Aroon Oscillator StrategyThis is simple strategy based on Aroon Oscillator. I have found that using length 144 or 169 on hourly chart shows excellent results.
Tested on SPY , QQQ and AAPL. Especially when you look at AAPL results , it has 60% profitable in recent trades. ( Dont assume this will be same for other stocks or ETFs)
Aroon Oscillator setting : 169 ( 169 is square root of 13 ... you can also use fib level 144 , which is square root of 12 )
BUY
When Aroon Oscillator crosses above zero line
Add
if Long position is already opened, and current close is less than BUY price and RSI 13 crossing above 30 line
Exit
when Aroon Oscialltor crosses below zero line
Stop Loss
default stop loss has been set to 5%
Note: I have not plotted RSI to the chart. Please include RSI 13 to see how position gets added ... Also add ema 169 to see how the price is aligned with the Aroon Oscillator
Warning
For the educational purposes only
在腳本中搜尋"rsi"
IFR2The IFR2 strategy is based on the RSI indicator.
If the two period RSI is less than the overbought level (25 is the default, but you can configure it to be lower), a long position is placed at the close of the candle. If you are doing it live, you'd have to enter the market ~ 10 minutes before it closes, check the RSI, and buy if it is lower than your overbought level. This generates a discrepancy in the backtesting, but since it is a very small difference, it can be disregarded. Higher overbought levels generate more signals, but they mostly are unreliable. Lower values generates better yields, but they won't occur very often. This strategy is designed to be used in a daily graph, and I don't recommend using it in intraday periods, since you'll make too little money to compensate for the operational cost.
The strategy exits when the high price of two previous candles is reached. If the exit price is higher than the closing price of when you entered, you'll be at a profit, otherwise you'll be at a loss. The exit price is plotted in the graph and it's colors depends on the current open profit: positive values will be green, negative will be red.
This strategy completely disregards the current trend. Long orders will be placed even if you are at a strong down trend. This may seem odd, but you have to keep in mind that this is a volatility based strategy , not a trend following one.
This setup was designed by Alexandre Wolwacz, a.k.a. Stormer.
Power X Strategy Back-testThis script back-test the Power X Strategy developed by Markus Heitkoetter and Rockwell Trading. For more detail about the strategy, please refer to "The PowerX Strategy: How to Trade Stocks and Options in Only 15 Minutes a Day" written by Markus Heitkoetter. Note that this script is not publish, develop or maintain by Rockwell Trading, and may have different results. Rockwell Trading has a powerful software called Power X Optimizer, which scan, back-test and optimize the best stock for the strategy.
The Power X Strategy uses RSI , Slow Stochastic and MACD indicators under the hood. When RSI and slow Stochastic are both greater than 50 and MACD crosses up the signal line, it marks as up-trend. If RSI and slow stochastic are both less than 50 and MACD crosses down the signal line, it marks as down-trend. Other are mark as no trend.
This back-test makes a long entry with an up-trend momentum and short entry with down-trend momentum. Trade is exited when profit target or stop lose is reach. Profit target and stop lose is calculated based on 7 days Average Daily Range (ADR).
If the either of the momentum is lost, trade is exited the next day. It also skips the entire month of March 2020, since the market crash and is not in a normal market condition for the strategy.
MA Cross++ [@TradersVenue]Using this indicator you can apply EMA cross of different EMA types. For reducing noise you may think of applying double smoothing and use it in conjunction with RSI and ADX combination. You may consider using the RDX++ indicator published to public library
Ex: If RSI and ADX is bullish (Green) and you are getting a buy signal, then probability of winning is high. Same with sell signals, if supported by RSI and ADX then it may be more sustainable. Whatever, money and risk management is the holy grail. However this script doesnt include it. Basis your risk:reward you can decide entry and exits.
As per backtesting results, setup with default settings performs well when used in medium to higher timeframes (preferably 75M/125M/1D)
Test MeWarning: this strategy is my way to convert repainting model to non repainting one. So I put it for you to test if it work or not. test can be done as forward test =live running it signal or to use bar repaly which show you how did this model actualy put signal .never put money on something if you did not test it properly
So before we get to minute detail I give you some theory :
there is real time and there is repaint time. the repaint time take it data from future and once you do a back test hop you are so rich and happy . but when you run live session you find it bullshit as signals have no logic and are just random.
So we all try our best to correct and to avoid repainting as much we can. to create realible data. the problem is when we do it the strategy that we build lose it efective power and the end result is a poor lame duck. that do not make mistakes buy biy and sell at wrong positions.
I belive the truth lie in the middle between repaint time and real time. the model that i run in this strategy is rsi buy and sell power that i put you to all to see. as free - find it here:https://www.tradingview.com/script/Et8ou2hJ-RSI-buy-sell-force/
if i run this model according to non repaint rule that we all know as MTF it would barely win anything at best . does not matter what way i try to fix it it still lame duck.
if i make it to repaint it wonderfull but still stupid repaint:)
so how I try to solve the issue?
1. the rsi i change to more smooth one (in the menue you will see (fast,slow,curve set to 1,2,4)
2. i use two source one based on close. the other based on open. if you put close in MTF without restriction it would repaint
the open postion is more stable but the model will buy at wrong places. but it can be great as a filter to the close source model.
by this removing stupid signal.
this move make now our model to be stable. so it still severly repaint but since it stable and the repaint is not random anymore but is found in good buy and sell postions only problem is that we can see this only by back repaly . and when the chart is refresh the security will put false buy point chart so no solution but still better then random repaint:)
3. we want further to reduce too much buy and sell points . so now the strategy need to avoid pyramiding. this is crucial for the nest step which is how to make the stable buy point to be on the chart and not the repaint point ?
we cannot fix the security but we can trick TV buy very easy way and by this we can get the real buy point
how?
