SPX Scalping StrategyThis strategy points out good entries and exits to go with the direction of SPY
Used with:
Ticker: SPX 500 USD
Heiken Ashi Candles
1, 3, 5 min timeframe
Đường Trung bình trượt Đơn giản (SMA)
Sig30MALICEHello everyone
Bot is optimalized BINANCE:ALICEUSDTPERP BOT, which select leverage betwen 2x and 4x
TimeFrame : 30min
TP : 80 point
SL : 120 point
the bot works as follows:
the way he opens a position consists of two conditions
1) Moving average (crossovers)
2) RSI
Backtesting is set for counting as 13 contrat, this bot can get more with 50% of equity.
I think this is really solid 30min bot, which is already really important to make something solid on 30min
However keep in mind this is scalper and optimalization scalpers are really hard and have to be set from time to time
This bot is also great for other optimalizations .
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Enjoy
Cheat Code- Example 1; Short-Term; Follow the Trend BINANCE:BTCUSDT ; BINANCE:ETHUSDT ; BINANCE:FILUSDT ;
This strategy is simple and easy to read and takes advantage of conditional signs of trend reversals. It works best in 10-minute time frames for most large and mid-cap crypto. This code is a tutorial for creating a profitable yet easy strategy, and hopefully, it can be put to good use :)
Optimizer ~ Beta 0.1 | Belfort TradersOptimizer
The Optimizer backtests the maximum amount of moving averages which can be possible created ((max amount of bars / 2)-1) and compares them all with one another to then plot the most profitable strategy.
Current Achievement:
-> Get it to work, make it work with 106 different moving averages. ==> Beta 0.1
Roadmap:
0.15 Basic Comparison of 5k moving averages <= 07.06.22
0.2 Risk Management Basics <= 07.06.22
0.3 Finding the most profitable timeframe <= 07.06.22
0.4 Testing the limits of Tradingview <= 14.06.22
0.5 Complex array sorting list, comparing 1k moving averages, taking the most profitable out, going to the next list ==> Bypassing calculation limit by doing that. <= 14.06.22
0.6 Volatility adjusted moving averages <= 14.06.22
==> Find more likely profitable moving averages, run those first -> Increase efficiency
0.7 Add second filter (Either most profitable strategy or most reliable strategy) ==> Order Frequency Ratio <= 14.06.22
0.8 Complex Risk Management <= 14.06.22
0.9 Reliability Ratio weekly volatility average filter used as a protective filter if current weekly volume is drastically different from the past's weekly volatility average with fractal patterns
<= 21.06.22
1.0 Finished Optimizer
Portfolio Management for this Performance:
Initial Capital: 20000 USD
Risk per Trade: 10% of capital
Commission: 0.01%
Slippage: 4 ticks
DaveStratThis script attempts to guess inflection points in cryptocurrency asset prices using change in two simple moving averages on the daily timescale.
Moving Average Crossover StrategyThe Moving Average Crossover indicator uses 3 moving averages (2 simple moving averages and 1 exponential moving average ) to signal long and short opportunities based on moving average crossovers. This strategy serves as a backtest to that indicator. By taking entry and exit positions based on moving average crossovers, we are able to project profit with this script. You are given the option to select which moving average crossings trigger entry and exit signals. Fast refers to an EMA which should be your shortest MA. Slow refers to the first SMA which will serve as a signal line. Trend refers to a long SMA which will help determine if you should take long positions or short. You can also filter by extra conditions such as minimum volume or RSI. For example, you may have the script trigger a buy signal if the 5ema crosses the 20 sma while RSI reads 60 and sell if it crosses again.
This strategy starts with $100,000 and uses 10% of the account per trade.
Estrategia Larry Connors [JoseMetal]============
ENGLISH
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- Description:
This strategy is based on the original Larry Connors strategy, using 2 SMAs and RSI.
The strategy has been optimized for better total profit and works better on 4H (tested on BTCUSDT).
LONG:
Price must be ABOVE the slow SMA.
When a candle closes in RSI oversold area, the next candle closes out of the oversold area and the closing price is BELOW the fast SMA = open LONG.
LONG is closed when a candle closes ABOVE the fast SMA.
SHORT:
Price must be BELOW the slow SMA.
When a candle closes in RSI overbought area, the next candle closes out of the overbought area and the closing price is ABOVE the fast SMA = open SHORT.
SHORT is closed when a candle closes BELOW the fast SMA.
*Larry Connor's strategy does NOT use a fixed Stop Loss or Take Profit, as he said, that reduces performance significantly.
