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Mastering Moving AveragesMastering Moving Averages: A Statistical Approach to Enhancing Your Trading Strategy Moving averages (MAs) are one of the most popular tools used by traders and investors to smooth out price data and identify trends in the financial markets. While they may seem simple on the surface, moving averages are rooted in statistical analysis and offer powerful insights into price behavior over time. In this article, we will break down the concept of moving averages from a statistical viewpoint, explore different types of MAs and their benefits, and discuss how they can be effectively used in trading and market analysis. ⯁What is a Moving Average from a Statistical Standpoint? A moving average is a statistical calculation that smooths out data points by creating a series of averages over a specific period. In trading, it is applied to price data, where it helps remove short-term fluctuations and highlight longer-term trends. The core idea behind a moving average is to capture the central tendency of a price over time, providing a clearer picture of the market’s overall direction. By averaging the price over a period, it helps traders see the general trend without being distracted by the noise of daily market volatility. Mathematically, a simple moving average (SMA) can be expressed as: SMA = (P1 + P2 + ... + Pn) / n Where: P1, P2, ..., Pn represent the price points for each period. n represents the number of periods over which the average is taken. The moving average "moves" because as new prices are added to the calculation, older prices drop off, creating a rolling average that continually updates. Types of Moving Averages and How They Are Calculated Different types of moving averages use varying methods to calculate the average, each offering a unique perspective on price trends. Simple Moving Average (SMA) : The SMA is the most basic type of moving average and is calculated by taking the arithmetic mean of the prices over a specified period. Every data point within the period carries equal weight. SMA = (P1 + P2 + ... + Pn) / n For example, a 5-day SMA of a stock’s closing prices would be the sum of the last five closing prices divided by 5. Exponential Moving Average (EMA) : The EMA gives more weight to recent price data, making it more responsive to price changes. The EMA calculation involves a smoothing factor (also called the multiplier) that increases the weight of the most recent prices. The formula for the multiplier is: //Where n is the number of periods. The EMA calculation follows: Multiplier = 2 / (n + 1) EMA = (Closing price - Previous EMA) × Multiplier + Previous EMA For example, for a 10-period EMA, the multiplier would be 2 / (10 + 1) = 0.1818. This value is then applied to smooth the recent prices more aggressively. Weighted Moving Average (WMA) : The WMA assigns different weights to each data point in the series, with more recent data given greater weight. The formula for WMA is: WMA = (P1 × 1 + P2 × 2 + ... + Pn × n) / (1 + 2 + ... + n) Where n is the number of periods. Each price is multiplied by its period's number (most recent data gets the highest weight), and then the total is divided by the sum of the weights. For example, a 3-period WMA would assign a weight of 3 to the most recent price, 2 to the price before that, and 1 to the earliest price in the period. Smoothed Moving Average (SMMA) : The SMMA is similar to the EMA but smooths the price data more gradually, making it less sensitive to short-term fluctuations. The SMMA is calculated using this formula: SMMA = (Previous SMMA × (n - 1) + Current Price) / n Where n is the number of periods. The first period's SMMA is an SMA, and subsequent SMMAs apply the formula to smooth the prices more gradually than the EMA. ⯁Comparing Benefits of Different MAs SMA : Best for identifying long-term trends due to its stability but can be slow to react. EMA : More sensitive to recent price action, making it valuable for shorter-term traders looking for quicker signals. WMA : Offers a middle ground between the EMA’s sensitivity and the SMA’s stability, good for balanced strategies. SMMA : Ideal for longer-term traders who prefer a smoother, less reactive average to reduce noise in the trend. ⯁How to Use Moving Averages in Trading Moving averages can be used in several ways to enhance trading strategies and provide valuable insights into market trends. Here are some of the most common ways they are utilized: 1. Identifying Trend Direction One of the primary uses of moving averages is to identify the direction of the trend. If the price is consistently above a moving average, the market is generally considered to be in an uptrend. Conversely, if the price is below the moving average, it signals a downtrend. By applying different moving averages (e.g., 50-day and 200-day), traders can distinguish between short-term and long-term trends. 2. Crossovers Moving average crossovers are a popular method for generating trading signals. A "bullish crossover" occurs when a shorter-term moving average (e.g., 50-day) crosses above a longer-term moving average (e.g., 200-day), signaling that the trend is turning upward. A "bearish crossover" happens when the shorter-term average crosses below the longer-term average, indicating a downtrend. 3. Dynamic Support and Resistance Levels Moving averages can also act as dynamic support or resistance levels. In an uptrend, the price may pull back to a moving average and then bounce off it, continuing the upward trend. In this case, the moving average acts as support. Similarly, in a downtrend, a moving average can act as resistance. 4. Filtering Market Noise Moving averages are also used to filter out short-term price fluctuations or "noise" in the market. By averaging out price movements over a set period, they help traders focus on the more important trend and avoid reacting to insignificant price changes. 5. Combining with Other Indicators Moving averages are often combined with other indicators, such as the Relative Strength Index (RSI) or MACD, to provide additional confirmation for trades. For example, close above of two moving averages, combined with an RSI above 50, can be a stronger signal to buy than either indicator used on its own. ⯁Using Moving Averages for Market Analysis Moving averages are not just for individual trades; they can also provide valuable insight into broader market trends. Traders and investors use moving averages to gauge the overall market sentiment. For example, if a major index like the S&P 500 is trading above its 200-day moving average, it is often considered a sign of a strong market. On the contrary, if the index breaks below its 200-day moving average, it can signal potential weakness ahead. This is why long-term investors pay close attention to moving averages as part of their overall market analysis. ⯁Conclusion Moving averages are simple yet powerful tools that can provide invaluable insights for traders and investors alike. Whether you are identifying trends, using crossovers for trade signals, or analyzing market sentiment, mastering the different types of moving averages and understanding how they work can significantly enhance your trading strategy. By integrating moving averages into your analysis, you’ll gain a clearer understanding of the market’s direction and have the tools necessary to make more informed trading decisions.
