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Monte Carlo Range Forecast [DW]This is an experimental study designed to forecast the range of price movement from a specified starting point using a Monte Carlo simulation. Monte Carlo experiments are a broad class of computational algorithms that utilize random sampling to derive real world numerical results. These types of algorithms have a number of applications in numerous fields of study including physics, engineering, behavioral sciences, climate forecasting, computer graphics, gaming AI, mathematics, and finance. Although the applications vary, there is a typical process behind the majority of Monte Carlo methods: -> First, a distribution of possible inputs is defined. -> Next, values are generated randomly from the distribution. -> The values are then fed through some form of deterministic algorithm. -> And lastly, the results are aggregated over some number of iterations. In this study, the Monte Carlo process used generates a distribution of aggregate pseudorandom linear price returns summed over a user defined period, then plots standard deviations of the outcomes from the mean outcome generate forecast regions. The pseudorandom process used in this script relies on a modified Wichmann-Hill pseudorandom number generator (PRNG) algorithm. Wichmann-Hill is a hybrid generator that uses three linear congruential generators (LCGs) with different prime moduli. Each LCG within the generator produces an independent, uniformly distributed number between 0 and 1. The three generated values are then summed and modulo 1 is taken to deliver the final uniformly distributed output. Because of its long cycle length, Wichmann-Hill is a fantastic generator to use on TV since it's extremely unlikely that you'll ever see a cycle repeat. The resulting pseudorandom output from this generator has a minimum repetition cycle length of 6,953,607,871,644. Fun fact: Wichmann-Hill is a widely used PRNG in various software applications. For example, Excel 2003 and later uses this algorithm in its RAND function, and it was the default generator in Python up to v2.2. The generation algorithm in this script takes the Wichmann-Hill algorithm, and uses a multi-stage transformation process to generate the results. First, a parent seed is selected. This can either be a fixed value, or a dynamic value. The dynamic parent value is produced by taking advantage of Pine's timenow variable behavior. It produces a variable parent seed by using a frozen ratio of timenow/time. Because timenow always reflects the current real time when frozen and the time variable reflects the chart's beginning time when frozen, the ratio of these values produces a new number every time the cache updates. After a parent seed is selected, its value is then fed through a uniformly distributed seed array generator, which generates multiple arrays of pseudorandom "children" seeds. The seeds produced in this step are then fed through the main generators to produce arrays of pseudorandom simulated outcomes, and a pseudorandom series to compare with the real series. The main generators within this script are designed to (at least somewhat) model the stochastic nature of financial time series data. The first step in this process is to transform the uniform outputs of the Wichmann-Hill into outputs that are normally distributed. In this script, the transformation is done using an estimate of the normal distribution quantile function. Quantile functions, otherwise known as percent-point or inverse cumulative distribution functions, specify the value of a random variable such that the probability of the variable being within the value's boundary equals the input probability. The quantile equation for a normal probability distribution is μ + σ(√2)erf^-1(2(p - 0.5)) where μ is the mean of the distribution, σ is the standard deviation, erf^-1 is the inverse Gauss error function, and p is the probability. Because erf^-1() does not have a simple, closed form interpretation, it must be approximated. To keep things lightweight in this approximation, I used a truncated Maclaurin Series expansion for this function with precomputed coefficients and rolled out operations to avoid nested looping. This method provides a decent approximation of the error function without completely breaking floating point limits or sucking up runtime memory. Note that there are plenty of more robust techniques to approximate this function, but their memory needs very. I chose this method specifically because of runtime favorability. To generate a pseudorandom approximately normally distributed variable, the uniformly distributed variable from the Wichmann-Hill algorithm is used as the input probability for the quantile estimator. Now from here, we get a pretty decent output that could be used itself in the simulation process. Many Monte Carlo simulations and random price generators utilize a normal variable. However, if you compare the outputs of this normal variable with the actual returns of the real time series, you'll find that the variability in shocks (random changes) doesn't quite behave like it does in real data. This is because most real financial time series data is more complex. Its distribution may be approximately normal at times, but the variability of its distribution changes over time due to various underlying factors. In light of this, I believe that returns behave more like a convoluted product distribution rather than just a raw normal. So the next step to get our procedurally generated returns to more closely emulate the behavior of real returns is to introduce more complexity into our model. Through experimentation, I've found that a return series more closely emulating real returns can be generated in a three step process: -> First, generate multiple independent, normally distributed variables simultaneously. -> Next, apply pseudorandom weighting to each variable ranging from -1 to 1, or some limits within