OTC Seasonal forecasting tool 2.0

2 May

Seasonality Forecasting Tool – Advanced Seasonal Pattern Analysis (Inspired by Bernd Skorupinski Methodology)

📈 Description:
This script provides a structured way to analyze seasonal trends across financial markets, helping traders identify historical patterns that tend to repeat at specific times of the year. Inspired by Bernd Skorupinski’s institutional strategy, it has been refined with enhanced smoothing and customization options to improve adaptability across asset classes like commodities, forex, and indices.

👉 Core Functionality:

Analyzes historical price data over multiple lookback periods (5, 10, and 15 years) to calculate average seasonal performance.

Generates a smoothed seasonal curve that visually highlights periods of expected strength or weakness.

Allows users to customize lookback periods and adjust smoothing parameters, offering flexibility based on market type and volatility.

This tool is designed to be used as a contextual filter rather than a trade trigger—adding a layer of time-based confluence to enhance decision-making.

📊 Applied Example – Crude Oil Seasonality & Demand Zone Alignment

To demonstrate practical usage, here’s an example using Light Crude Oil Futures (CL1!) where seasonal tendencies and price structure aligned to create a high-probability setup.

Setup Steps:

1️⃣ Structural Context – Price Reaching a Demand Zone:
The market had been in a decline and approached a well-defined institutional demand area, which historically attracts buying interest.



2️⃣ Seasonality Analysis – Bullish Bias Identified:
The Seasonality Tool was applied using three distinct lookback windows:

5-year average 🟢

10-year average 🔴

15-year average 🔵

All three seasonal curves showed consistent upward trends during the late December to February period, historically signaling accumulation phases in crude oil markets.

3️⃣ Execution – Trade Setup:

With both:

Price action confirming a technical demand zone,

and seasonality indicating a strong historical bullish period,

a long position was taken targeting the next significant supply zone.

Result:
The trade unfolded as anticipated, with price rebounding strongly and delivering a risk-reward ratio of approximately 1:5.8—an outcome consistent with historical seasonal performance patterns.

⚙️ What Sets This Tool Apart:

Combines multi-timeframe seasonal data into a unified, easy-to-interpret visual output.

Includes custom smoothing algorithms to reduce noise, making the seasonal curves clearer and more reliable in fast-moving markets.

Offers flexibility to analyze not only commodities but also forex, indices, and other instruments influenced by recurring cycles (e.g., agricultural products, metals).

📌 Best Practices for Use:

Apply the tool alongside key technical zones (demand/supply) to find optimal trade timing.

Look for confluence across at least two of the seasonal curves (e.g., 5-year and 10-year averages agreeing on direction).

Use in combination with other market analysis tools—such as valuation indicators, COT data, or smart money flow—for full confirmation.

5 May

Sürüm Notları

The Seasonality Foracsting Tool, inspired by Bernd Skorupinski

Seasonality Forecasting Tool – Advanced Seasonal Pattern Analysis (Inspired by Bernd Skorupinski Methodology)

📈 Description:
This script provides a structured way to analyze seasonal trends across financial markets, helping traders identify historical patterns that tend to repeat at specific times of the year. Inspired by Bernd Skorupinski’s institutional strategy, it has been refined with enhanced smoothing and customization options to improve adaptability across asset classes like commodities, forex, and indices.


👉 Core Functionality:

Analyzes historical price data over multiple lookback periods (5, 10, and 15 years) to calculate average seasonal performance.

Generates a smoothed seasonal curve that visually highlights periods of expected strength or weakness.

Allows users to customize lookback periods and adjust smoothing parameters, offering flexibility based on market type and volatility.

This tool is designed to be used as a contextual filter rather than a trade trigger—adding a layer of time-based confluence to enhance decision-making.

📊 Applied Example – Crude Oil Seasonality & Demand Zone Alignment

To demonstrate practical usage, here’s an example using Light Crude Oil Futures (CL1!) where seasonal tendencies and price structure aligned to create a high-probability setup.

Setup Steps:

1️⃣ Structural Context – Price Reaching a Demand Zone:
The market had been in a decline and approached a well-defined institutional demand area, which historically attracts buying interest.



2️⃣ Seasonality Analysis – Bullish Bias Identified:
The Seasonality Tool was applied using three distinct lookback windows:


5-year average 🟢

10-year average 🔴

15-year average 🔵

All three seasonal curves showed consistent upward trends during the late December to February period, historically signaling accumulation phases in crude oil markets.

3️⃣ Execution – Trade Setup:


With both:

Price action confirming a technical demand zone,

and seasonality indicating a strong historical bullish period,

a long position was taken targeting the next significant supply zone.



Result:
The trade unfolded as anticipated, with price rebounding strongly and delivering a risk-reward ratio of approximately 1:5.8—an outcome consistent with historical seasonal performance patterns.




⚙️ What Sets This Tool Apart:

Combines multi-timeframe seasonal data into a unified, easy-to-interpret visual output.

Includes custom smoothing algorithms to reduce noise, making the seasonal curves clearer and more reliable in fast-moving markets.

Offers flexibility to analyze not only commodities but also forex, indices, and other instruments influenced by recurring cycles (e.g., agricultural products, metals).

📌 Best Practices for Use:

Apply the tool alongside key technical zones (demand/supply) to find optimal trade timing.

Look for confluence across at least two of the seasonal curves (e.g., 5-year and 10-year averages agreeing on direction).

Use in combination with other market analysis tools—such as valuation indicators, COT data, or smart money flow—for full confirmation.

6 May

Sürüm Notları

Use it with other tools like: valuation, smart money index and Supply and demand levels.