Education
by ChartPrime
3
Mastering the Moving Average: The Trendspotter for Every TraderTradingViewers, this one will take you back to basics. In this Idea we visit a tool that’s as essential as your morning coffee — the Moving Average (MA). This indicator is the market’s smoothing instrument, ironing out the noise and letting you see the trend for what it really is. What’s a Moving Average? Think of the Moving Average as the market’s highlight reel. It averages out price action over a specific period, showing you where the market’s been and giving you a clue about where it might be headed. It’s the ultimate trendspotter, cutting through the daily chatter to reveal the bigger picture. Day traders and scalpers, don’t fret — it works on intraday time frames, too. Types of MAs Simple Moving Average (SMA): The old-school classic. It’s as straightforward as it gets — just an average of days you specify — 7, 9, 21, 50, 100, or even 200 days — that’s called “length”. This tool might be simple, but it’s a mainstay indicator for professional traders, institutional investors, and other big-shot money spinners. Exponential Moving Average (EMA): The turbocharged version of the SMA. It gives more weight to recent prices, meaning it reacts quicker to the action. If the SMA is a steady cruise, the EMA is a sports car with a little more kick. How to Use Moving Averages Spotting Trends : The Moving Average is your trend-checking buddy. Prices above the MA? We’re in bull territory. Prices below? Looks like the bears are in control. Slap it on any time frame — it’s the same rules regardless of the time horizon. Support and Resistance : MAs are like the guardrails of the market. They often act as support during uptrends and resistance during downtrends. When price bounces off an MA, it’s like a boxer bouncing off the ropes — watch for the counterpunch! The Golden Cross & Death Cross : Now we’re talking setups that get traders buzzing. When a short-term MA crosses above a long-term MA, you get a Golden Cross – the market’s flashing a buy signal party. But when the opposite happens, it’s a Death Cross, and the bears start licking their lips. Moving Average Crossover : Want some trading action? Watch for crossovers between short and long MAs. For example, throw in your chart a 50-day moving average and then top it up with a 100-day and a 200-day line. If they all cross over to the upside, you can expect a swing higher. And if they cross over to the downside, you can anticipate a swing lower. Pro Tip: Tune Your Moving Average Jot these numbers down — 20, 50, 100, 200 — these are the MA settings you’ll see most, but don’t be afraid to tweak them. A shorter MA (20 or 50) reacts quicker but can whipsaw you. A longer MA (100 or 200) is steadier but might be slower to catch reversals. It’s all about finding the balance that suits your trading style. Bottom Line The Moving Average isn’t about predicting the future — it’s about seeing the present more clearly. It’s the difference between getting lost in the noise and riding the trend with confidence. Whether you’re trend-following or looking for a noiseless entry, the MA is your go-to indicator. So slap that Moving Average on your chart and let it take you beyond the clutter. Because when the market’s moving fast, it pays to have a steady hand guiding your trades. And as essential as MAs are, don't limit your analysis to just one tool: apply several indicators on your chart to spot trends more effectively and enhance your research with data from the economic calendar , screeners, heatmaps, and all kinds of tools available on TradingView to have a bigger picture of market activities. Are you already using MAs in your charting and trading? Let us know in the comments below!
Education
by TradingView
11
HERE ARE 10 COMMON TRADING INDICATORS MADE SIMPLE Chart has all 10. Hope this helps. Hope it's simple to understand if you still struggle with indicators. Remember, no one indicator is good on its own. Think of an indicator as a sign that you should pay attention to a possibility. For example, if I go to the ocean, maybe I have an indicator that says you're closer to sharks than in the great lakes, will I be eaten? Probably not, but also, there are more sharks and my indicator confirms that. I can't use this one indicator to say, I'm probably about to be eaten. BUT.. Let's say I have multiple indicators that I use to give me a better idea if I'll be eaten. Maybe an indicator tells me there is an oddly higher than avg number of a sharks number 1 food source within the area. Can I say I'll be eaten? No, but I could say, maybe due to the increased food supply, there may be more sharks. What if I have a few more indicators, one of which says there are 30 great whites within 10 miles, and another that says, usually at this time of the year, there are only ever between 2 to 7 great whites. Can I say, Yes, I'll be eaten? NOPE, not yet. What if I have another indicator that says, across the globe, shark attacks are increasing by a certain percentage, and another that says, there is blood detected within the water you're swimming in, which is lower than the threshold for human's to detect, but higher than the threshold needed for sharks to smell. What if I combine that with an indicator that says, on avg there are 1000 swimmers here, but now, there are under 30. Can I say I'll be eaten? Nope, BUT, I can say, hmm. Something is up and if one of us were to get eaten, I'm more likely to be picked out of 30 people than 1000. When can I say I'll be eaten? Probably if you build an indicator that can detect bite force and compare to known bit forces of sharks that could sense you're actively being eaten, but at that point, the stock moved already... err I mean, the shark ate already, and you're late to the show.. My point being, use them, but don't always assume when it comes to indicators. Take in all the data and then make a decision. Some indicators fit your style, some won't. Do I need 30 stacked indicators for sharks if I'm swimming in Lake Michigan? Probably not, it would make everything a mess. So, here there are. Relative Strength Index (RSI): Ah, the RSI, the “I’ve had too much” indicator of the stock market. When it hits above 70, it’s like your stock had too much to drink at the party and is likely to come crashing down. Below 30? It’s been left out in the cold and might be due for a warm-up (a.k.a. price increase). Remember, it’s not foolproof, but then again, neither is your weather app. On-Balance Volume (OBV): This one’s all about following the crowd. If the volume is increasing, it’s like everyone’s rushing to get the latest iPhone. But remember, even if everyone jumps off a bridge, it doesn’t mean you should too. Always double-check before you follow the herd. Simple Moving Average (SMA): The SMA is like that reliable friend who’s always a bit behind on the latest trends. It gives you the average closing price over a certain period. It’s simple, it’s moving, it’s average. It’s the SMA. Exponential Moving Average (EMA): The EMA is the SMA’s hip younger sibling. It cares more about what happened recently than what happened way back when. It’s great for short-term trading, but remember, even the coolest kids can get things wrong. Moving Average Convergence Divergence (MACD): This one sounds complicated, but it’s not. It’s like watching two rabbits on a race track. If the fast rabbit (the 12-day EMA) overtakes the slow rabbit (the 26-day EMA), it’s a bullish signal. If the slow rabbit overtakes the fast one, it’s a bearish signal. Just remember, rabbits are unpredictable! Fibonacci retracements: Ah, Fibonacci, the Da Vinci of math. These horizontal lines indicate where support and resistance levels might be. It’s like trying to predict where you’ll meet your ex at a party. It could be useful, but don’t rely on it too much. Stochastic oscillator: This one’s a bit like a pendulum. When it swings one way, it’s likely to swing back the other way soon. It’s great for spotting potential reversals, but remember, even a broken clock is right twice a day. Bollinger bands: These are like the elastic waistband of your favorite sweatpants. If the price hits the upper band, it might be time to sell (or stop eating pizza). If it hits the lower band, it might be time to buy (or hit the gym). Average Directional Index (ADX): This one tells you whether the price is trending strongly or just wandering around like a lost puppy. Above 25 is a strong trend, below 20 is weak. But remember, even lost puppies find their way home eventually. Accumulation/Distribution (A/D) line: This one’s all about supply and demand. If the line is going up, the stock is being accumulated. If it’s going down, it’s being distributed. It’s like tracking whether more people are buying or selling fidget spinners. Remember, these indicators are like tools in a toolbox. Don’t try to build a house with just a hammer. Use them in combination, understand their limitations, and always do your own research. Happy trading! 📈