those bounds. This modulates each series to provide more variability in the shocks by producing product distributions. -> Lastly, add the results together to generate the final pseudorandom output with a convoluted distribution. This adds variable amounts of constructive and destructive interference to produce a more "natural" looking output. In this script, I use three independent normally distributed variables multiplied by uniform product distributed variables. The first variable is generated by multiplying a normal variable by one uniformly distributed variable. This produces a bit more tailedness (kurtosis) than a normal distribution, but nothing too extreme. The second variable is generated by multiplying a normal variable by two uniformly distributed variables. This produces moderately greater tails in the distribution. The third variable is generated by multiplying a normal variable by three uniformly distributed variables. This produces a distribution with heavier tails. For additional control of the output distributions, the uniform product distributions are given optional limits. These limits control the boundaries for the absolute value of the uniform product variables, which affects the tails. In other words, they limit the weighting applied to the normally distributed variables in this transformation. All three sets are then multiplied by user defined amplitude factors to adjust presence, then added together to produce our final pseudorandom return series with a convoluted product distribution. Once we have the final, more "natural" looking pseudorandom series, the values are recursively summed over the forecast period to generate a simulated result. This process of generation, weighting, addition, and summation is repeated over the user defined number of simulations with different seeds generated from the parent to produce our array of initial simulated outcomes. After the initial simulation array is generated, the max, min, mean and standard deviation of this array are calculated, and the values are stored in holding arrays on each iteration to be called upon later. Reference difference series and price values are also stored in holding arrays to be used in our comparison plots. In this script, I use a linear model with simple returns rather than compounding log returns to generate the output. The reason for this is that in generating outputs this way, we're able to run our simulations recursively from the beginning of the chart, then apply scaling and anchoring post-process. This allows a greater conservation of runtime memory than the alternative, making it more suitable for doing longer forecasts with heavier amounts of simulations in TV's runtime environment. From our starting time, the previous bar's price, volatility, and optional drift (expected return) are factored into our holding arrays to generate the final forecast parameters. After these parameters are computed, the range forecast is produced. The basis value for the ranges is the mean outcome of the simulations that were run. Then, quarter standard deviations of the simulated outcomes are added to and subtracted from the basis up to 3σ to generate the forecast ranges. All of these values are plotted and colorized based on their theoretical probability density. The most likely areas are the warmest colors, and least likely areas are the coolest colors. An information panel is also displayed at the starting time which shows the starting time and price, forecast type, parent seed value, simulations run, forecast bars, total drift, mean, standard deviation, max outcome, min outcome, and bars remaining. The interesting thing about simulated outcomes is that although the probability distribution of each simulation is not normal, the distribution of different outcomes converges to a normal one with enough steps. In light of this, the probability density of outcomes is highest near the initial value + total drift, and decreases the further away from this point you go. This makes logical sense since the central path is the easiest one to travel. Given the ever changing state of markets, I find this tool to be best suited for shorter term forecasts. However, if the movements of price are expected to remain relatively stable, longer term forecasts may be equally as valid. There are many possible ways for users to apply this tool to their analysis setups. For example, the forecast ranges may be used as a guide to help users set risk targets. Or, the generated levels could be used in conjunction with other indicators for meaningful confluence signals. More advanced users could even extrapolate the functions used within this script for various purposes, such as generating pseudorandom data to test systems on, perform integration and approximations, etc. These are just a few examples of potential uses of this script. How you choose to use it to benefit your trading, analysis, and coding is entirely up to you. If nothing else, I think this is a pretty neat script simply for the novelty of it. ---------- How To Use: When you first add the script to your chart, you will be prompted to confirm the starting date and time, number of bars to forecast, number of simulations to run, and whether to include drift assumption. You will also be prompted to confirm the forecast type. There are two types to choose from: -> End Result - This uses the values from the end of the simulation throughout the forecast interval. -> Developing - This uses the values that develop from bar to bar, providing a real-time outlook. You can always update these settings after confirmation as well. Once these inputs are confirmed, the script will boot up and automatically generate the forecast in a separate pane. Note that if there is no bar of data at the time you wish to start the forecast, the script will automatically detect use the next available bar after the specified start time. From here, you can now control the rest of the settings. The "Seeding Settings" section controls the initial seed value used to generate the children that produce the simulations. In this section, you can control whether the seed is a fixed value, or a dynamic one. Since selecting the dynamic parent option will change the seed value every time you change the settings or refresh your chart, there is a "Regenerate" input built into the script. This input is a dummy input that isn't connected to any of the calculations. The purpose of this input is to force an update of the dynamic parent without affecting the generator or forecast settings. Note that because we're running a limited number of simulations, different parent seeds will typically yield slightly different forecast ranges. When using a small number of simulations, you will likely see a higher amount of variance between differently seeded results because smaller numbers of sampled simulations yield a heavier bias. The more simulations you run, the smaller this variance will become since the outcomes become more convergent toward the same distribution, so the differences between differently seeded forecasts will become more marginal. When using a dynamic parent, pay attention to the dispersion of ranges. When you find a set of ranges that is dispersed how you like with your configuration, set your fixed parent value to the parent seed that shows in the info panel. This will allow you to replicate that dispersion behavior again in the future. An important thing to note when settings alerts on the plotted levels, or using them as components for signals in other scripts, is to decide on a fixed value for your parent seed to avoid minor repainting due to seed changes. When the parent seed is fixed, no repainting occurs. The "Amplitude Settings" section controls the amplitude coefficients for the three differently tailed generators. These amplitude factors will change the difference series output for each simulation by controlling how aggressively each series moves. When "Adjust Amplitude Coefficients" is disabled, all three coefficients are set to 1. Note that if you expect volatility to significantly diverge from its historical values over the forecast interval, try experimenting with these factors to match your anticipation. The "Weighting Settings" section controls the weighting boundaries for the three generators. These weighting limits affect how tailed the distributions in each generator are, which in turn affects the final series outputs. The maximum absolute value range for the weights is . When "Limit Generator Weights" is disabled, this is the range that is automatically used. The last set of inputs is the "Display Settings", where you can control the visual outputs. From here, you can select to display either "Forecast" or "Difference Comparison" via the "Output Display Type" dropdown tab. "Forecast" is the type displayed by default. This plots the end result or developing forecast ranges. There is an option with this display type to show the developing extremes of the simulations. This option is enabled by default. There's also an option with this display type to show one of the simulated price series from the set alongside actual prices. This allows you to visually compare simulated prices alongside the real prices. "Difference Comparison" allows you to visually compare a synthetic difference series from the set alongside the actual difference series. This display method is primarily useful for visually tuning the amplitude and weighting settings of the generators. There are also info panel settings on the bottom, which allow you to control size, colors, and date format for the panel. It's all pretty simple to use once you get the hang of it. So play around with the settings and see what kinds of forecasts you can generate! ---------- ADDITIONAL NOTES & DISCLAIMERS Although I've done a number of things within this script to keep runtime demands as low as possible, the fact remains that this script is fairly computationally heavy. Because of this, you may get random timeouts when using this script. This could be due to either random drops in available runtime on the server, using too many simulations, or running the simulations over too many bars. If it's just a random drop in runtime on the server, hide and unhide the script, re-add it to the chart, or simply refresh the page. If the timeout persists after trying this, then you'll need to adjust your settings to a less demanding configuration. Please note that no specific claims are being made in regards to this script's predictive accuracy. It must be understood that this model is based on randomized price generation with assumed constant drift and dispersion from historical data before the starting point. Models like these not consider the real world factors that may influence price movement (economic changes, seasonality, macro-trends, instrument hype, etc.), nor the changes in sample distribution that may occur. In light of this, it's perfectly possible for price data to exceed even the most extreme simulated outcomes. The future is uncertain, and becomes increasingly uncertain with each passing point in time. Predictive models of any type can vary significantly in performance at any point in time, and nobody can guarantee any specific type of future performance. When using forecasts in making decisions, DO NOT treat them as any form of guarantee that values will fall within the predicted range. When basing your trading decisions on any trading methodology or utility, predictive or not, you do so at your own risk. No guarantee is being issued regarding the accuracy of this forecast model. Forecasting is very far from an exact science, and the results from any forecast are designed to be interpreted as potential outcomes rather than anything concrete. With that being said, when applied prudently and treated as "general case scenarios", forecast models like these may very well be potentially beneficial tools to have in the arsenal.
