Ichimoku Cloud and Bollinger Bands (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 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 providing the best time for buying and selling it.
This strategy combines the Ichimoku Cloud with Bollinger Bands to better enter trades.
Long orders are placed when these 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
The closing price is greater than the upper standard deviation of the Bollinger Bands
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
The upper standard deviation of the Bollinger Band is greater than the closing price
The script is backtested from 1 January 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 BTC 30m/1h, ETH 2h, MATIC 2h/30m, AVAX 1h/2h, SOL 45m timeframes
Cari skrip untuk "bitcoin"
[Crypto] Supertrend - ADX - Reversal Candle* Commission: 0.06% = Binance future fee.
1. ADX INDICATOR: 1h & 4h timeframe have a strong strength for open trade.
- ADX smoothing: 14.
- DI length: 14.
- ADX STRONG > 25.
2. SUPERTREND INDICATOR:
- Long trend when closes candle is above the green line.
- Short trend when closes candle is below the red line.
3. REVERSAL CANDLES DETECT:
- Cancels the Short trend if occurs 5 bullish reversal candles.
- Cancels the Long trend if occurs 5 bearish reversal candles.
- Cancels the Short trend if occurs bullish Engulfing reversal candles.
- Cancels the Long trend if occurs bearish Engulfing reversal candles.
4. OPEN POSITION RULE:
- BUY/LONG: reject to Supertrend at current timeframe.
- SELL/SHORT: reject to Supertrend at current timeframe.
5. Autotrade with Money management: requires Pro, Pro +, Premium Tradingview & Webhook service.
6. Winrate of 129 coin pairs of Binance future
7. DEEP BACKTEST:
- BITCOIN ALL TIME HISTORY INDEX
- ETHEREUM ALL TIME HISTORY INDEX
- LITECOIN BINANCE FUTURE
- BINANCE COIN BINANCE FUTURE
- XRP BINANCE FUTURE
RSI SMA Crossover StrategyOverview
RSI SMA Crossover Strategy works the same way as traditional MA crossover strategies, but using RSI instead of price. When RSI crosses over the SMA, a long position is opened (buy). When RSI crosses under the SMA, the long position is closed (sell).
This strategy can be very effective when the right inputs are used (see below). Be sure to use the backtesting tool to determine the optimal parameters for a given asset/timeframe.
Inputs/Parameters
RSI Length: length for RSI calculation (default = 50)
SMA Length: length for SMA calculation (default = 25)
Strategy Properties
Initial Capital = $1000
No default properties are defined for Slippage, Commission, etc, so be sure to set these values to get accurate backtesting results. This script is being published open-source for a reason - save yourself a copy and adjust the settings as you like!
Backtesting Results
Testing on Bitcoin (all time index) 1D chart, with all default parameters.
$1,000 initial investment on 10/07/2010 turns into almost $2.5 billion as of 08/30/2022 (compared to $334 million if the initial investment was held over the same period)
Remember, results can vary greatly based on the variables mentioned above, so always be sure to backtest.
ALMA/EMA/SRSI Strategy + IndicatorBack with another great high hit rate strategy!!
Disclaimer* This strategy was sampled using source code written by @ClassicScott , as referred to in the script, there is a clear line where the source code was scripted by myself.
This Strategy consists of three key factors, the ALMA, EMA crossover, and a Stochastic Rsi
ALMA: The Alma is the step line shown, turning green and red at select times. This average value gives general oversight of the macro movement of price action. and this particular one was coded by Mr.ClassicScott.
EMA crossover: At the input screen you are given an option of the fast and slow ema's. The default is solely for the hit rate and correlation to the Alma of this strategy. The arrows you see depicted on the chart are the crossover events happening.
Stochastic Rsi: The Stochastic Rsi is a stochastic value, using data sampled from the rsi. The use of this indicator in my strategy is to prevent entries when too overbought and oversold, as well as closures and vice versa, to prevent holding bags either way.
Fixed % TP: In the input screen you are given a take profit and stop loss percentage, for good R/R the hit rate will take a notch down, but with no R/R it will be near perfect.
How to use this:
Add it to your chart to get the strategy inputs. (The strategy is really only useful on a 15min TF. However the indicator within it can be used on anything at anytime!)
Watch the yellow and aqua moving averages, these are your ema's and crossover's will trigger signals based on your integer inputs.
Find Correlation between other leading indicators, as well as crossover's down/up and a red/green alma.
DO NOT use the arrows as buy/sell signals. These are simply to show ema's are crossing under or over. Momentum indicator's paired with this can be useful to determine if it could be a buy signal or sell signal.
Cheat Code's Notes:
Almost at 1000 boosts!!! I appreciate the support from everyone and I will keep trying my best to deliver quality strategies for the people.
-Cheat Code
BYBIT:BTCUSDT
Mean reversal QFL v3My aim is to make the bots trade as you would trading QFL manually and “by the book” or at least to my experience and understanding from the material out there of how you should plan a QFL trade.
Im absolutely not a pro trader, I have made my share of costly mistakes trying to be clever or Beeing impatient resulting in painful losses. QFL is we’re I’ve had consistently good results tough.
Is this where I have to say I’m not a financial advisor and all that? Well I’m not. As always Do your own research and backtest, backtest, backtest.
First: I believe no bot strategy are set and forget, while they can run unattended 80-90% of the time you're always going to find yourself in a situation where you will have to manually handle a bad deal. It would also make sense to be somewhat involved in the really good trades making the most out of them. That’s why understanding the strategy the bot Is using is really important, hence why I prefer QFL. It's an easy concept to understand, and proved to be a safe way of making steady profit in pretty much all market conditions if done right.
Some changes in how aggressive you are might be needed if you are the impatient kind of trader who needs to see a lot of deals happening. But it is an added risk. In those cases Luc would advise to start “nibbling” but that would be hard to implement in a bot but I will see if that’s something I can implement.
Same goes for going the more conservative route when market conditions calls for it.
QFL stands for Quickfingersluc, and sometimes it is referred to as the Base Strategy or Mean Reversals. Its main idea is about identifying the moment of panic selling and buying below the base level and utilizing Safety orders.
