Super Oscillator - Advanced Trend & Momentum Indicator📖 Description
The Super Oscillator is an advanced oscillator-type indicator designed for trend & momentum analysis.
This tool helps traders identify overbought & oversold zones while also determining trend direction.
By incorporating SuperTrend elements, it enhances the accuracy of entry and exit signals.
📊 Features
✅ Trend & Momentum Analysis: Detects price momentum and trend reversals
✅ Overbought & Oversold Zones: Above 90 indicates overbought, below 10 suggests oversold conditions
✅ Filtering Function: Only allows long entries above 50 and short entries below 50
✅ Noise Reduction: Smooths price fluctuations to minimize false signals
✅ Customizable Settings: Adjustable ATR and filtering parameters
🎯 How to Use
1️⃣ Buy Signal: When the Super Oscillator drops below 10 and shows upward momentum
2️⃣ Sell Signal: When the Super Oscillator rises above 90 and shows downward momentum
3️⃣ Filtering: Long entries are only valid if the oscillator is above 50, short entries only below 50
4️⃣ Divergence Trading: Look for discrepancies between price action and the oscillator for potential reversals
⚙️ Indicator Settings
🔹 ATR Length: Used for trailing stop calculations
🔹 Super Oscillator Sensitivity: Adjusts the oscillator's responsiveness
🔹 Overbought/Oversold Thresholds: Customizable levels for extreme market conditions
📈 Example Usage
📌 Trend Following Strategy:
Uptrend: Super Oscillator stays above 50 and price continues making higher highs → Long entry
Downtrend: Super Oscillator stays below 50 and price makes lower lows → Short entry
📌 Reversal Strategy:
Buy when Super Oscillator is below 10 and starts rising
Sell when Super Oscillator is above 90 and starts falling
📢 Disclaimer
This indicator is provided for educational purposes only and does not constitute financial advice.
Traders should incorporate risk management strategies and use this indicator alongside other tools before making trading decisions.
Stockmarkets
Autocorrelation Price Forecasting Backtesting [ScrimpleAI]This script presents an innovative trading backtesting strategy designed to leverage autocorrelation models and linear regression on historical price returns . The goal is to forecast future price movements, identify recurring market cycles, and optimize trading decisions.
Main Functionality
This backtesting script is built to simulate trades by integrating historical autocorrelation with dynamic price forecasting . It incorporates risk management, stop-loss features, and an advanced backtesting date range, providing traders with maximum flexibility for evaluating strategies.
Key Features
1. Customizable Date Range for Backtesting
Allows users to define the exact date period for backtesting their strategies, ensuring they can fine-tune results for specific historical scenarios.
- Inputs: Start and End dates (day, month, year).
2. Autocorrelation Price Forecasting
- Detects cycles in market movements using the `ta.correlation` function.
- Highlights significant cycles when the autocorrelation exceeds a threshold value (default: 0.50).
- Stores projected values based on autocorrelation and linear regression of percentage returns for enhanced forecasting accuracy.
3. Forecast Threshold and Profit Assessment
- Evaluates hypothetical gains by comparing forecasted future prices to the current price.
- Customizable threshold gains to determine minimum profitability requirements for opening trades.
4. Strategy Side
- Long or Short Mode: Users can choose to test either long or short strategies to align with their trading approach.
5. Risk and Trade Management
- Order Sizing: Adjust position size as a percentage of the portfolio.
- Stop-Loss Integration: Dynamically calculates stop-loss based on user-defined percentages.
- Take Profit Target: Automatically sets take-profit levels based on forecasted gains.
6. Visual Alerts
- Provides clear visual signals of long and short entries on the chart, including labels and dynamic coloring.
- Forecasted prices are displayed directly on the chart as a continuous line, enhancing decision-making clarity.
Practical Applications
1. Cycle Detection: Utilize autocorrelation to identify repetitive market behaviors and cycles.
2. Forecasting for Backtesting: Simulate trades and assess the profitability of various strategies based on future price predictions.
