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 -_- *
Search in scripts for "bitcoin"
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!
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.
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
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.
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.
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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.
RSI correlation with cryptoindices [strategy version]Dear TV'ers,
Hereby the strategy script where the RSI of an altcoin can be compared to one of the selected cryptocap indices. Included are:
-total market cap
-total market cap minus bitcoin
-total market cap others
-total market cap usdt
-cix100 index
-btc dominance
-btc total cap
If the signal crosses over 1, then the altcoin is undervalued compared to the crypto index (and considered a buying signal here). If the signal crosses under 1, then the altcoin is overvalued compared to the selected crypto-index and a short signal is produced.
!!Please note that the selected timeframe for the reference pair should be a higher time of the chart in order to prevent repainting!!!
[MACLEN] TRUE RANGEThis is a true range (TR) based strategy with weighted moving average (WMA) smoothing to remove noise.
In addition, it includes a risk management strategy using 4 "safes" in the same operation to always seek to make a profit.
This is for evaluation only, and it is not recommended to use with real money.
It is a work in progress. I read your comments.
Follow the Crypto ShortsThis script allows to test the impact of variations in the number of BTCUSD Shorts Positions on its price. In particular, it compares the number of short positions with its moving average to decide if shorts are being liquidated. In case the number of short positions crosses below its moving average, it will generate a Long Position, which will be closed if shorts crosses above its moving average.
BEAM DCA Strategy MonthlyThis strategy is based on BEAM bands for BTC. The space between the original BEAM bands is broken up into 10 bands representing levels of risk for investing fresh capital.
The strategy will buy bitcoin when the price is in the bottom 5 bands, increasing the amount investmented as the price approaches the 1400 D SMA.
The strategy will limit sell bitcoin when the price is in the top 5 bands, increasing the amount sold as the price approaches the upper BEAM band.
Best used on Daily timeframe and on a chart with history of price data, i.e. INDEX:BTCUSD or BITSTAMP:BTCUSD
To use the strategy:
Set start date
Set day of month to invest
Set the maximum amount to be invested on any given month
Toggle buy/sell orders
Observe the backtest
You can see how the strategy backtests via the information boxes in the bottom right.
There is also functionality to adjust the bands for diminishing returns. Note, this should be used with great skepticism, as the adjustments were made by simple function fitting and not rigorous statistical processes.
That about sums it up! As you can see, even with just a small amount of capital invested at regular intervals can lead to huge realised gains using this version of BEAM bands!
MA Bollinger Bands + RSI This script uses the standard deviation of a given moving average along with an RSI direction.
When: rsi crossover neutral line + price crossover lower deviation boundary => long
When: rsi crossunder neutral line + price crossunder upper deviation boundary => short
Linear Regression Channel Breakout StrategyThis strategy is based on LonesomeTheBlue's Linear Regression Channel Indicator. First of all, I would like to thank LonesomeTheBlue. Breaking the Linear Regression Channel to close the candle triggers a Long or Short signal. If the slope of the Linear Regression Channel is positive, it is Short when it breaks out the lower line, and when the slope is negative, it is Long when it breaks out the upper line. The default is optimized for 8-hour candles, and for other hour candles, find the optimal value yourself. Below is a description of LonesomeTheBlue's Linear Regression Channel.
이 전략은 LonesomeTheBlue의 Linear Regression Channel Indicator를 기반으로 만들어졌습니다. 우선 LonesomeTheBlue님께 감사의 말씀을 드립니다. Linear Regression Channel을 돌파하여 봉 마감하면 Long 또는 Short 신호를 트리거합니다. Linear Regression Channel의 기울기가 양인 경우 하단 라인을 돌파하면 Short이고 그 기울기가 음인 경우 상단 라인을 돌파하면 Long입니다. 기본값은 8시간봉에 최적화 되어 있으며, 다른 시간봉은 직접 최적값을 찾아보십시오. 아래는 LonesomeTheBlue의 Linear Regression Channel에 대한 설명을 퍼왔습니다.
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There are several nice Linear Regression Channel scripts in the Public Library. and I tried to make one with some extra features too. This one can check if the Price breaks the channel and it shows where is was broken. Also it checks the momentum of the channel and shows it's increasing/decreasing/equal in a label, shape of the label also changes. The line colors change according to direction.
using the options, you can;
- Set the Source (Close, HL2 etc)
- Set the Channel length
- Set Deviation
- Change Up/Down Line colors
- Show/hide broken channels
- Change line width
meaning of arrows:
⇑ : Uptrend and moment incresing
⇗ : Uptrend and moment decreasing
⇓ : Downtrend and moment incresing
⇘ : Downtrend and moment decreasing
⇒ : No trend
No-lose trading targets (Based on EoRfA) By Mustafa ÖZVERI simulated the NLTTa_EoRfA indicator with the Bitcoin-USD
For details about the indicator, visit my profile on tradingview
For Simulation, with default settings, we order
When on Long setup and price on green area
- open a long position that closes on red area
When on Short setup and price on red area
- open a short position that closes on green area
And we got
- about 15% profit
But only this value can not guarantee good results for trading. BE CAREFUL
Swing Multi Moving Averages Crypto and Stocks StrategySimple and efficient multi moving average strategy combined with risk management and time condition.
