MACDPROThis MACDPRO indicator is based on MACD, RSI, ADX, BB and it has LONG/SHORT alerts for signals
In script settings you can specify:
1) Dispertion value, 3 by default.
2) Noise filter smooth factor, 16 by default.
3) Enable/Disable RSIPROv5 TrendIndicator algorythm
4) Setting RSI Overbought and Oversold values
5) Enable/Disable stop loss and take profit filter for indicator
6) Enable/Disable BB
Best fits for 30-60 min timeframe. Also good for 15min scalping strategy. Fits for any crypto coins, forex, metals, oil and bonds.
This is very powerfull script and will be private soon
Cerca negli script per "Oil"
Adaptivity: Measures of Dominant Cycles and Price Trend [Loxx]Adaptivity: Measures of Dominant Cycles and Price Trend is an indicator that outputs adaptive lengths using various methods for dominant cycle and price trend timeframe adaptivity. While the information output from this indicator might be useful for the average trader in one off circumstances, this indicator is really meant for those need a quick comparison of dynamic length outputs who wish to fine turn algorithms and/or create adaptive indicators.
This indicator compares adaptive output lengths of all publicly known adaptive measures. Additional adaptive measures will be added as they are discovered and made public.
The first released of this indicator includes 6 measures. An additional three measures will be added with updates. Please check back regularly for new measures.
Ehers:
Autocorrelation Periodogram
Band-pass
Instantaneous Cycle
Hilbert Transformer
Dual Differentiator
Phase Accumulation (future release)
Homodyne (future release)
Jurik:
Composite Fractal Behavior (CFB)
Adam White:
Veritical Horizontal Filter (VHF) (future release)
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman's adaptive moving average (KAMA) and Tushar Chande's variable index dynamic average (VIDYA) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is this Hilbert Transformer?
An analytic signal allows for time-variable parameters and is a generalization of the phasor concept, which is restricted to time-invariant amplitude, phase, and frequency. The analytic representation of a real-valued function or signal facilitates many mathematical manipulations of the signal. For example, computing the phase of a signal or the power in the wave is much simpler using analytic signals.
The Hilbert transformer is the technique to create an analytic signal from a real one. The conventional Hilbert transformer is theoretically an infinite-length FIR filter. Even when the filter length is truncated to a useful but finite length, the induced lag is far too large to make the transformer useful for trading.
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, pages 186-187:
"I want to emphasize that the only reason for including this section is for completeness. Unless you are interested in research, I suggest you skip this section entirely. To further emphasize my point, do not use the code for trading. A vastly superior approach to compute the dominant cycle in the price data is the autocorrelation periodogram. The code is included because the reader may be able to capitalize on the algorithms in a way that I do not see. All the algorithms encapsulated in the code operate reasonably well on theoretical waveforms that have no noise component. My conjecture at this time is that the sample-to-sample noise simply swamps the computation of the rate change of phase, and therefore the resulting calculations to find the dominant cycle are basically worthless.The imaginary component of the Hilbert transformer cannot be smoothed as was done in the Hilbert transformer indicator because the smoothing destroys the orthogonality of the imaginary component."
What is the Dual Differentiator, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 187:
"The first algorithm to compute the dominant cycle is called the dual differentiator. In this case, the phase angle is computed from the analytic signal as the arctangent of the ratio of the imaginary component to the real component. Further, the angular frequency is defined as the rate change of phase. We can use these facts to derive the cycle period."
What is the Phase Accumulation, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 189:
"The next algorithm to compute the dominant cycle is the phase accumulation method. The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle's worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio."
What is the Homodyne, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 192:
"The third algorithm for computing the dominant cycle is the homodyne approach. Homodyne means the signal is multiplied by itself. More precisely, we want to multiply the signal of the current bar with the complex value of the signal one bar ago. The complex conjugate is, by definition, a complex number whose sign of the imaginary component has been reversed."
What is the Instantaneous Cycle?
The Instantaneous Cycle Period Measurement was authored by John Ehlers; it is built upon his Hilbert Transform Indicator.