3. Risk Management: Test different stop-loss and take-profit configurations.
4. Custom Period Analysis: Evaluate strategy performance in specific historical market conditions using the date range filter.
Core Logic Walkthrough
1. Autocorrelation for Cycle Detection:
- Historical prices are analyzed for recurring patterns using the `ta.correlation` function.
- If a significant cycle is detected (above the `signal_threshold`), the `linreg_values` (linear regression of returns) are stored for price projection.
2. Future Price Estimation: Forecasted price is calculated based on linear regression values and current price movements.
3. Trade Entry Logic
Long Trades
- Triggered if the hypothetical gain exceeds the threshold gain.
- Sets a take-profit level based on the projected future price.
- Includes an optional stop-loss based on user-defined percentages.
Short Trades
- Triggered if the hypothetical gain is less than the negative of the threshold gain.
- Configures take-profit and stop-loss levels for bearish trades.
4. Risk Management
- Position Sizing: Automatically calculates the order size as a percentage of the portfolio.
- Stop-Loss: Dynamically adjusts stop-loss levels to minimize risk.
5. Date Range Filtering: Ensures trades are executed only within the defined backtesting period.
Example Use Case: Backtesting with Autocorrelation
- A trader analyzes a 6-month period using 50 historical bars for autocorrelation.
- Sets a threshold gain of 10% and enables a stop-loss at 5%.
- Evaluates the effectiveness of a long-only strategy in this period to assess its profitability and risk-adjusted performance.
If you find this strategy useful or have ideas for improvements, leave a comment! What new features would you like to see in this strategy?
Autocorrelation Price Forecasting [ScrimpleAI]Discover how to predict future price movements using autocorrelation and linear regression models to identify potential trading opportunities.
An advanced model to predict future price movements using autocorrelation and linear regression. This script helps identify recurring market cycles and calculates potential gains, with clear visual signals for quick and informed decisions.
Main Function
This script leverages an autocorrelation model to estimate the future price of an asset based on historical price relationships. It also integrates linear regression on percentage returns to provide more accurate predictions of price movements.
Key Features
1. Customizable Inputs:
- Analysis Length: number of historical bars used for autocorrelation calculation. Adjustable between 1 and 200.
- Forecast Colors: customize colors for bullish and bearish signals.
2. Price Autocorrelation: uses the ta.correlation function to measure price autocorrelation, detecting significant cycles when the value exceeds a defined threshold ( signal_threshold = 0.50 ).
3. Linear Regression on Returns: calculates percentage returns and applies linear regression to identify the future projected price value.
4. Hypothetical Gain Assessment: evaluates potential profit by comparing the estimated future price with the current price.
5. Visual Alerts:
- Labels: hypothetical gains or losses are displayed as labels above or below the bars.
- Dynamic Coloring: bullish (green) and bearish (red) signals are highlighted directly on the chart.
- Forecast Line: A continuous line is plotted to represent the estimated future price values.
Practical Applications
Short-term Trading : identify repetitive market cycles to anticipate future movements.
Visual Decision-making : colored signals and labels make it easier to visualize potential profit or loss for each trade.
Advanced Customization : adjust the data length and colors to tailor the indicator to your strategies.
💡 What do you think about this model?
If you already use autocorrelation-based analysis or want to try predictive strategies, leave a comment with your feedback!
S&P Short-Range Oscillator**SHOULD BE USED ON THE S&P 500 ONLY**
The S&P Short-Range Oscillator (SRO), inspired by the principles of Jim Cramer's oscillator, is a technical analysis tool designed to help traders identify potential buy and sell signals in the stock market, specifically for the S&P 500 index. The SRO combines several market indicators to provide a normalized measure of market sentiment, assisting traders in making informed decisions.