Base level or Support Level refers to the lowest price level that was reached before the moment the price started increasing again. At that level, you can notice that buyers of some cryptocurrencies make a strong reaction.
As a bit of a learning material i want to make a few points on important factors in trading using the QFL strategy:
• Identify strong bases
• Read the history of the chart
• No emotions
Trading QFL using a bot has it’s limitations:
· Some of the bases are questionable but im constantly trying to improve this
· The strategy don’t take into consideration chart history(success rate)*
· You need to follow a predefined (by you) buying ladder, hence not considering a particular coin's average price movement, which may vary quite a lot. This why I for now has limited the strategy to SIMPLE bots. So that unique alerts can be created for each pair.
· A set Take profit %, possibly making you miss out on higher profits(This is easy to change during a trade though), and no chance of selling in layers(This is coming soon).
1. Some of the bases are questionable
The strategy will start trades of bases that you wouldn’t consider being a strong base(or a base at all) when looking at the chart.
For those not as familiar with QFL. What is a base, and what qualifies as a strong base?
• A base is also called the Support Level, which is the lowest price level that was reached before the price started turning and increasing again.
• A strong base is recognized by a steep fall in price after breaking the base(Panic), followed by a big reaction pump.
• The reaction pump is the most important factor to say that it is a strong base.
• And also the last base, the one you are trading of is the one that counts
Tip: Look for V shapes on the chart, easy to spot when zoomed out.
2. The integrated signals don’t take into consideration chart history(success rate)*
How can you assess the success rate by looking at the chart?
After finding the bases based on the criterias from the 1st point. Looking at the, how many times did it respect the base after breaking it? 7/10, 8/10, 9/10 times? Great! Chances of the next trade also respecting the base is big, and I would consider raising the TP on that deal. Any lower than that I would keep a really close eye on the deal, or even consider closing the deal. And again remember the last base is the one that counts. If all the others are nice strong bases but that last one you are about to take a trade off is no good the base is invalidated so be cautious.
3. You need to follow a predefined (by you) buying ladder
Crypto is volatile, and there is a huge variation in price movements on all the coins.
Trading manually, looking at the chart gives you a good idea on how much a coin on avg. drops below base, and how big the following reaction is. This gives you an indication on how deep you need to set your layers, and where you can take profit.
Using the strategy you have the backtester to see how much max deviation has been in the past so that you can figure out what the optimal max deviation is.
4. A set Take profit %, possibly making you miss out on higher profits(This is easy to change during a trade though), and no chance of selling in layers.
Not going to say to much about this other than what I often do is:
When a bot has started a trade I usually take a look at the chart. If I like what I see, nice chart history, success rate and trading of a strong previous base etc, with the current base break resulting in a panic drop I will consider increasing the TP so that it will make more profit. This can be a bit risky but also very rewarding. Imagine filling all safeties and then selling just below base! Massive profits!! (Gotta be honest though, almost never stretch it that far with a bot though, but it is a possibility) .
If you have studied the chart and concluded that this particular trade has a 90% chance of success, there isn’t really any reason not to place TP just below base. This is where I would like to have the option of layering my sell orders as well so its something im working on implementing.
Trailing is an option in 3commas, but it’s slow to place orders making you miss a selling opportunity when the coin makes a sudden spike up.
ABOUT THIS STRATEGY
In this strategy we can also reverse the strategy and go short. But i must warn you that that is alot riskier.
QFL is meant to be used on higher TF's like 1hr, 2hr and 4hr. But this strategy also work well on lower Timeframes.
The script also simulates DCA strategy with parameters used in 3commas DCA bots for futures trading.
Experiment with parameters to find your trading setup.
Beware how large your total leveraged position is and how far can market go before you get liquidated!
Do that with the help of futures liquidation calculators you can find online!
Included:
An internal average price and profit calculating, instead of TV`s native one, which is subject to severe slippage.
A graphic interface, so levels are clearly visible and back-test analyzing made easier.
Long & Short direction of the strategy.
Table display a summary of past trades
Vertical colored lines appear when the new maximum deviation from the original price has
been reached
All the trading happens with total account capital, and all order sizes inputs are expressed in percent.
How to use:
- Add the script to the current chart
- Open the strategy settings
-Tweak the settings to to your liking.
-Make a SIMPLE bot in 3commas and use the same settings as you did in tradingview if you only want the strategy to send signals to open a deal and let 3commas handle the rest.
If you check safety orders, Take profit deal stop and Stop loss. The strategy will send all the orders to 3 commas. If that’s what you want set TP in 3commas to 50% set number of safety orders to 0 and keep stop loss unchecked.
- Insert bot details using the deal start condition message found in your 3commas bot.
- When happy, right click on the "..." next to the strategy name, then "Add alert'".
- Under "Condition", on the second line, chose "Any alert () function call". Add the webhook from 3commas( 3commas.io ), give it a name, use {{strategy.order.alert_message}} as a placeholder message and "create".
In the future this signal might make it to the 3commas marketplace. You can then subscribe to that signal where I have cherrypicked coins based on thorough backtesting and optimization.
How to obtain access to the script: send me a private message in Tradingview
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 -_- *
PlanB Quant Investing 101 v2This script has been Inspired by PlanB Article Quant Investing 101.
With this script, I implemented Plan B strategy outlined in that article, trying to reproduce his findings independently and allowing TradeView Users to do the same.
PlabB is aware of this effort, and he's positive about it, via Twitter commenting, liking and sharing of this resource .
Trading Idea:
This script uses RSI index to determine the Buy And Sell signal.
As per the original PlanB article:
IF ( RSI was above 90% last six months AND drops below 65%) THEN sell,
IF ( RSI was below 50% last six months AND jumps +2% from the low) THEN buy, ELSE hold
My simple code is aimed at replicating his study in Pine so that every TV user can check his signal.
Trade HourThis script is just finds the best hour to buy and sell hour in a day by checking chart movements in past
For example if the red line is on the 0.63 on BTC/USDT chart it mean the start of 12AM hour on a day is the best hour to buy (all based on
It's just for 1 hour time-frame but you can test it on other charts.
