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Buy the dips - sell the topsThis script is a merge of the RSI and the Williams %R.
I've observed that in strong uptrends, we go from RSI overbought to RSI overbought, but it hardly gets oversold. (the same in the opposite direction)
To find a better entry point, Williams %R is used to find oversold conditions in an uptrend or overbought in a downtrend.
=> When W%R returns from oversold/overbought to normal, a triangle will be plotted and this is the point of entry to add to your position. (there's an option to mark all candles in the overbought/oversold region, by default it is off)
=> When RSI goes from overbought back to normal it will tell you to buy the dip. In a downtrend it will tell you to sell the tops.
=> When the RSI gets oversold and the previous RSI was overbought, it will mark to exit the position
I did backtest this one with a risk to reward of 2 and exit when target is reached.
Trading EUR/USD on the daily would return 28% after 10 years of trading with a success ratio of 43%.
Trading BTC/USD on the daily would lose 12% after 7 years and a success rate of 28%.
Trading it this way is not the best idea ;-) 2 Interesting observations however:
- Once you get the entry right, in 80% of the cases, you do reach the next RSI oversold/overbought level. Keeping your position open until you reach that level can be an option to maximize profits.
- When a triangle is plotted and it is the low compared to the previous more or less 5 candles (same for the high), chances are high it will be taken out a few candles later, so don't take a trade yet.
Using classic technical analysis might improve more your entry and exit positions.
Feel free to comment your best strategy using this indicator ;-)
Happy trading! Indicator
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End-pointed SSA of Williams %R [Loxx]End-pointed SSA of Williams %R is an indicator that runes Williams %R SSA calculation through a Singular Spectrum Analysis (SSA) algorithm to derive a smoother final output. The reduction in noise from the traditional Williams %R is significant.
What is Williams %R?
Williams %R , also known as the Williams Percent Range, is a type of momentum indicator that moves between 0 and -100 and measures overbought and oversold levels. The Williams %R may be used to find entry and exit points in the market. The indicator is very similar to the Stochastic oscillator and is used in the same way. It was developed by Larry Williams and it compares a stock’s closing price to the high-low range over a specific period, typically 14 days or periods.
What is Singular Spectrum Analysis ( SSA )?
Singular spectrum analysis ( SSA ) is a technique of time series analysis and forecasting. It combines elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA aims at decomposing the original series into a sum of a small number of interpretable components such as a slowly varying trend, oscillatory components and a ‘structureless’ noise. It is based on the singular value decomposition ( SVD ) of a specific matrix constructed upon the time series. Neither a parametric model nor stationarity-type conditions have to be assumed for the time series. This makes SSA a model-free method and hence enables SSA to have a very wide range of applicability.
For our purposes here, we are only concerned with the "Caterpillar" SSA . This methodology was developed in the former Soviet Union independently (the ‘iron curtain effect’) of the mainstream SSA . The main difference between the main-stream SSA and the "Caterpillar" SSA is not in the algorithmic details but rather in the assumptions and in the emphasis in the study of SSA properties. To apply the mainstream SSA , one often needs to assume some kind of stationarity of the time series and think in terms of the "signal plus noise" model (where the noise is often assumed to be ‘red’). In the "Caterpillar" SSA , the main methodological stress is on separability (of one component of the series from another one) and neither the assumption of stationarity nor the model in the form "signal plus noise" are required.
"Caterpillar" SSA
The basic "Caterpillar" SSA algorithm for analyzing one-dimensional time series consists of:
Transformation of the one-dimensional time series to the trajectory matrix by means of a delay procedure (this gives the name to the whole technique);
Singular Value Decomposition of the trajectory matrix;
Reconstruction of the original time series based on a number of selected eigenvectors.
This decomposition initializes forecasting procedures for both the original time series and its components. The method can be naturally extended to multidimensional time series and to image processing.
The method is a powerful and useful tool of time series analysis in meteorology, hydrology, geophysics, climatology and, according to our experience, in economics, biology, physics, medicine and other sciences; that is, where short and long, one-dimensional and multidimensional, stationary and non-stationary, almost deterministic and noisy time series are to be analyzed.
Included:
Bar coloring
[*Alerts
[*Signals
[*Loxx's Expanded Source Types
Related Williams %R Indicators
Williams %R on Chart w/ Dynamic Zones
Williams %R w/ Bollinger Bands
Intermediate Williams %R w/ Discontinued Signal Lines
Related SSA Indicators
End-pointed SSA of FDASMA
End-pointed SSA of Normalized Price Oscillator
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Rsi/W%R/Stoch/Mfi: HTF overlay mini-plotsOverlay mini-plots for various indicators. Shows current timeframe; and option to plot 2x higher timeframes (i.e. 15min and 60min on the 5min chart above).
The idea is to de-clutter chart when you just want real-time snippets for an indicator.
Useful for gauging overbought/oversold, across timeframes, at a glance.
~~Indicators~~
~RSI: Relative strength index
~W%R: Williams percent range
~Stochastic
~MFI: Money flow index
~~Inputs~~
~indicator length (NB default is set to 12, NOT the standard 14)
~choose 2x HTFs, show/hide HTF plots
~choose number of bars to show (current timeframe only; HTF plots show only 6 bars)
~horizontal position: offset (bars); shift plots right or left. Can be negative
~vertical position: top/middle/bottom
~other formatting options (color, line thickness, show/hide labels, 70/30 lines, 80/20 lines)
~~tips~~
~should be relatively easy to add further indicators, so long as they are 0-100 based; by editing lines 9 and 11
~change the vertical compression of the plots by playing around with the numbers (+100, -400, etc) in lines 24 and 25
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Williams %R on Chart w/ Dynamic Zones [Loxx]Williams %R on Chart w/ Dynamic Zones is a Williams %R indicator but instead of being an oscillator it appears on chart. The WPR calculation used here leverages T3 moving average for its calculation. In addition, the WPR is bound by Dynamic Zones.