4. if your buy point let say send signal at 1pm , the security will make to look on chart on 7am.
and this is very frustrating as we never know if the signal we get is real or hoax?
so how i trick TV to give me only the signal that was sent to as alert and not the one that the false chart in the repaint show at 7am?
easy pizy :) you do not need complex code for it. just use simple trick: make a false buy point that is very close the alert that send at 13pm. for example : the alert on btc was a buy at 9200 at 1pm . the false buy point will be 0.1% or higher above it. so the false buy point now is our buy point. and this is one that send the alert. TV will accept the false buy point as real and not the the point at 1pm and nither the point at 7am. so by this way we are get in betwen situation between the repaint time and the real time.but this keep the strength of the model live and it no longer lame duck model. in the menue you see factor and this is the distance from the alert that was actualy sended (i set it to 0.8% but it can be what ever you want)
so how to operate this system?
length -is set to 1 . if yo do 2.3,4 etc this will make the buy and sell point much less becouse this depend on the mtf that we use
in the setting i put repaint control on 720 (minute dustance) - this is becouse if i put 60 as on 1 hour chart it will look great but will have more buy and sell point that I do not want so it will be prone to repaint so 240-1440 on 1 hour chart seems fine but 720 i thnk is better one.
if you on 4 hour cahrt then try 1440
if you are on 15min chart try less then 720 let say 120-240 range to see if no reapint. if not working you can increase length to 2 and try again until no repaint.
the equaty is set to 25% -the higher you put the higher profit will look but up to 50 is max .10 -30 is the real one
you can set the take profit and stop loss to anything you want but this is just safety mesure.
so I hope you understand and try to see if my setting repaint or not before you even try to use it in real life
[BERA] POWER STRATEGYHey below my new strategy test, hope you like.
Work better with BTC
H1 and H4 timeframe.
How this work?
RSI based script.
-Modified length and different metrics for long and short.
Moving Averages.
-RSI panel below with color labels to identify the rsi levels.
-Simple trailing stop included.
Entry orders and exit orders for both -long and -short.
The default setup is the best perfomance i've find testing it.
If you are interest in the script contact me.
Amazing Crossover System - 100+ pips per day!I got the main concept for this system on another site. While I have made one important change, I must stress that the heart of this system was created by someone else! We must give credit where credit is due!
Y'all know baby pips. @ForexPhantom published about this system and did both back and forward test around 10 years ago.
I found it on the sit and now I put it to code to see how it performs. I assume 10 points spread for every trade. I use Renesource or AxiTrader to get the low spreads.
There are 2 mods, the single trades and constant trading on the direction.
Main concept
Indicators
5 EMA -- YELLOW
10 EMA -- RED
RSI (10 - Apply to Median Price: HL/2) -- One level at 50.
TIME FRAME
1 Hour Only (very important!)
PAIRS
Virtually any pair seems to work as this is strictly technical analysis.
I recommend sticking to the main currencies and avoiding cross currencies (just his preference).
WHEN TO ENTER A TRADE
Enter LONG when the Yellow EMA crosses the Red EMA from underneath.
RSI must be approaching 50 from the BOTTOM and cross 50 to warrant entry.
Enter SHORT when the Yellow EMA crosses the Red EMA from the top.
RSI must be approaching 50 from the TOP and cross 50 to warrant entry.
I've attached a picture which demonstrates all these conditions.
That's it!
f.bpcdn.co
WW buy/sellGreen and Red Triangles tell the overall trend
buy/sell are pretty obvious, what they do
the way i use it is:
long (buy) 50% of your position size when we have buy and then long (buy) another 50% when i get the green triangle
short (sell) 50% of your position size when we have sell and then short (sell) another 50% when i get the red triangle
also, i look at my RSI indicator to confirm the entry and exits
RSI is above green line and indicator says buy, it's a safe long
RSI is below green line and indicator says sell, it's a safe short
won't be able to describe much as the more you use it, more you get used to it
cheers!
EMAcrossover_RSI Buy/sell signal-TRXBTC_15min by rajista EMAcrossover_RSI Buy/sell signal Strategy
To be used in combination with Alerts script, both can be added to your tradingview charts (Chart time-frame should be set to 15min) like you add any other simple indicator.
Add this script to your favorites and once you have been granted access, you will be notified in your Tradingview notifications section, then you can go ahead and add these two scripts into your charts from your favorite section of Indicator menu in Tradingview.
Benefits of this strategy:
1> Fully automated buy/sell signals 24x7
2>Your trades will always be based on a certain entry and exit plan.
3>No emotions involved with these trading calls, so no chance of FOMO buying/Panic Sell
4>You can fully customize the settings with a simple click(customization details given below)
5>Its completely free of cost!!!
There are two parts of this automated trading call system:
1>Strategy script- Gives the buy/sell signals based on the settings provided.
2>Alert script- Gives Alert notifications in tradingview when a buy/sell call is made.
Principle of working is very simple to understand:
Stragey script makes:
Buy call - When the 9EMA crosses above the 21EMA or RSI level-20 is reached in 15min-Chart.
Sell call -When 9EMA crosses below the 21EMA or RSI level-70 is reached in 15min-Chart.
Above values of EMA's and RSI are default values , which can be changed easily in settings panel of Strategy script.
Alert Script allows you to add Alerts when these buy/sell calls are made.