IMPORTANT: You can change time Zone in strategy settings.to get the real hours as your location timezone
IMPORTANT: Its for now just for BTC/USDT but you can optimize and test for other charts...
IMPORTANT: A green and red background color calculated for show the user the best places of buy and sell (green : positive signal, red: negative signals)
settings :
timezone : We choice a time frame for our indicator as our geo location
source : A source to calculate rate of change for it
Time Period : Time period of ROC indicator
About Calculations:
1- We first get a plot that just showing the present hour as a zigzag plot
2- So we use an indicator ( Rate of change ) to calculate chart movements as positive and negative numbers. I tested ROC is the best indicator but you can test close-open or real indicator or etc as indicator.
3 - for observe effects of all previous data we should indicator_cum that just a full sum of indicator values.
4- now we need to split this effects to hours and find out which hour is the best place to buy and which is the best for sell. Ok we should just calculate multiple of hour*indicator and get complete sum of it so:
5- we will divide this number to indicator_cum : (indicator_mul_hour_cum) / indicator_cum
6- Now we have the best hour to buy! and for best sell we should just reverse the ROC indicator and recalculate the best hour for it!
7- A green and red background color calculated for show the user the best places of buy and sell that dynamically changing with observing green and red plots(green : positive signal, red: negative signals) when green plot on 15 so each day on hour 15 the background of strategy indicator will change to 15 and if its go upper after some days and reached to 16 the background green color will move to 16 dynamically.
VIDYA Trend StrategyOne of the most common messages I get is people reaching out asking for quantitative strategies that trade cryptocurrency. This has compelled me to write this script and article, to help provide a quantitative/technical perspective on why I believe most strategies people write for crypto fail catastrophically, and how one might build measures within their strategies that help reduce the risk of that happening. For those that don't trade crypto, know that these approaches are applicable to any market.
I will start off by qualifying up that I mainly trade stocks and ETFs, and I believe that if you trade crypto, you should only be playing with money you are okay with losing. Most published crypto strategies I have seen "work" when the market is going up, and fail catastrophically when it is not. There are far more people trying to sell you a strategy than there are people providing 5-10+ year backtest results on their strategies, with slippage and commissions included, showing how they generated alpha and beat buy/hold. I understand that this community has some really talented people that can create some really awesome things, but I am saying that the vast majority of what you find on the internet will not be strategies that create alpha over the long term.
So, why do so many of these strategies fail?
There is an assumption many people make that cryptocurrency will act just like stocks and ETFs, and it does not. ETF returns have more of a Gaussian probability distribution. Because of this, ETFs have a short term mean reverting behavior that can be capitalized on consistently. Many technical indicators are built to take advantage of this on the equities market. Many people apply them to crypto. Many of those people are drawn down 60-70% right now while there are mean reversion strategies up YTD on equities, even though the equities market is down. Crypto has many more "tail events" that occur 3-4+ standard deviations from the mean.
There is a correlation in many equities and ETF markets for how long an asset continues to do well when it is currently doing well. This is known as momentum, and that correlation and time-horizon is different for different assets. Many technical indicators are built based on this behavior, and then people apply them to cryptocurrency with little risk management assuming they behave the same and and on the same time horizon, without pulling in the statistics to verify if that is actually the case. They do not.
People do not take into account the brokerage commissions and slippage. Brokerage commissions are particularly high with cryptocurrency. The irony here isn't lost to me. When you factor in trading costs, it blows up most short-term trading strategies that might otherwise look profitable.
There is an assumption that it will "always come back" and that you "HODL" through the crash and "buy more." This is why Three Arrows Capital, a $10 billion dollar crypto hedge fund is now in bankruptcy, and no one can find the owners. This is also why many that trade crypto are drawn down 60-70% right now. There are bad risk practices in place, like thinking the martingale gambling strategy is the same as dollar cost averaging while also using those terms interchangeably. They are not the same. The 1st will blow up your trade account, and the 2nd will reduce timing risk. Many people are systematically blowing up their trade accounts/strategies by using martingale and calling it dollar cost averaging. The more risk you are exposing yourself too, the more important your risk management strategy is.
There is an odd assumption some have that you can buy anything and win with technical/quantitative analysis. Technical analysis does not tell you what you should buy, it just tells you when. If you are running a strategy that is going long on an asset that lost 80% of its value in the last year, then your strategy is probably down. That same strategy might be up on a different asset. One might consider a different methodology on choosing assets to trade.
Lastly, most strategies are over-fit, or curve-fit. The more complicated and more parameters/settings you have in your model, the more likely it is just fit to historical data and will not perform similar in live trading. This is one of the reasons why I like simple models with few parameters. They are less likely to be over-fit to historical data. If the strategy only works with 1 set of parameters, and there isn't a range of parameters around it that create alpha, then your strategy is over-fit and is probably not suitable for live trading.
So, what can I do about all of this!?
I created the VIDYA Trend Strategy to provide an example of how one might create a basic model with a basic risk management strategy that might generate long term alpha on a volatile asset, like cryptocurrency. This is one (of many) risk management strategies that can reduce the volatility of your returns when trading any asset. I chose the Variable Index Dynamic Average (VIDYA) for this example because it's calculation filters out some market noise by taking into account the volatility of the underlying asset. I chose a trend following strategy because regressions are capturing behaviors that are not just specific to the equities market.
The more volatile an asset, the more you have to back-off the short term price movement to effectively trend-follow it. Otherwise, you are constantly buying into short term trends that don't represent the trend of the asset, then they reverse and loose money. This is why I am applying a trend following strategy to a 4 hour chart and not a 4 minute chart. It is also important to note that following these long term trends on a volatile asset exposes you to additional risk. So, how might one mitigate some of that risk?
One of the ways of reducing timing risk is scaling into a trade. This is different from "doubling down" or "trippling down." It is really a basic application of dollar cost averaging to reduce timing risk, although DCA would typically happen over a longer time period. If it is really a trend you are following, it will probably still be a trend tomorrow. Trend following strategies have lower win rates because the beginning of a trend often reverses. The more volatile the asset, the more likely that is to happen. However, we can reduce risk of buying into a reversal by slowly scaling into the trend with a small % of equity per trade.
