Double Inside Bar & Trend Strategy - KaspricciDouble Inside Bar & Trend Strategy - Kaspricci
This strategy combines the Double Inside Bar candlestick pattern with a trend filter. Once the second inside bar closes and price is above trend moving average, a buy stop order is placed at high of the candle. If price is below trend moving average, a sell stop order is placed at the low of the candle.
This strategy is for educational purposes only! It is not meant to be a financial advice.
Settings
Trend source, type of moving average and length for calculating trend
Stop Loss Type - default: ATR. You can switch between stop loss calculation based on Average True Range value or fixed value.
ATR Length / Factor / TP Ratio - default: 14 / 2.0 / 2.0. Used to calculate the Stop Loss as ATR * Factor and Take Profit as Stop Loss * TP Ratio.
FIX Stop Loss / Take Profit - default: 10 pips / 20 pips. In case you select Stop Loss Type = FIX, these value swill be used.
Risk in % - default: 1%, option to adjust the quantity of a trade based on a defined risk percentage. If enabled, it will overwrite the quantity parameter of the strategy settings.
On top you can filter trades by start and end date as well as time of the day.
Medie mobili
EMA RSI Strategy
Simple strategy
=============
If the last two closes are in ascending order, the rsi is below 50 and ascending, and the current candle is above 200 ema, then LONG. If the last two closes are in descending order, the rsi is above 50 and descending, and the current candle is below 200 ema, then SHORT.
LONG Exit strategy:
ATR: Last 14 day
Lowest: The lowest value of the last 14 candles
Limit points = (Trade Price - Lowest + ATR) * 100000
trail_points : Limit/2
trail_offset = Limit/2
SHORT Exit strategy:
ATR: Last 14 day
Highest: The higher value of the last 14 candles
Limit points = (Trade Price - Highest + ATR) * 100000
trail_points : Limit/2
trail_offset = Limit/2
Backtest results for the AUDUSD pair gave positive results over the last three months.
I am testing this strategy using a python bot in a real environment this week and will update the results at the end of the week.
Disclaimer
This is not financial advice. You should seek independent advice to check how the strategy information relates to your unique circumstances.
We are not liable for any loss caused, whether due to negligence or otherwise arising from the use of, or reliance on, the information provided directly or indirectly by this strategy.
Linear EDCA v1.2Strategy Description:
Linear EDCA (Linear Enhanced Dollar Cost Averaging) is an enhanced version of the DCA fixed investment strategy. It has the following features:
1. Take the 1100-day SMA as a reference indicator, enter the buy range below the moving average, and enter the sell range above the moving average
2. The order to buy and sell is carried out at different "speed", which are set with two linear functions, and you can change the slope of the linear function to achieve different trading position control purposes
3. This fixed investment is a low-frequency strategy and only works on a daily level cycle
----------------
Strategy backtest performance:
BTCUSD (September 2014~September 2022): Net profit margin 26378%, maximum floating loss 47.12% (2015-01-14)
ETHUSD (August 2018~September 2022): Net profit margin 1669%, maximum floating loss 49.63% (2018-12-14)
----------------
How the strategy works:
Buying Conditions:
The closing price of the day is below the 1100 SMA, and the ratio of buying positions is determined by the deviation of the closing price from the moving average and the buySlope parameter
Selling Conditions:
The closing price of the day is above the 1100 SMA, and the ratio of the selling position is determined by the deviation of the closing price and the moving average and the sellSlope parameter
special case:
When the sellOffset parameter>0, it will maintain a small buy within a certain range above the 1100 SMA to avoid prematurely starting to sell
The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
----------------
Version Information:
Current version v1.2 (the first officially released version)