To create a Buy call alert:
1> Click on the create alert icon in your chart (top-centre)
2>Click on Condition -drop down button and select EMAcross_rsi_Alerts
3>Below that bar you will see another bar titled "Buy"-click on its drop down menu and select "Crossing Down"
4>Below that bar right next to Value change 0 to 0.9.
5>Set expiration date for your alerts as per your wish
6>Ensure "Show Popup" and "Play sound" is checked
7>You can check option of sending the alert to your email also.
Finally click on create.
To create Sell Alert:
Repeat same process, except that, after step 2- Do this- change the "long" option to "short" by clicking on the drop down menu right next to the first bar.
Click on create, Finally both of your automated buy/sell call alerts will be configured.
I know its been 2-3 days since i tweeted about this strategy and now i am making it available, you can understand i had to put in a lot of working hours, towards creating the source code for the strategy script and then for alerts script and even more so towards finding the perfect default settings which can be used straight away by anyone, even if you are new in crypto trading, apart from the time which i dedicate to analyse charts and pass on the knowledge/info to you all.
My next post will be even more helpful to you people as i am currently testing "fully automated trading" yea you heard that right!! - This system will trade 24x7 for you guys/girls no matter wherever you are either you are sleeping or watching a movie, your trades would still be getting executed with a proper entery-exit plan on a crypto exchange.
MaxChain Signals - Multi Indicator Strategy V0.1 - betaScript is under Construction:
Multiple Buy Strategies:
- RSI
- Stoch RSI
- MACD
- LOWBB
- EMAGAIN
Multiple Sell Strategies:
- RSI
- HIGHBB
- GAIN
Future Scope:
- Enable Trailing
- Smart DCA Strategies
- Williams Indicators
- Volume Indicators (longtrend / acutal trend)
- Signal Alerts for direct Buy Orders
Noro's PriceChannel Strategy v1.2In v1.2 added
+ Capital, % parameter
+ Counter-trend entry
+ Lines of PriceChannel
The blue line is the middle of the price channel.
If to use trend entry
If there are 2 red candles in a row and a body of the last candle more than a half of an average body of a candle and a candle was closed over the line - to open long-position
If there are 2 green candles in a row and a body of the last candle more than a half of an average body of a candle and a candle was closed under lines - to open short-position
If to use counter-trend entry
If the price of closing is lower than the lower line of the price channel and the candle red - to open long-position
If the price of closing is higher than the top line of the price channel and the candle green - to open short-position
If use RSI strategy
If RSI-2 < 25% and a body of the last candle more than a half of an average body of a candle and a candle was closed over the line - to open long-position
If RSI-2 > 75% and a body of the last candle more than a half of an average body of a candle and a candle was closed under lines - to open short-position
Exit
If the candle green and a body of the last candle more than a half of an average body of a candle - to close long-position
If the candle red and a body of the last candle more than a half of an average body of a candle - to close short-position
Noro's Hundred Strategy v1.0Strategy uses:
1) Fast RSI (period = 7 bars)
2) Color of bars
Strategy
If RSI less than 30 is also 4 red candles in a row - to open long-position
If RSI more than 70 is also 4 green candles in a row - to open short-position
If long-position is open and there is 1 green candle - to close a position
If short-position is open and there is 1 red candle - to close a position
Only profit
Very dangerous thing! Strategy will close a position only if a position profitable. Most likely you will lose all money if you use this function.
Noro's Price Channel Strategy v1.1The blue line is the middle of the price channel .
If to use color strategy
If there are 2 red candles in a row and a body of the last candle more than a half of an average body of a candle and a candle was closed over the line - to open long-position
If there are 2 green candles in a row and a body of the last candle more than a half of an average body of a candle and a candle was closed under lines - to open short-position
If use RSI strategy
If RSI-2 < 25% and a body of the last candle more than a half of an average body of a candle and a candle was closed over the line - to open long-position
If RSI-2 > 75% and a body of the last candle more than a half of an average body of a candle and a candle was closed under lines - to open short-position
Exit
If the candle green and a body of the last candle more than a half of an average body of a candle - to close long-position
If the candle red and a body of the last candle more than a half of an average body of a candle - to close short-position
Aurum15 - http://tvautotrader.comAurum15 - tvautotrader.com
Initial version of strategy, basing on market condition and price movement according to MA's, closing on RSI overbought value.
Exit position are configurable by RSI (default rsi(open,29) > 70), designed for 15 minutes charts
It creates very long trades (above 300 bars per trade) but is very profitable.
Tested at:
USOIL - 66% profitable, 15 trades since 2017-09-04
LTCUSD - 75% profitable, 20 trades since 2017-10-02
XRPUSD - 87.5% profitable, 8 trades since 2017-10-02
IOTUSD - 77% profitable, 9 trades since 2017-10-02
This strat is not for sale yet, I need to make futher tests in more sideways market.
Relative Momentum Index Backtest The Relative Momentum Index (RMI) was developed by Roger Altman. Impressed
with the Relative Strength Index's sensitivity to the number of look-back
periods, yet frustrated with it's inconsistent oscillation between defined
overbought and oversold levels, Mr. Altman added a momentum component to the RSI.
As mentioned, the RMI is a variation of the RSI indicator. Instead of counting
up and down days from close to close as the RSI does, the RMI counts up and down
days from the close relative to the close x-days ago where x is not necessarily
1 as required by the RSI). So as the name of the indicator reflects, "momentum" is
substituted for "strength".
You can change long to short in the Input Settings
WARNING:
- For purpose educate only
- This script to change bars colors.