Our example "VIDYA Trend Strategy" executes this by looking at a medium-term, volatility adjusted trend on a 4 hour chart. The script scales into it with 4% of the account equity every 4-hours that the trend is still up. This means you become fully invested after 25 trades/bars. It also means that early in the trade, when you might be more likely to experience a reversal, most of your account equity is not invested and those losses are much smaller. The script sells 100% of the position when it detects a trend reversal. The slower you scale into a trade, the less volatile your equity curve will be. This model also includes slippage and commissions that you can adjust under the "settings" menu.
This fundamental concept of reducing timing risk by scaling into a trade can be applied to any market.
Disclaimer: This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
T&M/E Wave V2Trend and Momentum With Exception Wave Indicator and Strategy:
This strategy is hand made and I have spent days and many hours making it. The strategy is meant to determine the power between buyers and sellers, match the current power with a historic trend (through a moving average statistical equation), and finally volatility (measured with a mix between standard deviation from Bollinger Bands and HPV). Below will be a list of how to determine the inputs for the indicator
**For reference, all numbers, and settings displayed on the input screen are only what I HAVE FOUND to be profitable for my own strategy, Yours will differ. This is not financial advice and I am not a financial advisor. Please do your due diligence and own research before considering taking entries based on this strategy and indicator. I am not advertising investing, trading, or skills untaught, this is simply to help incorporate into your own strategy and improve your trading journey!**
INPUTS:
EV: This is an integer value set to default at 55. This value is equated to the lead value, volatility measurement, and standard deviation between averages
EV 2: This integer is used as the base value and is meant to always be GREATER THEN EV, the default is set at 163. There should be at least a 90+ integer difference between EVs for data accuracy.
EV TYPE & EV TYPE 2: This option only affects the output for the moving average histograms. (and data inserted for strategy)
Volatility Smoothing: This is the smoothness of the custom-made volatility oscillator. I have this default at 1 to show time-worthy-term (3.9%+) moves or significant trends to correspond with the standard deviation declination between EVMA and EVMA2.
Directional Length: This is the amount of data observed per candle in the bull versus bear indicator.
Take Profit: Pre-set takes profit level that is set to 4 but can be adjusted for user experience.
Style:
Base Length: Columns equated using a custom-made statistical equation derived from EV TYPE 2+EV2 to determine a range of differential in historic averages to a micro-scale.
Lead Length: Columns equated using a custom-made statistical equation derived from EV TYPE+EV to determine a range of differential in historic averages to a micro-scale.
Weighted EMA Differential: Equation expressing the differences between exponential and simple averages derived from EV+EV Type 2. Default is displaying none, but optional for use if found helpful.
Volatility: Represents volatility from multiple data sets spanning from Bollinger bands to HPV and translated through smoothing.
Bull Strength: The strength of Bulls in the current trend is derived from a DMI+RSI+MACD equation to represent where the trend lies.
Bear Strength: The strength of Bears in the current trend is derived from a DMI+RSI+MACD equation to represent where the trend lies.
CHEAT CODE'S NOTES:
Do not use this indicator on high leverage. I have personally used this indicator for a week and faced a max of 8% drawdown, albeit painful I was on low leverage and still closed on my take profit level.
85% is not 100% do not overtrade using this indicator's entry conditions if you have made 4 consecutive profitable trades.
Mess around with the input values and let me know if you find an even BETTER hit rate, 30+ entries and a good drawdown!!
V2 UPGRADES:
*Increased Opacity on Bull Bear Columns
*Removed the Stop Loss Input option
*Decreased EV2 to a default of 143 for accuracy
*Added additional disclaimers in the description
* Removed Bull/Bear offset values for accuracy
-Cheat Code
BYBIT:BTCUSDT
Smoothed Heikin Ashi Trend on Chart - TraderHalai BACKTESTSmoothed Heikin Ashi Trend on chart - Backtest
This is a backtest of the Smoothed Heikin Ashi Trend indicator, which computes the reverse candle close price required to flip a Heikin Ashi trend from red to green and vice versa. The original indicator can be found in the scripts section of my profile.
This particular back test uses this indicator with a Trend following paradigm with a percentage-based stop loss.
Note, that backtesting performance is not always indicative of future performance, but it does provide some basis for further development and walk-forward / live testing.
Testing was performed on Bitcoin , as this is a primary target market for me to use this kind of strategy.
Sample Backtesting results as of 10th June 2022:
Backtesting parameters:
Position size: 10% of equity
Long stop: 1% below entry
Short stop: 1% above entry
Repainting: Off
Smoothing: SMA
Period: 10
8 Hour:
Number of Trades: 1046
Gross Return: 249.27 %
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 28.01 %
Profit Factor (Expectancy): 2.019
Average Loss: 0.33 %
Average Win: 1.69 %
Average Time for Loss: 1 day
Average Time for Win: 5.33 days
1 Day:
Number of Trades: 429
Gross Return: 458.4 %
CAGR Return: 15.76 %
Max Drawdown: 6.37 %
Profit Factor (Expectancy): 2.804
Average Loss: 0.8 %
Average Win: 7.2 %
Average Time for Loss: 3 days
Average Time for Win: 16 days
5 Day:
Number of Trades: 69
Gross Return: 1614.9 %
CAGR Return: 26.7 %
Max Drawdown: 5.7 %
Profit Factor (Expectancy): 10.451
Average Loss: 3.64 %
Average Win: 81.17 %
Average Time for Loss: 15 days
Average Time for Win: 85 days
Analysis:
The strategy is typical amongst trend following strategies with a less regular win rate, but where profits are more significant than losses. Most of the losses are in sideways, low volatility markets. This strategy performs better on higher timeframes, where it shows a positive expectancy of the strategy.
The average win was positively impacted by Bitcoin’s earlier smaller market cap, as the percentage wins earlier were higher.
Overall the strategy shows potential for further development and may be suitable for walk-forward testing and out of sample analysis to be considered for a demo trading account.