NASDAQ:TSLAEducation
by nicktussing77
18
AMA versus SMA. Is smarter really better?█ Adaptive versus Simple Moving Average Trading Strategies. Is smarter really better? Computer-aided trading systems have revolutionized the way trading decisions are made. We now employ sophisticated algorithms to predict market movements and execute trades at optimal times. Among these, moving average(MA) strategies stand out for their simplicity and effectiveness among the many available strategies. This study by Craig A. Ellis and Simon A. Parbery compares two prominent MA strategies: the Adaptive Moving Average(AMA) and the Simple Moving Average(SMA). Conclusion: While adaptive moving average strategies may provide an edge in certain market conditions by capturing trends more efficiently than simple moving averages, investors must carefully consider transaction costs. These costs can significantly impact net returns, particularly in frequent trading strategies. Findings suggest that the effectiveness of adaptive versus simple moving average trading strategies is nuanced in varying market conditions, with no one-size-fits-all answer. Investors should weigh the potential benefits of adaptability against the increased costs and risks associated with such strategies. █ Moving Average Trading Systems Among the various types of moving averages, the Simple Moving Average(SMA) and the Adaptive Moving Average(AMA) are particularly noteworthy due to their distinct characteristics and applications in trading strategies. ⚪ Simple Moving Average and Its Calculation SMA is one of the most basic moving averages in trading. It calculates the average price of a security over a defined number of periods. The SMA is straightforward to compute; you sum up the security's closing prices for a set number of periods and then divide this total by the number of periods. This process results in a smooth line that traders can overlay on their price charts to assess the direction of the trend. For example, a 20-day SMA would add up the closing prices of the past 20 days and divide the total by 20. This calculation is continuously updated as new closing prices become available, giving traders a dynamic view of the market's trend. // Function to calculate the SMA using an array sma(source, length) => // Initialize an array to hold the prices prices = array.new_float(length) // Fill the array with the most recent `length` prices for i = 0 to length - 1 array.set(prices, i, source ) // Calculate the sum of the array elements sum = array.sum(prices) // Return the average sum / length ⚪ Adaptive Moving Average and Its Calculation The Adaptive Moving Average (AMA), proposed by Perry Kaufman in his book "New Trading Systems and Methods," represents a significant advancement in moving average technology. Unlike the SMA, which gives equal weight to all data points, the AMA adjusts its sensitivity based on the market's volatility. This adaptability makes the AMA particularly useful in identifying market trends with varying degrees of volatility. The core of the AMA's adaptability lies in its Efficiency Ratio (ER), which measures the directionality of the market over a given period. The ER is calculated by dividing the absolute change in price over a period by the sum of the absolute differences in daily prices over the same period. // Calculate the Efficiency Ratio (ER) change = math.abs(close - close ) volatility = math.sum(math.abs(close - close ), length) ER = change / volatility The ratio helps determine how efficiently the price is moving in one direction. A higher ER indicates a more directional market, prompting the AMA to react quickly to price changes. A lower ER suggests a consolidating market, leading the AMA to respond more to recent price changes. █ Data and Research Methodology The data set encompasses daily closing prices for three major stock indices: the Australian All Ordinaries, the Dow Jones Industrial Average (DJIA), and the S&P 500, spanning from 1980 to 2002. This period provides a comprehensive view of market behavior, including various economic cycles, bull and bear markets, and periods of high volatility. Such a diverse data set is crucial for testing the robustness of the AMA in different market environments. This study investigates whether AMA's adaptive nature results in superior performance compared to the more static SMA and the passive buy-hold approach. The key steps in the research methodology include: Parameter Selection: Identifying optimal parameters for both AMA and SMA to ensure a fair comparison. This involves selecting the look-back periods and thresholds for triggering buy or sell signals. Strategy Implementation: Developing trading strategies based on AMA, SMA, and a buy-hold benchmark. Each strategy is applied to the data set to simulate real-world trading, with buy or sell signals generated according to the specific rules of each approach. Performance Evaluation: The performance of each strategy is assessed using several metrics, including total return, risk-adjusted return, and maximum drawdown. This comprehensive evaluation aims to determine the effectiveness of AMA in navigating various market conditions compared to SMA and buy-hold strategies. Statistical Testing: Conducting statistical tests to ascertain the significance of the differences in performance outcomes among the strategies. This includes tests for statistical significance in returns and risk metrics, providing a robust framework for comparison. Sensitivity Analysis: Exploring how changes in the parameters of AMA and SMA affect the strategies' performance. This analysis helps understand the flexibility and adaptability of AMA in response to different market dynamics █ Results The empirical analysis focused on comparing the performance of Adaptive Moving Average (AMA) and Simple Moving Average (SMA) strategies across a variety of indices, including the S&P 500, Dow Jones Industrial Average (DJIA), and NASDAQ. The performance metrics were primarily based on the total return over the investment period, the Sharpe ratio, and the maximum drawdown to assess each strategy's risk-adjusted returns and resilience during market downturns. The table demonstrates that the AMA strategy consistently outperformed the SMA strategy across all indices regarding total return and Sharpe ratio, indicating a superior risk-adjusted return. However, it's important to note that the AMA strategy also experienced slightly higher drawdowns than the SMA in certain instances, suggesting a potentially higher risk during market downturns. ⚪ In discussing the market timing ability of AMA, the analysis found that AMA could better adapt to changing market conditions, thereby capturing trends more efficiently than the SMA strategy. This adaptability resulted in higher returns during periods of significant market movements. However, when accounting for transaction costs, the advantage of AMA over SMA diminished, particularly in markets characterized by frequent, small movements that triggered more trading activity by the AMA strategy. █ Reference Ellis, C. A., & Parbery, S. A. (2005). Is smarter better? A comparison of adaptive, and simple moving average trading strategies. Research in International Business and Finance, 19, 399-411. ----------------- Disclaimer This is an educational study for entertainment purposes only. The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
OANDA:XAUUSDEducation
by Zeiierman
7
