Camarilla Pivots

The Camarilla Pivots indicator is a powerful tool for traders seeking to decode market volatility and pinpoint hidden support and resistance levels. Developed in the late 1980s, this indicator has become a staple for both institutional and retail traders. It offers a systematic approach to anticipating price reversals and breakouts, making it invaluable for day traders, swing traders, and even algorithmic strategies. In this comprehensive guide, you'll learn the theory, calculation, practical application, and advanced nuances of Camarilla Pivots, with real-world code examples and actionable trading scenarios.

1. Hook & Introduction

Imagine you're a trader watching the market whip back and forth. Suddenly, price slams into a level and reverses sharply—leaving most traders confused. But you, using the Camarilla Pivots indicator, anticipated this move. Camarilla Pivots, a volatility-based technical indicator, helps traders identify where price is likely to stall, reverse, or break out. In this article, you'll master how to calculate, interpret, and trade with Camarilla Pivots, and even code your own indicator for any platform.

2. What Are Camarilla Pivots?

Camarilla Pivots are a set of mathematically derived price levels based on the previous trading session's high, low, and close. Invented by Nick Scott in 1989, the indicator was designed to help institutional traders identify intraday support and resistance zones. Unlike classic pivots, Camarilla Pivots use multipliers to create tighter, more responsive levels—making them ideal for volatile and range-bound markets. The core idea: price tends to oscillate between these levels, offering traders clear zones for entries, exits, and risk management.

3. Mathematical Formula & Calculation

The Camarilla Pivots formula uses the previous day's high, low, and close to calculate eight key levels—four above and four below the close. The most commonly used are H4, H3, L3, and L4. Here are the formulas:

• H4 = Close + (High - Low) × 1.1 / 2
• L4 = Close - (High - Low) × 1.1 / 2
• H3 = Close + (High - Low) × 1.025 / 2
• L3 = Close - (High - Low) × 1.025 / 2

Some traders also use H5/L5 and H2/L2 for more granular levels, but H4/L4 and H3/L3 are the most actionable. The multipliers (1.1 and 1.025) are empirically chosen to reflect typical volatility and mean-reversion behavior.

Worked Example:

Previous High: 110
Previous Low: 100
Previous Close: 105

H4 = 105 + (110-100) × 1.1 / 2 = 105 + 5.5 = 110.5
L4 = 105 - (110-100) × 1.1 / 2 = 105 - 5.5 = 99.5
H3 = 105 + (110-100) × 1.025 / 2 = 105 + 5.125 = 110.125
L3 = 105 - (110-100) × 1.025 / 2 = 105 - 5.125 = 99.875

These levels become your map for the next trading session.

4. How Camarilla Pivots Work in Practice

Camarilla Pivots are recalculated at the start of each session (daily, hourly, or custom timeframe). Traders plot these levels on their charts and watch how price interacts with them. The H4 and L4 levels act as strong resistance and support, respectively. When price approaches these zones, traders look for reversal signals or, if price breaks through, confirmation of a new trend. H3 and L3 serve as secondary levels, often used for partial profit-taking or tighter stop-loss placement.

• Reversal Trades: Enter short at H4 or long at L4, with stops just beyond the level.
• Breakout Trades: Enter in the direction of the breakout if price closes beyond H4 or L4, targeting further extension.

These strategies are especially effective in range-bound or mean-reverting markets.

5. Why Camarilla Pivots Matter

Many traders struggle to identify where price will reverse or accelerate. Camarilla Pivots provide a systematic, objective framework for mapping out these zones. Their strengths include:

• Precision: Levels are mathematically derived, reducing subjectivity.
• Adaptability: Works on any liquid market—stocks, forex, crypto, futures.
• Speed: Easy to calculate and plot, even for algorithmic trading.
• Risk Management: Clear zones for stop-loss and take-profit placement.

However, Camarilla Pivots are not a magic bullet. In strong trends, price may ignore these levels entirely. That's why combining them with other indicators is crucial.

6. Real-World Trading Scenarios

Let's walk through a typical trading day using Camarilla Pivots. Suppose you're trading EUR/USD on a 1-hour chart. You calculate the Camarilla levels at the start of the session:

• Price approaches H4 and forms a bearish engulfing candlestick. You enter a short trade, placing your stop just above H4 and targeting H3 for your first take-profit.
• Later, price drops to L4 and forms a bullish hammer. You go long, with a stop below L4 and a target at L3.
• If price breaks above H4 with strong momentum, you switch to a breakout strategy, entering long and trailing your stop as price extends.

These scenarios illustrate how Camarilla Pivots can guide both reversal and breakout trades, adapting to changing market conditions.