Indicators/ Tools used
Multi selection moving average type like SMA , EMA , SMMA , VWMA , VIDYA , FRAMA , T3 and much more
Limit 1 entry max per week, entry on monday exit on sunday or risk management tp/sl.
Rules for entry:
LONG:Close of the candle cross above the moving average while the previous close was below. All of this is happening during monday session.
SHORT:Close of the candle cross below the moving average while the previous close was above. All of this is happening during monday session.
Rules for exit:
We exit either on sunday or if we reach tp/sl levels.
Observations:
I recommend use the strategy 2 types, one for long and another for short, using different parameters since long and short movements behave differently.
For example for long we can use a shorter moving average longth and a higher tp/sl while for short we can use a bigger moving average length and a smaller tp/sl
If you have any questions let me know !
Orion Algo Strategy v2.0Hi everyone.
I decided to make the latest Orion Algo open to people. I don't have enough time to work on it lately, so I figured it would be best that everyone can have it to work on it. I took out some stuff from the original but it should give an idea on how things work. I made two strategies with this so far so you can use that to come up with your own. I recommend the DCA strategy because it gives you the most bang for Orion Algo's buck. It's pretty good at finding long entries.
Overall I hope you guys like this one. Also, Banano is the best crypto currency :)
-INFO-
Orion Algo is a trading algorithm designed to help traders find the highs and lows of the market before, during, and after they happen. We wanted to give an indicator to people that was simple to use. In fact we created the algorithm in such a way that it currently only needs a single input from the user. Since no indicator can predict the market perfectly, Orion should be used as just another tool (although quite a sharp one) for you to trade with. Fundamental knowledge of price action and TA should be used with Orion Algo.
Being an oscillator, Orion currently has a bias towards market volatility . So you will want to be trading markets over 30% volatility . We have plans to develop future versions that take this into account and adjust automatically for dead conditions. Also, while there are some similarities across all oscillators, what sets ours apart is the prediction curve. The prediction curve looks at the current signal values and gives it a relative score to approximate tops and bottoms 1-2 bars ahead of the signal curve. We also designed a velocity curve that attempts to predict the signal curve 2+ bars ahead. You can find the relative change in velocity in the Info panel. The bottom momentum wave is based on the signal curve and helps find overall market direction of higher time-frames while in a lower one.
Settings and How to Use them:
User Agreement – Orion Algo is a tool for you to use while trading. We aren’t responsible for losses OR the gains you make with it. By clicking the checkbox on the left you are agreeing to the terms.
Super Smooth – Smooths the main signal line based on the value inside the box. Lower values shift the pivot points to the left but also make things more noisy. Higher values move things to the right making it lag a bit more while creating a smoother signal. 8 is a good value to start with.
Theme – Changes the color scheme of Orion.
Dashboard – Turns on a dashboard with useful stats, such as Delta v, Volatility , Rsi , etc. Changing the value box will move the dashboard left and right.
Prediction – A secondary prediction model that attempts to predict a reversal before it happens (0-2bars). This can be noisy some times so make your best judgement. Curve will toggle a curve view of the prediction. Pivots will toggle bull/bear dots.
∆v – Delta v (change in velocity). This shows momentum of the signal. Crossing 0 signals a reversal. If you see the delta v changing direction, it may signify a reversal in the several bars depending on the overall momentum of the market.
Momentum Wave – Uses the signal as a macro trend indicator. Changes in direction of the wave can signify macro changes in the market. Average will toggle an averaging algorithm of the momentum waves and makes it easy to understand.
-STRATEGIES-
Simple - Just buy and sell on the dots
DCA - Uses the settings in the script for entries. If a buy dot appears then it will buy, if the price goes below the percentage it will wait for another dot before entering. This drastically improves DCA potential.
Bagheri IG Ether v2In this version, the winning ratio has been decreased, but the Risk to Reward Ratio (RRR) has been set to be better than the previous version.
This is a technical trading strategy for Ethereum ( BINANCE:ETHUSDT ). We built and developed it on MetaEditor and optimized it with MetaTrader optimizer.
The main indicators are Donchian Channel, Oscillator of ROC , Bears Power, Balance of Power , and Simple Moving Average ( SMA ). Default values in the input panel are the best combination of these indicators, but you can change any of them and try it for better results.
Please notice that this strategy has been optimized on the 1-minute chart of Ethereum .
For each position, you can see the Take Profit (TP) and Stop Loss (SL) levels. Also, you can find the values of mentioned TP and SL in points from the input panel of the script.