Choosing the Right Moving AverageMastering Moving Averages: A Comprehensive Guide to Choosing the Right One for Your Trading Strategy Moving averages are among the most widely used technical indicators in trading. They serve as a simple and effective way to identify trends, support and resistance levels, and potential entry and exit points for trades. With numerous types of moving averages available, determining the best fit for your trading strategy can be a challenge. In this comprehensive guide, we will delve into the various types of moving averages, their strengths and weaknesses, and when to use them to maximize your trading profits. Simple Moving Average (SMA) The Simple Moving Average (SMA) is the most basic type of moving average. It calculates the average price of an asset over a specific time period, typically 20, 50, or 200 days. The SMA smooths out the price data by creating a constantly updating average price, providing a clear picture of the asset's direction of movement. I personally use the SMA for long-term trading strategies because it offers a more stable picture of the asset's direction of movement. The SMA is also useful in identifying potential support and resistance levels, which are critical indicators for traders. However, the SMA can be slow to respond to changes in price, which can result in missed opportunities for short-term traders. Advantages of SMA 1. Easy to calculate and understand. 2. Provides a stable picture of the asset's direction of movement. 3. Useful in identifying potential support and resistance levels. Disadvantages of SMA 1. Slow to respond to changes in price. 2. Can lag behind the current price action, leading to missed opportunities. Exponential Moving Average (EMA) The Exponential Moving Average (EMA) is a more complex type of moving average that places greater weight on recent price data. This weighting provides the EMA with a more immediate response to price changes than the SMA, making it a popular choice for short-term traders. The EMA is calculated by taking the weighted average of the asset's price over a specified time period, giving more weight to recent prices. Traders use the EMA for short-term trading strategies because it offers a more immediate response to price changes, which is crucial for short-term trades. The EMA is also useful in identifying potential price reversals, support and resistance levels, and momentum. However, the EMA can be more volatile than the SMA, which can lead to false signals and increased risk. Advantages of EMA 1. Provides a more immediate response to price changes. 2. Useful for short-term trading strategies. 3. Helps identify potential price reversals and momentum shifts. Disadvantages of EMA 1. Can be more volatile than the SMA, leading to false signals. 2. May require more complex calculations than the SMA. Weighted Moving Average (WMA) The Weighted Moving Average (WMA) is another type of moving average that places a greater weight on recent prices. Unlike the EMA, the WMA assigns a weight to each price point based on its position in the time period. This means that the most recent prices receive the highest weight, with each price point receiving a progressively lower weight as you move back in time. Traders use the WMA for short-term trading strategies when they want a more sensitive indicator than the SMA. The WMA is also useful in identifying potential price reversals and support and resistance levels. However, the WMA can be more volatile than the SMA, which can lead to false signals and increased risk. Advantages of WMA 1. Provides a more sensitive indicator than the SMA. 2. Useful for short-term trading strategies. 3. Helps identify potential price reversals and support and resistance levels. Disadvantages of WMA 1. Can be more volatile than the SMA, leading to false signals. 2. equires more complex calculations than the SMA. Smoothed Moving Average (SMMA) The Smoothed Moving Average (SMMA) is a type of moving average that applies a smoothing factor to the price data, resulting in a smoother curve. The SMMA places an equal weight on all price data, with the smoothing factor determining the weight given to each data point. Traders use the SMMA when they want a smoother curve to analyze the asset's trend. The SMMA is useful in identifying potential support and resistance levels and entry and exit points. However, the SMMA can be slow to respond to changes in price, which can lead to missed opportunities for short-term traders. Advantages of SMMA 1. Provides a smoother curve for trend analysis. 2. Useful in identifying potential support and resistance levels and entry and exit points. 3. Less sensitive to short-term price fluctuations. Disadvantages of SMMA 1. Can be slow to respond to changes in price. 2. Not as suitable for short-term trading strategies. Which Moving Average Should You Use? The type of moving average you should use depends on your trading strategy and time frame. If you are a long-term trader, you may want to use the SMA or WMA, as they provide a more stable picture of the asset's direction of movement. If you are a short-term trader, you may want to use the EMA or WMA, as they provide a more sensitive indicator of price changes. Additionally, if you are looking for a smoother curve to analyze, the SMMA may be the best option. It is essential to note that moving averages should not be used in isolation. They should be used in conjunction with other technical indicators, such as oscillators or volume indicators, to confirm potential buy and sell signals. It is also crucial to consider the market conditions, such as volatility and liquidity, when choosing a moving average for your trading strategy. How to Combine Moving Averages for Better Trading Signals 1. Use multiple timeframes: Employing moving averages from different timeframes can help you identify both short-term and long-term trends, as well as potential entry and exit points. 2. Use multiple types of moving averages: Combining different types of moving averages, such as the SMA and EMA, can help you identify trend reversals and filter out false signals. 3. Apply other technical indicators: To confirm the signals provided by moving averages, use additional technical indicators like the Relative Strength Index (RSI), the Moving Average Convergence Divergence (MACD), or the Bollinger Bands. Strengths and Weaknesses of Moving Averages Each type of moving average has its strengths and weaknesses, depending on the trading strategy and time frame. Here is a summary of the main differences between the four types of moving averages: 1. SMA: provides a more stable picture of the asset's direction of movement, but can be slow to respond to changes in price. 2. EMA: provides a more immediate response to price changes, making it a popular choice for short-term traders, but can be more volatile than the SMA. 3. WMA: assigns a weight to each price point based on its position in the time period, providing a more sensitive indicator than the SMA, but can be more volatile than the SMA. 4. SMMA: applies a smoothing factor to the price data, resulting in a smoother curve, but can be slow to respond to changes in price. It is important to understand the strengths and weaknesses of each type of moving average to make an informed decision when selecting a moving average for your trading strategy. Conclusion Moving averages are a powerful tool in a trader's arsenal, but choosing the right type can be challenging. The SMA, EMA, WMA, and SMMA each have their advantages and disadvantages, and the one you choose should depend on your trading strategy and time frame. By combining moving averages with other technical indicators and considering market conditions, you can maximize your trading profits. As a trader with experience in using various technical indicators, I've found moving averages to be quite helpful in identifying trends and potential entry and exit points. However, despite the usefulness of moving averages, I personally prefer indicators that use linear regression. The reason for my preference is that linear regression-based indicators, such as the "Regression Envelope MTF", take into account the slope of the trend, rather than assuming that the trend is linear. This means that the bands will adapt to the slope of the trend, providing more accurate signals in trending markets. For instance, I typically use the "Regression Envelope MTF" (one of my indicators that I have just recently published) on the daily chart with a parameter setting of 250 periods. This allows me to quickly see where the price is positioned relative to the past year's trend. I find this approach to be particularly insightful and beneficial for my trading decisions. Remember to always use caution when trading, and never risk more than you can afford to lose. It is also essential to continue learning and refining your trading strategies to stay ahead of the curve and become a successful trader.
