Fast v Slow Moving Averages Strategy (Variable) [divonn1994]This is a simple moving average based strategy that takes 2 moving averages, a Fast and a Slow one, plots them both, and then decides to enter a 'long' position or exit it based on whether the two lines have crossed each other. It goes 'long when the Fast Moving Average crosses above the Slow Moving Average. This could indicate upwards momentum in prices in the future. It then exits the position when the the Fast Moving Average crosses back below. This could indicate downwards momentum in prices in the future. This is only speculative, though, but sometimes it can be a very good indicator/strategy to predict future action.
I've tried some strategy settings and I found different promising strategies. Here are a few:
BTCUSD ( BitStamp ) 1 Day Timeframe : EMA, Fast length 25 bars, Slow length 62 bars => 28,792x net profit (default)
BTCUSD ( BitStamp ) 1 Day Timeframe : VWMA, Fast length 21 bars, Slow length 60 bars => 15,603x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : SMA, Fast length 18 bars, Slow length 51 bars => 19,507x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : RMA, Fast length 20 bars, Slow length 52 bars => 5,729x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : WMA, Fast length 29 bars, Slow length 60 bars => 19,869x net profit
Features:
-You can choose your preferred moving average: SMA , EMA , WMA , RMA & VWMA .
-You can change the length average for each moving average
-I made the background color Green when you're currently in a long position and Red when not. I made it so you can see when you'd be actively in a trade or not. The Red and Green background colors can be toggled on/off in order to see other indicators more clearly overlayed in the chart, or if you prefer a cleaner look on your charts.
-I also have a plot of the Fast moving average and Slow moving average together. The Opening moving average is Purple, the Closing moving average is White. White on top is a sign of a potential upswing and purple on top is a sign of a potential downswing. I've made this also able to be toggled on/off.
Let me know if you think I should change anything with my script, I'm always open to constructive criticism so feel free to comment below :)
Search in scripts for "momentum"
Ichimoku Cloud with MACD (By Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
The MACD is a trend following momentum indicator and provides identification of short-term trend direction. In this variation it utilises the 12-period as the fast and 26-period as the slow length EMAs, with signal smoothing set at 9.
This strategy combines the Ichimoku Cloud with the MACD indicator to better enter trades.
Long/Short orders are placed when three basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
MACD line crosses over the signal line
Short Position:
Tenkan-Sen is below the Kijun-Sen
Chikou-Span is below the close of 26 bars ago
Close is below the Kumo Cloud
MACD line crosses under the signal line
The script is backtested from 1 June 2022 and provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
This script also works well on MATIC (1h timeframe), AVA (45m timeframe), and BTC (30m timeframe).
DyorTool PremiumWhat is the DyorTool Suite?
It is a toolkit that helps the trader to trade the market emotionless, under any condition.
This package is made of 3 scripts :
DyorTool Premium
DyorTool Oscillator
DyorTool Dashboard
What indicators are in these scripts?
DyorTool Premium
DyorTool Algo which gives buy and sell signals : 4 setups. The stats shown in the picture is set with a leverage of 0.4 on each trade with the commission of Binance ( without reduction ).
Range : 4 setups
Ribbon : 4 setups
Aggressiv Scalping : Trend Following - low UT : 2 setups
EVWMA : 4 setups
Ping Pong scalping : 4 setups
Support Line : 4 setups
DyorTool Oscillator
DyorTool RSI : 8 setups
DyorTool Oscillator : 8 setups
Smart candle color : Filter noise of the market
DyorTool Dashboard
Allows the user to feel the market sentiment with a custom candle
Measure the volatility of the market
Show DyorTool Algo trend
Show the momentum trend and measure his evolution.
Smart Stop Loss and Leverage calculation in order to not get in a trade if you are late, or to protect your capital.
All these indicators allow users to :
Trade the market easier, within a clearly defined framework - range.
Detect macro trend and the nearby momentum
Get early in a trade by entering in a trade with one of the 42 setups explained.
Have realistic target profit
Protect your capital with a smart stop loss and calculate the leverage for a defined stop loss
Detect if the market is with or against you so you are not holding more than you should.
This package is unique in its kind and it is complete. You can either do scalping or day-trading with it.
There are many different indicators in it. And a formation is given to explain in detail each indicator. This formation is easy to understand.
As you saw, each indicator has its own setups. These setups are explained one by one, under what condition you can enter in a trade, how to do it, where to exit, what to understand about the market next.
There is no interpretation possible. You are either in a setup or in a waiting zone.
These indicators are self-sufficient. You don't have to use all of them, and not at the same time. You use the ones which fit you better.