7. Combining Camarilla Pivots with Other Indicators

For best results, use Camarilla Pivots alongside other technical tools:

• RSI: Confirm overbought/oversold conditions at H4/L4.
• MACD: Gauge trend direction and momentum.
• ATR: Filter trades based on volatility.
• Volume: Confirm breakout strength.

Example Confluence: Only take reversal trades at H4/L4 if RSI is also overbought/oversold and MACD shows divergence. This increases the probability of a successful trade.

8. Coding Camarilla Pivots: Multi-Language Examples

Implementing Camarilla Pivots in your trading platform is straightforward. Below are code examples for Pine Script, Python, Node.js, C++, and MetaTrader 5. Use these templates to automate your analysis or build custom indicators.

// C++ Example
#include <iostream>
struct OHLC {
    double high, low, close;
};
void camarilla(const OHLC& ohlc) {
    double h4 = ohlc.close + (ohlc.high - ohlc.low) * 1.1 / 2;
    double l4 = ohlc.close - (ohlc.high - ohlc.low) * 1.1 / 2;
    double h3 = ohlc.close + (ohlc.high - ohlc.low) * 1.025 / 2;
    double l3 = ohlc.close - (ohlc.high - ohlc.low) * 1.025 / 2;
    std::cout << "H4: " << h4 << ", L4: " << l4 << ", H3: " << h3 << ", L3: " << l3 << std::endl;
}
int main() {
    OHLC ohlc = {110, 100, 105};
    camarilla(ohlc);
    return 0;
}

# Python Example
def camarilla_pivots(high, low, close):
    h4 = close + (high - low) * 1.1 / 2
    l4 = close - (high - low) * 1.1 / 2
    h3 = close + (high - low) * 1.025 / 2
    l3 = close - (high - low) * 1.025 / 2
    return {'H4': h4, 'L4': l4, 'H3': h3, 'L3': l3}

print(camarilla_pivots(110, 100, 105))

// Node.js Example
function camarillaPivots(high, low, close) {
  const h4 = close + (high - low) * 1.1 / 2;
  const l4 = close - (high - low) * 1.1 / 2;
  const h3 = close + (high - low) * 1.025 / 2;
  const l3 = close - (high - low) * 1.025 / 2;
  return { H4: h4, L4: l4, H3: h3, L3: l3 };
}
console.log(camarillaPivots(110, 100, 105));

// Pine Script v5: Camarilla Pivots Indicator
//@version=6
indicator("Camarilla Pivots", overlay=true)
length = input.int(1, title="Pivot Length (days)")
multH4 = input.float(1.1, title="H4/L4 Multiplier")
multH3 = input.float(1.025, title="H3/L3 Multiplier")
highPrev = ta.valuewhen(session.isfirst, high[1], 0)
lowPrev = ta.valuewhen(session.isfirst, low[1], 0)
closePrev = ta.valuewhen(session.isfirst, close[1], 0)
range = highPrev - lowPrev
H4 = closePrev + (range * multH4 / 2)
L4 = closePrev - (range * multH4 / 2)
H3 = closePrev + (range * multH3 / 2)
L3 = closePrev - (range * multH3 / 2)
plot(H4, color=color.red, linewidth=2, title="H4 (Strong Resistance)")
plot(L4, color=color.green, linewidth=2, title="L4 (Strong Support)")
plot(H3, color=color.orange, linewidth=1, title="H3 (Weak Resistance)")
plot(L3, color=color.lime, linewidth=1, title="L3 (Weak Support)")

// MetaTrader 5 Example
#property indicator_chart_window
input double multH4 = 1.1;
input double multH3 = 1.025;
double H4, L4, H3, L3;
int OnCalculate(const int rates_total,
                const int prev_calculated,
                const datetime &time[],
                const double &open[],
                const double &high[],
                const double &low[],
                const double &close[],
                const long &tick_volume[],
                const long &volume[],
                const int &spread[])
{
    double range = high[1] - low[1];
    H4 = close[1] + (range * multH4 / 2);
    L4 = close[1] - (range * multH4 / 2);
    H3 = close[1] + (range * multH3 / 2);
    L3 = close[1] - (range * multH3 / 2);
    // Plotting logic here
    return(rates_total);
}

9. Customizing Camarilla Pivots

Traders often tweak Camarilla Pivots to suit their style or market. Here are some customization options:

• Change Multipliers: Adjust 1.1 and 1.025 for more or less sensitivity.
• Timeframe: Use daily, weekly, or even intraday bars for calculation.
• Combine with Alerts: Add alert conditions in your code for H4/L4 cross events.
• Visuals: Change line colors, thickness, or add labels for clarity.

