. The parabola for LINK/BTC is still intact and it's very close to it. This all points to a reversal in the near future and looks like a great zone to accumulate for long-term positions. Let me know what you think and best of luck with your trades!
Long
by Wolfy_
2
Divergent to the downside So good evening everyone I have a trade idea for US30 as my trades have been getting better and better I see a divergent on US30 as we speak possibly going to the upside with a regular divergent and to the down side as a hidden bear on the lower timeframes as price is below my 200, My 21, 50 and 100 SMA are all separated and moving downwards so I am only looking for SELLS were on a Major support and resistance level as well hovering just on it, so what were going to do is wait for Asian session to open see how the market opens its definitely going to be slow but will eventually get to where we want it to go until London session, from their hoping for a big push down but we do have to be carful as well, their is news on USD Monday and on the COT says people added positions on longing the market so lets keep an eye out and see how it plays out just to wait for another confirmation as in say a three line strike or a engulfing bearish candle.
EIGHTCAP:US30Short
by Indicator_Whore1
This is When Bitcoin Will RallyBitcoin (BTC) world’s biggest cryptocurrency, started the new year stuck in a very narrow trading range shy below the considerable psychological number of $50,000 and near the critical 200-day simple moving average. The two key factors that can signal we’re bottoming out are: 1. A break above the 200-day moving average 2. RSI break above mid-level 50 Momentum Leads Price One of the basic principles of trading is that momentum leads and price follows. In this regard, to escape the current bearishness, we need the RSI to cross above the mid-level 50 to signal positive momentum development. In 2021, Bitcoin experienced three corrections (19 April, 8 September, and 16 November). In each case, the RSI crossed below the mid-level 50 right at the beginning of the sell-off. Similarly, each correction ended when the RSI crossed back above the 50 level. 200-Day Moving Average The second signal to confirm the bottom is a daily break and close above the 200-day moving average. More importantly, we need the BTC price to trade for consecutive days closing above the 200-SMA. The 200-day simple moving average is widely regarded as the most influential moving average that delimitates an uptrend from a downtrend. Moving forward: As long as the bearish momentum persists, the bears will face an important support zone in the $42,000 - $40,000 price range.
BINANCE:BTCUSD
by cryptohopper
3
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
9
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
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