DB1800 Gann Angle Levels Table (CMP Based)

4 天前

Gann Angles for Resistance and Support
2 = 360 degree for 1 month
1 = 180 degree for 1 week
0.5 = 90 degree for 1 to 2 days
0.25 = 45 degree for next day
0.125 = 22.5 degree for more granular than next day (scalping)

The only thing that multiplies when you share it is knowledge.

Inspired by Sudhir Sharma Sir
youtube.com/@SudhirSharmaStockMarketlearner

4 天前

發行說明

Gann Angles for Resistance and Support
2 = 360 degree for 1 month
1 = 180 degree for 1 week
0.5 = 90 degree for 1 to 2 days
0.25 = 45 degree for next day
0.125 = 22.5 degree for more granular than next day (scalping)

The only thing that multiplies when you share it is knowledge.

Inspired by Sudhir Sharma Sir
youtube.com/@SudhirSharmaStockMarketlearner

4 天前

發行說明

A Quantitative Framework for Time-Price Harmonics Using Gann Angular Projections

Abstract:
This document presents a systematic methodology to derive predictive support and resistance levels based on the geometric principles of W. D. Gann. By mapping temporal cycles to angular increments on a square-root-based price axis, the model offers a structured approach to forecasting short-, medium-, and long-term price inflection zones. The theoretical foundation aligns with Gann’s assertion that time and price are symmetrical and governed by natural law.

1. Introduction
W. D. Gann proposed that markets operate not solely under linear price progression but through rhythmic cycles that harmonize both price and time. His methods combined geometry, astrology, and numerology. Of particular interest is his use of angular divisions derived from circular motion (360 degrees), applied to price via its square root.

This method assumes that equal increments in the square root of price correspond to proportionate angular shifts, each representing specific temporal intervals.

2. Methodology

Let:

* P be the last closing price
* √P = x be the square root of price
* θ ∈ {22.5°, 45°, 90°, 180°, 360°}
* Let step s be the decimal representation of angle increments on the square root scale

| Timeframe | Angle (°) | Step (∆x) | Interpretation |
| ------------------- | --------- | --------- | --------------------------- |
| Intraday (Scalping) | 22.5° | ±0.125 | Micro-move (1–4 hours) |
| Next Day | 45° | ±0.25 | Daily rotational move |
| Short Swing | 90° | ±0.5 | 1–2 day price action |
| Weekly Projection | 180° | ±1.0 | Approximate 1-week range |
| Monthly Projection | 360° | ±2.0 | Monthly price-time rotation |

Support and Resistance Calculation:

Given:

* Rθ = (x + s)^2
* Sθ = (x - s)^2

Where:

* Rθ = projected resistance at angle θ
* Sθ = projected support at angle θ

These values represent price levels where harmonic resonance may occur, potentially leading to reversals or accelerations.

3. Interpretation and Application

These angular levels are not arbitrary, but rather reflect Gann’s view of natural law in market movement, analogous to planetary orbits or electromagnetic wave harmonics. When price aligns with one of these harmonics, a pivot (support or resistance) is more probable.

This technique is best applied:

* To high-liquidity instruments such as Nifty or Bank Nifty
* Alongside time cycle clusters
* On instruments that demonstrate geometric price behavior

4. Conclusion

The integration of square root scaling with angular divisions provides a powerful, non-linear approach to forecasting. Unlike linear regression or moving average-based support and resistance, this technique anticipates rotational harmonics of the market—suggesting that price and time are not separate variables but components of a unified cyclic system.

5. Attribution and Inspiration

The only thing that multiplies when you share it is knowledge.

This framework is inspired by the educational contributions of Sudhir Sharma Sir, whose teachings on Gann and time cycles continue to enrich market learners.
YouTube: [youtube.com/@SudhirSharmaStockMarketlearner]

4 天前

發行說明

A Quantitative Framework for Time-Price Harmonics Using Gann Angular Projections

Abstract:
This document presents a systematic methodology to derive predictive support and resistance levels based on the geometric principles of W. D. Gann. By mapping temporal cycles to angular increments on a square-root-based price axis, the model offers a structured approach to forecasting short-, medium-, and long-term price inflection zones. The theoretical foundation aligns with Gann’s assertion that time and price are symmetrical and governed by natural law.