The SRO utilizes two simple moving averages (SMAs) of different lengths: a 5-day SMA and a 10-day SMA. It also incorporates the daily price change and market breadth (the net change of closing prices). The 5-day and 10-day SMAs are calculated based on the closing prices. The daily price change is determined by subtracting the opening price from the closing price. Market breadth is calculated as the difference between the current closing price and the previous closing price.
The raw value of the oscillator, referred to as SRO Raw, is the sum of the daily price change, the 5-day SMA, the 10-day SMA, and the market breadth. This raw value is then normalized using its mean and standard deviation over a 20-day period, ensuring that the oscillator is centered and maintains a consistent scale. Finally, the normalized value is scaled to fit within the range of -15 to 15.
When interpreting the SRO, a value below -5 indicates that the market is potentially oversold, suggesting it might be a good time to start buying stocks as the market could be poised for a rebound. Conversely, a value above 5 suggests that the market is potentially overbought. In this situation, it may be prudent to hold on to existing positions or consider selling if you have substantial gains.
The SRO is visually represented as a blue line on a chart, making it easy to track its movements. Red and green horizontal lines mark the overbought (5) and oversold (-5) levels, respectively. Additionally, the background color changes to light red when the oscillator is overbought and light green when it is oversold, providing a clear visual cue.
By incorporating the S&P Short-Range Oscillator into your trading strategy, you can gain valuable insights into market conditions and make more informed decisions about when to buy, sell, or hold your stocks. However, always consider other market factors and perform your own analysis before making any trading decisions.
The S&P Short-Range Oscillator is a powerful tool for traders looking to gain insights into market sentiment. It provides clear buy and sell signals through its combination of multiple indicators and normalization process. However, traders should be aware of its lagging nature and potential complexity, and use it in conjunction with other analysis methods for the best results.
Disclaimer
The S&P Short-Range Oscillator is for informational purposes only and should not be considered financial advice. Trading involves risk, and you should conduct your own research or consult a financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this indicator. Use at your own risk.
Buy&Sell Bullish Engulfing - The Quant Science🇺🇸
GENERAL OVERVIEW
Buy&Sell Bullish Engulfing - The Quant Science It is a Buy&Sell strategy based on the 'Bullish Engulfing' candlestick pattern. The main goal of the strategy is to achieve a consistent and sustainable return over time, with a manageable level of risk.
Bullish Engulfing
The template was developed at the top of the Indicator provided by TradingView called 'Engulfing - Bullish'.
ENTRY AND EXIT CRITERIA
Entry: A single long order is opened when the candlestick pattern is formed, and the percentage size of the order (%) is fixed by the trader through the user interface.
Exit: The long trade is closed on a percentage equity take profit-stop loss.
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🇮🇹
PANORAMICA GENERALE
Buy&Sell Bullish Engulfing - The Quant Science è una strategia Buy&Sell basata sul candlestick pattern 'Bullish Engulfing'. L'obiettivo principale della strategia è ottenere un ritorno costante e sostenibile nel tempo, con un livello gestibile di rischio.
Bullish Engulfing
Il template è stato sviluppato al top dell' Indicatore fornito da Trading View chiamato 'Engulfing - Bullish'.
CRITERI DI ENTRATA E USCITA
Entrata: viene aperto un singolo ordine long quando si forma il candlestick pattern, la size percentuale dell'ordine (%) viene selezionato tramite l'interfaccia utente dal trader.
Uscita: la chiusura della posizione avviene unicamente tramite un take profit-stop loss percentuale calcolato sul capitale.
Grid Spot Trading Algorithm V2 - The Quant ScienceGrid Spot Trading Algorithm V2 is the last grid trading algorithm made by our developer team.
Grid Spot Trading Algorithm V2 is a fixed 10-level grid trading algorithm. The grid is divided into an accumulation area (red) and a selling area (green).
In the accumulation area, the algorithm will place new buy orders, selling the long positions on the top of the grid.
BUYING AND SELLING LOGIC
The algorithm places up to 5 limit orders on the accumulation section of the grid, each time the price cross through the middle grid. Each single order uses 20% of the equity.