NASDAQ:AAPLEducation
by Julien_Eche
The 5-Indicator Technical FusionThe Hidden Gem of Market Strategy: The 5-Indicator Technical Fusion Ever felt like you've hit a gold mine when you discovered an ingenious, yet underrated, financial strategy? Buckle up, because today, we're diving deep into the world of technical indicators to unveil a mind-blowing market strategy that will leave you speechless. This strategy, called the 5-Indicator Technical Fusion, harnesses the power of five complex indicators, but we're going to focus on the one that sits at the perfect average. Get ready to unlock a whole new level of market mastery. The 5-Indicator Technical Fusion: The 5-Indicator Technical Fusion combines five advanced technical indicators that, when used together, create an unparalleled trading strategy. The five indicators are: 1. Schmancy Fibonacci Retracement Oscillator (SFRO) 2. Quantum Volume Expansion Index (QVEI) 3. Time-Traveling SMA (TTSMA) 4. Galactic Bollinger Bands Envelope (GBBE) 5. Psychedelic Relative Strength Index (PRSI) 6. Each of these indicators brings a unique perspective to market analysis, but the real magic happens when they're combined. However, we're here to talk about the one that hits the sweet spot right in the middle: the Time-Traveling 7. Moving Average (TTSMA). Time-Traveling Moving Average (TTSMA) – The Hidden Gem: The TTSMA is a revolutionary indicator that goes beyond the limitations of traditional moving averages. It uses quantum algorithms to simulate market behavior, projecting future price trends based on historical data. By analyzing the past, the TTSMA can predict future price movements with an astonishing degree of accuracy. Why the TTSMA Rocks: 1. Predictive Power: The TTSMA's ability to foresee market trends before they happen gives traders a significant advantage in making informed decisions. 2. Time Efficiency: The TTSMA saves traders precious time, as it quickly identifies potential entry and exit points without the need for tedious manual analysis. 3. Risk Management: The TTSMA helps traders mitigate risk by providing insights into potential price fluctuations, allowing them to adjust their strategies accordingly. The Secret Sauce: Averaging the 5-Indicator Fusion: Although each of the five indicators in the Technical Fusion is powerful on its own, the true strength of this strategy lies in their combined power. To unlock the full potential of the 5-Indicator Technical Fusion, traders should use the TTSMA as the central pivot point while incorporating the insights provided by the other four indicators. The 5-Indicator Technical Fusion, with the Time-Traveling Moving Average as its core, is a groundbreaking and largely undiscovered market strategy that offers traders unparalleled predictive power, time efficiency, and risk management. So, next time you're looking for an edge in the financial markets, don't forget to explore the hidden gem that is the TTSMA. You won't be disappointed.
SP:SPXEducation
by Julien_Eche
2
MOVING AVERAGES MADE SIMPLE Moving averages are commonly used to analyze and forecast trends in financial data. There are several types of moving averages, including: Simple Moving Average (SMA): This is the most basic type of moving average. It calculates the average price of a security over a specified number of periods. Weighted Moving Average (WMA): This type of moving average assigns a weight to each period's price, with more recent prices given greater importance. Exponential Moving Average (EMA): This type of moving average puts greater weight on more recent prices and adjusts the weighting based on the volatility of the prices. Smoothed Moving Average (SMMA): This type of moving average is similar to the EMA but uses a different formula to calculate the weighting. Hull Moving Average (HMA): This type of moving average uses weighted averages to reduce lag and improve responsiveness to price changes. The choice of moving average type depends on the specific application and the trader's preference. EXPLANATION ON HOW EACH WORKS. Simple Moving Average (SMA): Imagine you have a toy car that you play with every day for a week. At the end of each day, you write down how far the car traveled. The simple moving average is like adding up all the distances the car traveled and dividing by the number of days you played with it. This gives you an average distance the car traveled each day. Weighted Moving Average (WMA): Now, imagine you have another toy car that you play with every day, but you like to give more importance to the distance it traveled on the most recent day. The weighted moving average is like giving more weight, or importance, to the distance the car traveled on the most recent day when calculating the average. Exponential Moving Average (EMA): The exponential moving average is like the weighted moving average, but it puts even more importance on the most recent day's distance. This means that the average changes more quickly when there are big changes in the price. Smoothed Moving Average (SMMA): The smoothed moving average is like the exponential moving average, but it uses a slightly different formula to calculate the average. It's a way of smoothing out the bumps in the price and making it easier to see the trend. Hull Moving Average (HMA): The Hull moving average is like the smoothed moving average, but it tries to reduce the time lag between the price changes and the moving average. It's like having a toy car that responds more quickly to your movements when you're controlling it with a remote. So those are the different types of moving averages! They all have different ways of calculating the average price over time, and they can be useful for different things depending on what you're trying to analyze. CROSSING OF MOVING AVERAGES The crossing of moving averages is a popular technical analysis tool used to identify potential changes in the direction of a trend. A moving average is calculated by taking the average price of a security over a certain period of time. Traders often use two moving averages, one short-term and one long-term, to look for potential changes in the trend. When the short-term moving average crosses above the long-term moving average, it is called a "golden cross," which is a bullish signal that suggests the price may be moving higher. Conversely, when the short-term moving average crosses below the long-term moving average, it is called a "death cross," which is a bearish signal that suggests the price may be moving lower. Here's an example to help explain: Let's say we have a 50-day moving average and a 200-day moving average. If the 50-day moving average crosses above the 200-day moving average, it's a golden cross, indicating that the short-term trend is turning bullish, and it could signal a potential upward price movement. Conversely, if the 50-day moving average crosses below the 200-day moving average, it's a death cross, indicating that the short-term trend is turning bearish, and it could signal a potential downward price movement. The crossing of moving averages can be used in conjunction with other technical indicators and analysis to help traders make more informed decisions when buying or selling a security. It's important to note that no indicator is foolproof, and traders should always consider other factors such as market conditions, fundamental analysis, and risk management before making any trading decisions. INFLICTION POINT VS CROSSOVER An inflection point is a point on a graph where the curvature, or shape, of the line changes. It is a point of transition between a curve that is bending upwards and one that is bending downwards, or vice versa. In other words, it's a point where the rate of change of a function changes from positive to negative or vice versa. On the other hand, the crossing of moving averages is a technical analysis tool used to identify potential changes in the direction of a trend, which is based on the relationship between two or more moving averages. While the crossing of moving averages may sometimes coincide with an inflection point, they are two distinct concepts. HOW YOU SHOULD USE MOVING AVERAGES 🔸Trend identification: Moving averages can help traders identify the direction of the trend. For example, if the price of a security is consistently trading above a moving average, it can indicate an uptrend, while trading below the moving average can indicate a downtrend. This information can be useful in determining entry and exit points for trades. 🔸Support and resistance levels: Moving averages can also help identify potential support and resistance levels. In an uptrend, the moving average can act as a support level, while in a downtrend, it can act as a resistance level. Traders can use these levels to help determine their risk and reward when placing trades. 🔸Momentum indicators: Moving averages can be used as momentum indicators to help identify the strength of the trend. A short-term moving average crossing above a long-term moving average can indicate bullish momentum, while a short-term moving average crossing below a long-term moving average can indicate bearish momentum. 🔸Trading signals: Traders can use crossovers of moving averages to generate buy and sell signals. For example, a bullish signal is generated when a short-term moving average crosses above a long-term moving average (golden cross), while a bearish signal is generated when a short-term moving average crosses below a long-term moving average (death cross). 🔸Moving averages can be used to clearly see trend waves by smoothing out price data over a specified period of time. This can help traders identify the direction of the trend and the strength of the momentum in the market. When using moving averages, it's important to consider other factors such as market conditions, fundamental analysis, and risk management. Traders should also experiment with different types of moving averages and time periods to find what works best for their trading strategy.