From his Ehlers' book Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading by John F. Ehlers, 2004, page 107:
"It is obvious that cycles exist in the market. They can be found on any chart by the most casual observer. What is not so clear is how to identify those cycles in real time and how to take advantage of their existence. When Welles Wilder first introduced the relative strength index (rsi), I was curious as to why he selected 14 bars as the basis of his calculations. I reasoned that if i knew the correct market conditions, then i could make indicators such as the rsi adaptive to those conditions. Cycles were the answer. I knew cycles could be measured. Once i had the cyclic measurement, a host of automatically adaptive indicators could follow.
Measurement of market cycles is not easy. The signal-to-noise ratio is often very low, making measurement difficult even using a good measurement technique. Additionally, the measurements theoretically involve simultaneously solving a triple infinity of parameter values. The parameters required for the general solutions were frequency, amplitude, and phase. Some standard engineering tools, like fast fourier transforms (ffs), are simply not appropriate for measuring market cycles because ffts cannot simultaneously meet the stationarity constraints and produce results with reasonable resolution. Therefore i introduced maximum entropy spectral analysis (mesa) for the measurement of market cycles. This approach, originally developed to interpret seismographic information for oil exploration, produces high-resolution outputs with an exceptionally short amount of information. A short data length improves the probability of having nearly stationary data. Stationary data means that frequency and amplitude are constant over the length of the data. I noticed over the years that the cycles were ephemeral. Their periods would be continuously increasing and decreasing. Their amplitudes also were changing, giving variable signal-to-noise ratio conditions. Although all this is going on with the cyclic components, the enduring characteristic is that generally only one tradable cycle at a time is present for the data set being used. I prefer the term dominant cycle to denote that one component. The assumption that there is only one cycle in the data collapses the difficulty of the measurement process dramatically."
What is the Band-pass Cycle?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 47:
"Perhaps the least appreciated and most underutilized filter in technical analysis is the band-pass filter. The band-pass filter simultaneously diminishes the amplitude at low frequencies, qualifying it as a detrender, and diminishes the amplitude at high frequencies, qualifying it as a data smoother. It passes only those frequency components from input to output in which the trader is interested. The filtering produced by a band-pass filter is superior because the rejection in the stop bands is related to its bandwidth. The degree of rejection of undesired frequency components is called selectivity. The band-stop filter is the dual of the band-pass filter. It rejects a band of frequency components as a notch at the output and passes all other frequency components virtually unattenuated. Since the bandwidth of the deep rejection in the notch is relatively narrow and since the spectrum of market cycles is relatively broad due to systemic noise, the band-stop filter has little application in trading."
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 59:
"The band-pass filter can be used as a relatively simple measurement of the dominant cycle. A cycle is complete when the waveform crosses zero two times from the last zero crossing. Therefore, each successive zero crossing of the indicator marks a half cycle period. We can establish the dominant cycle period as twice the spacing between successive zero crossings."
What is Composite Fractal Behavior (CFB)?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is VHF Adaptive Cycle?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
RSI, EMA, SMA Trendtrading - Oil Daytrading 1HThe Unitrend trading System produces trading recommendations on a pure Trend basis.
It is a Score based system.
--- How to use the System --
Simply adjust your capital you want to risk per trade and your TP Factor.
The TP Factor is the multiple of your risked Capital, also known as Risk/Reward ratio.
Furthermore you can toggle between a always Buy mode, to see if the System is better then market.
Compounding mode helps you to get a better understanding of your maximum drawdown with a total equity based approach.
--- How are Signals produced? ---
A score of 2 or 3 is a BUY signal.
You can count the score by looking at the lines above 1, or by reading the color.
Green is 3, yellow 2, orange 1 and red is 0.
The score is calculated by 3 conditions.
Each applying condition yields one point for the score.
The score resets each bar.
The rules are:
RSI > 45: Well known indicator, usually looks for reversal points but seems to produce above average results when above 45.
EMA(RSI) > SMA(RSI): My approach to momentum detection for the RSI movement, I consider a faster growing RSI as a good thing.
EMA(close) > SMA(close): My approach to trend detection for the market movement. Common Wisdom would be a fast SMA > slow SMA which I found to be too slow for the modern market.
I11L OIL BotThe System makes use of the Bolinger Bands strategy from TradingView and implements simple Money Management Rules like SL and TP.