Close v Open Moving Averages Strategy (Variable) [divonn1994]This is a simple moving average based strategy that works well with a few different coin pairings. It takes the moving average 'opening' price and plots it, then takes the moving average 'closing' price and plots it, and then decides to enter a 'long' position or exit it based on whether the two lines have crossed each other. The reasoning is that it 'enters' a position when the average closing price is increasing. This could indicate upwards momentum in prices in the future. It then exits the position when the average closing price is decreasing. This could indicate downwards momentum in prices in the future. This is only speculative, though, but sometimes it can be a very good indicator/strategy to predict future action.
What I've found is that there are a lot of coins that respond very well when the appropriate combination of: 1) type of moving average is chosen (EMA, SMA, RMA, WMA or VWMA) & 2) number of previous bars averaged (typically 10 - 250 bars) are chosen.
Depending on the coin.. each combination of MA and Number of Bars averaged can have completely different levels of success.
Example of Usage:
An example would be that the VWMA works well for BTCUSD (BitStamp), but it has different successfulness based on the time frame. For the 12 hour bar timeframe, with the 66 bar average with the VWMA I found the most success. The next best successful combo I've found is for the 1 Day bar timeframe with the 35 bar average with the VWMA.. They both have a moving average that records about a month, but each have a different successfulness. Below are a few pair combos I think are noticeable because of the net profit, but there are also have a lot of potential coins with different combos:
It's interesting to see the strategy tester change as you change the settings. The below pairs are just some of the most interesting examples I've found, but there might be other combos I haven't even tried on different coin pairs..
Some strategy settings:
BTCUSD (BitStamp) 12 Hr Timeframe : 66 bars, VWMA=> 10,387x net profit
BTCUSD (BitStamp) 1 Day Timeframe : 35 bars, VWMA=> 7,805x net profit
BNBUSD (Binance) 12 Hr Timeframe : 27 bars, VWMA => 15,484x net profit
ETHUSD (BitStamp) 16 Hr Timeframe : 60 bars, SMA => 5,498x net profit
XRPUSD (BitStamp) 16 Hr Timeframe : 33 bars, SMA => 10,178x net profit
I only chose these coin/combos because of their insane net profit factors. There are far more coins with lower net profits but more reliable trade histories.
Also, usually when I want to see which of these strategies might work for a coin pairing I will check between the different Moving Average types, for example the EMA or the SMA, then I also check between the moving average lengths (the number of bars calculated) to see which is most profitable over time.
Features:
-You can choose your preferred moving average: SMA, EMA, WMA, RMA & VWMA.
-You can also adjust the previous number of calculated bars for each moving average.
-I made the background color Green when you're currently in a long position and Red when not. I made it so you can see when you'd be actively in a trade or not. The Red and Green background colors can be toggled on/off in order to see other indicators more clearly overlayed in the chart, or if you prefer a cleaner look on your charts.
-I also have a plot of the Open moving average and Close moving average together. The Opening moving average is Purple, the Closing moving average is White. White on top is a sign of a potential upswing and purple on top is a sign of a potential downswing. I've made this also able to be toggled on/off.
Please, comment interesting pairs below that you've found for everyone :) thank you!
I will post more pairs with my favorite settings as well. I'll also be considering the quality of the trades.. for example: net profit, total trades, percent profitable, profit factor, trade window and max drawdown.
*if anyone can figure out how to change the date range, I woul really appreciate the help. It confuses me -_- *
Bollinger Bands and RSI Short Selling (by Coinrule)The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus provide the best time for buying and selling it.
The relative strength index ( RSI ) is a momentum indicator used in technical analysis . RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
The short order is placed on assets that present strong momentum when it's more likely that it is about to decrease further. The rule strategy places and closes the order when the following conditions are met:
ENTRY
The closing price is greater than the upper standard deviation of the Bollinger Bands
The RSI is less than 70
EXIT
The trade is closed in profit when the RSI is less than 70
Upper standard deviation of the Bollinger Band is greater than the the closing price.
This strategy comes with a stop loss and a take profit, and as you can see by the results, it is well suited for a bear market.
This trade works very well with ETH (1h timeframe), AVA (4h timeframe), and SOL (3h timeframe) and is backtested from the 1 December 2021 to capture how this strategy would perform in a bear market.
To make the results more realistic, the strategy assumes each order to trade 30% of the available capital. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange.
STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones BT [Loxx]STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones BT is the backtest strategy for "STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones " seen below:
Included:
This backtest uses a special implementation of ATR and ATR smoothing called "True Range Double" which is a range calculation that accounts for volatility skew.