Note in an actual trading setup, you may wish to use this with volatility filters, combined with support resistance zones for a better setup.
As always, this post/indicator/strategy is not financial advice, and please do your due diligence before trading this live.
Original indicator links:
On chart version -
Oscillator version -
Update - 27/06/2022
Unfortunately, It appears that the original script had been taken down due to auto-moderation because of concerns with no slippage / commission. I have since adjusted the backtest, and re-uploaded to include the following to address these concerns, and show that I am genuinely trying to give back to the community and not mislead anyone:
1) Include commission of 0.1% - to match Binance's maker fees prior to moving to a fee-less model.
2) Include slippage of 10 ticks (This is a realistic slippage figure from searching online for most crypto exchanges)
3) Adjust account balance to 10,000 - since most of us are not millionaires.
The rest of the backtesting parameters are comparable to previous results:
Backtesting parameters:
Initial capital: 10000 dollars
Position size: 10% of equity
Long stop: 2% below entry
Short stop: 2% above entry
Repainting: Off
Smoothing: SMA
Period: 10
Slippage: 10 ticks
Commission: 0.1%
This script still remains to shows viability / profitablity on higher term timeframes (with slightly higher drawdown), and I have included the backtest report below to document my findings:
8 Hour:
Number of Trades: 1082
Gross Return: 233.02%
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 25.6%
Profit Factor (Expectancy): 1.627
Average Loss: 0.46 %
Average Win: 2.18 %
Average Time for Loss: 1.33 day
Average Time for Win: 7.33 days
Once again, please do your own research and due dillegence before trading this live. This post is for education and information purposes only, and should not be taken as financial advice.
[BUBBLENUKE] BOB The Reversal Trader=============================================================: BOB The Reversal Trader :=============================================================
COMPONENTS:
- VWAP Anchored at Friday CME close
- Bitcoin CME close
- Volume bars
SETTINGS:
- Asset: BTCUSDTPERP
- Time frame: 30M
- Hard TP %: 1.5
- Hard SL %: 40
- Trading Session Start (UTC): 4
- Trading Session End (UTC): 17
DESCRIPTION:
BOB is a mean-reversion trading system focused in BTCUSDT asset in the 30M time frame. The system is divided into 2 types of entries:
WEEKENDS:
BOB will trigger his entry when the price of Bitcoin is at one of the two deviations from the VWAP anchored at Friday CME close and BOB will take your profits when the price returns to the VWAP. When BOB hits Sunday and the CME reopens, BOB will close all your open positions.
INTRA-WEEK:
BOB will trigger its entry when the price of Bitcoin is at one of the two deviations from the VWAP anchored at the Friday CME close or when a volume candle indicates a reversal. BOB will take your profits when the price returns to the VWAP or when the HARD TP % is reached (1.5% by default). When BOB hits Friday and the CME closes, BOB will close all your open positions.
Bot MasterSqueeze 1.1 (crypt)Countertrend strategy for correction to the average value. The strategy is designed primarily for crypto.
The principle of operation is that with a rapid price change, the strategy tends to take a reverse position to return to the average value, which statistically often happens. It is enough for you to determine the percentage of the offset about the average price and the size of the averaging position as a percentage of the deposit.
With the settings, you determine how to determine the average opening price. It can be MA at the price of opening, closing, etc., and DCMA. Soon I will add a few more options for determining the average opening price
You can also choose the average price at which the transaction will try to close.
Now there are 3 methods:
- closing when returning to the average price
- closing on the first correction candle
- opening on an abnormally large candle in the direction of correction and closing on the first one is opposite
Search for the settings by the selection method for each pair separately. It is better to trade using signals via a bot.
The strategy shows itself best on volatile coins paired with the dollar for 1 hour or more.
Soon I will add new options for opening and closing deals, as well as determining the average price.
ATTENTION: the strategy involves averaging, so be careful with levers and overestimating the percentage of the transaction from the deposit. It is best to allocate no more than 25 percent to the risk of the transaction.
Rate Of Change Trend Strategy (ROC)This is very simple trend following or momentum strategy. If the price change over the past number of bars is positive, we buy. If the price change over the past number of bars is negative, we sell. This is surprisingly robust, simple, and effective especially on trendy markets such as cryptos.
Works for many markets such as:
INDEX:BTCUSD
INDEX:ETHUSD
SP:SPX
NASDAQ:NDX
NASDAQ:TSLA
The Impossible TraderTHE IMPOSSIBLE TRADER
A simple, but effective High Freq Strategy script based on MACD or RSI trend, with extra customizable Alert Messages for Bots.
WHAT IT DOES
This script (works best at lower TimeFrames) just follow the trend of MACD or RSI on your asset.
Why it should work? Because in an upper trend, there are more chance of green candles than reds. And in dump trend there are more chance of red candles than greens.
While trend is positive, it will try to open Long orders as fast as possible at market price.
While trend is negative, it will try to open Short orders as fast as possible at market price.
HOW TO SETUP YOUR PREFERENCES
Capital : Insert a % of Margin you want to use for your positions (usually 30% is quite good)
Leverage : Choose leverage based on your plans
Trail Tick @ : This value (in Tick) tell the script "when" the "Trail Stop" order must be activated (from the Entry price)
Offset Tick @ : This is the price (in Tick) from the Trail Stop Price activated. Basically it is a Stop Loss that follow the price at a fixed distance.
SL Tick @ : Set a Stop Loss at amount Tick distance from the Entry Price. (Let's call it a Safety Stop Loss for bad decisions...)
TP Tick @ : Set a Take Profit at amount Tick distance from the Entry Price. Sometimes is better to exit in full Gain than keep positions.
Strategy : You can choose a Only Long, Only Short or Long+Short sametime strategy.
with MACD or RSI : You can try the strategy applied on MACD or applied on customizable RSI EMA
EMA : If you choosed RSI EMA, you can set any value for your testing (usually 80-120 works very nice)
Exit order after bars : Some Exchanges / Brokers apply fixed cost, and a strategy too fast could not be productive. This set will let you to delay the Exit Order on already Opened positions.