What is Williams %R?
Williams %R , also known as the Williams Percent Range, is a type of momentum indicator that moves between 0 and -100 and measures overbought and oversold levels. The Williams %R may be used to find entry and exit points in the market. The indicator is very similar to the Stochastic oscillator and is used in the same way. It was developed by Larry Williams and it compares a stock’s closing price to the high-low range over a specific period, typically 14 days or periods.
What is T3 moving average?
Developed by Tim Tillson, the T3 Moving Average is considered superior to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
Bar coloring
Channels fill
Loxx's Expanded Source Types
35+ moving average types
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All TimeFrame OscillatorsI have always fighted to understand the market direction because it looks different on different timeframes.
I wanted an indicator where I can see all the different timeframes at once.
This indicator shows already existing oscillators but not only in the current chart's timeframe, but all the most important higer timeframes at once.
I have started with the stoch, then added as many oscillators as I could.
Experimenting with this I have saw that confluence of 4H 1D and 1W Stoch can be very interesting and can highlight higher timeframe take profit areas and sometimes major tops/bottoms.
Also bounces can be interesting when a lower timeframe stoch is bounced or rejected from a higher one.
Oscillators:
Stoch - Stochastic Oscillator
SMI - Stochastic Momentum Index
Rsi - Relative Strength Index
StochRsi - Stochastic RSI
WaveTrend - Vumanchu alias Market Cypher Wave Trend line
CCI - Commodity Channel Index
CCIStoch - Stochastic CCI
Williams Percent Range - Williams %R
Norm. MACD - Normalized Moving Average Convergence Divergence
Norm. MACD Hist - Normalized MACD Histogramm
PVT - Normalized Price Volume Trend
MFI - Money Flow Index
CMF - Chaikin Money Flow
Chande Momentum - Chande Momentum
Volume - Normalized Volume
CandleValue - Vumanchu alias Market Cypher MoneyFlow
BBWP - Bollinger Band Width Percentile
Line Type
Smooth: lines are smoothed, but the actualy not closed values are not shown
Step: Step lines, the actually open timeframes are calculated as they closed at the current values
Plot Oscillator or it's Slope:
its possible to not plot the oscillator but it's slope
Print dots when:
Cross Up/Down oversold/overbougt level - best for most oscillators. for example when Stoch crosses above 20 or below 80
Cross os/ob and the one higher TF is about to cross - when it's crosses beolw 80 and the higher timeframe oscillator is still above ans sloping down
Cross above/below middle line - for example on RSI being above or below 50 can be interesting
Print triangles when:
All Slope Match - all visible timeframe lines are pointing up or down at the same time
All above/belove middle line - all visible lines are above or belove the middle line
All above/belove middle line and slope match - like the previous one and the slope direction is the same
All above/below oversold/overbougt - all lines are above or below os/ ob. this is the default. it can be a very important confluence
Lower TF in order - 5, 15, 30, 60 minute timeframes are in order.
Higher TF in order - 4H 1D 1W in order (like 4H above 1D abd 1D above 1W). can be interesting at RSI
4H-1D in order - 4H 1D in order .
Print triangles
Print all triangles - print all triangles when the condition is met
Print only first triangles - only show when the condition starts to met
Print only last triangles - small triangles when the condition met first, large when last. tis is the default.
Timeframes to show:
You can turn on/off different timeframs to show or not from the list below:
1m 5m 15m 30m 1H 4H D 5D W M
This is for experimenting/ understanding the market direction on multiple timeframes at once.
Don't take it's signals (and any other indicator's) as exact trade signals. use it as confirmation instead.
Any comments, insights, ideas are welcome.
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Williams Vix Fix Bottoms and TopsThis indicator uses the very popular Williams Vix Fix for Bottoms by Chris Moody but not only does it search for bottoms, it can also be switch to work for tops for those who look to short the market. I've also added in a few options like flipping the indicator, color adjustments on the settings page, as well as cut a few of the options I feel did not need to be in which cluttered the screen when the settings were opened. In his later revisions of the Williams Vix Fix, CM took out the functions which draw the high/low ranges as well as the standard deviation which is what this indicator uses to show entry points. I have added options back on to draw these, I think it's useful. To be honest, I have not messed around with the number settings much so I am not sure how adjusting the look back range or going for smaller / bigger percentage changes would change how well the indicator works. It seems to work very well at its default settings.
With the Bollinger Band deviation, you have to remember that it looks back at the set amount of candles (20 by default) and uses those for the standard deviation: 1 dev = 68%, 2 dev = 95%, 3 dev = 99.7%
These percentages mean that at 2 dev, 95% of the last 20 candles will remain within the boundaries of the Bollinger Bands. Three tends to be too high, one is usually too low. Two is pretty good.
The lowest percentile option probably won't change much other than bring up the bottom line which doesn't effect the alerts or signals, just something to observe.
The highest percentile option makes a difference similar to the stand deviation and Bollinger Band. The higher you put it, the less likely it will get triggered but the more reliant it of a signal it should be.
As always, I have left notes throughout the code and I did leave in the code that was original but commented it out as I don't believe it's worth having.
I like to have the high/lows drawn, as well as the standard deviation. Then I find that the filtered entries are most accurate signals to follow. Simple entry is hit or miss, Aggressive entry is always early but sometimes that's not a great thing. Indicator
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