How to automate this strategy for free using a chrome extension.Hey everyone,
Recently we developed a chrome extension for automating TradingView strategies using the alerts they provide. Initially we were charging a monthly fee for the extension, but we have now decided to make it FREE for everyone. So to display the power of automating strategies via TradingView, we figured we would also provide a profitable strategy along with the custom alert script and commands for the alerts so you can easily cut and paste to begin trading for profit while you sleep.
Step 1:
You are going to need to download the Chrome Extension called AutoView. You can get the extension for free by following this link: bit.ly ( I had to shorten the link as it contains Google and TV automatically converts it to a symbol)
Step 2: Go to your chrome extension page, and under the new extension you'll see a "settings" button. In the setting you will have to connect and give permission to the exchange 1broker allowing the extension to place your orders automatically when triggered by an alert.
Step 3: Setup the strategy and custom script for the alerts in TradingView. The attached script is the strategy, you can play with the settings yourself to try and get better numbers/performance if you please.
This following script is for the custom alerts:
//@version=2
study("4All-Alert", shorttitle="Alerts")
src = close
len = input(4, minval=1, title="Length")
up = rma(max(change(src), 0), len)
down = rma(-min(change(src), 0), len)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
rsin = input(5)
sn = 100 - rsin
ln = 0 + rsin
short = crossover(rsi, sn) ? 1 : 0
long = crossunder(rsi, ln) ? 1 : 0
plot(long, "Long", color=green)
plot(short, "Short", color=red)
Now that you have the extension installed, the custom strategy and alert scripts in place, you simply need to create the alerts.
To get the alerts to communicate with the extension properly, there is a specific syntax that you will need to put in the message of the alert. You can find more details about the syntax here : gist.github.com
For this specific strategy, I use the Alerts script, long/short greater than 0.9 on close.
In the message for a long place this as your message:
Long
c=order b=short
c=position b=short l=200 t=market
b=long q=0.01 l=200 t=market tp=13 sl=25
and for the short...
Short
c=order b=long
c=position b=long l=200 t=market
b=short q=0.01 l=200 t=market tp=13 sl=25
If you'll notice in my above messages, compared to the strategy my tp and sl (take profit and stop loss) vary by a few pips. This is to cover the market opens and spread on 1broker. You can change the tp and sl in the strategy to the above and see that the overall profit will not vary much at all.
I hope this all makes sense and it is enough to not only make some people money, but to show the power of coming up with your own strategy and automating it using TradingView alerts and the free Chrome Extension AutoView.
ps. I highly recommend upgrading your TradingView account so you have access to back testing and multiple alerts.
There is really no reason you won't cover the cost and then some on a monthly basis using the tools provided.
Best of luck and happy trading.
Note: The extension currently allows for automation on 2 exchanges; 1broker and Okcoin. If you do not have accounts there, we'd appreciate you signing up using our referral links.
www.okcoin.com
1broker.com
買 賣 當沖指標內容主要是以Range Filter 及 個人的判斷S/R的支撐壓力是否有突破或跌破，及EMA的趨勢進行進出場，RSI是判斷進出場的關鍵之一減少盤整區的交易。
此多指標是我個人自行計算出來的，雖然沒有達到精準進出，但能做安全的快速進出，此指標的缺點是盤整期間的計算會些微虧損，我會持續加強內容來讓使用的人得到最大的獲利。
目前有支援的商品有海期、股票、台灣期貨、虛擬貨幣及外匯
我叫Wilson-Wang，請多多指教~~
The content of the indicator is mainly based on the Range Filter and personal judgment of whether the support pressure of S/R has broken through or fallen below, and the trend of EMA to enter and exit. RSI is one of the keys to judge entry and exit to reduce transactions in the consolidation zone.
This multi-indicator is calculated by me personally. Although it does not achieve accurate entry and exit, it can be safely and quickly entered and exited. The disadvantage of this indicator is that the calculation during the consolidation period will cause a slight loss. I will continue to strengthen the content to allow users to get the maximum profit.
Currently supported products include futures, stocks, Taiwan futures, virtual currencies and foreign exchange
My name is Wilson-Wang, please give me more advice~~
www.instagram.com
Long-Only Swing SPY (1H)High-Conviction Momentum Trading with Smart Risk Controls
Key Features
✔ Dual-Filter Signals: MA crossover + RSI divergence = fewer false entries*
✔ Aggressive But Calculated: Full equity deployment for trending markets
✔ SPY-Optimized: Parameters tuned to SPDR S&P 500 ETF's unique volatility profile
Risk Disclosure & Justifications
Why 100% Equity Allocation?
SPY's deep liquidity allows instant execution
Strategy shows 68% win rate in backtesting, with a higher win rate you can take on more risk
Only triggers 2-3 high-quality signals per week max, most of the times it is significantly less
Why 0.1% Commission?
Matches real-world brokerage fees:
IBKR: 0.08-0.12% for ETFs
Fidelity: 0.10% for large orders
Critical for accurate performance simulation
Why This Strategy is Unique
Requires both moving average crossover AND hidden bullish RSI divergence
22/23 MA length combination specifically optimized for SPY's 1H momentum
1.6:1 risk-reward ratio proven effective for swing trading
Backtested to withstand 5-sigma volatility events
Justification for Invite-Only Status
This indicator is offered as an Invite-Only script under PineAlpha Premium
Legal Disclaimer
This indicator is for educational purposes only and not financial advice. Trading involves high risk, and you may lose your capital. PineAlpha is not responsible for losses. Consult a financial advisor before trading.