v1.2 version setting parameter description:
defInvestRatio: The default fixed investment ratio, the strategy will calculate the position ratio of a single fixed investment based on this ratio and a linear function. The default 0.025 represents 2.5% of the position
buySlope: the slope of the linear function of the order to buy, used to control the position ratio of a single buy
sellSlope: the slope of the linear function of the order to sell, used to control the position ratio of a single sell
sellOffset: The offset of the order to sell. If it is greater than 0, it will keep a small buy within a certain range to avoid starting to sell too early
maxSellRate: Controls the maximum sell multiple. The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
maxBuyRate: Controls the maximum buy multiple. The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
maPeriod: the length of the moving average, 1100-day MA is used by default
smoothing: moving average smoothing algorithm, SMA is used by default
useDateFilter: Whether to specify a date range when backtesting
settleOnEnd: If useDateFilter==true, whether to close the position after the end date
startDate: If useDateFilter==true, specify the backtest start date
endDate: If useDateFilter==true, specify the end date of the backtest
investDayofweek: Invest on the day of the week, the default is to close on Monday
intervalDays: The minimum number of days between each invest. Since it is calculated on a weekly basis, this number must be 7 or a multiple of 7
The v1.2 version data window indicator description (only important indicators are listed):
MA: 1100-day SMA
RoR%: floating profit and loss of the current position
maxLoss%: The maximum floating loss of the position. Note that this floating loss represents the floating loss of the position, and does not represent the floating loss of the overall account. For example, the current position is 1%, the floating loss is 50%, the overall account floating loss is 0.5%, but the position floating loss is 50%
maxGain%: The maximum floating profit of the position. Note that this floating profit represents the floating profit of the position, and does not represent the floating profit of the overall account.
positionPercent%: position percentage
positionAvgPrice: position average holding cost
--------------------------------
策略说明：
Linear EDCA（Linear Enhanced Dollar Cost Averaging）是一个DCA定投策略的增强版本，它具有如下特性：
1. 以1100日SMA均线作为参考指标，在均线以下进入定买区间，在均线以上进入定卖区间
2. 定买和定卖以不同的“速率”进行，它们用两条线性函数设定，并且你可以通过改变线性函数的斜率，以达到不同的买卖仓位控制的目的
3. 本定投作为低频策略，只在日级别周期工作
----------------
策略回测表现：
BTCUSD（2014年09月~2022年09月）：净利润率26378%，最大浮亏47.12%（2015-01-14）
ETHUSD（2018年08~2022年09月）：净利润率1669%，最大浮亏49.63%（2018-12-14）
----------------
策略工作原理：
买入条件：
当日收盘价在 1100 SMA 之下，由收盘价和均线的偏离度，以及buySlope参数决定买入仓位比例
卖出条件：
当日收盘价在 1100 SMA之上，由收盘价和均线的偏离度，以及sellSlope参数决定卖出仓位比例
特例：
当sellOffset参数>0，则在 1100 SMA以上一定范围内还会保持小幅买入，避免过早开始卖出
单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
----------------
版本信息：
当前版本v1.2（第一个正式发布的版本）
v1.2版本设置参数说明：
defInvestRatio: 默认定投比例，策略会根据此比例和线性函数计算得出单次定投的仓位比例。默认0.025代表2.5%仓位
buySlope: 定买的线性函数斜率，用来控制单次买入的仓位倍率
sellSlope: 定卖的线性函数斜率，用来控制单次卖出的仓位倍率
sellOffset: 定卖的偏移度，如果大于0，则在一定范围内还会保持小幅买入，避免过早开始卖出
maxSellRate: 控制最大卖出倍率。单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
maxBuyRate: 控制最大买入倍率。单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
maPeriod: 均线长度，默认使用1100日MA
smoothing: 均线平滑算法，默认使用SMA
useDateFilter: 回测时是否要指定日期范围
settleOnEnd: 如果useDateFilter==true，在结束日之后是否平仓所持有的仓位平仓
startDate: 如果useDateFilter==true，指定回测开始日期
endDate: 如果useDateFilter==true，指定回测结束日期
investDayofweek: 每次在周几定投，默认在每周一收盘
intervalDays: 每次定投之间的最小间隔天数，由于是按周计算，所以此数字必须是7或7的倍数
v1.2版本数据窗口指标说明（只列出重要指标）：
MA：1100日SMA
RoR%: 当前仓位的浮动盈亏
maxLoss%: 仓位曾经的最大浮动亏损，注意此浮亏代表持仓仓位的浮亏情况，并不代表整体账户浮亏情况。例如当前仓位是1%，浮亏50%，整体账户浮亏是0.5%，但仓位浮亏是50%
maxGain%: 仓位曾经的最大浮动盈利，注意此浮盈代表持仓仓位的浮盈情况，并不代表整体账户浮盈情况。
positionPercent%: 仓位持仓占比
positionAvgPrice: 仓位平均持仓成本
Simple RSI and SMA Long and Short (by Coinrule)The relative strength index ( RSI ) is a momentum indicator used in technical analysis . RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
A simple moving average ( SMA ) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range.