You can set the backtest to 1-2 take profits with stop-loss
Signals can't exit on the same candle as the entry, this is coded in a way for 1-candle delay post entry
This should be coupled with the INDICATOR version linked above for the alerts and signals. Strategies won't paint the signal "L" or "S" until the entry actually happens, but indicators allow this, which is repainting on current candle, but this is an FYI if you want to get serious with Pinescript algorithmic botting
You can restrict the backtest by dates
It is advised that you understand what Heikin-Ashi candles do to strategies, the default settings for this backtest is NON Heikin-Ashi candles but you have the ability to change that in the source selection
This is a mathematically heavy, heavy-lifting strategy with multi-layered adaptivity. Make sure you do your own research so you understand what is happening here. This can be used as its own trading system without any other oscillators, moving average baselines, or volatility/momentum confirmation indicators.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
What is R-squared Adaptive?
One tool available in forecasting the trendiness of the breakout is the coefficient of determination ( R-squared ), a statistical measurement.
The R-squared indicates linear strength between the security's price (the Y - axis) and time (the X - axis). The R-squared is the percentage of squared error that the linear regression can eliminate if it were used as the predictor instead of the mean value. If the R-squared were 0.99, then the linear regression would eliminate 99% of the error for prediction versus predicting closing prices using a simple moving average .
R-squared is used here to derive a T3 factor used to modify price before passing price through a six-pole non-linear Kalman filter.
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
Signals
Alerts
Loxx's Expanded Source Types
CAPTAIN ALTS VVMTCaptain Alts VVMT indicator provides signals and trend based on vlume , volatility , momentum and Trend
For volume it used on balance volume , Chaikin Moneey flow , vwap and candle pattern status
for Momentum it use ATR , S&R , RVI AND bOLLINGER BAND
Use 5min and 15min timeframe for scalping , The cap line change its colour according to the trend if it reds it means market is getting bearish if blue means market is turning bullish
Inverse MACD + DMI Scalping with Volatility Stop (By Coinrule)This script is focused on shorting during downtrends and utilises two strength based indicators to provide confluence that the start of a short-term downtrend has occurred - catching the opportunity as soon as possible.
This script can work well on coins you are planning to hodl for long-term and works especially well whilst using an automated bot that can execute your trades for you. It allows you to hedge your investment by allocating a % of your coins to trade with, whilst not risking your entire holding. This mitigates unrealised losses from hodling as it provides additional cash from the profits made. You can then choose to hodl this cash, or use it to reinvest when the market reaches attractive buying levels.
Alternatively, you can use this when trading contracts on futures markets where there is no need to already own the underlying asset prior to shorting it.
ENTRY
The trading system uses the Momentum Average Convergence Divergence (MACD) indicator and the Directional Movement Index (DMI) indicator to confirm when the best time is for selling. Combining these two indicators prevents trading during uptrends and reduces the likelihood of getting stuck in a market with low volatility.
The MACD is a trend following momentum indicator and provides identification of short-term trend direction. In this variation it utilises the 12-period as the fast and 26-period as the slow length EMAs, with signal smoothing set at 9.
The DMI indicates what way price is trending and compares prior lows and highs with two lines drawn between each - the positive directional movement line (+DI) and the negative directional movement line (-DI). The trend can be interpreted by comparing the two lines and what line is greater. When the negative DMI is greater than the positive DMI, there are more chances that the asset is trading in a sustained downtrend, and vice versa.
The system will enter trades when two conditions are met:
1) The MACD histogram turns bearish.
2) When the negative DMI is greater than the positive DMI.
EXIT
The strategy comes with a fixed take profit combined with a volatility stop, which acts as a trailing stop to adapt to the trend's strength. Depending on your long-term confidence in the asset, you can edit the fixed take profit to be more conservative or aggressive.
The position is closed when:
Take-Profit Exit: +8% price decrease from entry price.
OR
Stop-Loss Exit: Price crosses above the volatility stop.
In general, this approach suits medium to long term strategies. The backtesting for this strategy begins on 1 April 2022 to 18 July 2022 in order to demonstrate its results in a bear market. Back testing it further from the beginning of 2022 onwards further also produces good returns.
Pairs that produce very strong results include SOLUSDT on the 45m timeframe, MATICUSDT on the 2h timeframe, and AVAUSDT on the 1h timeframe. Generally, the back testing suggests that it works best on the 45m/1h timeframe across most pairs.