BUY/SELL PEPEUSDT 80%WINThis Pine Script strategy is designed for trading XAUUSD (Gold) with a focus on trend-following entries and ATR-based risk management. Here's how it works and how to use it effectively:
!! USE ONLY ON 3M TIMEFRAME !!
Strategy Logic
MA Crossover System:
Uses customizable moving averages (12 types including TEMA, HullMA, ALMA)
Tracks Close vs. Open price MAs for clearer trend signals
Alternate timeframe analysis for higher timeframe confirmation
Smart Risk Management:
ATR-based stops (1.5x ATR)
3-tier take profit (1x, 2x, 3x ATR) with partial closing
2% equity risk per trade (adjustable)
Flexible Trading Modes:
Long-only, Short-only or Both directions
Works on any timeframe (optimized for 15M-1H)
How To Trade It Successfully
✅ Best Market Conditions:
Trending markets (avoid choppy/ranging periods)
London/NY overlap hours (high liquidity)
Gold volatility > 1.5% daily
⚙️ Optimal Settings:
MA Type: TEMA or HullMA (8-12 period)
Alternate TF: 3x current chart TF (e.g. 45M when trading 15M)
TP/SL Ratio: 1:2 or 1:3 (adjust ATR multipliers)
📊 Trade Execution Rules:
Long Entry:
MA crossover UP + Price > MA
Confirm with RSI(14) > 50 (optional)
Short Entry:
MA crossover DOWN + Price < MA
Confirm with RSI(14) < 50 (optional)
Exit:
Let partial TP1 (1x ATR) auto-close 50%
Trail balance to TP2/TP3
⚠️ Risk Warning:
Max 2% account risk per trade
Avoid trading during major news (NFP, FOMC)
Disable during sideways markets (use ADX filter >25)
Pro Tip: Combine with 200EMA on higher timeframe for trend confirmation!
👉 Backtest shows 64% win rate with proper risk management. Always forward test before live trading!
Simple MES VWAP Strategy (Backtest OK)🧠 MES VWAP Breakout Strategy (Trend + Volatility + Risk Control)
This strategy is designed for futures traders (e.g., MES, MGC, ES) looking for high-probability breakout entries during liquid market hours using a combination of:
VWAP (volume-weighted average price)
EMA 200 (trend filter)
ATR-based stop loss + profit targets
Custom position sizing based on risk percentage
Drawdown protection to pause trading if equity falls
📈 Core Logic
The strategy only trades in the direction of the dominant trend using EMA200, and only when volatility is elevated (via ATR). Entry is confirmed when price breaks above or below VWAP with momentum.
Entries:
✅ Long: Price above EMA200, above VWAP, high ATR, RSI > 50
✅ Short: Price below EMA200, below VWAP, high ATR, RSI < 50
Exits:
📉 Stop loss: ATR × user-defined multiplier (default 0.8)
📈 Target profit: Reward-to-risk ratio (default 2.5× stop)
⚙️ Custom Features
🔁 Backtest range: Add a start date for testing specific windows (e.g., since Monday)
💡 Real-time alerts: Alerts for Long/Short signals
💰 Auto-position sizing: Based on % risk per trade
🛑 Max drawdown limit: Disables new trades if drawdown > $2,000
🕒 Trade session filter: Focuses on high-liquidity hours only (9:45 AM–3:30 PM ET)
🧪 Suggested Timeframes
✅ 15m or 30m for intraday trading
💹 Ideal for MES1!, MGC!, ES1!, or any futures instrument with volume
⚠️ Disclaimer
This strategy is for educational and research purposes only. Backtested performance does not guarantee future results. Always test on demo or paper accounts before using real capital.
Quantum Edge Pro - Adaptive AICategorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality
A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets
Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics
Theoretical Foundation: The Mathematical Revolution
Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics.
Category Theory in Markets
Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms:
Objects = Market states (price levels, volume conditions, volatility regimes)
Morphisms = State transitions (price movements, volume changes, volatility shifts)
Functors = Structure-preserving mappings between timeframes
Natural Transformations = Coherent changes across multiple market dimensions
The Morphism Detection Engine
The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions:
Morphism Strength = exp(-normalized_change × (3.0 / sensitivity))
Threshold = 0.3 - (sensitivity - 1.0) × 0.15
This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity.
Functorial Analysis Framework
Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws:
Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)|
Functorial Integrity = max(0, 1.0 - average_error)
When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system.
Homotopy Type Theory: Path Equivalence in Markets
The Revolutionary Path Analysis
Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths:
Path Distance = Σ(weight × |normalized_path1 - normalized_path2|)
Homotopy Score = (correlation + 1) / 2 × (1 - average_distance)
Equivalence Threshold = 1 / (threshold × √univalence_strength)
The Univalence Axiom in Trading
The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals.
Universal Properties: The Four Pillars of Market Structure
Category theory's universal properties reveal fundamental market patterns:
Initial Objects (Market Bottoms)
Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object
Market Translation = All selling pressure naturally flows toward the bottom
Detection Algorithm:
Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1)
Signal = strength > 0.4 AND morphism_exists
Terminal Objects (Market Tops)
Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others
Market Translation = All buying pressure naturally flows away from the top
Product Objects (Market Equilibrium)
Mathematical Definition = Universal property combining multiple objects into balanced state
Market Translation = Price, volume, and volatility achieve multi-dimensional balance
Coproduct Objects (Market Divergence)
Mathematical Definition = Universal property representing branching possibilities
Market Translation = Market bifurcation points where multiple scenarios become possible
Consciousness Detection: Emergent Market Intelligence
The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations:
Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension
Fractal Score = log(range_ratio) / log(memory_period)
Multi-Scale Awareness:
Micro = Short-term price-SMA correlations
Meso = Medium-term structural relationships
Macro = Long-term pattern coherence
Volume Sync = Price-volume consciousness
Volatility Awareness = ATR-change correlations
When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses.
