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Standard Deviation Measurement ToolIf you like the script please come back and leave me a comment or find me on the interwebs. I get notified you "liked" it... but I have no idea if you actually use it. So, let me know =) The script uses the open price as the mean and calculates the standard deviation from the open price on a per candle basis - Goal: - To establish a mean based on the Open Price and calculate the standard deviation. The reason for this is if the Open is the mean, then the Standard deviation implies a standardized distance a given candle can be expected to travel from the open price - Edge: - If you know that there is a 68%/95%/99.7% probability that price will NOT move more than One Standard Deviation/Two Standard Deviations/Three Standard Deviations from the open price respectively you can set reasonable price targets that relate to those probabilities in a given timeframe. e.g. if you're on a 1h chart and your target is 3.5% from the open price, but 1 standard deviation of the hourly candle is equal to 0.78%. You can make assumptions on either: - The reasonableness of your target or - The holding period likely required for the trade. Also, Standard Deviation is a function of volatility and this tool provides a unique mechanism for measuring volatility as well on a candle by candle basis - Customization Options- - Set 3 independent upper and lower standard deviations. - Each set of standard deviations are on a switch so you can show 1, 2, or 3 sets of standard deviations - You can set the distribution width - Though it's not recommended, you can change the mean source. - There is a switch to show the standard deviation on only the real-time bar or real-time and historical bars. - How I Think About This Script - This strategy is predicated the same principle as Bollinger Bands: the reality that 68% of all data points will fall within one standard deviation of the mean, 96% of all data points will fall within two standard deviations, and 98% of al data points will fall within 3 standard deviations. By understanding the standard deviation, you can possibly infer an edge by understanding the probabilistic range price will be bound to the limits of standard deviation rules according to their probabilistic outcomes for the single candle on any given timeframe. Bollinger Bands are designed to provide this information with the mean being a 20-period moving average and this indicator. This indicator is designed to provide standard deviation information with the mean being based on the distance price travels away from the open of individual candles in the lookback period. If you use a strategy where you enter on major candle closes, this can be useful to set targets for those entries based on the intended hold period or at least add/remove validity to other target metrics. Example: Your target is at the 1.618 Fibonacci level and your confirmation triggers on the 4h candle close (H4 if that's your thing lol). You set up the indicator based on the standard deviation of price movement in 4h candles over the last week. Let's say the indicator shows that the 1.618 Fibonacci level is 3 standard deviations away. This being the case this statistically indicates that within the next 4 hours, you have a very low probability of achieving your target (>2%). This doesn't invalidate your target, but it does indicate a low probability of achieving it in the next 4hrs. With this information, you can infer that you are either going to be (a) really lucky (b) in this trade for a lot longer than 4hrs or (c) your target is unrealistic given your intended hold period. You can develop a more probabilistically favorable hold period calculation by looking at the standard deviation on a higher time frame (e.g. 1d-1w). Bonus feature: You'll find that the 2 and 3 standard deviations will often "cluster" and these clusters often provide future S/R levels. That's a pretty sweet feature no one things to look for. But, try it. Find a cluster of 2nd and 3rd stdevs that are in somewhat of a horizontal pattern (usually the result of a range) and you'll find that to be a good s/r area. Even better if you use the 3.2 standard deviation, you'll find that is a fantastic breakout signal! Summary So, you can use it for target setting, a confluence test, a reasonableness test, or just a measurement tool. This was the first TV script I ever wrong.. Got taken down. But, I've re-released it because there are other TV scripts that attempt to do this but are completely wrong. Please be careful about using other people's scripts. Always validate the math of the script before you use it if possible. Stay safe out there and I hope all your dreams come true.