A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Strategy: Combo Z ScoreStrategy version of Combo Z Score
Objective:
Can we use both VIX and MOVE relationships to indicate movement in the SPY? VIX (forward contract on SPY options) correlations are quite common as forward indicators however MOVE (forward contract on bonds) also provides a slightly different level of insight
Using the Z-Score of VIX vs VVIX and MOVE vs inverted VIX (there is no M of Move so we use inverted Vix as a proxy) we get some helpful indications of potential future moves. Added %B to give us some exposure to momentum. Toggle VIX or MOVE.
If anyone has a better idea of inverted Vix to proxy forward interest in MOVE let me know.
Noticeable delta is that Vix only approach over the back test period is slightly better. Questions would be, what is the structure and nature of the market over the test period and in a bear market would MOVE or combined perform better.
Cycle strategy DEMO V1.0READ BEFORE USING:
This indicator includes the Cycle strategy and 2 bonus indicators ( pivot strategy & volume strategy). This is a DEMO version that doesn't show the signals after end of January 2022. This indicator only allows you the backtest/study previous results and give a general idea on the workings on the indicator.
Introduction
Cycle strategy works on the following timeframes, 1HR, 4HR, 12HR and 1D. Cycle strategy is mostly used by me on the 1D timeframe, however, if you prefer shorter timeframes you can select those. Indicator settings will automatically adjust based off the timeframe on your chart. I use this indicator mainly for BTC , however, altcoins such as ETH, LTC, DOGE, ADA, ETC, SOL and more have shown reasonable results in the past.
The theory behind cycle strategy
The cycle strategy is based off the theory that Bitcoin moves in cycles, each time followed by periods of sideways action. This strategy tries to breakout trade momentum out of a sideways range by calculating things such as momentum, volatility and average price. The indicators, based off calculations, tries to spot breakout trends. When a trend break up it gives a "long" signal on the chart and when the trend breaks down it gives a "short" signal.
Sometimes the price doesn't break out, this is called a fakeout. The bot will automatically reverse its previous signal and take a small loss.
Applications of it in my trading setup
I apply the wave strategy in my own trading enviroment as a tool to determine buy/sell moments and general trend.
Whenever Bitcoin reaches extreme overbought level I'll wait for the indicator to give me a "sell" signal in order to hedge myself against possible corrections. In the past I've seen many bearmarkets before, I tended to not have any fiat on the side to buy these dips. The indicator has be allowed in the past to almost perfectly sell the top multiple times allowing me to accumulate BTC on lower levels and therefor increase my BTC position. I also use this indicator to spot the current Bitcoin trend. If the indicator shows a "long" signal I'll generally be looking to long on dips and whenever there is a "sell" signal I tend to look for shorts.
Bonus indicators
There are 2 bonus indicators included in this strategy. These are "bonus" indicators as I haven't had a long enough time to backtest them. They are based off my own strategies that I apply when trading. The bonus indicators have been highly succesful in the past though they are a bit more experimental.
Bonus indicator 1: Pivot strategy
Pivot points is a powerful indicator that Bitcoin tends to be very reactive to. The pivot strategy tries to determine if Bitcoin is in a bulltrend/beartrend. If Bitcoin is inside a bulltrend it will look to buy on pivot points . If the price is in a beartend it'll be looking to sell on pivot points .
Pivot strategy only works on 1HR timeframe, optimized on BYBIT:BTCUSD
Bonus indicator 2: Volume strategy
Volume strategy tries to look for large spikes of volume , once price breaks under this volume spike it'll try to buy/sell. The theory is that large volume spikes are traders getting stopped out on their leverage positions. By buying under these spikes it tries to counter trade these small price sqeeuzes.
Volume strategy only works on 1HR timeframe, only works on BYBIT:USD
Trend Follower Strategy v2 [divonn1994]The Trend Follower Strategy that I made classifies red and green candles into tiny, small, and big sizes and will send buy or sell signals depending on if the candle is classified as "big" so you get into and out of a position when there is a big candle. Out during a big green candle to take profit. Out during a big red candle in case the market is turning down. It also won't enter a position unless there is positive EMA momentum.
For the chart there is a Buy and a Sell signal. Buy = 1, Sell = 0, and when the value crosses above or below 0.5 it will trigger a long position or close the long position. The graph isn't necessary to the strategy, but can help with visualizing the trade patterns in the past if you like.
This strategy works best so far with these coins at time of posting (March 4th, 2022):
KCSUSDT (621x profit), HTUSDT (45x profit), LUNAUSDT (45x profit), BNBBTC (1553x profit), ETHBTC (219x profit), KCSBTC (1222x profit), LUNABTC (83x profit), FTMBTC (52x profit).
It can work with other pairings, but I personally like these pairings best. I didn't test it with coins outside of the top 100 coins by market cap. Use it however you want.