You can adjust the following Parameters:
Leverage: Leverage.
Risk Capital per Trade: The amount you are willing to lose per Trade, keep in mind that changes in Leverage should follow changes in Risk Capital.
TP_Factor: Default is 2:1 Risk:Reward, you might want to adjust this according to the underlying market.
InvertBuyLogic: Inverts the Logic of the System, important for checking if you have a true performance advantage from using the System. I look for a flat looking Curve in the wrong mode.
LookbackDistance: The distance your standart Deviation is refering to. A Lookback Distance too big might result in very few signals.
DevMult: We only want outliers, so we multiply our standart Deviation Bands by a Factor.
Accurate BUY & SELL 5 mins TF by RRAlways trade using 5 mins Time frame of chart.
For Buy entry always buy 1 point above the candle closing price & SL would be previous candle low or 30 points.
For Sell Entry Always Sell 1 point below the candle opening price & SL would be previous candle high or 30 points.
Do not take trades using 3 mins Time frame, as there is lot of noise. It works best with 5 mins Time frame.
I have adjusted/set according my trading pattern, if needed use the settings options to set accordingly .
Removed range highlighter to keep the chart simple.
Original Version credits to ZacVaughn
Actual Version i just set alerts and change the parameters for Crude OIL 5min Chart.
NO REPAINT.
Wait For Barclose
Weighted Least Squares Moving AverageLinearly Weighted Ordinary Least Squares Moving Regression
aka Weighted Least Squares Moving Average -> WLSMA
^^ called it this way just to for... damn, forgot the word
Totally pwns LSMA for some purposes here's why (just look up):
- 'realistically' the same smoothness;
- less lag;
- less overshoot;
- more or less same computationally intensive.
"Pretty cool, huh?", Bucky Roberts©, thenewboston
Now, would you please (just look down) and see the comparison of impulse & step responses:
Impulse responses
Step responses
Ain't it beautiful?
"Motivation behind the concept & rationale", by gorx1
Many been trippin' applying stats methods that require normally distributed data to time series, hence all these B*ll**** Bands and stuff don't really work as it should, while people blame themselves and buy snake oil seminars bout trading psychology, instead of using proper tools. Price... Neither population nor the samples are neither normally nor log-normally distributed. So we can't use all the stuff if we wanna get better results. I'm not talking bout passing each rolling window to a stat test in order to get the proper descriptor, that's the whole different story.
Instead we can leverage the fact that our data is time-series hence we can apply linear weighting, basically we extract another info component from the data and use it to get better results. Volume, range weighting don't make much sense (saying that based on both common sense and test results). Tick count per bar, that would be nice tho... this is the way to measure "intensity". But we don't have it on TV unfortunately.
Anyways, I'm both unhappy that no1 dropped it before me during all these years so I gotta do it myself, and happy that I can give smth cool to every1
Here is it, for you.
P.S.: the script contains standalone functions to calculate linearly weighted variance, linearly weighted standard deviation, linearly weighted covariance and linearly weighted correlation.
Good hunting
Reversal off EMA-XsEMA-Xs works mostly on Forex due to the small prices and price fluctuations. It does work on Gold, oddly enough, and some others like UKX 100...but mostly on forex. It doesn't work as well on JPY pairs but occasionally does; the JPY pairs give less signals, but when a JPY pair gives a signal, its a high probability setup. Another script EMA-XL works better on the higher priced instruments like S&P, DJI, OIL, BTC etc.
This script will show 3 moving averages: 13, 34, 200 and works on the 5m, 1hr, 4hr, daily charts. Signals "B" or "S" will be on the chart above or below the candles respectively.
When to open:
The script gives buy and sell signals based on a counter-trend move away from the MA's. When the price rises a specific percent above/below the EMA, it'll give a signal. It's best to take a trade when it gives a cluster of consecutive signals near the same price. If using on the 5m, definitely wait for consecutive signals. Also, use this in conjunction with support and resistance areas. Using with fibs for confirmation really makes this a good tool with high probability: IE, when price hits a fib and the script gives a signal, its a high probability setup.