1. Introduction
W. D. Gann proposed that markets operate not solely under linear price progression but through rhythmic cycles that harmonize both price and time. His methods combined geometry, astrology, and numerology. Of particular interest is his use of angular divisions derived from circular motion (360 degrees), applied to price via its square root.

This method assumes that equal increments in the square root of price correspond to proportionate angular shifts, each representing specific temporal intervals.

2. Methodology

Let:

* P be the last closing price
* √P = x be the square root of price
* θ ∈ {22.5°, 45°, 90°, 180°, 360°}
* Let step s be the decimal representation of angle increments on the square root scale

| Timeframe | Angle (°) | Step (∆x) | Interpretation |
| ------------------- | --------- | --------- | --------------------------- |
| Intraday (Scalping) | 22.5° | ±0.125 | Micro-move (1–4 hours) |
| Next Day | 45° | ±0.25 | Daily rotational move |
| Short Swing | 90° | ±0.5 | 1–2 day price action |
| Weekly Projection | 180° | ±1.0 | Approximate 1-week range |
| Monthly Projection | 360° | ±2.0 | Monthly price-time rotation |

Support and Resistance Calculation:

Given:

* Rθ = (x + s)^2
* Sθ = (x - s)^2

Where:

* Rθ = projected resistance at angle θ
* Sθ = projected support at angle θ

These values represent price levels where harmonic resonance may occur, potentially leading to reversals or accelerations.

3. Interpretation and Application

These angular levels are not arbitrary, but rather reflect Gann’s view of natural law in market movement, analogous to planetary orbits or electromagnetic wave harmonics. When price aligns with one of these harmonics, a pivot (support or resistance) is more probable.

This technique is best applied:

* To high-liquidity instruments such as Nifty or Bank Nifty
* Alongside time cycle clusters
* On instruments that demonstrate geometric price behavior

4. Conclusion

The integration of square root scaling with angular divisions provides a powerful, non-linear approach to forecasting. Unlike linear regression or moving average-based support and resistance, this technique anticipates rotational harmonics of the market—suggesting that price and time are not separate variables but components of a unified cyclic system.

5. Attribution and Inspiration

The only thing that multiplies when you share it is knowledge.

This framework is inspired by the educational contributions of Sudhir Sharma Sir, whose teachings on Gann and time cycles continue to enrich market learners.
YouTube: [youtube.com/@SudhirSharmaStockMarketlearner]

4 天前

發行說明

A Quantitative Framework for Time-Price Harmonics Using Gann Angular Projections

Abstract:
This document presents a systematic methodology to derive predictive support and resistance levels based on the geometric principles of W. D. Gann. By mapping temporal cycles to angular increments on a square-root-based price axis, the model offers a structured approach to forecasting short-, medium-, and long-term price inflection zones. The theoretical foundation aligns with Gann’s assertion that time and price are symmetrical and governed by natural law.

1. Introduction
W. D. Gann proposed that markets operate not solely under linear price progression but through rhythmic cycles that harmonize both price and time. His methods combined geometry, astrology, and numerology. Of particular interest is his use of angular divisions derived from circular motion (360 degrees), applied to price via its square root.

This method assumes that equal increments in the square root of price correspond to proportionate angular shifts, each representing specific temporal intervals.

2. Methodology

Let:

* P be the last closing price
* √P = x be the square root of price
* θ ∈ {22.5°, 45°, 90°, 180°, 360°}
* Let step s be the decimal representation of angle increments on the square root scale

| Timeframe | Angle (°) | Step (∆x) | Interpretation |
| ------------------- | --------- | --------- | --------------------------- |
| Intraday (Scalping) | 22.5° | ±0.125 | Micro-move (1–4 hours) |
| Next Day | 45° | ±0.25 | Daily rotational move |
| Short Swing | 90° | ±0.5 | 1–2 day price action |
| Weekly Projection | 180° | ±1.0 | Approximate 1-week range |
| Monthly Projection | 360° | ±2.0 | Monthly price-time rotation |

Support and Resistance Calculation:

Given:

* Rθ = (x + s)^2
* Sθ = (x - s)^2

Where:

* Rθ = projected resistance at angle θ
* Sθ = projected support at angle θ

These values represent price levels where harmonic resonance may occur, potentially leading to reversals or accelerations.

