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Moving Averages

The power of the VWAP!As day traders we use the VWAP lots in our trading and have even created custom versions of it which help us manage our trades. In this video I go over exactly what happened to US30 / Down Jones at the Frankfurt open and the New York open, and by using the VWAP today we could have taken advantage of these moves, both up and down! Do you use the VWAP? Let us know in the comments below! Also attached to this video are other educaitonal videos you might find value in!
OANDA:US30USDEducation
by PrimedGroup
Moving Average ChannelA lot of traders like myself, like to visualize the moving averages on their chart and incorporate them in their trading strategies. But what is extremely common in doing this, is traders being under the assumption that a moving average is the exact price in which we see supply and demand in the market. In this video, I clearly outline how to add a channel around your moving averages, to give you an idea of where we may see a change in supply and demand. Having clarity in an area can help traders understand the moving average better than just a thin line. If you do use moving averages in your trading strategies, I recommend trying this little trick to improve your success rate and understand breakouts better. - Jordon
Education
by the5erstrading
Weekly Line Chart DivergencesHello traders, I am not a financial advisor. I am not telling you to trade any asset. I am simply sharing my ideas on how to use tools to implement my own investment strategy. Here is a zoomed-out look you can use to come up with some of your own ideas on where the $SPX may go and how to manage your risk. Most of my core strategies are developed on the indices so I will have to implement them on individual tickers unless the comments are interesting. This is a lagging indicator and should put me on the side of the trade that is *probably* likely to continue. By probably, I mean you need to do your own research and look at what the markets want to go and develop your own tools to work with the data. Orientation: Line Chart of ticker on weekly time frame RSI using 12 periods (or weeks, in this case) Signals can be marked using a vertical line or time-based axis marker . In this case, I am using 3 colors of lines, explained by the "Monday Action" legend. We will dive into more detail later on. I also have EMA using ohlc4 on periods (or weeks) 10, 25, 50, 100, 200. Now to the good stuff: Divergences have been around for quite some time. Research about the RSI (Relative Strength Index) and it's roots It is much easier to see something that is larger, than smaller, thus we look at weekly time frames One can use volume, closing price and RSI to help manage one's risk Narrowing a decision to 3 choices can help alleviate indecision So for this application of the RSI and divergence, one can use a simple line chart on a weekly time frame (this chart is based on the closing price from what I can tell, but I was unable to confirm that with the Help Center. I was able to confirm by checking yesterday's close with current reading - it will be different after this post as the weekly close will come in today (writing before market close Friday morning)). We can start at the March 2020 rally. We can see the March 23rd, 2020 weekly close paint a divergence on the RSI. One can see the price close at a higher high when compared to March, 16th, 2020. The RSI values remain relatively flat: 17.95 to 18.04. Find entry One might conclude this is a time to buy. Because of the magnitude of the move DOWN, the move up was also shorted. One would have to employ the use of other tools in order to find entry in the following week. (Use the white anchored notes to see the explanations of thought process). Find an entry in the next week. One can place orders on the weekend in "shotgun fashion" perhaps placing 50% order above current price and 50% below, or whatever method suits you. Hedge Risk The next yellow line is 08/24 - 31/2020. The close indicates indecision in the market. Since this is the first divergence I would simply hedge the FANTASTIC long during the March 2020 buy. This can help to be determined from YELLOW vs RED using the 10 period moving-average of volume. Use options or other means to protect one's long investments Sell of Heavy Hedge The next divergence is JAN 2021. This is the second one so I would probably sell at this point. I would use my other tools to figure out what to do. Heavy hedging can be using derivatives or shorting your long positions. Timing A simple way to use this strategy might be to use the color's GREEN, YELLOW, RED, just like traffic lights. There will be deviations, and variations to the method, but if you back-test this you will probably find this works generally well. Monday Action Now I used the words Monday Action simply because that was the next possible day to make a decision. I can make my decision probably anytime within Friday if I feel comfortable with it. I can also place actions for Monday on the weekend. Bottom Line This week's close is very important. If we follow the green, yellow, red method from above, this very well can be a RED. It can also be another YELLOW. Volume is indicating something big, but we will see!