Works best on 1 Day charts.
The strategy would rather be in the market than out. It gets out when it see's a red flag, but can immediately go back in in the next bar if the red flags are all gone. So it makes a lot of trades.
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Update: This is the same strategy I uploaded before but I made the code Open for anyone to check it out and so it has a similar description as the previous version. Let me know what you think. I'd remove the old version if I could, but I guess it's site policy to not be able to remove scripts that have been uploaded.
Trend Follower Strategy [divonn1994]The Trend Follower Strategy that I made classifies red and green candles into tiny, small, and big sizes and will send buy or sell signals depending on if the candle is classified as "big" so you get into and out of a position when there is a big candle. Out during a big green candle to take profit. Out during a big red candle in case the market is turning down. It also won't enter a position unless there is positive EMA momentum.
For the chart there is a Buy and a Sell signal. Buy = 1, Sell = 0, and when the value crosses above or below 0.5 it will trigger a long position or close the long postion. The graph isn't necessary to the strategy, but can help with visualizing the trade patterns in the past if you like.
This strategy works best so far with BNBUSDT, ETHUSDT, KCSUSDT, HTUSDT, BNBUSDT, BNBBTC, ETHBTC, KCSBTC, LUNABTC, SOLBTC, ADABTC, SANDBTC, HNTBTC, KDABTC.
It can work with other pairings, but these have the healthiest charts in my opinion, as in, the profit factor is high and is greater than a simple buy and hold strategy, and the largest drawdown isn't very high.
Works best on 1 Day charts.
Crypto Spot Market Bot | BacktestHello Friends.
This script is only for long positions.
How does the algorithm work ?
The Relative Momentum Index
Relative Strength İndex
Average Directional Movement İndex
Momentum
When rsi and adx produce signals in the same direction, the rmi indicator confirms the signal. After the Confirmed Signal, the buy-side transaction is entered , the closed according to the % of profit taking and stoploss specified on the algorithm in the entered transaction.
In the spot market, it is possible to make money even in a down trend
All shared charts run within a 1-hour time frame.
Note : The shared backtest results have been shared as of 9/9/2021 by calculating 50% balance and 2 pyramiding methods in an account of 1000 dollars. Keep in mind that this algorithm will want to try to average down in possible worst-case scenarios. 2% - %3take profit levels will provide consecutive gains in the spot market.
How should the adjustments be made?
Value variables should be made according to formula a and formula b values and backtest results. You can increase the frequency of transactions by lowering the adx and rsi values.
Overview :
Combo 2/20 EMA & Absolute Price Oscillator (APO) This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
The Absolute Price Oscillator displays the difference between two exponential
moving averages of a security's price and is expressed as an absolute value.
How this indicator works
APO crossing above zero is considered bullish, while crossing below zero is bearish.
A positive indicator value indicates an upward movement, while negative readings
signal a downward trend.
Divergences form when a new high or low in price is not confirmed by the Absolute Price
Oscillator (APO). A bullish divergence forms when price make a lower low, but the APO
forms a higher low. This indicates less downward momentum that could foreshadow a bullish
reversal. A bearish divergence forms when price makes a higher high, but the APO forms a
lower high. This shows less upward momentum that could foreshadow a bearish reversal.
WARNING:
- For purpose educate only
- This script to change bars colors.
SPXL Futures Strategy- Buy/sell signals for SPXL using futures momentum.
- For real-time signals at close, use ES1! on 2 minute chart and sign up for real-time cboe mini futures data feed in tradingview.
- All buys and sells are at near close of US RTH market at 4pm.
- Best to use the script with other breadth signals to decide on trading strategy.
- Script is compatible with SPY, SPXL, RSP, QQQ, TQQQ and many other SPX correlated tickers, however it’s primarily developed for SPX.
Eternal BTC Strategy - 2This is a summary of how this strategy works.
- Momentum, Volatility detection:
1. First of all detects market momentum
2. Uses volume indicators to make sure of the movement existence
- Trade execution:
3. Uses crossovers of some MAs
4. After crossovers, waits for trend analysis indicators signals to trigger the order
- Take profit & Stop loss:
5. Calculates SL and TP using a formula (combined of volume , MAs and others)
* This is just a simple representation of how this strategy works, It's coded in about a 2000 lines script.
This strategy works best on Bitcoin / TetherUS • BINANCE
No setting is needed to be applied by you, you'll just simply add the script and receive alarms.
Alarms are included opening of the trade, TP and SL touch.
BTC Strategy - EternalThis is a summary of how this strategy works.