For example, in Pine Script, you can add alertcondition() to notify you when price crosses H4 or L4, or use input fields to let users set their own multipliers.

10. FastAPI Python Implementation

For algorithmic traders and developers, integrating Camarilla Pivots into a backend API is simple. Here’s a FastAPI example for serving Camarilla levels via HTTP:

// See previous C++ example

# FastAPI + Pandas: Calculate Camarilla Pivots
from fastapi import FastAPI
from pydantic import BaseModel
import pandas as pd

app = FastAPI()

class OHLC(BaseModel):
    high: float
    low: float
    close: float

@app.post("/camarilla")
def camarilla_pivots(data: OHLC):
    high, low, close = data.high, data.low, data.close
    h4 = close + (high - low) * 1.1 / 2
    l4 = close - (high - low) * 1.1 / 2
    h3 = close + (high - low) * 1.025 / 2
    l3 = close - (high - low) * 1.025 / 2
    return {"H4": h4, "L4": l4, "H3": h3, "L3": l3}

// Node.js Express Example
const express = require('express');
const app = express();
app.use(express.json());
app.post('/camarilla', (req, res) => {
  const { high, low, close } = req.body;
  const h4 = close + (high - low) * 1.1 / 2;
  const l4 = close - (high - low) * 1.1 / 2;
  const h3 = close + (high - low) * 1.025 / 2;
  const l3 = close - (high - low) * 1.025 / 2;
  res.json({ H4: h4, L4: l4, H3: h3, L3: l3 });
});
app.listen(3000);

// See previous Pine Script example

// See previous MetaTrader 5 example

This API can be integrated with trading bots, dashboards, or even mobile apps. Store results in a database for backtesting or analytics.

11. Backtesting & Performance

Backtesting Camarilla Pivots is essential to understand their effectiveness. Here’s a sample Python backtest setup:

# Python Backtest Example
import pandas as pd

def backtest_camarilla(df):
    wins, losses = 0, 0
    for i in range(1, len(df)):
        high, low, close = df.iloc[i-1][['High', 'Low', 'Close']]
        h4 = close + (high - low) * 1.1 / 2
        l4 = close - (high - low) * 1.1 / 2
        # Simple reversal logic
        if df.iloc[i]['High'] >= h4:
            # Short at h4, exit at h3
            if df.iloc[i]['Low'] <= close + (high - low) * 1.025 / 2:
                wins += 1
            else:
                losses += 1
        if df.iloc[i]['Low'] <= l4:
            # Long at l4, exit at l3
            if df.iloc[i]['High'] >= close - (high - low) * 1.025 / 2:
                wins += 1
            else:
                losses += 1
    return wins, losses

In range-bound markets like EUR/USD 1H, reversal trades at H4/L4 can yield a 55-60% win rate with a 1:1 risk/reward. In trending markets, false signals increase, so always use a trend filter (e.g., moving average slope).

12. Advanced Variations

Advanced traders and institutions often modify Camarilla Pivots for specific strategies:

• Dynamic Multipliers: Adjust multipliers based on ATR or recent volatility.
• VWAP Confluence: Combine Camarilla levels with VWAP for institutional setups.
• Scalping: Use on 5-minute charts for rapid mean-reversion trades.
• Swing Trading: Apply on daily/weekly charts for broader moves.
• Options Trading: Use levels to structure iron condors or straddles around expected reversals.

Institutions may also use proprietary multipliers or blend Camarilla with other pivot systems for added robustness.

13. Common Pitfalls & Myths

Despite their power, Camarilla Pivots are often misunderstood:

• Myth: Every touch of H4/L4 will reverse. Reality: In strong trends, price can break through—always confirm with price action or trend filters.
• Pitfall: Overfitting multipliers to past data. Solution: Use standard values unless you have statistical evidence for change.
• Pitfall: Ignoring market context. Solution: Use Camarilla Pivots in conjunction with trend indicators and volume.
• Myth: Camarilla Pivots work on all assets equally. Reality: They are most effective in liquid, range-bound markets.

14. Conclusion & Summary

Camarilla Pivots are a versatile, mathematically sound tool for mapping out key price levels. Their strengths lie in precision, adaptability, and ease of use. They shine in range-bound markets and when combined with other indicators. However, they are not foolproof—traders must avoid over-reliance and always consider market context. For best results, use Camarilla Pivots as part of a broader trading plan, alongside trend filters, momentum indicators, and sound risk management. Related indicators worth exploring include Classic Pivots, Woodie’s Pivots, and Fibonacci Pivots. Mastering Camarilla Pivots can give you a decisive edge in anticipating market moves and managing trades with confidence.