Keep Stop Loss active : If you are planning a delay for Exit Orders, sometime could be useful to keep activated Stop Loss.
Strategy Preset : Some preset I've found interesting, with good results.
BackTest Days : If there are too many results and script doesn't work, you can choose a closer range to show results.
EXTRA FEATURES
On Screen Display : OSD will show you some realtime stats about your strategy, like Asset Tick, Trading Period Range, Drawdown, Gains and not closed trade.
Alert Message : You can enter custom Long Entry/Exit and Short Entry/Exit message for your Bots (like AutoView, WunderBit, etc...). When alert is triggered, you can send custom message with {{strategy.order.comment}} in the text field
AutoView Alert Message : If you are user of AutoView, you can generate your calls. Those are tested only on Oanda with index like Sp500, US100, Us30.
TIPS ON USE
Some asset on TradingView require an higher initial capital. Go to this Script Settings -> Properties and rise Initial Capital.
Be aware of commissions and spread when evalutating a strategy. Go to this Script Settings -> Properties and set Commission and Slippage
Trail Stop and Ticks could be difficult to understand, but very profitable. Please take your time and study how it works.
Consider Tick like the minimum movement your asset can do. Ticks occurs "intra-bar", so some of your positions could be closed almost instantly.
Consider Trail Stop like a Stop Loss that keep always the same distance from your positions, but never came back . If you are in gain, say of 10 Ticks, and your Trail have 5 Ticks, this means for sure a close at minimum 5 Ticks from Entry Price.
On Screen Display will show you Ticks for your asset. This will help you on strategy settings, because not all asset responds on the same way.
ONLY LONG EXAMPLE
ONLY SHORT EXAMPLE
Bot fib/pivot Hello, friends!
This strategy is based on the fibonacci level you choose in the setup and possible pivot points under the control of Williams’ Percent Range.
Williams' Percent Range is a dynamic indicator that detects overbought/oversold conditions.
When the possible reversal points coincide with the fibonacci level, and the high or low points according to Williams also coincide, then an entry occurs.
One of the oldest and most reliable trading tools are widely used support and resistance levels.
In this strategy, we are trying to find these reversal levels based on fibonacci.
//LOGIC ENTRY SETTINGS
Deviation-deviation from the pivot point, the lower this figure, the more entries. The yellow lines on the chart are pivot points.
Fibonacci lvl-fibonacci level, from which the entry will occur, provided that other conditions match
Highest lookback-The setting, which refers to Williams' Percent Range , looks at how many candles ago, was high or low. The smaller the number, the larger, but less accurate inputs.
//AMOUNT(USDT) FIRST ORDER AND > % NEXT
-Martingale first order (the amount of the entrance to the usdt) / next order (Increase of each subsequent order as a percentage)
//EXIT SETTINGS (%, RSI)
-Use RSI for close position? (the position will not be closed if it is in the red, even if the RSI conditions worked)
-Use % for exit? Exit immediately upon reaching the specified percentage
-Use trailing? When the checkbox is checked, the position will be exited by trailing.
Activation trail,after?- When the specified percentage is reached, trailing is activated!
Stop_trail,%- if the last candle falls from the high (after the trailing is activated), the position will be exited.
For example:
We entered the purchase at 100 per asset, activation costs 10, and stop is 2.
the price reached 110, there was an activation, after that it went up to 120, and from the high of the last candle, a 2% drop occurs and the trade is exited.
PS:The default value is 1%, what does this give us? if there is a sharp increase, then we take away all the movement
Use only long?
Allow long?- Only long trades will be displayed
Allow short? Only short trades will be displayed
Allo reverse? Upon receipt of a return signal, the opposite position will be closed.
//MARTINGALE GRID
If there is a check mark in the line "Use martingale and grid?"
then the grid will be active
If there is a check mark in the "Limit each next entry,%?" then, even if the entry from the bot logic is triggered, and the price does not fall by the specified percentage, then there will be no entry!
If there is a check mark in the "Grid,%" column, then purchases with martingale support will be added with a decrease by the specified percentage!
PS: "Grid" always starts anew, as the input from logic triggered!
//FILTER SETTINGS
1) Use filter oscillator? (The filter uses 7 averaged oscillators)
Period-the period for which you will be billing
Upper line-Short entry border.
(if 40, then there will be no entry until it reaches)
Lower line-Long entry border.
(20 until below 20 no entry)
2)Use filter range?
Filter type-moving average selection
Bars back-offset speed based on number of last bars
Period-period to calculate
3)Use filter supertrend?
Supertrend filter with multitimeframe
// How do filters work 2 and 3?
Filters can work either one by one or together.
A trade is entered when conditions from the logic and filters in the red zone are triggered, when there are no entries in the green zone.
//DATA RANGE:
-Testing results for any period of time
//PIRAMIDING
-Also in the settings there is a pyramid of order, keep this in mind. Make a deal for a small part of the deposit, and not for all the money at once!
PS: to use martingale, you need to write in the hook messages:
"amount": "{{strategy.order.contracts}}" (purchases will be in the amount of coins equivalent to USDT)
The default settings for TF are 1 minute, 10 inputs.
You can choose your settings for any TF, but look at different coins to make sure you have good statistics
Sideways Strategy DMI + Bollinger Bands (by Coinrule)Markets don’t always trade in a clear direction. At a closer look, most of the time, they move sideways. Relying on trend-following strategies all the time can thus lead to repeated false signals in such conditions.
However, before you can safely trade sideways, you have to identify the most suitable market conditions.
The main features of such strategies are:
Short-term trades, with quick entries and quick exits
Slightly contrarian and mean-reversionary
Require some indicator that tells you it’s a sideways market
This Sideways DMI + Bollinger Bands strategy incorporates such features to bring you a profitable alternative when the regular trend-following systems stop working.
ENTRY
1. The trading system requires confirmation for a sideways market from the Directional Movement Index (DMI) before you can start opening any trades. For this purpose, the strategy uses the absolute difference between positive and negative DMI, which must be lower than 20.
2. To pick the right moment to buy, the strategy looks at the Bollinger Bands (BB). It enters the trade when the price crosses over the lower BB.