Chỉ báo Pine Script®
của kurtsmock
47
Backtesting on Non-Standard Charts: Caution! - PineCoders FAQMuch confusion exists in the TradingView community about backtesting on non-standard charts. This script tries to shed some light on the subject in the hope that traders make better use of those chart types. Non-standard charts are: Heikin Ashi (HA) Renko Kagi Point & Figure Range These chart types are called non-standard because they all transform market prices into synthetic views of price action. Some focus on price movement and disregard time. Others like HA use the same division of bars into fixed time intervals but calculate artificial open, high, low and close (OHLC) values. Non-standard chart types can provide traders with alternative ways of interpreting price action, but they are not designed to test strategies or run automated traded systems where results depend on the ability to enter and exit trades at precise price levels at specific times, whether orders are issued manually or algorithmically. Ironically, the same characteristics that make non-standard chart types interesting from an analytical point of view also make them ill-suited to trade execution. Why? Because of the dislocation that a synthetic view of price action creates between its non-standard chart prices and real market prices at any given point in time. Switching from a non-standard chart price point into the market always entails a translation of time/price dimensions that results in uncertainty—and uncertainty concerning the level or the time at which orders are executed is detrimental to all strategies. The delta between the chart’s price when an order is issued (which is assumed to be the expected price) and the price at which that order is filled is called slippage . When working from normal chart types, slippage can be caused by one or more of the following conditions: • Time delay between order submission and execution. During this delay the market may move normally or be subject to large orders from other traders that will cause large moves of the bid/ask levels. • Lack of bids for a market sell or lack of asks for a market buy at the current price level. • Spread taken by middlemen in the order execution process. • Any other event that changes the expected fill price. When a market order is submitted, matching engines attempt to fill at the best possible price at the exchange. TradingView strategies usually fill market orders at the opening price of the next candle. A non-standard chart type can produce misleading results because the open of the next candle may or may not correspond to the real market price at that time. This creates artificial and often beneficial slippage that would not exist on standard charts. Consider an HA chart. The open for each candle is the average of the previous HA bar’s open and close prices. The open of the HA candle is a synthetic value, but the real market open at the time the new HA candle begins on the chart is the unrelated, regular open at the chart interval. The HA open will often be lower on long entries and higher on short entries, resulting in unrealistically advantageous fills. Another example is a Renko chart. A Renko chart is a type of chart that only measures price movement. The purpose of a Renko chart is to cluster price action into regular intervals, which consequently removes the time element. Because Trading View does not provide tick data as a price source, it relies on chart interval close values to construct Renko bricks. As a consequence, a new brick is constructed only when the interval close penetrates one or more brick thresholds. When a new brick starts on the chart, it is because the previous interval’s close was above or below the next brick threshold. The open price of the next brick will likely not represent the current price at the time this new brick begins, so correctly simulating an order is impossible. Some traders have argued with us that backtesting and trading off HA charts and other non-standard charts is useful, and so we have written this script to show traders what happens when order fills from backtesting on non-standard charts are compared to real-world fills at market prices. Let’s review how TV backtesting works. TV backtesting uses a broker emulator to execute orders. When an order is executed by the broker emulator on historical bars, the price used for the fill is either the close of the order’s submission bar or, more often, the open of the next. The broker emulator only has access to the chart’s prices, and so it uses those prices to fill orders. When backtesting is run on a non-standard chart type, orders are filled at non-standard prices, and so backtesting results are non-standard—i.e., as unrealistic as the prices appearing on non-standard charts. This is not a bug; where else is the broker emulator going to fetch prices than from the chart? This script is a strategy that you can run on either standard or non-standard chart types. It is meant to help traders understand the differences between backtests run on both types of charts. For every backtest, a label at the end of the chart shows two global net profit results for the strategy: • The net profits (in currency) calculated by TV backtesting with orders filled at the chart’s prices. • The net profits (in currency) calculated from the same orders, but filled at market prices (fetched through security() calls from the underlying real market prices) instead of the chart’s prices. If you run the script on a non-standard chart, the top result in the