The Strategy enters and closes the trade when the following conditions are met:
LONG
SMA100 is greater than SMA150
RSI is greater than 50
SHORT
SMA100 is less than SMA150
RSI is less than 50
When a long position is opened, it remains open until the conditions for a short are met at which point the long position is closed and the short position is opened. Then, when the conditions for the long position are met, the short will be closed and a long will be opened.
This strategy is back tested from 1 January 2022 to simulate how the strategy would work in a bear market. The strategy 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.
Multi Trend Cross Strategy TemplateToday I am sharing with the community trend cross strategy template that incorporates any combination of over 20 built in indicators. Some of these indicators are in the Pine library, and some have been custom coded and contributed over time by the beloved Pine Coder community. Identifying a trend cross is a common trend following strategy and a common custom-code request from the community. Using this template, users can now select from over 400 different potential trend combinations and setup alerts without any custom coding required. This Multi-Trend cross template has a very inclusive library of trend calculations/indicators built-in, and will plot any of the 20+ indicators/trends that you can select in the settings.
How it works : Simple trend cross strategies go long when the fast trend crosses over the slow trend, and/or go short when the fast trend crosses under the slow trend. Options for either trend direction are built-in to this strategy template. The script is also coded in a way that allows you to enable/modify pyramid settings and scale into a position over time after a trend has crossed.
Use cases : These types of strategies can reduce the volatility of returns and can help avoid large market downswings. For instance, those running a longer term trend-cross strategy may have not realized half the down swing of the bear markets or crashes in 02', 08', 20', etc. However, in other years, they may have exited the market from time to time at unfavorable points that didn't end up being a down turn, or at times the market was ranging sideways. Some also use them to reduce volatility and then add leverage to attempt to beat buy/hold of the underlying asset within an acceptable drawdown threshold.
Special thanks to @Duyck, @everget, @KivancOzbilgic and @LazyBear for coding and contributing earlier versions of some of these custom indicators in Pine.
This script incorporates all of the following indicators. Each of them can be selected and modified from within the indicator settings:
ALMA - Arnaud Legoux Moving Average
DEMA - Double Exponential Moving Average
DSMA - Deviation Scaled Moving Average - Contributed by Everget
EMA - Exponential Moving Average
HMA - Hull Moving Average
JMA - Jurik Moving Average - Contributed by Everget
KAMA - Kaufman's Adaptive Moving Average - Contributed by Everget
LSMA - Linear Regression , Least Squares Moving Average
RMA - Relative Moving Average
SMA - Simple Moving Average
SMMA - Smoothed Moving Average
Price Source - Plotted based on source selection
TEMA - Triple Exponential Moving Average
TMA - Triangular Moving Average
VAMA - Volume Adjusted Moving Average - Contributed by Duyck
VIDYA - Variable Index Dynamic Average - Contributed by KivancOzbilgic
VMA - Variable Moving Average - Contributed by LazyBear
VWMA - Volume Weighted Moving Average
WMA - Weighted Moving Average
WWMA - Welles Wilder's Moving Average
ZLEMA - Zero Lag Exponential Moving Average - Contributed by KivancOzbilgic
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!
[Sniper] SuperTrend + SSL Hybrid + QQE MODHi. I’m DuDu95.
**********************************************************************************
This is the script for the series called "Sniper".
*** What is "Sniper" Series? ***
"Sniper" series is the project that I’m going to start.
In "Sniper" Series, I’m going to "snipe and shoot" the youtuber’s strategy: to find out whether the youtuber’s video about strategy is "true or false".
Specifically, I’m going to do the things below.