Pine Script® göstergesi
DonovanWall tarafından
79
Ichimoku + 2 base linesIchimoku + 2 base line This indicator is a combination of Ichimoku cloud indicator with two base lines. The first base line is the same as the Ichimoku default settings but the baseline 2 indicates an average of 108 candles in the past and it acts as a strong support and resistance level. How to use this indicator? You can use this indicator to see if a break out is true or is a false break. For example if the price broke up the Ichimoku cloud and base line 2 is above the price, it will probably react to that area but if it's below the price, it is a good opportunity to buy. (for sell/short position it is in the opposite way the base line 2 should be above the price) If you want to trade in support zones base line 2 (108) is a very good area that you can wait for a good candlestick pattern to enter a position. Caution: before using this indicator please back test it and if the results were good enough, use it as a confirmation.
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salarkamjoo tarafından
RSI Support & Resistance by DGTRSI Sᴜᴘᴘᴏʀᴛ & Rᴇꜱɪꜱᴛᴀɴᴄᴇ ʙʏ DGT This experimental study attempts to translate Relative Strength Index (RSI) threshold levels of oversold/overbought and bull/bear zones as probable Price Support and Resistance levels █  OPTIONS Support & Resistance Levels , the main aim of the study. Level calculations are based on Relative Strength Index (RSI) threshold levels of oversold/overbought and bull/bear zones, where all threshold values are customizable through the user dialog box. Background of the levels can be colored optionally RSI Weighted Colored Bars and/or Mark Overbought/Oversold Bars , Bar colors can be painted to better emphasis RSI values. Darker colors when the oscillator is in oversold/overbought zones, light colors when oscillator readings are below/above the bull/bear zone respectively, and remain unchanged otherwise. Besides the colors, with “Display RSI Overbought/Oversold Price Bars” option little triangle shapes can be plotted on top or bottom of the bars when RSI is in oversold/overbought zones Example usage of the study with explanations █  OTHERS More regarding Support & Resistance concept (definition, identifying levels, trading S&R, etc) you are kindly invited to check my previous publication Price Action - Support & Resistance by DGT More regarding Relative Strength Index (RSI) and Relative Strength of Volume Indicators , please check Relative Strength of Volume Indicators by DGT Disclaimer: Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Pine Script® göstergesi
dgtrd tarafından
93
FIBS S/R IndicatorHello, I've decided to publish a new script. The previous version of this script was removed by admins for breaking community rules. So I present to you the Fibonacci Support / Resistance. 1. How does it work Ratio plots I first take the input of pivot look back and search for pivots high and low. And then it takes a second look back to search highest high and lowest low to establish the top bottom range. Then using the top and bottom I plot ratios provided as input. Defaults to most relevant 5 ratios I've found (Fibonacci): Ratio 0 = 0 - can't be changed Ratio 1 = 0.5 Ratio 2 = 0.618 Ratio 3 = 1 Ratio 4 = 1.618 Ratio 5 = 2.618 Any changes done to these ratios should be in order, otherwise conditions could get messed up. So R1 needs to the lowest and R5 the highest. Also the same ratios are used in reverse as negative ratios. There is a option to plot all ratios but gets really confusing for me but maybe for you it works. By default there are certain conditions set so that as we go up new resistance ratio get displayed and as we go down we see new resistance plots. Trendlines I've also added some automatic trendline plots with breakout warning labels based on the pivots high and low. Start and end for trendlines can be changed via inputs. Labels can be deactivated via input. On a older version the trendlines and labels where not removed from the chart but I felt like there was to much information. Overcooked/Undercooked I've also added some fills and background colors that indicate if the price action is over R5 or under Negative R5 ratios. This usually indicates some "overcooking" or "undecooking". I've notices that after "crossunder"/"crossover" top bottom ratios it goes in consolidation or it dumps. So then I plot a bgcolor to signal that. 2. How to use it Using plot lines we can determine where we have support and resistance. I found that the best way to use the default ratios values is on the 1H chart. Very good for trading on crypto because of current situation in the market where there is a lot of new people entering the space and volatility and sentiment make swings respect the Fibonacci ratios. 3. Examples For instance lets look at BINANCE:BTCUSDT . On the left we see that the price action between 20 and 21 February was "overcooked". So after we got the signal that we "crossunder" the R5 the signal was triggered and we got a small red candle followed by a small dip and after that we got a small bounce and a dump. If we also look at MF-RSI we can also see we got multiple bear divs. Lets entertain the idea that we went short at ~57.1k as soon as we get signaled and it starts dumping. Where does it stop ? We can see it went all the way down to Negative R5 ratio. Normally that should signal "undercooking" but this was not triggered as it did not close under it (signaled in green). We can also see that previous support now becomes resistance (signaled in red). If we take a look at BINANCE:ETHUSDT , we do see that the "undercooking" was triggered here. I will be publishing a more detailed Idea with examples of using this on the BINANCE:BTCUSDT chart in combination with Volume and other technical analysis. Use with caution, this is not 100% signal indicator as the markets do what they want. But by using this in combination with other indicators like MF-RSI, EMAs and regular patterns we can get some targets for Support/Resistance. I'm trying to create a strategy based on this indicator but I'm not getting very good results. Best results were on the 15 min chart with gross profits around ~50%. Please try to play around with the inputs and let me know if you find something interesting, maybe I can incorporate new features in the indicator. You can find the MF-RSI indicator here
