Trading Psychology - Fear & Greed Index by DGTPsychology of a Market Cycle - Where are we in the cycle?
Before proceeding with the question "where", let's first have a quick look at "What is market psychology?"
Market psychology is the idea that the movements of a market reflect the emotional state of its participants. It is one of the main topics of behavioral economics - an interdisciplinary field that investigates the various factors that precede economic decisions. Many believe that emotions are the main driving force behind the shifts of financial markets and that the overall fluctuating investor sentiment is what creates the so-called psychological market cycles - which is also dynamic.
Stages of Investor Emotions:
* Optimism – A positive outlook encourages us about the future, leading us to buy stocks.
* Excitement – Having seen some of our initial ideas work, we begin considering what our market success could allow us to accomplish.
* Thrill – At this point we investors cannot believe our success and begin to comment on how smart we are.
* Euphoria – This marks the point of maximum financial risk. Having seen every decision result in quick, easy profits, we begin to ignore risk and expect every trade to become profitable.
* Anxiety – For the first time the market moves against us. Having never stared at unrealized losses, we tell ourselves we are long-term investors and that all our ideas will eventually work.
* Denial – When markets have not rebounded, yet we do not know how to respond, we begin denying either that we made poor choices or that things will not improve shortly.
* Fear – The market realities become confusing. We believe the stocks we own will never move in our favor.
* Desperation – Not knowing how to act, we grasp at any idea that will allow us to get back to breakeven.
* Panic – Having exhausted all ideas, we are at a loss for what to do next.
* Capitulation – Deciding our portfolio will never increase again, we sell all our stocks to avoid any future losses.
* Despondency – After exiting the markets we do not want to buy stocks ever again. This often marks the moment of greatest financial opportunity.
* Depression – Not knowing how we could be so foolish, we are left trying to understand our actions.
* Hope – Eventually we return to the realization that markets move in cycles, and we begin looking for our next opportunity.
* Relief – Having bought a stock that turned profitable, we renew our faith that there is a future in investing.
It's hard to predict with certainty where we exactly are in the market cycle, we can only make an educated guess as to the rough stage based on data available. And here comes the study "Trading Psychology - Fear & Greed Index"
Factors taken into account in this study include:
1-Price Momentum : Price Divergence/Convergence versus its Slow Moving Average
2-Strenght : Rate of Return (RoR) also called Return on Investment (ROI) is a performance measure used to evaluate the efficiency of an investment, net gain or loss of an investment over a specified time period, the rate of change in price movement over a period of time to help investors determine the strength
3-Money Flow : Chaikin Money Flow (CMF) is a technical analysis indicator used to measure Money Flow Volume over a set period of time. CMF can be used as a way to further quantify changes in buying and selling pressure and can help to anticipate future changes and therefore trading opportunities. CMF calculations is based on Accumulation/Distribution
4-Market Volatility : CBOE Volatility Index (VIX), the Volatility Index, or VIX, is a real-time market index that represents the market's expectation of 30-day forward-looking volatility. Derived from the price inputs of the S&P 500 index options, it provides a measure of market risk and investors' sentiments. It is also known by other names like "Fear Gauge" or "Fear Index." Investors, research analysts and portfolio managers look to VIX values as a way to measure market risk, fear and stress before they take investment decisions
5-Safe Haven Demand : in this study GOLD demand is assumed
What to look for :
*Fear and Greed Index as explained above,
*Divergencies
Tool tip of the label displayed provides details of references
Conclusion:
As investors, we always get caught up in the day to day price movements, and lose sight of the bigger picture. The biggest crashes happen not when investors are cautious and fearful, it's when they're euphoric and expecting financial instruments to continue going higher. So as we continue investing, don’t forget to stop and ask yourself, where in the chart do you think we are right now? The Market Psychology Cycle shines light on how emotions evolve, fear and greed index can come in handy, provided that it is not the only tool used to make investment decisions. It is easy to look back at market cycles and recognize how the overall psychology changed. Analyzing previous data makes it obvious what actions and decisions would have been the most profitable. However, it is much harder to understand how the market is changing as it goes - and even harder to predict what comes next. Many investors use technical analysis (TA) to attempt to anticipate where the market is likely to go. Investors are advised to keep tabs on fear for potential buying the dips opportunities and view periods of greed as a potential indicator that financial instruments might be overvalued.