1. Implement "Youtuber’s strategy" into pinescript code.
2. Then I will "backtest" and prove whether "the strategy really works" in the specific ticker (e.g. BTCUSDT) for the specific timeframe (e.g. 5m).
3. Based on the backtest result, I will rate and judge whether the youtube video is "true" or "false", and then rate the validity, reliability, robustness, of the strategy. (like a lie detector)
*** What is the purpose of this series? ***
1. To notify whether the strategy really works for the people who watched the youtube video.
2. To find and build my own scalping / day trading strategy that really works.
**********************************************************************************
*** Strategy Description ***
This strategy is from " QQE MOD + supertrend + ssl hybrid" by korean youtuber "코인투데이".
"코인투데이" claimed that this strategy will make you a lot of money in any crypto ticker in 15 minute timeframe.
### Entry Logic
1. Long Entry Logic
- Super Trend Short -> Long
- close > SSL Hybrid baseline upper k
- QQE MOD should be blue
2. Short Entry Logic
- Super Trend Long -> Short
- close < SSL Hybrid baseline lower k
- QQE MOD should be red
### Exit Logic
1. Long Exit Logic
- Super Trend Long -> Short
2. Short Entry Logic
- Super Trend Short -> Long
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
3. SuperTrend and SSL Hybrid Baseline is by default drawn on the chart.
4. If you check EMA filter, EMA would be drawn on the chart.
5. Should add QQE MOD indicator manually if you want to see QQE MOD.
**********************************************************************************
*** Rating: True or False?
### Rating:
→ 3.5 / 5 (0 = Trash, 1 = Bad, 2 = Not Good, 3 = Good, 4 = Great, 5 = Excellent)
### True or False?
→ True but not a 'perfect true'.
→ It did made a small profit on 15 minute timeframe. But it made a profit so it's true.
→ It worked well in longer timeframe. I think super trend works well so I will work on this further.
### Better Option?
→ Use this for Day trading or Swing Trading, not for Scalping. (Bigger Timeframe)
→ Although the result was not good at 15 minute timeframe, it was quite profitable in 1h, 2h, 4h, 8h, 1d timeframe.
→ Crypto like BTC, ETH was ok.
→ The result was better when I use EMA filter.
### Robust?
→ Yes. Although result was super bad in 5m timeframe, backtest result was "consistently" profitable on longer timeframe (when timeframe was bigger than 15m, it was profitable).
→ Also, MDD was good under risk management option on.
**********************************************************************************
*** Conclusion?
→ I recommend you not to use this on short timeframe as the youtuber first mentioned.
→ In my opinion, I can use on longer timeframe like 2h or bigger with EMA filter, stoploss and risk management.
Davin's 10/200MA Pullback on SPY Strategy v2.0Strategy:
Using 10 and 200 Simple moving averages, we capitalize on price pullbacks on a general uptrend to scalp 1 - 5% rebounds. 200 MA is used as a general indicator for bullish sentiment, 10 MA is used to identify pullbacks in the short term for buy entries.
An optional bonus: market crash of 20% from 52 days high is regarded as a buy the dip signal.
An optional bonus: can choose to exit on MA crossovers using 200 MA as reference MA (etc. Hard stop on 50 cross 200)
Recommended Ticker: SPY 1D (I have so far tested on SPY and other big indexes only, other stocks appear to be too volatile to use the same short period SMA parameters effectively) + AAPL 4H
How it works:
Buy condition is when:
- Price closes above 200 SMA
- Price closes below 10 SMA
- Price dumps at least 20% (additional bonus contrarian buy the dip option)
Entry is on the next opening market day the day after the buy condition candle was fulfilled.
Sell Condition is when:
- Prices closes below 10 SMA
- Hard stop at 15% drawdown from entry price (adjustable parameter)
- Hard stop at medium term and long term MA crossovers (adjustable parameters)
So far this strategy has been pretty effective for me, feel free to try it out and let me know in the comments how you found :)
Feel free to suggest new strategy ideas for discussion and indicator building
Trend #4 - ATR+EMA channelOverview:
This strategy use ATR to take-profit, Red-EMA to stop-loss, Blue-EMA channel to judgment breakout.