Positions are closed at the top of the grid by default, with the algorithm closing all orders at the first sell level. The exit level can be adjusted using the user interface, from the first level up to the fifth level above.
CONFIGURING THE ALGORITHM
1) Add it to the chart: Add the script to the current chart that you want to analyze.
2) Select the top of the grid: Confirm a price level with the mouse on which to fix the top of the grid.
3) Select the bottom of the grid: Confirm a price level with the mouse on which to fix the bottom of the grid.
4) Wait for the automatic creation of the grid.
USING THE ALGORITHM
Once the grid configuration process is completed, the algorithm will generate automatic backtesting.
You can add a stop loss that destroys the grid by setting the destruction price and activating the feature from the user interface. When the stop loss is activated, you can view it on the chart.
Stock Intrinsic Value & MOS IndicatorStock Intrinsic Value and MOS Indicator is a powerful tool that can help investors to evaluate the potential value of a particular stock. By taking into account key financial metrics such as earnings per share, price-to-earnings ratio, and dividend yield, this indicator provides a comprehensive analysis of a company's fundamentals, and can be used to estimate its intrinsic value.
To use this indicator, simply input the relevant financial metrics for the stock you're interested in from Yahoo finance, including the P/E ratio, earnings per share, and dividend yield. The indicator will then calculate the stock's intrinsic value based on these inputs, taking into account the company's earnings potential and dividend payments.
In addition to calculating the intrinsic value, the Stock Intrinsic Value and MOS Indicator also allows investors to add a margin of safety to their analysis, which can help to account for unexpected market events or uncertainties. By adding a margin of safety of 20% - 30%, for example, investors can ensure that they are buying the stock at a significant discount to its intrinsic value, providing a cushion against potential losses.
Using the Stock Intrinsic Value and MOS Indicator can be a valuable tool for investors looking to make informed decisions about their investments. By taking into account key financial metrics and adding a margin of safety, investors can be more confident in their investment decisions, and can potentially maximize their returns over the long-term.
However, it's important to remember that the Stock Intrinsic Value and MOS Indicator is just one tool among many that investors can use to evaluate potential investments. As with any investment strategy, it's important to conduct thorough research and analysis before making any investment decisions. Additionally, it's important to keep in mind that no investment strategy is foolproof, and that even the most well-informed investment decisions can still result in losses.
Overall, the Stock Intrinsic Value and MOS Indicator can be a valuable tool for investors looking to evaluate potential investments and make informed decisions about their portfolio. By using this indicator in combination with other tools and strategies, investors can potentially maximize their returns and achieve their long-term investment goals.
Terminal : USD Based Stock Markets Change (%)Hello.
This script is a simple USD Based Stock Markets Change (%) Data Terminal.
You can also set the period to look back manually in the menu.
In this way, an idea can be obtained about Countries' Stock Markets.
And you can observe the stock exchanges of relatively positive and negative countries from others.
Features
Value changes on a percentage basis (%)
Stock exchange values are calculated in dollar terms.
Due to the advantage of movement, future data were chosen instead of spot values on the required instruments.
Stock Markets
Usa : S&P 500 Futures
Japan: Nikkei 225 Futures
England: United Kingdom ( FTSE ) 100
Australia: Australia 200
Canada: S&P / TSX Composite
Switzerland: Swiss Market Index
New Zealand: NZX 50 Index
China: SSE Composite (000001)
Denmark: OMX Copenhagen 25 Index
Hong-Kong: Hang Seng Index Futures
India: Nifty 50
Norway: Oslo Bors All Share Index
Russia: MOEX Russia Index
Sweden: OMX Stockholm Index
Singapore: Singapore 30
Turkey: BIST 100
South Africa: South Africa Top 40 Index
Spain: IBEX 35
France: CAC 40
Italy: FTSE MIB Index
Netherlands: Netherlands 25
Germany : DAX
Regards.