EXIT
The strategy then exits when the move has been exhausted. Generally, in sideways markets, the price should revert lower. The position is closed when the price crosses back down below the upper BB.
The best time frame for this strategy based on our backtest is the 1-hr. Shorter timeframes can also work well on certain coins that are more volatile and trade sideways more often. However, as expected, these exhibit larger volatility in their returns. In general, this approach suits medium timeframes. 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.
Three EMAs Trend-following Strategy (by Coinrule)Trend-following strategies are great because they give you the peace of mind that you're trading in line with the market.
However, by definition, you're always following. That means you're always a bit later than your want to be. The main challenges such strategies face are:
Confirming that there is a trend
Following the trend, hopefully, early enough to catch the majority of the move
Hopping off the trade when it seems to have run its course
This EMA Trend-following strategy attempts to address such challenges while allowing for a dynamic stop loss.
ENTRY
The trading system requires three crossovers on the same candle to confirm that a new trend is beginning:
Price crossing over EMA 7
Price crossing over EMA 14
Price crossing over EMA 21
The first benefit of using all three crossovers is to reduce false signals. The second benefit is that you know that a strong trend is likely to develop relatively soon, with the help of the fast setup of the three EMAs.
EXIT
The strategy comes with a fixed take profit and a volatility stop, which acts as a trailing stop to adapt to the trend's strength. That helps you get out of the way as soon as market conditions change. 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:
The price increases by 4%
The price crosses below the volatility stop.
The best time frame for this strategy based on our backtest is the 4-hr. Shorter timeframes can also work well, although they exhibit larger volatility in their returns. In general, this approach suits medium timeframes. 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.
Optimised RSI strategy for Reversals (by Coinrule)The most common way to use the RSI to spot a good buy opportunity is to check for values lower than 30. Unfortunately, the RSI can remain in oversold territory for long periods, and that could leave you trapped in a trade in loss. It would be appropriate to wait for a confirmation of the trend reversal.
In the example above I use a short-term Moving Average (in this case, the MA9) coupled with an RSI lower than 40. This combination of events is relatively rare as reversal confirmations usually come when RSI values are already higher. As unusual as this setup is, it provides buy-opportunities with much higher chances of success.
The parameters of this strategy would be:
ENTRY: RSI lower than 40 and MA9 lower than the price
TAKE PROFIT and STOP-LOSS with a ratio of at least 2. That means that if you set up a take profit of 3%, your stop-loss shouldn’t be larger than 1.5%.
The advantage of this approach is that it has a high rate of success and allows you the flexibility of setting up the percentages of the take profit and stop-loss according to your preferences and risk appetite.
Crypto Correlation Strategy based on Technical Ratings This is a swing trading crypto correlation strategy, based initially on technical ratings but adapted to the entire crypto market environment , by using as a source of calculations the candle values from CRYPTOCAP:TOTAL.
So since TOTAL, is the sum of all the crypto currencies, its going to be our leader. We will get the entries and exits , internally from it and input them into the crypto coins(more than 80-90% of the usdt perpetual pairs are following the same direction but with a higher volatility), and with this in general is going to give us as much better risk/reward than just by trading 1 coin alone.
So this means that all coins will enter and exit at the same time forom a trade. With this, since sometimes we have sudden big changes in the price form one side to another, is going to break a little this effect and since the initial movements were bigger, it would make us lose less. At the same time it can also make us lose more if the changes happen to soon.
One of the things of this particular idea is we dont have to worry about particular optimizations for each asset/coin.
This scenario has been adapted for 30min timeframe, using 0.1% comission per entry and 0.1% comission for exit from the trade.
I have tested so far with most USDT Perpetual Pairs from binance, and it seems to give good results with most of the pairs.
If you have any question please let me know !
Maddrix_club III (strategy)Maddrix club III (STRATEGY) is an advanced trading algorithm that goes long and short in spite of the market condition. It aims to capture large moves. It is the fruit of over a thousand hours of work, trials, errors, research, etc.
The STUDY version is also posted.
There are 5 main variables to adjust the indicator:
Framework length – Use this to establish the environment. Shorter length = volatile environment. Longer length = steadier.
Framework multiplier – Use this to adjust the environment to the asset. Lower value for less volatile price action and higher value for very volatile price action.
Search timeframe – Use this to lookback for a fractal . In theory, the longer the lookback the more reliable the fractal recognition.
Trigger line – Use this to adjust the trigger level. In theory, the lower the trigger the more signals you get.
Threshold – Use this to filter the signals. The higher the threshold, the less signal you get.
The best way to go about changing the settings, is to start off the default value. I’d do a monthly check-in playing with few of them and readjusting based on results from the exchange.
They are different, as this one can show you the equity curve.
It works on many markets as long as there is sufficient activity to create patterns and repetition.
You will notice a slight difference between the strategy calculation and the algo calculation (built in the algo) - this is because the exits are not exactly at the same levels. I left this on purpose, so that you can see that even with a little slippage, overall this is positive.
Very good results have been observed on the 15 min time frame though it technically works on all timeframe (5 min for example, 1 hour also). On the example above ETHUSDT – 15 min, the back test shows consistency in the results for the last 2 years. The theory behind it is based on probabilities, human emotions, and repetition in market patterns.
Results have also shown great adaptability, meaning the total profits don’t change considerably when we play with settings. This is very good because even if you try to fine tune a set of settings to the past, the probability that it keeps working in the future is rather high.
Very important note: the calculations DO NOT take into account any fee or slippage that you always experience on the exchanges.
The indicators only uses real time data, therefore it can’t repaint.
There are absolutely no guarantees about this algorithm and past results are not indicative of future performance.
Fees, slippage and API delay: for any algorithm you will use (from me or others), please keep in mind that fees add up, slippage and delay creates differences between algo theory and reality. We can put in place systems to circumvent that, but we will always have them.
BB + RSI double strategy developeI'm Korean, and it may not be enough to explain this script in English. I feel sorry for the users of TradingView for this lack of English skills. If you are Korean, please return it to the translator using Papago. It will be a useful manual for you.