When to close:
1. After a fast move up/down you may use this to counter trade a scalp 10+ pips, but you need to be quick; applies mostly to the 5m chart.
2. If you have the tenacity wait until you see an opposite signal. With this method you may be holding a loosing trade for a while. But what I've noticed is if it trends against you, price usually with come near to the first time it signaled. You may want to stack trades on each cluster of signals. IE first trade is 1000 units, next is 2000 units, etc... then close when prices comes near the first time it signaled. By this time, if you held, you should have profit. This strategy will really test your mental resilience.
3. Wait until it comes back to one of the trendlines; remember this is a counter trend signal so price is moving away from the MA and it always returns to touch one of the MA's...LOL eventually
4. Applying to scalping on the 5m, keep the stops tight because if the instrument trends hard and fast, you'll be upside-down quickly.
If you put a lot of time into using this signal generator, you can really make good profit. But with all tools, you need to master it. There are nuances to the simple logic of this script that can be both fun and frustrating. With all endeavors, if you put the time into it, you will reap the rewards.
Good luck and let me know if you have any questions/comments.
vol_premiaThis script shows the volatility risk premium for several instruments. The premium is simply "IV30 - RV20". Although Tradingview doesn't provide options prices, CBOE publishes 30-day implied volatilities for many instruments (most of which are VIX variations). CBOE calculates these in a standard way, weighting at- and out-of-the-money IVs for options that expire in 30 days, on average. For realized volatility, I used the standard deviation of log returns. Since there are twenty trading periods in 30 calendar days, IV30 can be compared to RV20. The "premium" is the difference, which reflects market participants' expectation for how much upcoming volatility will over- or under-shoot recent volatility.
The script loads pretty slow since there are lots of symbols, so feel free to delete the ones you don't care about. Hopefully the code is straightforward enough. I won't list the meaning of every symbols here, since I might change them later, but you can type them into tradingview for data, and read about their volatility index on CBOE's website. Some of the more well-known ones are:
ES: S&P futures, which I prefer to the SPX index). Its implied volatility is VIX.
USO: the oil ETF representing WTI future prices. Its IV is OVX.
GDX: the gold miner's ETF, which is usually more volatile than gold. Its IV is VXGDX.
FXI: a china ETF, whose volatility is VXFXI.
And so on. In addition to the premium, the "percentile" column shows where this premium ranks among the previous 252 trading days. 100 = the highest premium, 0 = the lowest premium.
pricing_tableThis script helps you evaluate the fair value of an option. It poses the question "if I bought or sold an option under these circumstances in the past, would it have expired in the money, or worthless? What would be its expected value, at expiration, if I opened a position at N standard deviations, given the volatility forecast, with M days to expiration at the close of every previous trading day?"
The default (and only) "hv" volatility forecast is based on the assumption that today's volatility will hold for the next M days.
To use this script, only one step is mandatory. You must first select days to expiration. The script will not do anything until this value is changed from the default (-1). These should be CALENDAR days. The script will convert to these to business days for forecasting and valuation, as trading in most contracts occurs over ~250 business days per year.
Adjust any other variables as desired:
model: the volatility forecasting model
window: the number of periods for a lagged model (e.g. hv)
filter: a filter to remove forecasts from the sample
filter type: "none" (do not use the filter), "less than" (keep forecasts when filter < volatility), "greater than" (keep forecasts when filter > volatility)
filter value: a whole number percentage. see example below
discount rate: to discount the expected value to present value
precision: number of decimals in output
trim outliers: omit upper N % of (generally itm) contracts
The theoretical values are based on history. For example, suppose days to expiration is 30. On every bar, the 30 days ago N deviation forecast value is compared to the present price. If the price is above the forecast value, the contract has expired in the money; otherwise, it has expired worthless. The theoretical value is the average of every such sample. The itm probabilities are calculated the same way.
The default (and only) volatility model is a 20 period EWMA derived historical (realized) volatility. Feel free to extend the script by adding your own.
The filter parameters can be used to remove some forecasts from the sample.
Example A:
filter:
filter type: none
filter value:
Default: the filter is not used; all forecasts are included in the the sample.
Example B:
filter: model
filter type: less than
filter value: 50
If the model is "hv", this will remove all forecasts when the historical volatility is greater than fifty.