Warren Buffett's quote, buy when others are fearful, and sell when others are greedy
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
Disclaimer : 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
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Ehlers Cyber Cycle [CC]The Cyber Cycle was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pg 34) and this is one of my favorite Ehlers indicators. I use it personally for exits but it has several uses. It gives great entry and exit signals when you enter when it is at the bottom or at the very top during a cycle. When it is above 0 then the stock is in a strong uptrend and when it is below 0 then the stock is in a strong downtrend. It is also very reactive as well with zero lag according to Ehlers. Buy when the indicator line is green and sell when it is red.
Let me know if there are other scripts you would like to see me publish or if you want something custom done!
Ehlers Sinewave Indicator V2 [CC]The Sinewave Indicator was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pgs 154-155) and this is an updated version of his original Sinewave Indicator which in my opinion seems to be more reactive to changes. Buy when the blue line crosses over the red line and sell when the blue line crosses under the red line. Also keep in mind that this indicator is based on cycles so it won't act the same as a typical indicator.
Let me know if there are other scripts you would like to see me publish or if you want something custom done!
Ehlers Spectrum Derived Filter Bank [CC]The Spectrum Derived Filter Bank was created by John Ehlers (Stocks & Commodities V. 26:3 (16-22)) and this is technically two indicators in one. This will let you know the current cycle period which is in blue and the other indicator will let you know if you should buy the stock or not. Buy when it is green and sell when it is red.
Let me know if you would like me to publish other scripts or if you want something custom done!
Note: I'm republishing this because the original script couldn't be found in searches so this will fix that.
Ehlers Dominant Cycle Tuned Bypass Filter [CC]The Dominant Cycle Tuned Bypass Filter was created by John Ehlers (Stocks & Commodities V. 26:3 (16-22)) and this is a particularly unique indicator because this does a pretty good job at predicting the future stock movements. If the blue line crosses over the red then a few bars from now the stock price will most likely go up and if the blue line crosses below the red then a few bars from now the stock price should go down. Since this is such a unique indicator to use with entry and exit points, I don't have them color coded but try this out and let me know what you think.
This was a special request so let me know what other scripts you would like to see me publish or if you want anything custom done!
Note: I'm republishing this because the original script couldn't be found in searches so this will fix that.
Ehlers Correlation Cycle IndicatorThe Correlation Cycle Indicator was created by John Ehlers (Stocks & Commodities V. 38:06 (8–15)) and this is technically part of three indicators in one so I'm splitting each one to a separate script. This particular indicator was designed for trend direction and trend strength and simply buy when it is green and sell when it turns red. Also keep in mind that the higher the indicator is above the signal then the stronger the trend and when they are close together, conditions get choppy.
Let me know if you would like to see me publish other scripts or if you want something custom done!
Phase CalculationPhase Calculation was authored by John F. Elders in the Stocks and Commodities Magazine 11/1996
This indicator will tell you if the stock is in a uptrend or downtrend. A phase number with a low number means it is in a uptrend and a phase number with a high number means it is in a downtrend.
Let me know if you want to see me write code for different indicators!
Envelope BTMStudi cicli? Questo fa per te, le bande che altro non sono due medie mobili, tengono il prezzo alle due estremità (in alto e in basso).
Questo ti farà semplicemente analizzare e tenere traccia i cicli dello strumento in questione.
Do you study cycles? This is for you, the bands, formed by two moving averages, keep the price between the two ends (top and bottom).
This will simply cause you to analyze and track the cycles of price in question.
Stochastic Pop and Drop by Jake Bernstein v1 [Bitduke]I found a simple strategy by Jake Bernstein, modified it a little and created a strategy with Risk Management System (SL+TP); After that I test it on the different cryptocurrency pairs.
About the Indicator
Basically it's the strategy of 2 indicators: Stochastic Oscillator to define the bias and Average Directional Index to confirm it.
One again, It uses Stochastic Oscillator to define the trading bias. In particular, the trading bias was deemed bullish when the weekly 14-period Stochastic Oscillator was above some default value (in him paper - 50) and rising and vice versa.
Once the trading bias is established, Steckler used the Average Directional Index (ADX) to define a slowdown in the trend. ADX measures the strength of the trend and a move below 20 signals a weak trend.
Modifications
I didn't implement Average Directional Index (ADX) and test just different sources for data, oscillator periods and different levels in relation to the crypto market.
So, it shows good results with two tight thresholds at 55 and 45 level.
The bar chart below the defining the bullish and bearish periods (green and red) and gives a signal to enter the trade (purple bars).
Backtesting
Backtested on XBTUSD , BTCPERP (FTX) pairs. You may notice it shows good results on 3h timeframe.
Relatively low drawdown
~ 10% (from 2019 to date) FTX
~ 22% (4 years from 2016) Bitmex
I backtested on the different altcoin pairs as well, but the results were just not good.