- Visual:
Both SMAs (fast and slow) are shown in the chart.
By default, the fast SMA is aqua color, the slow changes between green and red depending on the "trend" (price over slow SMA = bullish, below = bearish).
RSI can't be shown because TradingView doesn't allow to show both overlay and panel indicators, so candles get a RED color when RSI is in OVERBOUGHT area and GREEN when they're on OVERSOLD area to help with that.
Background is colored when conditions are met and a position is going to be open, green for LONGs red for SHORTs.
- Usage and recommendations:
As this is a coded strategy, you don't even have to check for indicators, just open and close trades as the strategy shows.
The original strategy uses a 5 period SMA instead of the 10, and 10/90 for oversold/overbought levels, this has been optimized after the testings and results but feel free to change settings and test by yourself.
Also, the original strategy was developed for daily, but seems to work better en 4H.
- Customization:
As usual I like to make as many aspects of my indicators/strategies customizable, indicators, colors etc., feel free to ask if you feel that something that should be configurable is missing or if you have any ideas to optimize the strategy.
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ESPAÑOL
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- Descripción:
Esta estrategia está basada en la estrategia original de Larry Connors, utilizando 2 SMAs y RSI.
La estrategia ha sido optimizada para un mejor beneficio total y funciona mejor en 4H (probado en BTCUSDT).
LONG:
El precio debe estar por encima de la SMA lenta.
Cuando una vela cierra en la zona de sobreventa del RSI, la siguiente vela cierra fuera de la zona de sobreventa y el precio de cierre está POR DEBAJO de la SMA rápida = abre LONG.
Se cierra cuando una vela cierra POR ENCIMA de la SMA rápida.
SHORT:
El precio debe estar POR DEBAJO de la SMA lenta.
Cuando una vela cierra en la zona de sobrecompra del RSI, la siguiente vela cierra fuera de la zona de sobrecompra y el precio de cierre está POR ENCIMA de la SMA rápida = abre SHORT.
Se cierra cuando una vela cierra POR DEBAJO de la SMA rápida.
*La estrategia de Larry Connor NO utiliza un Stop Loss o Take Profit fijo, como él dijo, eso reduce el rendimiento significativamente.
- Visual:
Ambas SMAs (rápida y lenta) se muestran en el gráfico.
Por defecto, la SMA rápida es de color aqua, la lenta cambia entre verde y rojo dependiendo de la "tendencia" (precio por encima de la SMA lenta = alcista, por debajo = bajista).
El RSI no puede mostrarse porque TradingView no permite mostrar tanto los indicadores superpuestos como los del panel, así que las velas obtienen un color ROJO cuando el RSI está en el área de SOBRECOMPRA y VERDE cuando están en el área de VENTA para ayudar a ello.
El fondo se colorea cuando se cumplen las condiciones y se va a abrir una posición, verde para LONGs rojo para SHORTs.
- Uso y recomendaciones:
Como se trata de una estrategia ya programada, ni siquiera hay que comprobar los indicadores, sólo hay que abrir y cerrar las operaciones tal y como muestra la estrategia en el gráfico.
La estrategia original utiliza una SMA de 5 periodos en lugar de 10, y 10/90 para los niveles de sobreventa/sobrecompra, esto ha sido optimizado después de las pruebas y los resultados, pero sé libre de cambiar la configuración y probarla por sí mismo.
Además, la estrategia original fue desarrollada para diario, pero parece funcionar mejor en 4H.
- Personalización:
Como siempre me gusta hacer personalizables todos los aspectos de mis indicadores/estrategias, indicadores, colores, etc., preguntar si notas que falta algo que debería ser configurable o si tienes alguna idea para optimizar la estrategia.
Uptrend and Oversold Index Swing Trading System 8H--- Foreword ---
The Overbought and Oversold Index Swing Trading System or short: I11L Hypertrend primarily uses money management Strategies, EMA and SMA and my momentum Ideas for trying to produce satisfactory Alpha over a timespan of multiple years.
--- How does it Work? ---
It uses 20 different EMA's and SMA's to produce a score for each Bar.
It will credit one Point If the EMA is above the SMA.
A high score means that there is a strong Uptrend.
Spotting the strong Uptrend early is important.
The I11L Hypertrend System trys to spot the "UPTREND" by checking for a crossover of the Score(EMA) / Score(SMA).
A low score means that there is a strong Downtrend.
Its quite common to see a reversal to the mean after a Downtrend and spotting the bottom is important.
The System trys to spot the reversal, or "OVERSOLD" state by a crossunder of the Score(EMA) / Score(SMA).