Example C:
filter: rank
filter type: greater than
filter value: 75
If the model volatility is in the top 25% of the previous year's range, the forecast will be included in the sample apart from "model" there are some common volatility indexes to choose from, such as Nasdaq (VXN), crude oil (OVX), emerging markets (VXFXI), S&P; (VIX) etc.
Refer to the middle-right table to see the current forecast value, its rank among the last 252 days, and the number of business days until
expiration.
NOTE: This script is meant for the daily chart only.
Sideways detection bollinger bandsSideways detection indicator using Bollinger bands .
In this case we take the original ratio between lower and upper and we smooth it even harder in order to get a better idea about the accuracy of the trend.
If the initial ratio is not between 0 and 1 and the smooth ratio is higher than our selected value, we get an idea if we are a in trending market or not.
Of course using it as a standalone has no usage, and it has to be combined with other tools like moving average, oscillators and so on.
IF you have any questions let me know
Financial Astrology Neptune LongitudeNeptune energy influence the charity, confusion, imagination, waste, crime, intuition, occult, scandal, illusion and dreams. It rules the industries related to chemicals, gas and oil, drugs and alcoholic beverages, scams, non profit organisations, spirituality. The last decade Neptune have been traveling through Piscis sign which caused humanity to have an illusion that economical growth don't have limits, as consequence we saw US indexes growth toward new all time highs. However, Neptune is close to leave Piscis, in 7 more degrees as per July 2021 and new cycle is going to start. It will be interesting to see what happens as Neptune moves into Aries sign.
This longitude indicator show a zodiac signs horizontal line boundaries that identify the start of the sign marked in the corresponding horizontal line label in the Y axis, this simplify the analysis of a planet effect within specific zodiac sign.
Note: The Neptune longitude indicator is based on an ephemeris array that covers years 2010 to 2030, prior or after this years the data is not available, this daily ephemeris are based on UTC time so in order to align properly with the price bars times you should set UTC as your chart timezone.
Rate ConverterThis is a simple rate converter that can convert almost anything into almost anything else. It supports cryptocurrencies, currencies and most commodities.
On the chart we see the following:
USD (US Dollar) into EUR (Euro) as a candle stick chart
WTICO (West Texas Intermediate Crude Oil) into ISK (Icelandic Krona) as a bar chart
ADA (Cardano) into JMD (Jamaican Dollar) as a line chart
XPT (Platinum) into XAG (Silver) as a scatter plot
It supports plotting the rates as japanese candlesticks, bars, lines, or as a scatter plot.
COT GRAINS FUNDS NET POSITION(GRAINSTATS)- Retrieves fund net position from CFTC Commitments of Traders(COT) Reports
- Overlays fund net positions on left y-axis vs price on right y-axis
- Current supported Grain Products
- Corn (CBOT) (QUANDL: 002602)
- Soybeans (CBOT) (QUANDL: 005602)
- Kansas City Wheat(CBOT) (Hard Red Winter) (QUANDL: 001612)
- Oats (CBOT) (QUANDL: 004603)
- Soybean Meal (CBOT) (QUANDL: 026603)
- Soybean Oil (CBOT) (QUANDL: 007601)
- Wheat (CBOT) (Soft Red Winter) (QUANDL: 001602)
(MGEX WHEAT IS UNSUPPORTED)
quandl_cme_oilquandl data for oil (set for 1Day)
-Brent and WTI
-Contract selection
-Data type selection
Bollinger Bands %B + ATR This indicator is best suitable for the 30-minutes interval OIL charts, due to ATR accuracy.
BB%B is great for showing oversold/overbought market conditions and offers excellent entry/exit opportunities for Day Trading (30 minutes chart), as well as reliable convergence/divergence patterns. ATR is conveniently combined and shows potential market volatility levels for the day when used in 30-minutes charts, thus demarcating your day trade exit point.
To use the ATR on this indicator: Just read the ATR value of the lowest (for a new bull trend) or the highest (for a new bear trend) candlestick of the newly formed trend leg. Let's suppose the ATR reads 0.2891, then you project a move of 2.891 points towards the given trend direction using the ruler tool (30-minutes charts). That's all, and there you have your take profit target!