Relatively good results were shown by some index pairs from the FTX exchange ( FTX:SHITPERP ), but I think there is a few data for backtesting to be asure in them.
Bitmex 3h (2017 - 2020) :
i.imgur.com
FTX 3h (2019 - 2020):
i.imgur.com
Possible Improvements
- Regarding trading algorithm it would be good to check with strategy with ADX somehow. Maybe for the better entries
- As for Risk Management system, it can be improved by adding trailing stop to the strategy.
Link: school.stockcharts.com
Grover Llorens Cycle Oscillator [alexgrover & Lucía Llorens]Cycles represent relatively smooth fluctuations with mean 0 and of varying period and amplitude, their estimation using technical indicators has always been a major task. In the additive model of price, the cycle is a component :
Price = Trend + Cycle + Noise
Based on this model we can deduce that :
Cycle = Price - Trend - Noise
The indicators specialized on the estimation of cycles are oscillators, some like bandpass filters aim to return a correct estimate of the cycles, while others might only show a deformation of them, this can be done in order to maximize the visualization of the cycles.
Today an oscillator who aim to maximize the visualization of the cycles is presented, the oscillator is based on the difference between the price and the previously proposed Grover Llorens activator indicator. A relative strength index is then applied to this difference in order to minimize the change of amplitude in the cycles.
The Indicator
The indicator include the length and mult settings used by the Grover Llorens activator. Length control the rate of convergence of the activator, lower values of length will output cycles of a faster period.
here length = 50
Mult is responsible for maximizing the visualization of the cycles, low values of mult will return a less cyclical output.
Here mult = 1
Finally you can smooth the indicator output if you want (smooth by default), you can uncheck the option if you want a noisy output.
The smoothing amount is also linked with the period of the rsi.
Here the smoothing amount = 100.
Conclusion
An oscillator based on the recently posted Grover Llorens activator has been proposed. The oscillator aim to maximize the visualization of cycles.
Maximizing the visualization of cycles don't comes with no cost, the indicator output can be uncorrelated with the actual cycles or can return cycles that are not present in the price. Other problems arises from the indicator settings, because cycles are of a time-varying periods it isn't optimal to use fixed length oscillators for their estimation.
Thanks for reading !
If my work has ever been of use to you you can donate, addresses on my signature :)
Grover Llorens Activator [alexgrover & Lucía Llorens] Trailing stops play a key role in technical analysis and are extremely popular trend following indicators. Their main strength lie in their ability to minimize whipsaws while conserving a decent reactivity, the most popular ones include the Supertrend, Parabolic SAR and Gann Hilo activator. However, and like many indicators, most trailing stops assume an infinitely long trend, which penalize their ability to provide early exit points, this isn't the case of the parabolic SAR who take this into account and thus converge toward the price at an increasing speed the longer a trend last.
Today a similar indicator is proposed. From an original idea of alexgrover & Lucía Llorens who wanted to revisit the classic parabolic SAR indicator, the Llorens activator aim to converge toward the price the longer a trend persist, thus allowing for potential early and accurate exit points. The code make use of the idea behind the price curve channel that you can find here :
I tried to make the code as concise as possible.
The Indicator
The indicator posses 2 user settings, length and mult , length control the rate of convergence of the indicator, with higher values of length making the indicator output converge more slowly toward the price. Mult is also related with the rate of convergence, basically once the price cross the trailing stop its value will become equal to the previous trailing stop value plus/minus mult*atr depending on the previous trailing stop value, therefore higher values of mult will require more time for the trailing stop to reach the closing price, use higher values of mult if you want to avoid potential whipsaws.
Above the indicator with slow convergence time (high length) and low mult.
Points with early exit points are highlighted.
Usage For Oscillators
The difference between the closing price and an overlay indicator can provide an oscillator with characteristics depending on the indicators used for differencing, Lucía Llorens stated that we should find indicators for differencing that highlight the cycles in the price, in other terms : Price - Signal , where we want to find Signal such that we maximize the visibility of the cycles, it can be demonstrated that in the case where the closing price is an additive model : Trend + Cycles + Noise , the zero lag estimation of the Trend component can allow for the conservation of the cycle and noise component, that is : Price - Estimate(Trend) , for example the difference between the price and moving average isn't optimal because of the moving average lag, instead the use of zero lag moving averages is more suitable, however the proposed indicator allow for a surprisingly good representation of the cycles when using differencing.
The normalization of this oscillator (via the RSI) allow to make the peak amplitude of the cycles more constant. Note however that such method can return an output with a sign inverse to the one of the original cycle component.