SP:SPXEducation
by elkenpolar
My Love For 200 Moving averageOne of my most used indicators is the moving average. I personally believe that hypothetically, moving average "alone" is sufficient enough to build a profitable trading strategy. I hope to implement this thought in the coming years. In the chart, we can see the 200 WMA for the 1H, 2H, and 1D moving average. I'm particularly fascinated by how price is respecting the WMA as support and resistance. I think this is worth taking a deep dive into. What do you think?
COINBASE:LTCUSDEducation
by Aghughu
Trade Using Exponential Moving Average and Trend LineHigher Lows Are Represented By Diagonal Trend Line Lower Highs Are Represented By Diagonal Trend Line After Price Closes Above Diagonal Resistance Line (Lower Highs), Enter A Long Position. Enter using the closing price of breakout candle. Enter a second long position when price forms a rejection candlestick wick in the EMA 10 EMA 20 Area. Enter using the closing price of rejection candlestick. H2, H3, H4 Chart. EMA 10 is above EMA 20 in these chart timeframes. EMA 10 Above EMA 20 on multiple timeframes is a good indicator that the market is bullish.
ZEducation
by TradeLive-
1
My Strategy Works On All Markets and All Time FramesPrice closed above EMA 20, EMA 10, Horizontal Support Resistance, and Trend Line. A pin bar formed on the retest and the pin bar candlestick wick protruded through the support levels. The support levels are EMA 20, EMA 10, Horizontal Support Resistance, and Trend Line. In this example, there are three higher lows moving into a diagonal resistance level and a horizontal resistance level. Price broke through those two levels and retested those levels with a pin bar. After the break and close above the horizontal and diagonal level; those levels became support. Entry is the closing price of the pin bar. Target price is the previous swing high.
DEducation
by TradeLive-
1
CoRA Ribbons - Two ideas how to use themSince CoRA Waves and Ribbons could help you to identify the trend better and more reliably, this indicator provides a good baseline for your strategy. The indicator " CoRA Ribbon - Multiple Compound Ratio Weighted Moving Averages " (#revision: lv21) was used in the following screenshots. Information and details on CoRA waves can be found in the description of the indicator. Let yourself be inspired. Let's start. These are just two of the many possibilities. I look forward to any further suggestion or idea. Comments and additional screenshots are always welcome. Even if CoRA Waves lag less than other moving averages, note, as with all other strategies, that one indicator alone is usually not sufficient. Usually further analyzes and the like are required. Therefore, understand the two examples for what they are: A hint that it is worth taking a look and perhaps one or the other known moving average can be exchanged very well with a CoRA Wave or a CoRA Ribbon - in order to get faster entry points.
Education
by consilus
2
How To Set Stop Losses And Take Profits using EMA StrategyWait for price to break and close below a level. In this example, price closed below support level and turned resistance. Next, wait for price to retest level as new resistance. The retest in this example formed a candlestick that created a wick which protruded through Horizontal Resistance Level, EMA 20 Resistance Level, and Diagonal Trend Resistance Level. For short trade opportunity, set stop loss above EMA 20 Price Level and Rejection Candlestick High Price. Set take profit at previous swing low.
Education
by TradeLive-
McGinley Dynamic IndicatorMcGinley Dynamic Indicator: It was invented by John R. McGinley. It would automatically adjust itself in relation to the speed of the market. This future can be very helpful as it is sometimes difficult to choose the right period for the MA. It also helps to account for the gap that often exists between prices and moving average lines. Can't be used as a single indicator and we need to combine this with other indicators or another McGinley indicator. Price actions respect moving averages because so many traders use them in their strategies. Because of the formula, the Dynamic Line speeds up in down markets and moves more slowly in uptrends. One wants to be quick to sell in a down market, yet ride an up-market as long as possible.