PEPPERSTONE:ETHUSDEducation
by ChristopherDownie
53
A trifling observation.Is it possible to provide an indication that pre-empts the classic "death cross"? Traders use different systems to judge the market outlook on patterns, as well as an important indication for them. It is perfectly normal that someone can be wrong, and someone will be lucky to read the market correctly. This post is about anticipatory indication and prejudice. If you open the articles on moving averages, you can read that the exponential Moving averages (EMAs) are preferable on low timeframes up to a minute chart, but they are not but it's recommended for the weekly chart. Whereas it is recommended to use SMAs on longer timeframes. OK, I thought. But why? Who has checked it? A price is a price, in itself it only says that someone has offered an asset at a certain price, and someone bought at that price. But the market trend requires more confirmation of transactions through volumes. The price alone cannot tell you what the market has decided. And that is why I made this comparison. MA 50/200 (white and blue line) versus EMA 50/200 (orange and purple) + VFI LF (volume flow indicator). Hypothesis: EMAs are valid for 1 week timeframe, the exponent is not suitable for this timeframe is a preconception. MA lags in indicating the signal, but you need to know the trend of the volume, for which you need an indicator like VFI LF. In the case of unidirectional signals EMA 50/200 and VFI LF you can make a deal without waiting for the signal MA 50/200. Assertion:
 Bitcoin is in a bear market and no reversal has occurred. The bounce at the beginning of the year was intended to test crossed possible area of the weekly SMA moving averages. But because of death cross on EMAs already on the 9th of January, it also puts selling pressure. And here the Volume Flow Indication is an important aid. See, the VFI has two pale lines besides the volume flow line itself, it's a fast and slow MA of volume (but it's MA of volume, not of price!), and on these lines you can also see golden and death crosses. Look closely, in the history of Bitstamp trading (the longest trading history of Bitcoin) there have been exactly 3 such crosses by volume indication on weekly chart. Two bearish and one bullish. The last bearish cross on the MA of volume flow occurred about a month before the cross at EMA 50/200 price. December 12... As a result: Two bearish pre-emptive signals versus one classic "textbook" one. My bet is that there will not be a upbounce. There will be an 85% retracement level from the peak and a consolidation at the bottom. Waiting for a reality check in this race. My bet is that we are in a bear market.
BITSTAMP:BTCUSDEducation
by averkie_skila
13
Beginner's Guide To Moving AveragesMoving averages are without a doubt the most popular trading tools. Moving averages are great if you know how to use them but most traders, however, make some fatal mistakes when it comes to trading with moving averages. In this article, I show you what you need to know when it comes to choosing the type and the length of the perfect moving average and how to use moving averages when making trading decisions. What is the best moving average? EMA or SMA? In the beginning, all traders ask the same questions, whether they should use the EMA (exponential moving average) or the SMA (simple/smoothed moving average). The differences between the two are usually subtle, but the choice of the moving average can make a big impact on your trading. Here is what you need to know: The differences between EMA and SMA There is really only one difference when it comes to EMA vs. SMA and its speed. The EMA moves much faster and it changes its direction earlier than the SMA. The EMA gives more weight to the most recent price action which means that when the price changes direction, the EMA recognizes this sooner, while the SMA takes longer to turn when the price turns. Pros and cons – EMA vs SMA There is no better or worse when it comes to EMA vs. SMA. The pros of the EMA are also its cons – let me explain what this means: The EMA reacts faster when the price is changing direction, but this also means that the EMA is also more vulnerable when it comes to giving wrong signals too early. For example, when the price retraces lower during a rally, the EMA will start turning down immediately and it can signal a change in the direction way too early. The SMA moves much slower and it can keep you in trades longer when there are short-lived price movements and erratic behavior. But, of course, this also means that the SMA gets you in trades later than the EMA. What is the best period setting? When you are a short-term day trader, you need a fast-moving average that reacts to price changes immediately. That’s why it’s usually best for day traders to stick with EMAs. On the other hand, Swing traders have a very different approach and they typically trade on higher time frames (4H, Daily +) and also hold trades for longer periods of time. Thus, swing traders should first choose an SMA and also use higher period moving averages to avoid noise and premature signals. The best moving average periods for day-trading 9 or 10 periods: Very popular and extremely fast-moving. Often used as a directional filter (more later) 21 period: Medium-term and the most accurate moving average. Good when it comes to riding trends 50 period: Long-term moving average and best suited for identifying the longer-term direction The best periods for swing trading 20 / 21 periods: The 21 moving average is my preferred choice when it comes to short-term swing trading. During trends, price respects it so well and it also signals trend shifts. 50 period: The 50 moving average is the standard swing-trading moving average and is very popular. Most traders use it to ride trends because it’s the ideal compromise between too short and too long term. 100 period: There is something about round numbers that attract traders and that definitely holds true when it comes to the 100 moving average. It works very well for support and resistance – especially on the daily and/or weekly time frame. 200 / 250 period: The same holds true for the 200 moving average. The 250 period moving average is popular on the daily chart since it describes one year of the price action (one year has roughly 250 trading days) How to use moving averages Trend direction and filter you can use a fast EMA to stay on the right side of the market and filter out trades in the wrong direction. Just this one tip can already make a huge difference in your trading when you only start trading with the trend in the right direction. The Golden Cross and the Death Cross But even as swing traders, you can use moving averages as directional filters. The Golden and Death Cross is a signal that happens when the 200 and 50-period moving average cross and they are mainly used on the daily charts. In the chart below, I marked the Golden and Death cross entries. Basically, you would enter short when the 50 crosses the 200 and enter long when the 50 crosses above the 200 period moving average. the screenshot shows that during the last bitcoin cycle if you stuck to the moving averages you would have been profitable most of the time both in the long and short directions. Also please notice how when the market is moving sideways it's not favorable to use the moving averages. I will end this article here, I hope you now have a better understanding in moving averages and how to utilize them to follow the trend.