3. Interpretation and Application

These angular levels are not arbitrary, but rather reflect Gann’s view of natural law in market movement, analogous to planetary orbits or electromagnetic wave harmonics. When price aligns with one of these harmonics, a pivot (support or resistance) is more probable.

This technique is best applied:

* To high-liquidity instruments such as Nifty or Bank Nifty
* Alongside time cycle clusters
* On instruments that demonstrate geometric price behavior

4. Conclusion

The integration of square root scaling with angular divisions provides a powerful, non-linear approach to forecasting. Unlike linear regression or moving average-based support and resistance, this technique anticipates rotational harmonics of the market—suggesting that price and time are not separate variables but components of a unified cyclic system.

5. Attribution and Inspiration

The only thing that multiplies when you share it is knowledge.

This framework is inspired by the educational contributions of Sudhir Sharma Sir, whose teachings on Gann and time cycles continue to enrich market learners.
YouTube: youtube.com/@SudhirSharmaStockMarketlearner

4 天前

發行說明

A Quantitative Framework for Time-Price Harmonics Using Gann Angular Projections

Abstract:
This document presents a systematic methodology to derive predictive support and resistance levels based on the geometric principles of W. D. Gann. By mapping temporal cycles to angular increments on a square-root-based price axis, the model offers a structured approach to forecasting short-, medium-, and long-term price inflection zones. The theoretical foundation aligns with Gann’s assertion that time and price are symmetrical and governed by natural law.

1. Introduction
W. D. Gann proposed that markets operate not solely under linear price progression but through rhythmic cycles that harmonize both price and time. His methods combined geometry, astrology, and numerology. Of particular interest is his use of angular divisions derived from circular motion (360 degrees), applied to price via its square root.

This method assumes that equal increments in the square root of price correspond to proportionate angular shifts, each representing specific temporal intervals.

2. Methodology

Let:

* P be the last closing price
* √P = x be the square root of price
* θ ∈ {22.5°, 45°, 90°, 180°, 360°}
* Let step s be the decimal representation of angle increments on the square root scale

| Timeframe | Angle (°) | Step (∆x) | Interpretation |
| ------------------- | --------- | --------- | --------------------------- |
| Intraday (Scalping) | 22.5° | ±0.125 | Micro-move (1–4 hours) |
| Next Day | 45° | ±0.25 | Daily rotational move |
| Short Swing | 90° | ±0.5 | 1–2 day price action |
| Weekly Projection | 180° | ±1.0 | Approximate 1-week range |
| Monthly Projection | 360° | ±2.0 | Monthly price-time rotation |

Support and Resistance Calculation:

Given:

* Rθ = (x + s)^2
* Sθ = (x - s)^2

Where:

* Rθ = projected resistance at angle θ
* Sθ = projected support at angle θ

These values represent price levels where harmonic resonance may occur, potentially leading to reversals or accelerations.

3. Interpretation and Application

These angular levels are not arbitrary, but rather reflect Gann’s view of natural law in market movement, analogous to planetary orbits or electromagnetic wave harmonics. When price aligns with one of these harmonics, a pivot (support or resistance) is more probable.

This technique is best applied:

* To high-liquidity instruments such as Nifty or Bank Nifty
* Alongside time cycle clusters
* On instruments that demonstrate geometric price behavior

4. Conclusion

The integration of square root scaling with angular divisions provides a powerful, non-linear approach to forecasting. Unlike linear regression or moving average-based support and resistance, this technique anticipates rotational harmonics of the market—suggesting that price and time are not separate variables but components of a unified cyclic system.

5. Attribution and Inspiration

The only thing that multiplies when you share it is knowledge.

This framework is inspired by the educational contributions of Sudhir Sharma Sir, whose teachings on Gann and time cycles continue to enrich market learners.
YouTube: [youtube.com/@SudhirSharmaStockMarketlearner]

3 天前

發行說明

Update with Table positioning