Conclusion
We proposed an indicator which share the logic of the SAR indicator, that is using convergence toward the price in order to provide early exit points detection. We have seen that this indicator can be used to highlight cycles when used for differencing and i don't exclude publishing more indicators based on this method.
Lucía Llorens has been a great person to work with, and provided enormous feedback and support while i was coding the indicator, this is why i include her in the indicator name as well as copyright notice. I hope we can make more indicators togethers in the future.
(altho i was against using buy/sells labels xD !)
Thanks for reading !
Combo Backtest 123 Reversal & D_DSP (Detrended Synthetic Price) This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
Detrended Synthetic Price is a function that is in phase with the
dominant cycle of real price data. This DSP is computed by subtracting
a half-cycle exponential moving average (EMA) from the quarter cycle
exponential moving average.
See "MESA and Trading Market Cycles" by John Ehlers pages 64 - 70.
WARNING:
- For purpose educate only
- This script to change bars colors.
3 EMA & SMA (Market Cycle)Simple Indicator based on 3 Simple and 3 Exponential Moving Averages. Used to indicate Market Cycles.
Definition of Bull Market: 10 SMA is above 21 EMA . 30 SMA slope is up. 55 EMA is trending above 200 EMA .
Definition of Bear Market: 10 SMA is below 21 EMA . 30 SMA slope is down. 55 EMA is trending below 200 EMA .
[Maco] PUELL MULTIPLEReverse formulated what the closed source version is and releasing open source publicly to give back to the community.
If you have any questions feel free to join our Discord!
Simple CycleIntroduction
A simple and really clean cycle oscillator, in fact its quite precise even if the script use recursion which can sometime produce totally uncorrelated results.
On The Code
The calculations start with a who is a smoothing/averaging constant. Then comes src who is the input and is defined as the sum of the closing price with the output, then the output is high-pass filtered in b , after that the output is just the weighted average of the input change with b .
All those recursions and detrending steps make the indicator able to highlights cycles.
Morphed Sine WaveIntroduction
If you rescale a sine wave to the price you will need to correlate it with it in order to show good results, today i present a different method that does not involve correlation to "morph" a sine wave to the price in order to provide forecast's and highlight market periodic patterns.
Parameters
length control the period of the sine wave, power control the "morphing" amount, if you see for example that the results are going nuts try to increase power , if the results are just the price and the delayed price try to decrease power .
power = 1
power = 100
Those settings might be different depending on which market you are in.
Various Uses
You can do a lot of things with this indicator, use filters as source :
Use the indicator as source for oscillators in order to create cycles indicators :
And certainly many more things
Conclusion
I presented a way to morph a sine wave to the price i order to highlight cycles. You can use any function that return a value between -1 and 1 instead of sin , this can be a scaled rsi/stochastic or correlation coefficient, its up to you :)
If you need help don't hesitate to commend or pm me. I hope you will like the indicator and that it will inspire you to make great things.
Thanks for reading !
Dominant Cycle Tuned RsiIntroduction
Adaptive technical indicators are importants in a non stationary market, the ability to adapt to a situation can boost the efficiency of your strategy. A lot of methods have been proposed to make technical indicators "smarters" , from the use of variable smoothing constant for exponential smoothing to artificial intelligence.
The dominant cycle tuned rsi depend on the dominant cycle period of the market, such method allow the rsi to return accurate peaks and valleys levels. This indicator is an estimation of the cycle finder tuned rsi proposed by Lars von Thienen published in Decoding the Hidden Market Rhythm/Fine-tuning technical indicators using the dominant market vibration/2010 using the cycle measurement method described by John F.Ehlers in Cybernetic Analysis for Stocks and Futures .
The following section is for information purpose only, it can be technical so you can skip directly to the The Indicator section.
Frequency Estimation and Maximum Entropy Spectral Analysis
“Looks like rain,” said Tom precipitously.
Tom would have been a great weather forecaster, but market patterns are more complex than weather ones. The ability to measure dominant cycles in a complex signal is hard, also a method able to estimate it really fast add even more challenge to the task. First lets talk about the term dominant cycle , signals can be decomposed in a sum of various sine waves of different frequencies and amplitudes, the dominant cycle is considered to be the frequency of the sine wave with the highest amplitude. In general the highest frequencies are those who form the trend (often called fundamentals) , so detrending is used to eliminate those frequencies in order to keep only mid/mid - highs ones.