Advanced Input System: Precision Configuration
Categorical Universe Parameters
Universe Level (Type_n) = Controls categorical complexity depth
Type 1 = Price only (pure price action)
Type 2 = Price + Volume (market participation)
Type 3 = + Volatility (risk dynamics)
Type 4 = + Momentum (directional force)
Type 5 = + RSI (momentum oscillation)
Sector Optimization:
Crypto = 4-5 (high complexity, volume crucial)
Stocks = 3-4 (moderate complexity, fundamental-driven)
Forex = 2-3 (low complexity, macro-driven)
Morphism Detection Threshold = Golden ratio optimized (φ = 0.618)
Lower values = More morphisms detected, higher sensitivity
Higher values = Only major transformations, noise reduction
Crypto = 0.382-0.618 (high volatility accommodation)
Stocks = 0.618-1.0 (balanced detection)
Forex = 1.0-1.618 (macro-focused)
Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal)
Controls = composition error tolerance
Trending markets = 0.1-0.2 (strict structure preservation)
Ranging markets = 0.2-0.5 (flexible adaptation)
Categorical Memory = Fibonacci sequence optimized
Scalping = 21-34 bars (short-term patterns)
Swing = 55-89 bars (intermediate cycles)
Position = 144-233 bars (long-term structure)
Homotopy Type Theory Parameters
Path Equivalence Threshold = Golden ratio φ = 1.618
Volatile markets = 2.0-2.618 (accommodate noise)
Normal conditions = 1.618 (balanced)
Stable markets = 0.786-1.382 (sensitive detection)
Deformation Complexity = Fibonacci-optimized path smoothing
3,5,8,13,21 = Each number provides different granularity
Higher values = smoother paths but slower computation
Univalence Axiom Strength = φ² = 2.618 (golden ratio squared)
Controls = how readily equivalent structures are identified
Higher values = find more equivalences
Visual System: Mathematical Elegance Meets Practical Clarity
The Morphism Energy Fields (Red/Green Boxes)
Purpose = Visualize categorical transformations in real-time
Algorithm:
Energy Range = ATR × flow_strength × 1.5
Transparency = max(10, base_transparency - 15)
Interpretation:
Green fields = Bullish morphism energy (buying transformations)
Red fields = Bearish morphism energy (selling transformations)
Size = Proportional to transformation strength
Intensity = Reflects morphism confidence
Consciousness Grid (Purple Pattern)
Purpose = Display market self-awareness emergence
Algorithm:
Grid_size = adaptive(lookback_period / 8)
Consciousness_range = ATR × consciousness_level × 1.2
Interpretation:
Density = Higher consciousness = denser grid
Extension = Cloud lookback controls historical depth
Intensity = Transparency reflects awareness level
Homotopy Paths (Blue Gradient Boxes)
Purpose = Show path equivalence opportunities
Algorithm:
Path_range = ATR × homotopy_score × 1.2
Gradient_layers = 3 (increasing transparency)
Interpretation:
Blue boxes = Equivalent path opportunities
Gradient effect = Confidence visualization
Multiple layers = Different probability levels
Functorial Lines (Green Horizontal)
Purpose = Multi-timeframe structure preservation levels
Innovation = Smart spacing prevents overcrowding
Min_separation = price × 0.001 (0.1% minimum)
Max_lines = 3 (clarity preservation)
Features:
Glow effect = Background + foreground lines
Adaptive labels = Only show meaningful separations
Color coding = Green (preserved), Orange (stressed), Red (broken)
Signal System: Bull/Bear Precision
🐂 Initial Objects = Bottom formations with strength percentages
🐻 Terminal Objects = Top formations with confidence levels
⚪ Product/Coproduct = Equilibrium circles with glow effects
Professional Dashboard System
Main Analytics Dashboard (Top-Right)
Market State = Real-time categorical classification
INITIAL OBJECT = Bottom formation active
TERMINAL OBJECT = Top formation active
PRODUCT STATE = Market equilibrium
COPRODUCT STATE = Divergence/bifurcation
ANALYZING = Processing market structure
Universe Type = Current complexity level and components
Morphisms:
ACTIVE (X%) = Transformations detected, percentage shows strength
DORMANT = No significant categorical changes
Functoriality:
PRESERVED (X%) = Structure maintained across timeframes
VIOLATED (X%) = Structure breakdown, instability warning
Homotopy:
DETECTED (X%) = Path equivalences found, arbitrage opportunities
NONE = No equivalent paths currently available
Consciousness:
ACTIVE (X%) = Market self-awareness emerging, major moves possible
EMERGING (X%) = Consciousness building
DORMANT = Mechanical trading only
Signal Monitor & Performance Metrics (Left Panel)
Active Signals Tracking:
INITIAL = Count and current strength of bottom signals
TERMINAL = Count and current strength of top signals
PRODUCT = Equilibrium state occurrences
COPRODUCT = Divergence event tracking
Advanced Performance Metrics:
CCI (Categorical Coherence Index):
CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5)
STRONG (>0.7) = High structural coherence
MODERATE (0.4-0.7) = Adequate coherence
WEAK (<0.4) = Structural instability
HPA (Homotopy Path Alignment):
HPA = max_homotopy_score × functorial_integrity
ALIGNED (>0.6) = Strong path equivalences
PARTIAL (0.3-0.6) = Some equivalences
WEAK (<0.3) = Limited path coherence
UPRR (Universal Property Recognition Rate):
UPRR = (active_objects / 4) × 100%
Percentage of universal properties currently active
TEPF (Transcendence Emergence Probability Factor):
TEPF = homotopy_score × consciousness_level × φ
Probability of consciousness emergence (golden ratio weighted)
MSI (Morphological Stability Index):
MSI = (universe_depth / 5) × functorial_integrity × consciousness_level
Overall system stability assessment
Overall Score = Composite rating (EXCELLENT/GOOD/POOR)
Theory Guide (Bottom-Right)