--- What can i customize? ---
-> Trading Mode: You can choose between two different trading modes, Oversold and Overbought(trend) and Random Buys to check if your systems Profitfactor is actually better then market.
-> Work with the total equity: The system uses the initial capital per default for Backtesting purposes but seeing the maximum drawdown in a compounding mode might help!
-> Use a trailing SL: A TSL trys to not lose too much if the trade goes against your TP
-> Lookbackdistance for the Score: A higher Lookbackdistance results in a more lagging indicator. You have to find the balance between the confirmation of the Signal and the frontrunning.
-> Leverage: To see how your strategie and your maximum Drawdown with the total equity mode enabled would have performed.
-> Risk Capital per Trade unleveraged: How much the underlying asset can go against your position before the TSL hits, or the SL if no TSL is set.
-> TPFactor: Your risk/reward Ratio. If you risk 3% and you set the ratio to 1.2, you will have a TP at 3 * 1.2 = 3.6%
-> Select Date: Works best in the 8H Timeframe for CFD's. Good for getting a sense of what overfitting actually means and how easy one can fool themself, find the highest Profitfactor setting in the first Sector (Start - 2012) and then see if the second Sector (2012 - Now) produces Alpha over the Random Buy mode.
--- I have some questions about the System ---
Dear reader, please ask the question in the comment Section and i will do my best to assist you.
rsisma imkind dailyrsi 14
sma 8
time fram : weekly and daily
rsi 14
sma 8
time fram : weekly and daily
rsi 14
sma 8
time fram : weekly and daily
rsi 14
sma 8
time fram : weekly and daily
Long Term Heat/Volatility - Accumulation/Distribution v1This is a strategy specifically made for 1D BTC/USD with the aim of capturing cycle tops and bottoms. It's mainly based on two indicators: 21d average of ATR (volatility) and (BTC.price - 180d sma)/BTC.price (heat). The strategy only signals buys or sells after occurrences of high volatility, followed by extremely high or low heat values. It's optimized for utilizing accumulation and distribution at lower and higher prices respectively with respect to last 14 days. 2nd version will include dynamic dollar cost averaging during the accumulation and distribution periods.
Mix1 : Ema Cross + Trend Channel [Gu5] - BacktestBacktest of the indicator "Mix1: Ema Cross + Trend Channel "
Trend indicator, by the crossing of moving averages
SMA200 with a channel as a filter confirms the trend.
The crossing of two moving averages, give alert only in trend.
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
Dollar cost averaging This is a testing startergy based on dollar cost averaging and sell on high points.
MA_Script- Entry Point : base on MA20, MA50, MA100, MA200.
- Exit Point : base on stop loss, MA and trailing stop.
NRTH_ Momentum AlgoA NRTH_ Premium Momentum Based Strategy
Comes included with the Premium Package.
Indicator features
Built-In Alerts
Visual Risk Management
Customizable Entry Rules
4 Levels of confirmation
Customizable MA Ribbon
Usage Tips
This strategy is designed for Swing Trading and Intra-Day timeframes (1hr+)
The Algo uses multiple levels of convolution and confirmation before entering a trade, best used in trending markets. utilizing Stochasitc RSI overbought and oversold levels and an 1-3 MAs to identify trends and pullbacks.
Maximize the accuracy of your signals with up to 4 levels of convolution before entering a trade, filtering out the noise as much as possible.
You can set the overbought and oversold levels required for trade entries and set the types of MAs and how many are required to confirm trending momentum
Works for all markets with the ability to customize to your liking.
Backtesting Results Info
Period 23/9/2021-15/11/2021
Entry value at $1000 with 10x leverage
Binance standard taker fee rate (0.04%)
ATR Exits : 1:2.66 RR
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Disclaimer
Copyright NRTH_ Indicators 2021.
NRTH_ and all affiliated parties are not registered as financial advisors. The products & services NRTH_ offers are for educational purposes only and should not be construed as financial advice. You must be aware of the risks and be willing to bear any level of risk to invest in financial markets. Past performance is not necessarily indicative of future results. NRTH_ and all individuals associated assume no responsibility for your trading results or investments.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
RSI & SMA Strategy By DenizIntroduction
It has always been a major challenge to detect the current market price in technical analysis . There are some basic but strong indicators that help us to estimate the next market action. Relative Strength Index and Simple Moving Average indicators were used in this strategy.
This strategy aims to detect the next market action with different calculations & usages of RSI and SMA indicators.
Strategy Features
As per the result of the calculation from RSI and SMA outputs the strategy will decide to go "Long" or "Short" if the directions are changed from long to short the trade will be closed and it's opening new trade as per to the new direction.