A lot of methods have been introduced but not that many target market price, Lars von Thienen proposed a method relying on the following processing chain :
Lars von Thienen Method = Input -> Filtering and Detrending -> Discrete Fourier Transform of the result -> Selection using Bartels statistical test -> Output
Thienen said that his method is better than the one proposed by Elhers. The method from Elhers called MESA was originally developed to interpret seismographic information. This method in short involve the estimation of the phase using low amount of information which divided by 360 return the frequency. At first sight there are no relations with the Maximum entropy spectral estimation proposed by Burg J.P. (1967). Maximum Entropy Spectral Analysis. Proceedings of 37th Meeting, Society of Exploration Geophysics, Oklahoma City.
You may also notice that these methods are plotted in the time domain where more classic method such as : power spectrum, spectrogram or FFT are not. The method from Elhers is the one used to tune our rsi.
The Indicator
Our indicator use the dominant cycle frequency to calculate the period of the rsi thus producing an adaptive rsi . When our adaptive rsi cross under 70, price might start a downtrend, else when our adaptive rsi crossover 30, price might start an uptrend. The alpha parameter is a parameter set to be always lower than 1 and greater than 0. Lower values of alpha minimize the number of detected peaks/valleys while higher ones increase the number of those. 0.07 for alpha seems like a great parameter but it can sometimes need to be changed.
The adaptive indicator can also detect small top/bottoms of small periods
Of course the indicator is subject to failures
At the end it is totally dependent of the dominant cycle estimation, which is still a rough method subject to uncertainty.
Conclusion
Tuning your indicator is a great way to make it adapt to the market, but its also a complex way to do so and i'm not that convinced about the complexity/result ratio. The version using chart background will be published separately.
Feel free to tune your indicators with the estimator from elhers and see if it provide a great enhancement :)
Thanks for reading !
References
for the calculation of the dominant cycle estimator originally from www.davenewberg.com
Decoding the Hidden Market Rhythm (2010) Lars von Thienen
Ehlers , J. F. 2004 . Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading . Wiley
Ehlers Triple Delay-Line DetrenderThis indicator was originally developed by John F. Ehlers (Stocks & Commodities , V.18:7 (July, 2000): "Optimal Detrending").
Mr. Ehlers applied the ideas of the radar systems for the financial time series detrending.
Mr. Ehlers constructed the Triple Delay-Line Canceller first, then smoothed it with the Modified Optimum Elliptic Filter with minimal lag. The smoothed detrended signal is smoothed again with the Modified Optimum Elliptic Filter to obtain signal line.
As result, the crossings of the two indicator lines catch every major cyclic move and the detrender itself can be used as the first step in more sophisticated analyses.
Recursive StochasticThe Self Referencing Stochastic Oscillator
The stochastic oscillator bring values in range of (0,100). This process is called Feature scaling or Unity-Based Normalization
When a function use recursion you can highlights cycles or create smoother results depending on various factors, this is the goal of a recursive stochastic.
For example : k = s(alpha*st+(1-alpha)*nz(k )) where st is the target source.
Using inputs with different scale level can modify the result of the indicator depending on which instrument it is applied, therefore the input must be normalized, here the price is first passed through a stochastic, then this result is used for the recursion.
In order to control the level of the recursion, weights are distributed using the alpha parameter. This parameter is in a range of (0,1), if alpha = 1, then the indicator act as a normal stochastic oscillator, if alpha = 0, then the indicator return na since the initial value for k = 0. The smaller the alpha parameter, the lower the correlation between the price and the indicator, but the indicator will look more periodic.
Comparison
Recursive Stochastic oscillator with alpha = 0.1 and bellow a classic oscillator (alpha = 1)
The use of recursion can both smooth the result and make it more reactive as well.
Filter As Source
It is possible to stabilize the indicator and make it less affected by outliers using a filter as input.
Lower alpha can be used in order to recover some reactivity, this will also lead to more periodic results (which are not inevitably correlated with price)
Hope you enjoy
For any questions/demands feel free to pm me, i would be happy to help you
Bollinger Breaks and Cycles Indicator - JDThe BBC indicator shows price in relation to the upper (in red) and lower (in green) Bollinger Bands
It highlights breaks in the Bands, where the 0-line represents a price equal to the band.
These breaks can either be used as take-profit points or as entry points, depending on trend direction.
Entries can be at the beginning of a break (eg. for impulse or continuation moves)
or at the end (mostly for expected trend reversals)
To find the best setups, the BBC should be accompanied by other indicators (preferably ones that focus on different aspects)
The oscilating line in the middle indicates market cycles
JD.
#NotTradingAdvice #DYOR
RSI Bollinger WaveTrend Cycle Multi Free TSPMulti indicator
Bollinger Band x RSI
Wave Trend
Cycles
Free users will like it :)
Fell free to like share comments... and check my other stuff :]