- Momentum, Volatility detection:
1. First of all detects market momentum
2. Uses volume indicators to make sure of the movement existence
- Trade execution:
3. Uses crossovers of some MAs
4. After crossovers, waits for trend analysis indicators signals to trigger the order
- Take profit & Stop loss:
5. Calculates SL and TP using a formula (combined of volume , MAs and others)
* This is just a simple representation of how this strategy works, It's coded in about a 2000 lines script.
As you can see, it has a great performance, 71.59% win rate in 989 trades so it's a very confident result.
This strategy works best on Bitcoin / TetherUS • BINANCE
No setting is needed to be applied by you, you'll just simply add the script and receive alarms.
Alarms are included opening of the trade, TP and SL touch.
Bollinger band & Volume based strategy V2this script is upgraded version of previous one the major change is deleted script which find a highest price after entry the last of strategy is same.
If current volume is above daily average volume, and three bollinger band`s Standard Deviation, 1 and 1.5 and 2 if the current lowest price is bigger then 1 stdev and current closed is bigger then 1.5 stdev and the last,highest price is above 2.0 stdev, it defined current market is bullish and had momentum.
and the Short will entered when ma60 and ma120 is undercrossed it work as prevent current price is way lower then entry price.
**this script is working in 15min Only in BTC market or USDT**
** basic equity setting is 500$, set your own**
**if you will use this in real-trade,plz comment the result to me**
Ps: i wanna know why my script is only working well in 15 min tick, anyone who has similar phenomenon or if you had a answer about it, please comment me.
OnePunch Algo KITEIntroducing One of OnePunch ALGO Flagship plugin. In this plugin it comes with a in-built risk management system plus it allows users stop loss input per trade. This can be used with Cryptocurrency and Stocks equally.
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########## User Guide ###########
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OnePunch ALGO KITE should be used with 30min or upper time limits, this is built for long term trading strategies. Make sure once you pick a crypto or stock to trade, check its backtest data: which can be found at Strategy Tester. A good strategy should always out perform the Buy & Hold for a given timeframe.
Best Bar Time: 45m
Other Options
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Short Term/Day Trading Setup
For Short Term or Day Trade: 5min, 15min & 30min candlesticks
Mid Term Trading Setup
For Mid-term traders: 45m, 1hr, 2hr, and 3hr setup works really well.
For Long Term Trading Setup
For long term traders: 4hr, 1D, 1Week and 1Month Setup works well.
* Best timeframe should beat buy and hold for a given timeline.
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####### How Strategy Work ########
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Strategy use multiple signals and technical data. Including and not limited to Simple Moving Averages, Volume , & Trends. In this chart, we picked Polkadot (DOTUSD) crypto coin as an example with an initial capital of $1k. We have also added a slippage of 1 just to be on the safe side and a commission rate of 0.01% (Commission rates depends of your broker).
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######## Built with Inputs #########
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Date Pick: User can backtest the plugin with exact date you want from to till. For an example, you can check date from 01 / 01 /2020 (Default setting date) till day, and compare apple to apple results with other stocks. This is mostly used to check if another stock/crypto do better than the other compared to a given timeframe.
Risk Management per Trade: This also allows users to put their own risk management loss percentage. In default it is set to 100%. This allows user to see in the long run, if this provide better results with or without a stop loss.
Commission Rates: User can update commission rates according to their broker's fees
Slippage: To be more conservative about the entry and exit of a trade, user can input any slippage amount
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#### How to Detect BUY Signals #####
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When a teal color BUY signal is given, it is a BUY. This signal basically happen when a stock land in a high volatility zone. We use in-build systems such as MA , Support and Resistance and Trends to come up with the Buy Signal. Algorithm make a market order when the criteria's are met and algorithm exit if this turns out to be a bluff bullish signal.
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#### How to Detect SELL Signals #####
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When a maroon color SELL signal is given, it is a SELL happen when a momentum changed in a bearish downtrend. Sell happen when a momentum changed in a bearish downtrend. We use moving averages and trend analysis to identify downtrends. Algorithm make a market order when the criteria's are met. There is a in-built risk management that make an exit order when a bullish alert turns out to be a bluff.
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#### Bullish and Bearish Signals #####
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When a silver color Bearish signal is given, it is a BEARISH trend alert. It's up to the user to decide what to do when this alert is given. (Note: Backtest data only shows Buy and Sell Signal market orders results, it does not account bearish alerts), a Bearish signal given when the stock/crypto is overbought in multiple technical indicators.
When a sea blue Bullish trend signaled. (Mind this sea blue color signal will not be calculated in the backtest, it is up to the users to decide what to do with this bullish signal) - This signal happen when a stock is oversold in multiple technical indicators.