Good Luck!!!
Rain On Me IndicatorFinally, we made it :D
Rain On Me Indicator, As the name suggests this indicator will make money rain on you. More seriously, this indicator contains :
This indicator contains:
-Bullish and bearish RSI divergences showing on chart with alerts.
-Parabolic SAR with Labels on chart with buying or selling alerts.
-3 Moving Average (MA 1 : 7, MA 2 : 21 MA 3 HIDDEN : 50 (Cross alerts for Pullback)
-Customizable Bollinger band
-Fibonacci on 10 levels with the level 0 to the middle. This Fibonacci help a lot since it can let you find easily entry/exit point, trend and even where to place your Take Profit and Stop Loss. It have alerts for most important levels (0.382, 0.§, 0.618) for Crossunder and Crossover in Bullish or Bearish trend.
-Fully Customizable Ichimoku Cloud.
-Trend Buy/Sell Labels on chart with buying or selling signal alerts.
-Trend color visible on candles.
If an alert trigger of Buy/Sell Signal with the same alert based on PSAR, so you can be confident to enter in position. Alway checking fibs level that is the key thing with this indicator. the script has been set to have the best possible results on as many market as possible. But.best result for zfter backtesting is on
Forex : EUR/USD, USDJPY, USDCAD.
Indice : S&P500, NASDAQ, DOWJONES
Commodities : OIL, WTI
Everything work on following timeframe :
15MN, 1H, 4H, DAILY, WEEKLY.
So that you can avoid having to set it again, whether it be in minutes, hours, days, months.
So you can easily trade in the mode that suits you best. It works well on everything from indices to forex to commodities etc. I thank all those who allowed me to carry out this project. IF you feelt free to give your ideas, suggestions, for improve it by sending me messages.
This is really a first version sp it may contain bugs / errors that will be fixed over time.
A BIG THANK YOU TO QUANTNOMAD WHO GIVE ME HIS PERMISSION TO USE, MODIFY AND REPUBLISH HIS "Ultimate Pivot Points Alerts" Script Indicator :
Good trade to all !
Position Size Calculator ATRThis tool calculates your position size based on the ATR.
Caution: You MUST convert the capital amount into the same currency as the instrument you are trading before inputting it into the calculator.
Ex) Assume your capital is in USD...
Ex) GBP/JPY >>> So convert 10,000 USD capital into JPY.
Ex) BTC/USD >>> No conversion necessary.
Ex) Apple stock traded on US stock exchange; AAPL/USD >>> Capital must be in USD; thus, no conversion necessary.
Ex) WTI Oil/USD >>> Capital is already in USD, no conversion necessary.
Hopefully this helps, if your confused about the conversion process, message me or comment below.
Feel free to follow me, and happy trading guys!
Revolution Kagi Reversal Amount IndicatorThis is one of my favorite indicators. You simply type in the significant price levels for whatever asset you are trading and it will plot pivots accordingly. As in title, the indicator is based on the fantastic Kagi reversal indicator.
For instance, if, say, brent crude oil is trading at $60, you can assume that $10 and $5 will be significant price levels. If gold is trading at $1500, $100 and $500 might be significant and so on.
Cross Asset VolatilityThis script brings together a number of volatility indexes from the CBOE in one space making it easier to use rather than adding a number of different securities to one chart. One could create a template with these securities attached, but sometimes, you don't want to switch charts, for whatever reason, and adding an indicator for is quick and simple.
One note is that due some securities exhibit much larger volatility than others (i.e. oil vs bonds) and it can be difficult to see clearly those securities whose volatilities are low, and hence we have added the ability to calculate the values as a Log value to make the indicator more readable. Another way to do this is to change the Y-axis on the chart to Logarithmic while leaving the indicator at its default settings (i.e. the checkbox for using Log calculations remains unchecked).
Price CorrelationsThis indicator shows price correlations of your current chart to various well-known indices.
Values above 0 mean a positive correlation, below 0 a negative correlation (not correlated).
It works well with daily candle charts and above, but you may also try it on 1h candles.