This strategy use commission setting is 0.05%, slippage setting is 2 ticks, you can set the appropriate value size in the properties page.
What it does:
This strategy detects when a trend is emerging and buy or sell.
How it does it:
When the price breaks through the blue EMA channel, the trend is judged to be strong in the short term, strategy generates a buy or sell order.
After buying or selling,, if the price moves in the expected direction, uses ATR to determine the appropriate spread to take profit, otherwise use red EMA for stop loss.
How to use it:
Start Date and Stop Date - This parameter adjusts the time range used by the strategy.
Stoploss - This parameter adjusts the stop loss amount after each order is placed.
Blue EMA length - This parameter adjusts the length of the channel.
Blue EMA multy - This parameter adjusts the width of the top and bottom of the channel.
ATR Period - This parameter adjusts the number of candles used by the ATR.
ATR mult - This parameter adjusts the upper and lower widths of the ATR. Lowering this parameter can improve the win rate, but not necessarily the profitability.
Red EMA length - This parameter adjusts the number of candles used by the red EMA .
Long - This switch is used to turn Long position on or off.
Short - This switch is used to turn short position on or off.
TradeIQ - Crazy Scalping Trading Strategy [Kaspricci]This strategy script is a combination of two indicators developed by LuxAlgo:
Triangular Momentum Oscillator & Real Time Divergences ( TMO )
Adjustable MA & Alternating Extremities (AMA)
The script combines the BUY and SELL signals from the TMO indicator with the BUY and SELL extremities shown by the AMA script and waits for the smoothed candles to grow in size. It places a SHORT or LONG order and sets a stop loss at the latest swing high or low (highes high or lowest low for a defined number of recent bars). A new LONG trade is highlighted by a green background. A new SHORT trade is highlighted by red background.
The trades will be closed once a new TMO indicator BUY or SELL signal appears or the color of the AMA extremities is switching from green to red and vice versa.
All parameters of TOM and AMA indicators are added as well and work the same way as in the original scripts provided by LuxAlgo.
The idea to combine these two indicators has been provided to me by TradIQ in his youtube video.
Please leave a comment in case you find a bug. In case you find a combination of parameters with a high win rat and high PnL I would be interested as well.
Catching the Bottom (by Coinrule)This script utilises the RSI and EMA indicators to enter and close the trade.
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
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 simple moving average (SMA), which applies an equal weight to all observations in the period.
The strategy enters and exits the trade based on the following conditions.
ENTRY
RSI has a decrease of 3.
RSI <40.
EMA100 has crossed above the EMA50.
EXIT
RSI is greater than 65.
EMA9 has crossed above EMA50.
This strategy is back tested from 1 April 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include ETH on the 5m timeframe, BNB on 5m timeframe, XRP on the 45m timeframe, MATIC on the 30m timeframe and MATIC on the 2H timeframe.
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.
Trailing Stop SnippetThis is an example snippet that should allow for adding a trailing stop and trailing stop activation to almost any script.
You can use it by setting a trailing stop alone. This will provide you standard trailing stop functionality allowing you to lock in profits and increase your stop-loss as the price moves in your direction.
You can also set the trailing stop activation to trigger the original trailing stop at a certain level. "Once price rises 5%, set a trailing stop at break even". This would be set as 5 and 5 in the settings.
Altered OBV On MACDHere is another strategy along with an indicator that is already published for everyone to use wisely in the tradingview platform. The strategy is not very planned to highlight where to enter and when to exit as it is just a system. So, it is always good practice to follow the signal of simple moving averages and that is the reason you could find those color lines in this strategy as well.
As the indicator signals the entry point, it is wise to decide what the SMA (21, 50, 90, 200) signals us. When the price oscillated around the higher timeframe of moving averages, then it is wise to wait before entering.
OBV:
The OBV is perfect indicator to understand the strength of the particular stock. As the strength increase, the trend of the stock goes high along with price. But, the OBV is considered only with close of previous close which is to make sure the double confirmation on the price to accumulate the volume .
Altered OBV:
So, here is the altered OBV, which basically consider the close of previous close and also buying interested of the day when close is higher than open.