DISCLAIMER: Stocks and options trading involves substantial RISK of LOSS and is NOT suitable for every investor. The valuation of stocks and options may fluctuate, and, as a result, clients may lose more than their original investment. If the market moves against you, you may sustain a total loss greater than the amount you deposited into your account. You are responsible for all the risks and financial resources you use and for the chosen trading system. You should not engage in trading unless you fully understand the nature of the transactions you are entering into and the extent of your exposure to loss. If you do not fully understand these risks, you must seek independent advice from your financial advisor.
All trading strategies are used at your own risk. And OnePunch ALGO Developer does NOT take any responsibility for your losses using any of the advice or suggestions or strategies are shown/said in any of OnePunch ALGO publications.
Hophop Reversion Strategy
█ OVERVIEW
Mean reversion is a financial term assuming that an asset's price will tend to converge to the average price over time.
Due to the trending nature of the crypto markets, mean reversion on a high timeframe could be pretty dangerous. When it comes to running mean reversion strategy on low timeframe, commission and slippage may cost more than strategy gains.
In this strategy, I tried to achieve being conservative in the trending market while avoiding trades if necessary and trading high probability reversion opportunities .
█ CONCEPTS
Strategy is build based on the combination of the momentum and the historical / implied volatility; when the price exceeds the potential volatility range, the strategy places the orders, and the target point is the mean of the expected range high and range low.
The range low and high lines displayed on the chart shows where to short or long, to make sure that the orders are limit orders; orders are placed 0.5% above/below the ranges!
Key information about the strategy
• All the orders are limit entry
• 0.02% commission is included in the backtest
• 30 ticks set for Verify Price Limit for Orders
• 30 ticks set for Slippage
• Initial version does not include the money management and hard stops hence you need to be extra cautious in trending markets
• Restricted to be used for BTC and ETH for 15 min timeframe
█ Ozet
Ortalamaya dönme, bir varlığın fiyatının zaman içinde ortalama fiyata yakınsama eğiliminde olacağını varsayan bir finansal terimdir.
Kripto piyasalarının trend egilimli doğası nedeniyle, yüksek zaman diliminde ortalamaya dönüş oldukça tehlikeli olabilir.
Ortalama geri dönüş stratejisini düşük zaman diliminde calistirmak söz konusu olduğunda, komisyon ve kayma, strateji kazanımlarından daha pahalıya mal olabilir.
Bu stratejide, gerektiğinde alım satımlardan kaçınırken ve yüksek olasılıklı ortalamaya dönüş fırsatlarını degerlendiren, trend olan piyasada ise isleme girerken temkinli olmasi uzerine calistim
█ Aciklama
Strateji, momentum ve tarihsel / zımni oynaklığın birleşimine dayalı olarak inşa edilmistir; fiyat potansiyel oynaklık aralığını aştığında, strateji emirleri verir ve hedef nokta, beklenen yüksek aralığın ve düşük aralığın ortalamasıdır.
Grafikte görüntülenen aralık alt ve üst satırları,
Stratejiye ait onemli bilgiler/b]
• Tüm emirler limit emirdir girişlidir
• Backtest performansinda %0.02 komisyon dahildir
• Limit Emir fiyat dogrulamasi icin 30 tick bekleme kullanilmistir
• Slippage için 30 tick bekleme kullanilmistir
• İlk sürüm para yönetimini ve stoploss içermez, bu nedenle trend olan piyasalarda ekstra dikkatli olmanız gerekir.
• 15 dakikalık zaman dilimi ile BTC ve ETH için kullanımla sınırlıdır
Emirlerin limit emir olduğundan emin olmak için nerede short veya long isleme girilecegini gosteren cizgilerin %0.5 üstünde/altında verilir!
Multi timeframe RSI StrategyMulti Time Frame RSI is based on Concept of capturing Higher Time frame Momentum. Generally Higher TF Trends are more reliable and long
This strategy get the Monthly Weekly Daily and Current Time frame RSI and then trade on lower time frame taking as base of Higher TF
For Monthly, Weekly and Daily TF => RSI is set to = 40
for Lower TF => Upper RSI is = 65 Lower RSI is = 45
Trading Logic
Long = Current RSI > ( upper RSI and Monthly, Weekly and Daily TF RSI )
Short = Current RSI < ( Lower RSI and Monthly, Weekly and Daily TF RSI )
Brokerages Set to = 0.03%
Risk Mgmt=> Per trade risk = 5000 Rs
Alert=> alert are coded once you schedule TV alert, following singnal will get generated at current TF Candle close
Long = LE,
Close Long = LX
Short = SE,
Close Short= SX
For Bank Nifty = 1 hrs TF is preffered and Nifty = 15 Min TF
AT_MR-15m-ALGO Strategy IndicatorsThis strategy includes systems based on the return-to-mean method.