The default indices:
- Gold
- S&p 500
- Mini Dow Jones
- Dow Jones
- Russel 2000
- Nasdaq 100
- Crude Oil
- Nikkei 225 (Japan)
- FTSE 100 (UK)
- Silver
- DAX Futures (DE)
You can change the defaults to compare prices with other indices or stocks.
Crack SpreadPlots the two common crack spreads for oil:
- RB only
- 3-2-1 RB and HO
Can specify any RB, HO and CL contracts, default is the continous front-month.
If using full-screen scaling, it is best to use one line at a time per indicator instance.
ANN MACD : 25 IN 1 SCRIPTIn this script, I tried to fit deep learning series to 1 command system up to the maximum point.
After selecting the ticker, select the instrument from the menu and the system will automatically turn on the appropriate ann system.
Listed instruments with alternative tickers and error rates:
WTI : West Texas Intermediate (WTICOUSD , USOIL , CL1! ) Average error : 0.007593
BRENT : Brent Crude Oil (BCOUSD , UKOIL , BB1! ) Average error : 0.006591
GOLD : XAUUSD , GOLD , GC1! Average error : 0.012767
SP500 : S&P 500 Index (SPX500USD , SP1!) Average error : 0.011650
EURUSD : Eurodollar (EURUSD , 6E1! , FCEU1!) Average error : 0.005500
ETHUSD : Ethereum (ETHUSD , ETHUSDT ) Average error : 0.009378
BTCUSD : Bitcoin (BTCUSD , BTCUSDT , XBTUSD , BTC1!) Average error : 0.01050
GBPUSD : British Pound (GBPUSD,6B1! , GBP1!) Average error : 0.009999
USDJPY : US Dollar / Japanese Yen (USDJPY , FCUY1!) Average error : 0.009198
USDCHF : US Dollar / Swiss Franc (USDCHF , FCUF1! ) Average error : 0.009999
USDCAD : Us Dollar / Canadian Dollar (USDCAD) Average error : 0.012162
SOYBNUSD : Soybean (SOYBNUSD , ZS1!) Average error : 0.010000
CORNUSD : Corn (ZC1! ) Average error : 0.007574
NATGASUSD : Natural Gas (NATGASUSD , NG1!) Average error : 0.010000
SUGARUSD : Sugar (SUGARUSD , SB1! ) Average error : 0.011081
WHEATUSD : Wheat (WHEATUSD , ZW1!) Average error : 0.009980
XPTUSD : Platinum (XPTUSD , PL1! ) Average error : 0.009964
XU030 : Borsa Istanbul 30 Futures ( XU030 , XU030D1! ) Average error : 0.010727
VIX : S & P 500 Volatility Index (VX1! , VIX ) Average error : 0.009999
YM : E - Mini Dow Futures (YM1! ) Average error : 0.010819
ES : S&P 500 E-Mini Futures (ES1! ) Average error : 0.010709
GAZP : Gazprom Futures (GAZP , GZ1! ) Average error : 0.008442
SSE : Shangai Stock Exchange Composite (Index ) ( 000001 ) Average error : 0.011287
XRPUSD : Ripple (XRPUSD , XRPUSDT ) Average error : 0.009803
Note 1 : Australian Dollar (AUDUSD , AUD1! , FCAU1! ) : Instrument has been removed because it has an average error rate of over 0.13.
The average error rate is 0.1850.
I didn't delete it from the menu just because there was so much request,
You can use.
Note 2 : Friends have too many requests, it took me a week in total and 1 other script that I'll share in 2 days.
Reaching these error rates is a very difficult task, and when I keep at a low learning rate, they are trained for a very long time.
If I don't see the error rate at an average low, I increase the layers and go back into a longer process.
It takes me 45 minutes per instrument to command artificial neural networks, so I'll release one more open source, and then we'll be laying 70-80 percent of the world trade volume with artificial neural networks.
Note 3 :
I would like to thank wroclai for helping me with this script.
This script is subject to MIT License on behalf of both of us.
You can review my original idea scripts from my Github page.
You can use it free but if you are going to modify it, just quote this script .
I hope it will help everyone, after 1-2 days I will share another ann script that I think is of the same importance as this, stay tuned.
Regards , Noldo .