MACD:
I always admire the magic of MACD with pre-defined timeframe. Now, this MACD applied on top of altered OBV to signal us the moving of the ticker strength.
Long:
The long entry occurs when the MACD on Altered OBV signal bullish and the same time the MACD on close already bullish.
Short
The short denotes when the MACD on Altered OBV signal bearish and at the same time the MACD on close already bearish.
I hope this would help on your swing trading strategy.
Happy Investing.
[DuDu95] SSL 4C MACD Laugerre RSI StrategyHello Guys! Nice to meet you all!
Before I start, my nickname has changed to 'DuDu95'!!
This is the Strategy introduced by youtube channel.
I made this based on the open source indicator by kevinmck100, vkno422, KivancOzbilgic. Thank you All!
### Entry Logic
1. Long Entry Logic
- close > SSL Hybrid baseline upper k (keltner channel)
- macd signal > 0 and current MACD value > previous MACD value
- Laguerre RSI < overbought Line.
2. short Entry Logic
- close < SSL Hybrid baseline lower k (keltner channel)
- macd signal < 0 and current MACD value < previous MACD value
- Laguerre RSI > overbought Line.
### Exit Logic
1. Long Exit Logic
- close < SSL Hybrid baseline lower k (keltner channel)
- macd signal < 0
2. short Entry Logic
- close > SSL Hybrid baseline upper k (keltner channel)
- macd signal > 0
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
[fpemehd] Strategy TemplateHello Guys! Nice to meet you all!
This is my fourth script!
This is the Strategy Template for traders who wants to make their own strategy.
I made this based on the open source strategies by jason5480, kevinmck100, myncrypto. Thank you All!
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
[2022] MACD Cross Strategy (version 1)Early workings of a macd crossover. User inputs, strategy parameters, use on forex, crypto, stocks, etc,..
EMA Slope AyEWe create our own indicator to calculate the slope of a 20 period EMA over the last candle.
EMA Slope AyEWe create our own indicator to calculate the slope of a 50 period EMA over the last 3 candles.
Strategy Myth-Busting #10 - InsideBar+EMA - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our 10th one we are automating is the " 75% Win Rate High Profit Inside Bar Trading Strategy - What If You ... " strategy from " Trade Pro " who claims to have backtested this manually and achieved 11,063% profit with a 75% winrate over 100 trades. I was unable to emulate these results consistently accommodating for slippage and commission but even so, the results look promising. I was only able to achieve this win-rate with some multiple take profit staggering. Even so the markdown is above where I would normally consider comfortable (>20%).
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
Inside Bar Ind/Alert by CMA
EMA (built-in)
Trading Rules
4 hour candles
Stop Loss at EMA Line with TP Target 1.5x the risk
Long Entry when these conditions are true
inside bar and bullish
Bar close's above 50 ema
Price action rises above high of inside bar .
Short Entry when these conditions are true
inside bar and bearish
Bar close below 50 ema
Price action falls below low of inside bar
Crypto BTC Correlation Scalper Gaps StrategyThis strategy is based on the gaps theory.
In this case we have the BTC futures from CME, which acts in a way similar to stocks, and we can have gaps present between close/open session, and also sometimes between same candle due to huge movements intra candle.
At the same time I have combined this with a daily moving average, to help out a bit with the trend, since we are looking at small timeframe like 1-15/30min .
On top of that we have a reverse option, where long = short and viceversa, which can be used with against BTC pairs .
Rule are simple:
For long, we have a long gap and the close of the correlated candle is above daily sma
For short, we have a short gap and the close of the correlated candle is below daily sma
For exit:
For exit, we take the highest highest values for short entry TP, meaning we get the different from the HH and rest the current open candle distance, and use that distance as a TP.
At the same time for long entry, we take the lowest low value and rest current close of the candle to that value, and we get the TP.
Can also be applied this logic for SL aswell but from the test I have found out that exiting based on a reverse condition(when tp is not being hit), gives better results/dd overall.
If you have any questions, please let me know !
LarryWillians - Simple StrategyA simple and classic strategy on market, created by LarryWillians using a EMA9.