Education
by apadanaforex
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: 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
How To Trade Support Resistance Levels Price closed above EMA 10, EMA 20, Trend Line, and Horizontal Support & Resistance Level. Enter at close price of rejection candlestick. Close price of rejection candlestick is 0.73150. Set Stop Loss below EMA 20 Close Price and Low Price. Set Target at next support resistance level. Support and Resistance Levels are: EMA 10 EMA 20 Horizontal Line Diagonal Line High Price 0.73195 Close Price 0.73150 Open Price 0.73046 EMA 20 Price 0.72939 Low Price 0.72921 Close Price 0.73150 EMA 10 Close Price 0.73045 EMA 20 Close Price 0.72939
Education
by TradeLive-
1
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
How to adjust your charts for dividend paymentsBond funds like the SPDR Portfolio Mortgage Backed Bond ETF (SPMB) often look like money-losers when you view their returns on a non-adjusted basis. In this case, the price is down about -0.74% over the life of the fund. The picture looks very different when you adjust for dividends. For SPMB, the return changes to +46.09% over the life of the fund: That's obviously a very different chart than the non-adjusted chart. Dividend adjustment can also make a large difference for high-yield dividend stocks. For instance, IBM is down over the last ten years on a non-adjusted basis, but on an adjusted basis it has gone sideways. IBM, non-adjusted: IBM, adjusted: The commonly accepted adjustment methodology is that the most recent closing price will be the same on an adjusted and non-adjusted chart, but historical closing prices will be different. On an adjusted chart, the stock price on a historical date will be shown as the current closing price minus all dividends paid since then. Dividend subtractions typically are made on a percentage rather than dollar basis to prevent historical prices from showing as negative values. To actually perform the calculation is a little technical, but that's the overall idea. To apply dividend adjustment to a TradingView chart is super easy. In the lower right-hand corner of your chart, you will see the letters "adj". Click to toggle between adjusted and non-adjusted price data. When the text is blue, you are viewing the adjusted chart. When the text is black, adjustment is turned off. Right next to the letters "adj" is a "%" symbol. Toggling this on and off will switch the axis of the chart between dollars and percent change over the period visible on the chart. This is useful for comparing adjusted and non-adjusted returns. One implication of using adjusted charts is that the support levels and moving averages will be in different places. For instance, on a non-adjusted basis, VALE is currently below its 200-week moving average. On an adjusted basis, it is well above the average. VALE, non-adjusted: Vale, adjusted: In short, on an adjusted basis a stock may not be as cheap as it looks on a non-adjusted basis. Many quant traders and hedge funds will be using adjusted moving averages rather than non-adjusted ones.
AMEX:SPMBEducation
by ChristopherCarrollSmith
28
Bullish Golden Cross (How To Trade)What Is a Golden Cross? A golden cross occurs when a faster-moving average crosses a slower moving average. Sounds simple enough right? However, the key point is the moving averages which constitute the cross, and the direction in which they cross. Specifically, you need the 50-period and 200-period simple moving averages. Anything other than these two periods and it is not a true golden cross. Golden cross happens when a 50-day moving average for an asset trades higher than a 200-day moving average. In other words, prior to the the cross, the 50 moving average would have been below the 200 sma. You can use either MAs or EMAs- your choice. What are the three stages of a golden cross? 1) As the downtrend in the stock market ends, the short-term 50-day moving average moves below the 200- day moving average. 2) In a crossover, when a stock recovers, the short-term moving average crosses over the long-term moving average. That’s where the term golden cross comes from, when the two average lines cross on a chart. 3) In the last stage, the short-term moving average continues to move upward. That’s usually a sign that the market is on a bullish trend. "All big rallies start with a golden cross, but not all golden crosses lead to a big rally,” Golden crosses are not a definite timing signal to buy. “They tend not to be timing signals, but more for confirmation of a move that has been in place.” Look for both 50 ema and 200 ema to be close together, confirming indicators like Demand or Supply zone, pivot points, pair, price, session & time.
Education
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