Chapter 1: Understanding Support and Resistance Levels

Identifying objective support and resistance levels can be challenging, yet it is achievable. This article introduces a groundbreaking method for determining quality levels that can serve as indicators to validate our trading biases. Following the success of my previous publication, "Trend Following Strategies in Python," I am excited to announce a new book that delves into advanced contrarian indicators and strategies. For those interested, you can explore a sample at the Amazon link provided below, or if you prefer, you can purchase the PDF version at the end of this article.

Introduction to Support and Resistance

In its simplest terms, a support level is a price point expected to prevent further declines. When the market approaches this area, adopting a bullish outlook is typically advisable. Conversely, a resistance level is a price point expected to halt upward movement, and a bearish stance is warranted when approaching such an area. The chart below illustrates the support and resistance levels, with support indicated in green and resistance in blue, based on subjective empirical observation.

There are various methods to identify support and resistance levels:

1. Charting: This method relies on past price reactions to project future levels. While useful, it can be highly subjective and vary between traders.
2. Fibonacci Retracements: Utilizing the Fibonacci sequence, this technique provides less subjectivity in determining reactionary levels.
3. Moving Averages: This objective method employs moving averages as dynamic support and resistance levels. However, the multitude of periods and types can affect reliability.
4. Pivot Points: A time-tested approach, this method calculates potential future support and resistance lines effectively and quickly.

It's essential to grasp the underlying concepts rather than focusing solely on code. My books contain the coding details for most strategies.

Chapter 2: K's Objective Support & Resistance Lines

Finding support and resistance zones can be inherently complex. While pivot points and moving averages are common tools, a novel approach based on range techniques has emerged. This method involves identifying support around specific thresholds of historical ranges. Here’s how to establish K's objective support and resistance levels:

1. Calculate the difference between the highest highs and lowest lows over a defined lookback period to determine the maximum range.
2. Establish the support level as a percentage of the previously measured range.
3. Set the resistance level as another percentage of the same range.

For example, with a maximum range of 0.125 on the EURUSD, the current support can be calculated by adding the minimum lows to 0.125 multiplied by 0.10, while the resistance is determined by adding the maximum highs to 0.125 multiplied by 0.90.

Video Description: This tutorial explains how to identify support and resistance levels effectively in trading.

Chapter 3: Generating Trading Signals

We assume that the market will bounce off support levels and stall at resistance levels. A long (Buy) signal is triggered when the market reaches support, while a short (Sell) signal is generated at resistance.

def signal(data, high_price, low_price, support_level, resistance_level, buy_column, sell_column):

data = adder(data, 5)

for i in range(len(data)):

if data[i, low_price] <= data[i, support_level] and

data[i - 1, low_price] > data[i - 1, support_level] and

data[i - 2, low_price] > data[i - 2, support_level]:

data[i, buy_column] = 1

elif data[i, high_price] >= data[i, resistance_level] and

data[i - 1, high_price] < data[i - 1, resistance_level] and

data[i - 2, high_price] < data[i - 2, resistance_level]:

data[i, sell_column] = -1

return data

Video Description: Learn how to master the support and resistance trading strategy with essential insights and techniques.