label will be the result you would normally get from the TV backtesting results window. The bottom result will show you a more realistic result because it is calculated from real market fills. If you run the script on a normal chart type (bars, candles, hollow candles, line, area or baseline) you will see the same result for both net profit numbers since both are run on the same real market prices. You will sometimes see slight discrepancies due to occasional differences between chart prices and the corresponding information fetched through security() calls. Features • Results shown in the Data Window (third icon from the top right of your chart) are: — Cumulative results — For each order execution bar on the chart, the chart and market previous and current fills, and the trade results calculated from both chart and market fills. • You can choose between 2 different strategies, both elementary. • You can use HA prices for the calculations determining entry/exit conditions. You can use this to see how a strategy calculated from HA values can run on a normal chart. You will notice that such strategies will not produce the same results as the real market results generated from HA charts. This is due to the different environment backtesting is running on where for example, position sizes for entries on the same bar will be calculated differently because HA and standard chart close prices differ. • You can choose repainting/non-repainting signals. • You can show MAs, entry/exit markers and market fill levels. • You can show candles built from the underlying market prices. • You can color the background for occurrences where an order is filled at a different real market price than the chart’s price. Notes • On some non-standard chart types you will not obtain any results. This is sometimes due to how certain types of non-standard types work, and sometimes because the script will not emit orders if no underlying market information is detected. • The script illustrates how those who want to use HA values to calculate conditions can do so from a standard chart. They will then be getting orders emitted on HA conditions but filled at more realistic prices because their strategy can run on a standard chart. • On some non-standard chart types you will see market results surpass chart results. While this may seem interesting, our way of looking at it is that it points to how unreliable non-standard chart backtesting is, and why it should be avoided. • In order not to extend an already long description, we do not discuss the particulars of executing orders on the realtime bar when using non-standard charts. Unless you understand the minute details of what’s going on in the realtime bar on a particular non-standard chart type, we recommend staying away from this. • Some traders ask us: Why does TradingView allow backtesting on non-standard chart types if it produces unrealistic results? That’s somewhat like asking a hammer manufacturer why it makes hammers if hammers can hurt you. We believe it’s a trader’s responsibility to understand the tools he is using. Takeaways • Non-standard charts are not bad per se, but they can be badly used. • TV backtesting on non-standard charts is not broken and doesn’t require fixing. Traders asking for a fix are in dire need of learning more about trading. We recommend they stop trading until they understand why. • Stay away from—even better, report—any vendor presenting you with strategies running on non-standard charts and implying they are showing reliable results. • If you don’t understand everything we discussed, don’t use non-standard charts at all. • Study carefully how non-standard charts are built and the inevitable compromises used in calculating them so you can understand their limitations. Thanks to @allanster and @mortdiggiddy for their help in editing this description. Look first. Then leap.
Chiến lược Pine Script®
của PineCoders
49
Standard Error Bands by @XeL_arjonaStandard Error Bands - Code by @XeL_arjona Original implementation by: Traders issue: Stocks & Commodities V. 14:9 (375-379): Standard Error Bands by Jon Andersen Version 1 For a quick and publicly open explanation of this Statistical indicator, you can refer at Here! Extract from the former URL: Standard Error bands are quite different than Bollinger's. First, they are bands constructed around a linear regression curve. Second, the bands are based on two standard errors above and below this regression line. The error bands measure the standard error of the estimate around the linear regression line. Therefore, as a price series follows the course of the regression line the bands will narrow, showing little error in the estimate. As the market gets noisy and random, the error will be greater resulting in wider bands.
Chỉ báo Pine Script®
của xel_arjona
4
UCS_Value BandsThis Indicator is yet another variation of KC. Inspired from Value Charts webinar. I have seen their videos on youtube. What appears to be a variation of KC. They use 12 bands Showing the zone, and different MA for different timeframes. You can get this indicator close to accuracy by changing the inputs (ATR) and (Deviations) This also can be used with the triple ATR setup - Change the values to EMA to desired value. To obtain the First band to plot @ 1, Change the Band deviation to 0.25. Also can be used as as the Acceleration Band. With Current Settings, the Third Band will plot the Acceleration band. List of All my Indicators - www.tradingview.com Lycka Till
Chỉ báo Pine Script®
của UDAY_C_Santhakumar
3