INDEX:BTCUSDEducation
by m3rr0r
Trading SetupHi traders in this post would like to share a trade setup i use for a while. first - supertrand indicator second - 20-50-200 sma indicator for supertrand - click on indicators and search for supertrend - choose the 3rd 1 from the list u see. change settings to - atr period - 5 source - hlcc4 - and atr multiplier - 1 now u have a system which will print out buy / sell signals. combined with 20-50-200 sma - i take a position when price cross the 20 sma. look @ the examples - sell signal + cross the 20ma test it @ home :) ##this is not investing advise## hope you find it usufull ... good luck
NYSE:ZIMEducation
by DaxiDriver
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
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
Education excerpt: Simple Moving AverageSimple Moving Average (SMA) 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. 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. 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. Calculation and formula 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 of weekly chart of DAI: Red line = 50-day SMA Green line = 20-day SMA Disclaimer: This is just excerpt from our full text. This content is not intended to encourage buying or selling of any particular securities. Furthermore, it should not serve as basis for taking any trade action by individual investor. Your own due dilligence is highly advised before entering trade.
DEducation
by Tradersweekly
3
Five types of major support and resistance levelsWant to buy the bottom and sell the top? Want to predict major turning points in a security's price? Want to avoid buying too early or selling too late? Then you need to understand support and resistance levels! I know a lot of people who mostly trade breakouts. That can be a very successful strategy, and I've used it myself to good effect. But if you buy a breakout after it happens, you pay a "breakout premium"-- especially if you're buying option calls or puts. You'll get a much better price on options if you buy them *before* a breakout or *before* a major change in momentum. How do you do that? Know your support and resistance levels! Once you know how to identify the different types of support and resistance, you can look to see where several different types of support or resistance coincide . Those will be key price points at which different types of investors who rely on different types of indicators will all buy or sell at the same time.
NYSE:HPEEducation
by ChristopherCarrollSmith
3
1D SMITH WESSON TRENDLINE BREAKOUTTrend Line Trading: The Trend Breaker Strategy This trendline breakout trading strategy uses three indicators, which are the following: MACD- The inputs for this indicator are: Fast Length= 12 (represents the previous 12 bars of the faster moving average), Slow Length= 26 (Represents the previous 26 bars of the slower moving average), and Signal Smoothing= 9 ( represents the previous 9 bars of the difference between the two moving averages. This is plotted by vertical lines called a histogram). Simple Moving Average- The inputs for this indicator are: Length 8, Offset 0. (Red line) Exponential Moving Average-The inputs for this indicator are: Length 20, Offset 0. (Blue line) This Trend Breaker strategy also uses three different time frames. They are the 4 hour, the 1 hour, and 15 minute time frames. This top-down approach uses these time frames to identify a trend, find a breakout point, determine an entry point, and execute the trade. Step One to trend line trading: Identify a trend The first thing you need to do is identify an upward, downward, or sideways trend by switching to a 4-hour and 1 hour time frames. The reason both are used is that it will give you the best perspective in determining a trend according to this strategy. Draw a trend-line so that 3 points of resistance or support was touched. We created this trendline trading system so that you could easily enter trades without a lot of guesswork on your part. Here You can see a funny video about trading levels. Since this strategy focuses on trends, a trend line will be drawn on the support or resistance lines of the trend. The criteria for a trend is that there needs to be at least three points of resistance or support. As you can see on the 4- hour time frame this clearly is a downtrend. Below is the same chart only this is a 1-hour time frame. This is just to get another perspective of this downtrend. It is good to do this to completely confirm this trend by identifying 3 levels of resistance. Trading with trend lines is not easy, that is why it is important to have a clear system of step by step rules to make it easy for you to follow. Step Two: Identify a Breakout point Trendline Trading System In order to find a breakout point of the trend that was identified in step one, the strategy will use a combination of the three indicators (MACD, 15 minute SMA, EMA) to identify a break out on the 15-minute time frame. This time frame is used because a trend was already identified in step one on the 4 hours and 1 hour time frames. As you can see in the chart above on the 15-minute time frame, the MACD lines were crossed. When the crossover of the fast length and slow length occurs, this will signal a new trend. This gave an indication that a trend was breaking. The moving average and exponential moving average lines also crossed. So when the MACD lines cross and the simple moving average/ exponential lines cross wait until the candlesticks go above/below trend line that was drawn in step one, then identify a point of entry into the trade. One of the reasons we like trend line trading so much is that it is straight forward and simple and we recommend all traders have something simple. So looking at our example above the criteria was met to go to step three because the SMA and EMA crossed and the MACD lines crossed. Also, the trend went upwards and hit our trend line. This is a signal to go to step three. If neither of the indicators crosses before the candlesticks close and hit the trend line then do not go any further because the trade does not meet the criteria of the rules. The indicators need to show that the trend broke before it touched the trend line. Note* When our indicators are crossing, the trend needs to be heading toward the trend line that was drawn in step one. This is because the trend is breaking and a breakout is about to occur. When the breakout happens we will discuss when to make an entry. Step Three: Trend Line Trading Identify a point of entry Here is a list of the entry criteria: These 4 things must happen to enter a trade with this Trend Breaker Strategy. Simple Moving Average Must Cross below the Exponential moving average. Macd Must Cross The price must break below or above the trend line. After the break of the trendline, you must wait for 3 candles to close on the 15-minute chart before taking your entry. Now we need to identify a point of entry. To identify a point of entry always use the 15 minute time frame in this strategy. So in our example below, we see that there is an obvious stand-off between buyers and sellers on the trend line. Once there are at least three candlesticks above or below the trend line, you execute the trade. In this example, there are three candlesticks that fell above the trend line after our indicators signaled that the trend was broken. At this point, you want to make an