PyInvesting

Market breadth Updated 11 Sep 2026

Fear & Greed Index

A rules-based view of market participation—and how that signal changes the balance between stocks and cash.

Current breadth

55% uptrending

Greed

Share of stocks trading above their six-month exponential moving average.

Model exposure

Current allocation

100% invested in stocks and 0% cash.

S&P 500
100%
Cash
0%

As of 11 Sep 2026

Market participation

Current breadth history

Higher readings mean more stocks are participating in the market’s advance.

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Risk response

How the signal changes portfolio exposure

As fewer stocks remain in an uptrend, the model raises cash. As participation recovers, it moves back toward equities.

The index observes the percentage of stocks above their six-month exponential moving average. Broad participation supports a larger equity allocation; weakening participation increases the cash allocation.

This is a systematic risk-management rule, not a prediction of the market’s next move. It can reduce exposure during prolonged weakness, but it can also react after prices have already moved.

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Backtest evidence

Historical risk-managed performance

Compare an illustrative S&P 500 allocation using the model’s cash signal with an S&P 500 buy-and-hold benchmark.

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Illustrative backtest only. Results do not include every fee, tax, or implementation constraint and do not represent live performance.

Methodology

How to interpret this index

Use the reading as one input to a defined investment process, not as a standalone instruction to buy or sell.

What fear and greed describe

“Fear” and “greed” are plain-language labels for weak and strong market participation. The measurement itself is mechanical: how many stocks remain above a medium-term trend line.

A low reading can persist during a drawdown, while a high reading can remain elevated through a long advance. The regime label is context, not a turning-point forecast.

How this differs from CNN

CNN’s Fear & Greed Index combines seven market indicators, including momentum, options activity, volatility, and safe-haven demand. PyInvesting uses one transparent market-breadth rule and connects it directly to a testable stock-and-cash allocation.

The narrower method is easier to reproduce, but it captures less information. The two indices should not be expected to report the same regime.