This script referenced Chartart's Double Strategy. But there are some changes in his script.
0. Basically, when you break through the top or bottom of the 100th period balliser band and come back into the band, you track the overbuying and overselling of the RSI to determine your position entry. The order is triggered only when both conditions are satisfied at the same time. However, only one condition applies to clearing the position. This is because it is most effective in reducing risk and increasing assets in terms of profit and loss.
1. This script is optimized for 15 minutes of bitcoin futures chart and API via webbook alert. By default, 10x leverage usage and 10 pyramids are applied.
2. Setting a chart period other than 15 minutes will not guarantee sufficient effectiveness. It can also be applied to Ethereum , but it is not recommended to apply to other symbols.
3. I added Enable Date Filter because Chartart's script could not apply the strategy to the user's desired period. This feature allows you to set a period of time when you do not want to use the strategy. You can also uncheck it if you don't want to fully use this feature. Please remember that it is an exclusion period, not a usage period. With this feature, we can see the effectiveness of the strategy from a point in time, not from the entire period. You can also clearly differentiate the effectiveness of the strategy from the point you use it.
4. You can also stop using strategies at certain times of the day when you don't want to apply them. This works similarly to the Enalbe Date Filter described above. This allows you to sleep comfortably even if you don't fully trust this strategy.
5. The period, overbuying, and overselling figures of RSI can be set individually. For example, when you take a long position, you can set the RSI to a period of 7, and at the same time, the RSI entering the short position can be set to a period of 14. You can also set the base figures for overbuying and overselling to levels that you think are reasonable. This figure works in conjunction with the Bollinger Band and affects position entry when it is crossed or returned.
6. Based on API futures trading, basic Sleepy and commission are applied. This is geared towards market price transactions. This makes your revenue look more reasonable.
Thank you very much, Chartart. You are a genius.
-
저는 한국인이고, 영어로 이 스크립트를 설명하는 것이 어렵기 때문에 설명이 부족할 수 있습니다. 이런 영어 능력 부족에 대해서 TradingView 사용자들에게 미안하게 생각합니다. 만약 당신이 한국인이라면 파파고를 사용하여 번역기에 돌려주십시오. 당신에게 유익한 설명서가 될 것입니다.
이 스크립트는 Chart art의 Double Strategy를 참조했습니다. 그러나 그의 스크립트에서 달라진 점이 몇 가지 있습니다.
0. 기본적으로 100기간의 볼린져밴드의 상단 또는 하단을 돌파한 뒤 다시 밴드 안으로 들어올 때 RSI의 과매수, 과매도를 추적하여 포지션 진입을 결정합니다. 두 가지 조건이 동시에 만족되어야만 주문이 트리거 됩니다. 그러나 포지션을 청산하는 것에는 볼린져밴드 하나의 조건만 적용합니다. 여러가지 테스트를 거친 결과 이것이 손익 면에서 가장 효과적으로 리스크를 줄이고 자산을 늘리는 것에 효율적이기 때문입니다.
1. 이 스크립트는 15분의 비트코인 선물 차트와 webhook alert을 통한 API에 최적화되어 있습니다. 기본적으로 10배의 레버리지 사용과 10개의 피라미딩이 적용되어 있습니다.
2. 15분 외에 다른 차트 기간을 설정한다면 충분한 효과를 보장할 수 없습니다. 또한 이더리움에도 적용할 수 있지만, 그 외에 다른 심볼에는 적용하지 않는 것을 권장합니다.
3. Chart art의 스크립트는 전략을 사용자가 원하는 기간에 적용할 수 없었기 때문에, 저는 Enable Date Filter를 추가하였습니다. 이 기능을 통해 전략 사용을 원하지 않는 기간을 설정할 수 있습니다. 또한 이 기능을 완전히 사용하고싶지 않다면 체크를 해제할 수 있습니다. 사용 기간이 아닌 제외 기간인 점을 상기하시길 바랍니다. 이 기능을 통해 우리는 전체 기간이 아닌 가까운 특정 시점부터의 전략 적용 효과를 확인할 수 있습니다. 또한 사용자가 전략을 사용한 시점부터의 효과를 명백히 구분할 수 있습니다.
4. 또한 사용자가 적용을 원하지 않는 하루 중의 특정 시간대에 전략 사용을 멈출 수도 있습니다. 이는 위에 설명한 Enalbe Date Filter와 유사하게 작동합니다. 이를 통해 당신이 온전히 이 전략을 신뢰하지 못하여도 당신은 마음 편하게 잠에 들 수 있습니다.
5. RSI의 기간 및 과매수, 과매도 수치를 개별적으로 설정할 수 있습니다. 예를 들어 당신이 롱 포지션을 취할 때에는 RSI를 7의 기간으로 설정할 수 있고, 동시에 숏 포지션을 진입하는 RSI는 14의 기간으로 설정될 수 있습니다. 또한 과매수 및 과매도의 기준 수치를 당신이 합리적이라고 생각하는 수준으로 설정할 수 있습니다. 이 수치는 볼린져밴드와 함께 작동하여 그것을 넘어서거나 다시 되돌아올 때 포지션 진입에 영향을 미칩니다.
6. API 선물거래를 기준으로 하여 기본적인 슬리피지와 커미션이 적용되어있습니다. 이는 시장가 거래에 맞춰져 있습니다. 이는 당신의 수익을 좀 더 합리적인 수치로 보일 수 있게 합니다.
Chartart에게 특별히 감사합니다. 당신은 천재입니다.
Fukuiz Octa-EMA + Ichimoku (Strategy)This strategy is based EMA of 8 different period and Ichimoku Cloud which works better in 1hr 4hr and daily time frame.
#A brief introduction to Ichimoku #
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.
#A brief introduction to EMA#
An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average . An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average ( SMA ), which applies an equal weight to all observations in the period.
#How to use#
The strategy will give entry points itself, you can monitor and take profit manually(recommended), or you can use the exit setup.
EMA (Color) = Bullish trend
EMA (Gray) = Bearish trend
#Condition#
Buy = All Ema (color) above the cloud.
SELL= All Ema turn to gray color.