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CryptoSlots777 tarafından
1
HTF Highs Lows [JV]█  OVERVIEW This script presents a label with an overview of higher timeframe highs and lows. This can be useful information as we all know that price likes to revisit previous highs and lows area, specially on the higher timeframe. █  CONCEPTS This information can be relevant and valuable for various reasons: Finding horizontal Support and Resistance Get a better view on Market Structure Provide some information about Order Flow TrendLines ... █  FEATURES Plots This script provides the option to show information about 3 timeframes Each timeframe can be separately shown or hidden The Y position of the info label can be user defined, based on high or low of the chosen timeframe The X offset of the info label can be adjusted to the user's liking and the chart resolution The label color and text color can be user defined The info label's size can be user defined █  NOTES Caveat The timeframes must be chosen in order of size. Meaning that the highest timeframe should be on top. This is title as such on the info label, but I want to mention it again as it's something to pay attention to. Repainting The question that pops up all the time is: Does it repaint ? I will quote PineCoders on this: We're pretty sure Wilder was not asked very often if RSI repainted. Why? Because it wasn't in fashion—and largely unnecessary—to ask that sort of question in the 80's. Many traders back then used daily charts only, and indicator values were calculated at the day's close, so everybody knew what they were getting. Additionally, indicator values were calculated by generally reputable outfits or traders themselves, so data was pretty reliable. Today, almost anybody can write a simple indicator, and the programming languages used to write them are complex enough for some coders lacking the caution, know-how or ethics of the best professional coders, to get in over their heads and produce code that does not work the way they think it does. Briefly: yes, it repaints and no it does not matter. Simple because we are working with highs and lows on a higher timeframe. So if we get a new high or low within a certain time frame, we want this new high or low to be displayed and, for me, it's not relevant if this information appears when it happens or when the candle closes. Questions & Suggestions Questions, suggestions or even a word of thanks are always welcomed in the comments section. I usually answer within the same day. █  THANKS A word of thanks to, and I hope I am allowed to use hyperlinks here, LonesomeTheBlue for being an inspiration on coding style and his work on arrays in Pine Script and to lmatl for his support, words of advice and letting me borrow his brain now and then.
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jurlvarg tarafından
3
coates moving averages (cma)This indicator uses three moving averages: 2 period low simple ma 2 period high simple ma 9 period least squares ma The trend is determined by the angle of the moving averages, current close relative the the 9 least squares ma (lsm) and the current close relative to the prior two periods high and low. When there are consecutive closes inside the prior two candles high and low then a range is signaled: In ranges the buy zone is between the lowest low and the lowest close of the current range. The sell zone is between the highest high and the highest close. The zones are adjusted as long as the new close is within the prior two candles range: When price closes above the 2 high ma and the 9 lsm then a bull trend is signaled if all moving averages are angled upward (as seen at #4 in the chart above and #1 the chart below ). If the 9 lsm and / or the 2 low ma continue to angle downward, following a close above the 2 high ma and 9 lsm, then a prolonged range or reversal is expected (#2 in the chart below): During a bull trend the buy zone is between the 2 low ma and the 9 lsm. The profit target is the 2 high ma: During dip buying opportunities price should resist closing below the 9 lsm. If there is one close below the 9 lsm then it is a canary in the coalmine that tells us to proceed with caution. This will often signal a range, based on the conditions outlined above. To avoid a prolonged range, or reversal, price needs to immediately react in the direction of the prevailing trend: If the moving averages are angled down and the most recent close is below the 2 low ma and 9 lsm then trend is fully bearish: During a bear trend the short zone is between the 2 high ma and 9 lsm. The profit target is the 2 low ma: When the 2 high ma angles down and the 2 low ma angles up while price closes inside both mas then it indicates a cma squeeze: Volatility is expected in the direction of the breakout following the squeeze. In this situation traps / shakeouts are common. If there is a wick outside the cma, with a close inside, then it indicates a trap / shakeout. If there is a close outside the 2 high / low ma then it signals a breakout. A trend is considered balanced when the 9 lsm is roughly equidistant from the 2 low and 2 high mas. If the 9 lsm crosses the 2 high or 2 low ma then it signals exhaustion / imbalance. For a stop loss I use the prior three periods low, for bull trends, and the prior three periods high for bear trends. I would expect other reliable stops, such as the parabolic sar or bill williams fractal, to be effective as well. The default moving averages should be very effective on all timeframes and assets classes, however this indicator was developed for bitcoin with a focus on higher timeframes such as the 4h, daily and weekly. As with any other technical indicator there will be bad signals. Proceed with caution and never risk more than you are willing to lose.