The brute model use a Cross from closing price on EMA9. But occurs many false entries.
In other to correct this kind of thing, I add a SMA21 to confirm the trend and decrease numbers of false trades.
The strategy waits to break the last High (for buy) a position.
As a strategy requires a Risk Mannager, I created a simple way to trailing this, as well a Take Proft and Stop Loss in %.
Is not the best strategy but, is one of the most famous on financial markets. I did my adaptive version as simples as it is :)
MA Simple Strategy with SL & TP & ATR FiltersHello Guys! Nice to meet you all!
This is my second script!
This Logic is trend following logic, This detects long & short trends by comparing the value of MAs.
This fits to the longer time frame.
### Long Condition
1. Compare 4 MAs (you can chose MA Type)
- Shortest MA (MA 1)
- Shorter MA (MA 2)
- Normal MA (MA 3)
- Longer MA (MA 4)
2. If MA 1 > MA 2 > MA 3 > MA 4, then Enter Long Position
- ‘The arrangement of MAs in descending orders’ is the proxy of the long trend.
### Short Condition
1. Compare 4 MAs (you can chose MA Type)
- Shortest MA (MA 1)
- Shorter MA (MA 2)
- Normal MA (MA 3)
- Longer MA (MA 4)
2. If MA 1 < MA 2 < MA 3 < MA 4, then Enter Short Position
- ‘The arrangement of MAs in ascending orders’ is the proxy of the short trend.
### Close Condition
1. When trend Changes
- When (MA 1 > MA 2 > MA 3 > MA 4) breaks or (MA 1 < MA 2 < MA 3 < MA 4) breaks.
2. When the price hits the stoploss
3. When the price hits the take profit level (basically 50% of qty will be closed)
### Etc
1. Trend filter (ATR should be bigger than SMA of ATR)
- If the volatility of price is to small (ATR), then there could be false signal. To filter this out, I used the condition ‘ATR should be larger than SMA of ATR’.
2. Stoploss
- Enabled Stoploss based on ATR, Percent, Risk-Reward Ratio,
- Enabled Trailing Stoploss.
3. Choose MA Type
- You can choose MA Type
+ Thanks for the stoploss template @jason5480
Morning Scalp StrategyThe Morning Scalp Strategy combines the 50EMA with the Stochastic Momentum Index. The morning period is when penny stocks usually have the highest volatility, so the strategy works between 10:00 AM and 12:10 PM.
***It opens only long positions. The ideal timeframe for this scalping strategy is 5 minutes on low-price stocks. The stock should spike in the morning with momentum and Volume.
***Look for a daily or intraday support area, close to the open position, to increase the confidence in the play
The components are:
- EMA50: Exponential Moving Average (EMA50)
- Stochastic Momentum Index (SMI)
Rules:
- Period: 10:00 AM and 12:10 PM
- if SMI Crossover and SMI < 0, open a position
- If close < EMA50, close the position
- Profit target: To be decided by the user, default value = 10% above the entry price
If you have any questions, let me know!
Faytterro Estimator StrategyWhat is "Faytterro Estimator Strategy"?
"Faytterro Estimator Strategy" is strategy of faytterro estimator. if you want to know more about faytterro estimator:
What it does?
It trades according to the signals given by faytterro estimator and some additional restrictions.
How it does it?
Using the faytterro estimator and the following variables, it gives buy and sell signals in different sizes at ideal points.
How to use it?
The "source" part is used to change the source of faytterro estimator.
The "length" is the length of the fayterro estimator.
"Minimum entry-close gap" is the minimum distance between two transactions opened in opposite directions. For example, if you opened long at 20 500 and "Minimum entry-close gap" is 400, you will not receive a sell signal before the price goes above 20900.
If "minimum entry-entry gap" is the minimum difference between two transactions opened in the same direction. For example, if you open long at 20500 level and the "minimum entry-entry gap" is 400, you will not receive a "buy" signal before the price goes below the 20100 level.
"strong entry size" determines the size of strong signals. The size of ordinary signals is always 1.
note: default values for btc/usdt 1 hour timeframe.