Attention: The price of Ethereum has 2 decimal places.
Therefore, 3000 points for TP means 30 USDT for trading 1 BINANCE:ETHUSDT .
MACD + DMI Scalping with Volatility Stop by (Coinrule)Trend-following strategies are cool because they allow you to catch potential high returns.
The main limit of such strategies are:
False signals > the asset is not experiencing a strong trend. The strategy gets stuck with a sideways move or, worst, with the beginning of a downtrend.
The sell signal may come later than the actual top, leading in some cases to turn a trade in profit into a loss.
This strategy tries to address these limitations to develop a trading system that optimises the entry and closes trade once the profit achieves a pre-set level.
ENTRY
The trading system uses the MACD and the DMI to confirm when is the best time for buying. Combining these two indicators prevents trading during downtrends and reduces the likelihood of getting stuck in a market with low volatility.
The system confirms the entry when:
The MACD histogram turns bullish.
When the positive DMI is greater than the negative DMI, there are more chances that the asset is trading in a sustained uptrend.
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:
The price increases by 3%
The price crosses below the volatility stop.
The best time frame for this strategy based on our backtest is the 3-hr . The 4-hr can work well. In general, this approach suits medium to long term strategies
The strategy assumes each order to trade 30% of the available capital to make the results more realistic. 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.
WEEKLY BTC TRADING SCRYPTWeekly BTC Trading Scrypt(WBTS)
This script is only suggested for cryptocurrencies and weekly buying strategy which is long term.Using it in another markets(e.g forex,stock,e.t.c) is not suggested. The thing makes it different than other strategies we try to understand bull and bear seasons and buying selected crypto currency as using formula if weekly closing value crossover eight weeks simple moving avarage buy,else if selected crypto currency's weekly closing value crossunder eight weeks simple avarage sell. Eight week moving avarage is also uses weekly closing prices but for being able to use this strategy ,trading pair must have more than eight candles in weekly chart otherwise the 8 weeks simple moving avarage value cannot be calculated and script does not work.
This script has a chart called WBTS and it has following features:
Strategy group consist of 3 inputs:
1)Source: Close by default. Our whole strategy uses close values. You can change it but not suggested.
2)Loss Ratio: Because of the cases like the circumstances that manipulates market or high volatility , sometimes graphic show wrong buying signals and this ratio saves user from big money looses(Note : This ratio will always work when selling condition occurs to make user take his profit or prevent him to loss more money because of a wrong positive comes from the indicator.)
3)Reward Ratio : When selling condition happens it will exit user with more profit(if price is already higher than buying point) otherwise it will dimunish loss a bit(if user is below of buying point) or prevents looses(if user is in buying point when selling condition happened.
MA group consist of 2 inputs:
COLOR:Specifies color of the moving avarage.It is equal to #FF3232by hex color code by default.
LINE WIDTH: Specifies linewidth of the moving avarage. It is 2 by default.
GRAPHIC group consist of 2 inputs:
COLOR: It specifies the color of the line which consist of weekly closing prices. It is equal to #6666FF hex color code by default.
LINE WIDTH: Specifies linewidth of the line which consist of weekly closing prices. It is 2 by default.
STRATEGY EXECUTION YEAR: It will show the orders,profits and looses done by script after the input year giving in it.It is 2020 by default.
The last feature is strategy equity,it is not in one of these groups. User should click on settings button on the WBTS indicator than chose Style section and there is a deactivated check box near in the plot section if user activate it, the equity line will show in indicator's graph.
Logic of This Strategy:The story of this strategy began when I studied BTC's price movement from 2020 to today with 8 weeks simple moving avarage (it takes weekly closes as source) and weekly clossing values. I understood that there was a perfect interest between bull and bear market and following conditions:
buy_condition=crossover(weekly_closing_values,8_week_simple_moving_avarage)
sell_condition=crossover(weekly_closing_values,8_week_simple_moving_avarage)
and I tried same thing on the same and bigger time frames("for example i studied how the strategy works from the beginning to today with bitcoin and what is our final equity") with bitcoin and other cryptocurrencies and this made me saw better the relation between giving conditions and general market psychology, however I also witnessed some wrong positives coming by script and used a risk reward ratio to save user and set risk reward ratio 1/3 after a research.
For both conditions(buy_condition and sell_condition),when they are realised,script will alert users and an order will be triggered.
Before finishing the description,from settings/properties/ user can set initial capital,base currency,order size and type,but it is 100000 for initial_amount and 1 contract for order size by default.
In backtesting I used the options like the following example :
Initial capital=1000
Base_curreny=USD
Order size=40 USD
Properties place must set different by every single user according to his or her capital and order size must not be higher than his total money because this script is not the best or a good script for derivatives. It is only written for long term-crypto spot trading and I strongly recommend to users that margin may cause bad results and please do not use it with any margin or any market different than crypto market.
Thank you very much for reading)