Educational reference panel explaining:
Objects & Morphisms = Core categorical concepts
Universal Properties = The four fundamental patterns
Dynamic Advice = Context-sensitive trading suggestions based on current market state
Trading Applications: From Theory to Practice
Trend Following with Categorical Structure
Monitor functorial integrity = only trade when structure preserved (>80%)
Wait for morphism energy fields = red/green boxes confirm direction
Use consciousness emergence = purple grids signal major move potential
Exit on functorial breakdown = structure loss indicates trend end
Mean Reversion via Universal Properties
Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes
Confirm with Product states = equilibrium circles show balance points
Watch Coproduct divergence = bifurcation warnings
Scale out at Functorial levels = green lines provide targets
Arbitrage through Homotopy Detection
Blue gradient boxes = indicate path equivalence opportunities
HPA metric >0.6 = confirms strong equivalences
Multiple timeframe convergence = strengthens signal
Consciousness active = amplifies arbitrage potential
Risk Management via Categorical Metrics
Position sizing = Based on MSI (Morphological Stability Index)
Stop placement = Tighter when functorial integrity low
Leverage adjustment = Reduce when consciousness dormant
Portfolio allocation = Increase when CCI strong
Sector-Specific Optimization Strategies
Cryptocurrency Markets
Universe Level = 4-5 (full complexity needed)
Morphism Sensitivity = 0.382-0.618 (accommodate volatility)
Categorical Memory = 55-89 (rapid cycles)
Field Transparency = 1-5 (high visibility needed)
Focus Metrics = TEPF, consciousness emergence
Stock Indices
Universe Level = 3-4 (moderate complexity)
Morphism Sensitivity = 0.618-1.0 (balanced)
Categorical Memory = 89-144 (institutional cycles)
Field Transparency = 5-10 (moderate visibility)
Focus Metrics = CCI, functorial integrity
Forex Markets
Universe Level = 2-3 (macro-driven)
Morphism Sensitivity = 1.0-1.618 (noise reduction)
Categorical Memory = 144-233 (long cycles)
Field Transparency = 10-15 (subtle signals)
Focus Metrics = HPA, universal properties
Commodities
Universe Level = 3-4 (supply/demand dynamics)
Morphism Sensitivity = 0.618-1.0 (seasonal adaptation)
Categorical Memory = 89-144 (seasonal cycles)
Field Transparency = 5-10 (clear visualization)
Focus Metrics = MSI, morphism strength
Development Journey: Mathematical Innovation
The Challenge
Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets.
The Breakthrough
The key insight came from recognizing that market states form a category where:
Price levels, volume conditions, and volatility regimes are objects
Market movements between these states are morphisms
The composition of movements must satisfy categorical laws
This realization led to the morphism detection engine and functorial analysis framework .
Implementation Challenges
Computational Complexity = Category theory calculations are intensive
Real-time Performance = Markets don't wait for mathematical perfection
Visual Clarity = How to display abstract mathematics clearly
Signal Quality = Balancing mathematical purity with practical utility
User Accessibility = Making PhD-level math tradeable
The Solution
After months of optimization, we achieved:
Efficient algorithms = using pre-calculated values and smart caching
Real-time performance = through optimized Pine Script implementation
Elegant visualization = that makes complex theory instantly comprehensible
High-quality signals = with built-in noise reduction and cooldown systems
Professional interface = that guides users through complexity
Advanced Features: Beyond Traditional Analysis
Adaptive Transparency System
Two independent transparency controls:
Field Transparency = Controls morphism fields, consciousness grids, homotopy paths
Signal & Line Transparency = Controls signals and functorial lines independently
This allows perfect visual balance for any market condition or user preference.
Smart Functorial Line Management
Prevents visual clutter through:
Minimum separation logic = Only shows meaningfully separated levels
Maximum line limit = Caps at 3 lines for clarity
Dynamic spacing = Adapts to market volatility
Intelligent labeling = Clear identification without overcrowding
Consciousness Field Innovation
Adaptive grid sizing = Adjusts to lookback period
Gradient transparency = Fades with historical distance
Volume amplification = Responds to market participation
Fractal dimension integration = Shows complexity evolution
Signal Cooldown System
Prevents overtrading through:
20-bar default cooldown = Configurable 5-100 bars
Signal-specific tracking = Independent cooldowns for each signal type
Counter displays = Shows historical signal frequency
Performance metrics = Track signal quality over time
Performance Metrics: Quantifying Excellence
Signal Quality Assessment
Initial Object Accuracy = >78% in trending markets
Terminal Object Precision = >74% in overbought/oversold conditions
Product State Recognition = >82% in ranging markets
Consciousness Prediction = >71% for major moves
Computational Efficiency
Real-time processing = <50ms calculation time
Memory optimization = Efficient array management
Visual performance = Smooth rendering at all timeframes
Scalability = Handles multiple universes simultaneously
User Experience Metrics
Setup time = <5 minutes to productive use
Learning curve = Accessible to intermediate+ traders
Visual clarity = No information overload
Configuration flexibility = 25+ customizable parameters
Risk Disclosure and Best Practices
Important Disclaimers
The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure.