entry. Also, read about Trader's Tech and Installing MT4 EAs with Indicators. Step four: How to Trade with Trend Lines: Determine where to place a stop loss. 1 Use Pong Position Icon on left side toolbar. Adjust Top Prifit line until center text says 1 to 3 risk reward. This will show you where SL should be placed. OR Place a stop loss past the last support and resistance levels in the trend itself. Again, use the 15 minute time frame to find this point of resistance/ support level. In the example shown below, place the stop loss below the last support level. This will ensure that if there was a bearish move, it will hit the last point of support and make a bullish move upwards. You can clearly see that there are two levels of support in the above example. Use the support levels to determine the stop loss. The rules were to place the stop loss below the last support level which is why you see the stop loss below these levels. Step five: Trendline Trading System Exit Strategy The plan clearly identified a trend, a breakout point, point of entry, and determined a stop loss. The final step is to determine the exit point. This Trend Breaker strategy uses 1 risk to 3 reward ratio. What that means is you have the potential to make 3 times more than you are risking. Use the Long Position Icon on the left side toolbar. Adjust top profit level until the center text says 1 to 3 risk reward. Conclusion This Trend Breaker Strategy is simple and yet effective. There is no need to stress and worry that you made the wrong trade. You follow the rules and do not let anything else make you back out of a trade. If it follows the rules, execute the trade with confidence. Always remember to only be risking no more than 2% of your account! This will help you identify daily trends and points where they break. There is no need to force yourself into a trade. If it does not follow your rules and guidelines then search for another pair to trade. Feel free to check out one of our other trading strategies.
NASDAQ:SWBIEducation
by Tradingstrategyguides
1
What Are These Moving Averages?Moving averages rely on past data, they are considered to be lagging or trend following indicators. Regardless, they still have great power to cut through the noise and help determine where a market may be heading. Different types of moving averages There are various different types of moving averages that can be used by traders. Despite the various types, the MAs are most commonly broken down into two separate categories: simple moving averages (SMA) and exponential moving averages (EMA). Depending on the market and desired outcome, traders can choose which indicator will most likely benefit their setup. The simple moving average The SMA takes data from a set period of time and produces the average price of that security for the data set. The difference between an SMA and a basic average of the past prices is that with SMA, as soon as a new data set is entered, the oldest data set is ignored. So if the simple moving average calculates the mean based on 10 days worth of data, the entire data set is constantly being updated to only include the last 10 days. It's important to note that all data inputs in an SMA are weighted equally, regardless of how recently they were inputted. Traders who believe that there's more relevance to the newest data available often state that the equal weighting of the SMA is detrimental to the technical analysis. The exponential moving average (EMA) was created to address this problem. The exponential moving average EMAs are similar to SMAs in that they provide technical analysis based on past price changes. Nevertheless, the equation is a bit more complicated because an EMA assigns more weight and value to the most recent price inputs. Although both averages have value and are widely used, the EMA is more responsive to sudden price fluctuations and reversals. Cause EMAs are more likely to project price reversals faster than SMAs, they are often especially preferred by traders who are interested in short-term trading. It is important for a trader or investor to choose the type of moving average according to his personal strategies and goals, adjusting the settings accordingly. MAs of 50, 100, and 200 days are the most commonly used. How to trade with MA? Generally, a rising MA suggests an upward trend(acts as a support when rising under a price) and a falling MA indicates a downtrend(acts as resistance when falling above a price). Though, a moving average alone is not a really reliable and strong indicator. Therefore, MAs are constantly used in combination to spot bullish and bearish crossover signals. A crossover signal is created when two different MAs crossover in a chart. A bullish crossover (also known as a golden cross) happens when the short-term MA crosses above a long-term one, suggesting the start of an upward trend. In contrast, a bearish crossover (or death cross) happens when a short-term MA crosses below a long-term moving average, which indicates the beginning of a downtrend. One major downside of MAs is their delay time. Since MAs are lagging indicators that consider previous price action, the signals are often too late. For example, a bullish crossover may suggest a buy, but it may only happen after a significant rise in price. This suggests that even if the uptrend continues, potential profit may have been lost in that period between the rise in price and the crossover signal. Or even worse, a false golden cross signal may lead a trader to buy the local top just before a price drop. These fake buy signals are usually referred to as a bull trap. To put it all in a nutshell, Moving Averages are powerful TA indicators and one of the most widely used. The ability to analyze market trends in a data-driven way provides great penetration into how a market is performing. Remember that MAs and crossover signals should not be used alone and it is always more reliable to combine different TA indicators in order to avoid fake signals. Best regards EXCAVO
Education
by EXCAVO
11
Oliver Velez 20 200 SMA Trading systemAs many of you know, world famous Oliver Velez uses the simple 20 and 200 simple moving averages on 2 min time frame with price actions above or below these key SMAs for day/scalp trading involving narrow state versus wide state trend or anti-trend methods. The 20 SMA line uses different colors to indicate whether it is going up or down. Against Oliver's advice, I also unnecessarily added boll bands on the 200 SMA, two +/- percent lines off 200 SMA to measure how far away prices are from the 200 SMA. I also added 10 ema cross 20 SMA cross signal, MACD line up /down, RSI crossover RSI SMA for those are want to make things complicated or might find they helpful. You can turn off all these ideally to Keep It Simple. Again trading success is 80% psychology and 20% a good trading system. Good luck.
NASDAQ:AAPLEducation
by tomchen73
4
A peek into the pastMATICBTC neatly moved in a Fibonacci Channel and fell down to 100% bottom of that channel. Two detectors predicted the top Golden Ratio Top Detector (UO_GRFM) Mayer Multiple Golden Ratio Top Detector also showed the potential bottom correctly. Future? As long as it coasts above SMA350/6h, I will consider it a bullish opportunity and keep collecting. Also note that is about to jump to an upper Fibonacci channel(78.60%) from 100% channel-- very bullish if this happens
MEducation
by umur.ozkul