It creates BUY-SELL signals by getting approval from volatility, trend, momentum, volume, incompatibility and artificial intelligence formations in the system.
Unaffected by Pump and Dump (extreme spikes and dips). In some cases, it can turn this into an opportunity.
Our loss rates in transactions are minimized by algorithms. In other words, it has minimized the loss rates in the position with the stop loss systems and artificial intelligence in it.
IMPORTANT NOTE:
1-) In order for our indicator to be used efficiently, it is necessary to optimize its parameters on a monthly basis. It is offered to you by optimizing regularly by our technical team every month so that it can work efficiently in variable market conditions. Non-optimized systems do not work efficiently in new market conditions.
2-) Strategy should definitely be used on 15-minute charts. Otherwise, it will lead to losses!!!
Turkish Information:
Bu strateji ortalamaya geri dönüş metodu üzerine kurulmuş sistemleri içerir.
Sistem içerisindeki volatilite, trend, momentum, hacim, uyumsuzluk ve yapay zeka formasyonlarından onay alarak AL-SAT sinyallerini oluşturur.
Pump ve Dump(aşırı ani yükselişler ve düşüşler) durumlarından etkilenmez. Bazı durumlarda bunu fırsata çevirebilir.
İşlemlerdeki zarar oranlarımız algoritmalar tarafından minimize edilir. Yani, içerisinde bulunan zarar durdurma sistemleri ve yapay zeka ile pozisyondaki zarar oranlarını minimuma indirmiştir.
ÖNEMLİ NOT:
1-) İndikatörümüzün verimli bir şekilde kullanılabilmesi için her ay düzenli bir şekilde parametrelerinin optimizasyonunun yapılması gerekiyor. Değişken piyasa koşularında verimli çalışabilmesi için her ay düzenli olarak teknik ekibimiz tarafından optimizasyonu yapılarak sizlere sunulmaktadır. Optimize olmayan sistemler yeni piyasa koşullarında verimli çalışmazlar.
2-) Strateji kesinlikle 15 dakikalık grafiklerde kullanılmalıdır. Aksi taktirde kayıplara yol açacaktır!!!
[VJ]Phoenix Force of PSAR +MACD +RSIThis is a simple intraday strategy for working on Stocks or commodities based out on PSAR, MACD , RSI and chop index . You can modify the start time and end time based on your timezones. Session value should be from market start to the time you want to square-off
Important: The end time should be at least 2 minutes before the intraday square-off time set by your broker
Comment below if you get good returns
Strategy: Entry Exits using PSAR and momentum and trend using MACD and RSI. A chop index is used as filtering
Indicators used :
Parabolic SAR is a technical indicator that is used to determine the price direction of stocks and it also draws attention to the traders when the price is changing
PSAR helps you:
Identify when a certain price trend is going to change direction
Indicate the most effective level at which to enter into the trade
Indicate the most effective exit point for the trade
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security's price. ... Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line
RSI is intended to chart the current and historical strength or weakness of a stock or market based on the closing prices of a recent trading period.
Buying/Selling
When trading with the parabolic SAR, you would buy a market when the dots move below the current asset price and are green in colour. Alternatively, you would sell a market when the dots move above the current asset price and are red in colour. We use MACD , RSI to ensure that a right trade is picked when PSAR gives an indication. CI is used to stay away from the range bound market as much as possible.
Usage & Best setting :
Choose a good volatile stock and a time frame - 5m.
MA length : 200
RSI threshold : 50
MACD: 12,26,9
There is stop loss and take profit that can be used to optimise your trade
The template also includes daily square off based on your time.
Kwan NRP Backtest To calculate the coordinates in which the kink of the line will cross,
the standard Forex instruments are used - Relative Strenght Index, Stochastic and Momentum.
It is very easy to optimize them for the existing trading strategy: they all have very
flexible and easily customizable parameters. Signals to enter the market can be 2 situations:
Change of color of the indicator line from red to blue. At the same time, it is worth entering into the purchase;
Change of color of the indicator line from blue to red. In this case, it is worth entering for sale.
The signals are extremely clear and can be used in practice even by beginners. The indicator
itself shows when to make deals: the user only has to accompany them and set the values
of Take Profit and Stop Loss. As a rule, the signal to complete trading is the approach of
the indicator level to the levels of the maximum or minimum of the previous time period.