Apart from basic "take profit" and "stop" options there is an additional closing trade option named "Long/Short Bar Count". If the trade could not reach the target in a certain period, it will look for a quit with a 0 loss.
Advantages
Informative alarm messages.
High ratio of Profitable trade numbers.
Disadvantages
Less trade count.
Mean Reversion Strategy v2 [KL]Description :
This strategy will enter a position when the following conditions are met:
a) Main signal: When source data (ATR) diverts from its moving average value, and
b) Confirmation: If predicted direction of trend is favorable.
Assumptions :
During periods of high price volatility, ATR diverts from its moving average value. Eventually, ATR should revert. But since just knowing the magnitude of increase/decrease of ATR does not indicate a trend signal, we need to introduce a model to predict the current trend.
In short:
• Trend Prediction : This strategy calculates the expected logarithmic return of the security (the "Drift") and considers prices to be moving in uptrend if the drift curve is upward sloping.
• Assessment of ATR diversion : To determine "yes/no" regarding whether ATR at a given point in time has diverted, this script conducts a two-tailed hypothesis test at each candlestick period. The null hypothesis (H0) is that the fast moving average value should equal the slow moving average value (say, denoted as H0: atr14 == atr28; it is assumed that atr28 is more meaningful for the purpose of describing the current trend because it has a larger sample size). Investopedia has an article summarizing this topic .
Exit Condition :
When trailing stop loss hits.
Previous version :
This strategy is based on Version 1 published back in September . This older version considers +/- one standard deviation to be the critical values relative to average ATR when testing whether ATR has diverted from the mean. This does not take Standard Error ("SE") into account. As a result, the threshold is often too wide and it generates too many entry signals.
Arch1tect's New Toy (Strategy Tester Version)Description:
The version of Arch1tect's New Toy indicator with Strategy Tester added.
This indicator tries to predict market trends by simply utilising 2 moving averages crossovers.
How it works:
Buy signals are triggered when the faster MA crosses over the slower MA from the downside to the upside.
Sell signals are triggered when the faster MA crosses under the slower MA from the upside to the downside.
How to use:
Take buys when buy signal is triggered AND close existing sell position
Take sells when sell signal is triggered AND close existing buy position
Note:
Settings are optimised for XAUUSD on the M1 chart.
Extra:
Alerts are included.
You can toggle between EMA, WMA and SMA to your liking.
Indicator version:
Moving Average Band - Taylor V1A Very Simple Strategy From Moving Average
- Price Breakout Upper Band = Long
- Price Breakout Lower Band = Short
Moving Average Type = Able to Change RMA, EMA, SMA, WMA
Moving Average Period = Able to Change
Upper Band & Lower Band Gap = Able to Change
With Stop Lose & Take Profit = Able to Change
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 .
[KL] Double Bollinger Bands Strategy (for Crypto/FOREX)This strategy uses a setup consisting of two Bollinger Bands based on the 20 period 20-SMA +/-
(a) upper/lower bands of two standard deviations apart, and
(b) upper/lower bands of one standard deviation apart.
We consider price at +/- one standard deviation apart from 20-SMA as the "Neutral Zone".
If price closes above Neutral Zone after a period of consolidation, then it's an opportunity for entry. Strategy will long, anticipating for breakout.
The illustration below shows price closing above the Neutral Zone after a period of consolidation.
a.c-dn.net
Position is exited when prices closes at Neutral Zone (being lower than prior bars)
Rate of Change StrategyThis strategy calculates the rate of change over time to determine buy/sell points. This strategy is best run with 1 hour candles .
Configurable values:
SMA Fast (days)
SMA Slow (days)
SMA Reference (days)
ROC Low (%)
ROC High (%)
Order Stake (%)
Look back Candles
SMA Offset StrategyThis strategy uses simple moving averages and some math to determine buy/sell points. We keep a SMA 100 day line as our basis for our offset. If the close price is below the line, we choose our open position based on how low below the line it is goes, this value (Low Offset) is a percentage and can be configured by the user. Same for closing your position, when the close is above our SMA 100 line, we determine how high above the line before selling. If we try to sell too early (while the price is still rising), the trailing stop loss will kick in. Backtested with Bitcoin and Ethereum.
Configurable variables:
SMA Fast (default is 14 days)
SMA Slow (default is 100)
SMA Reference (default is 30)
Low Offset % (default is 0.001)
High Offset % (default is 0.0164)
Order Stake % (default is 0.96)
Trailing stop loss % (default is 1.35)