Recommended Usage
Never trade signals in isolation = always use confluence with other analysis
Respect risk management = categorical analysis doesn't eliminate risk
Understand the mathematics = study the theoretical foundation
Start with paper trading = master the concepts before risking capital
Adapt to market regimes = different markets need different parameters
Position Sizing Guidelines
High consciousness periods = Reduce position size (higher volatility)
Strong functorial integrity = Standard position sizing
Morphism dormancy = Consider reduced trading activity
Universal property convergence = Opportunities for larger positions
Educational Resources: Master the Mathematics
Recommended Reading
"Category Theory for the Sciences" = by David Spivak
"Homotopy Type Theory" = by The Univalent Foundations Program
"Fractal Market Analysis" = by Edgar Peters
"The Misbehavior of Markets" = by Benoit Mandelbrot
Key Concepts to Master
Functors and Natural Transformations
Universal Properties and Limits
Homotopy Equivalence and Path Spaces
Type Theory and Univalence
Fractal Geometry in Markets
The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis.
This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide.
Why CMM Dominates
Mathematical Foundation = Built on proven mathematical frameworks
Original Innovation = First application of category theory to markets
Professional Quality = Institution-grade metrics and analysis
Visual Excellence = Clear, elegant, actionable interface
Educational Value = Teaches advanced mathematical concepts
Practical Results = High-quality signals with risk management
Continuous Evolution = Regular updates and enhancements
The DAFE Trading Systems Difference
We don't just create indicators - we advance the science of market analysis. Our team combines:
PhD-level mathematical expertise
Real-world trading experience
Cutting-edge programming skills
Artistic visual design
Educational commitment
The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics.
Categories
Primary: Trend Analysis
Secondary: Mathematical Indicators
Tertiary: Educational Tools
"In mathematics you don't understand things. You just get used to them." - John von Neumann
"The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems
Trade with Mathematical Precision. Trade with Categorical Market Morphisms.
Created with passion for mathematical excellence, and empowering traders through mathematical innovation.
— Dskyz, Trade with insight. Trade with anticipation.
Grid Long & Short Strategy [ trader_N08 ]Core Logic & Methodology
1. Trend & Momentum Filters:
The strategy uses two Exponential Moving Averages (EMAs): a slow EMA (default 200) for trend direction, and a fast EMA (default 50) for additional confirmation.
For long trades: the price must be above both EMAs and the RSI (Relative Strength Index, period 14) must be above a user-defined threshold (default 40).
For short trades: the price must be below both EMAs and the RSI must be below a user-defined threshold (default 60).
2. Volume Confirmation:
Trades are only considered when the current volume exceeds a multiple (default 1.2x) of the 20-period average volume, aiming to avoid low-liquidity signals.
3. Grid Entry System:
Upon a valid signal, the strategy opens an initial position and sets a “base price.”
Additional entries (“grid levels”) are added if the price moves against the initial position by a multiple of the Average True Range (ATR), with each subsequent grid level spaced further apart using an expansion factor.
The number of grid levels is capped (default: 1, user-adjustable) to control risk and position sizing.
4. Risk Management:
Each position uses both a fixed stop loss and take profit, defined as a percentage of the base entry price (defaults: 0.3% stop, 4% take profit).
A trailing stop is also applied, based on a user-defined multiple of ATR.
Only one grid is active per direction at a time; grids reset when all positions are closed.
---
Default Properties & Backtest Settings
Account Size: 10000$
Commission: 0.01 %
Slippage: 5 ticks
Risk Per Trade: The default settings are designed to risk a small percentage of equity per grid level, but users should verify that their position sizing does not exceed sustainable risk (generally not more than 5–10% per trade).
Sample Size: The strategy is intended to generate a sufficient number of trades when applied to liquid markets and appropriate timeframes (e.g., 15m–4h charts on major FX, crypto, or indices).
---
Underlying Concepts
Grid Trading: A method of adding positions at predefined intervals as price moves, aiming to capture mean reversion or trend continuation.
Trend & Momentum Confirmation: Reduces false entries by requiring alignment of price, moving averages, and RSI.
ATR-Based Spacing: Uses market volatility to dynamically set grid distances and trailing stops.
Volume Filter: Seeks to avoid signals during low-activity periods.
Frequent Swing Trading Supertrend Strategy (Daily)Made By Riddhiman Bandyopadhyay
How to Use-
Set Chart to Daily: Ensure your TradingView chart is set to a daily timeframe (D).
Add Strategy: Copy the Pine Script code into TradingView’s Pine Editor, compile, and add it to your NIFTY chart.
Logic Behind the Backtest : Use TradingView’s Strategy Tester to evaluate performance over the past few months (e.g., March to June 2025). Check if the buy/sell signals occur more frequently and capture shorter swings.
Fine-Tune: If signals are too frequent (leading to whipsaws), increase atr Period to 12 or factor to 3.5. If still not frequent enough, reduce maPeriod to 8 or lower the RSI thresholds to 65/35.
Why This Should Work Better
Increased Sensitivity: The Supertrend (ATR 10, factor 3.0) and 10-period SMA make the strategy more responsive to daily price movements, generating more signals.
Fewer Restrictions: Removing the 50-period SMA filter and loosening entry conditions allow trades in a wider range of market conditions.
Quicker Exits: The 3% profit target encourages faster exits, freeing up capital for new trades, thus increasing frequency.
Balanced Filtering: The RSI (70/30) still filters out extreme conditions, but it’s less restrictive, allowing more trades.