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Sawcruhteez tarafından
3
pivot semaphore support&resistance levels [LM]Hello Traders, I would like to introduce you pivot semaphore support&resistance levels. The idea is the same as the zigzag script of mine to spot the importance of support&resistence The Semafor is used to spot future multi-level Supports and Resistance zones. It is also useful to spot HL or LL or HH or LH zones at different Depth settings. The red zones are the extreme places where the market has a higher chance of reversing while the green zones have the lowest setting with lower chances of the market reversal The lines can be extended like so The lines also can just stop extending when price will reach it Enjoy!
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lmatl tarafından
14
ACD - Layers 1 & 2An implementation of layers 1 & 2 of ACD strategy of Mark Fisher, based on the book "The Logical Trader". This implementation contains: - OR lines - A lines - C lines - Daily pivot range - N days pivot range - Customizable trading session Strategy summary (This implementation): There is 3 main concepts, each of which represented as two price levels. 1) OR (Opening Range) is the range of the first bar of the day. In other words, it's just "high - low" of the first resolution (usually 15min.) bar of the day. So, OR lines (Aqua color) visualize this range for each trading session. As stated by Mark Fisher in his book, this range is meant to be a statistically significant range such that when price breaks the range in one direction, This is UNUSUAL to infiltrate it again AND break through the other side. So we can consider it as a potential enter signal (long or short). 2) A lines (Blue color) are drawn above and below OR lines with difference of 10% 0f 10 days ATR. The ATR period and the A multiplier (usually 10%) is customizable. 3) C lines (Gray color) are drawn above and below OR lines at 15% of 10 Days ATR difference. These lines help detecting AND confirming that UNUSUAL situation. These concepts form the layer 1, which you can spot potential opportunities with it. There is also two ranges to show support and resistance levels based on price action of previous days. Pivot ranges are rolling ranges that calculated and last for each day separately. They only differ in calculation period - the first one is daily (yellow color area) and the other one (red color area) is customizable, but is usually 3 or 5 days. Each range consists of two price levels, valid for the current trading session. One of theme is HL2 , and the other one is "HLC3 + abs(HLC3 - HL2 )". These two ranges, "Daily pivot range" and "N days pivot range", form the layer 2, which you can see them as two dynamic support/resistance ranges - one for daily, and the other for N days. They help filtering opportunities spotted from layer 1. There is 2 more layers in the ACD strategy, which is omitted in this free implementation.
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QuantCT tarafından
32
Multi Time Frame Candles with Volume Info / 3DHello Traders, This is my second Multi Time Frame Candles script but with this new one, you will have some new features such volume info, remaining time to close of higher time frame candle and also developed using new features of Pine such array of lines. also I tried to make it 3D for better visualization ;) also it shows new highs/lows / breakouts. I tried to make many things optional, so you can change almost everything using options. What you can change using options: - Higher time frame - Number of Candles - Candle Colors Up/Down - Wick Color - Volume colors Up/Down - Text color of Remaining Time - Shadow Color - Background color - Start bar of the candles (so you can see many higher times frame candles in same window) - 3D effect, by default it's enables but you can disable 3D view Lets see some examples: Remaining time: Breakouts: You can combine different higher time frames: if you don't want 3D view then combining different higher time frames: You can change background color: Enjoy!
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LonesomeTheBlue tarafından
102