S&P 500 Information Technology Sector
P/E Ratio
38.12
28 August 2025

The estimated Price-to-Earnings (P/E) Ratio for S&P 500 Information Technology Sector is 38.12, calculated on 28 August 2025.

Considering the last 5 years, an average P/E interval is [26.70 , 33.80]. For this reason, the current P/E can be considered Expensive

P/E Ratio is calculated on the XLK Etf, whose benchmark is the S&P 500 Information Technology Sector.

Historical P/E Ratio

When evaluating the P/E Ratio, it's important to not only look at its absolute value but also compare it to the average of previous periods. This allows for a more comprehensive understanding of the index/market valuation.

The following chart shows how the S&P 500 Information Technology Sector P/E Ratio has changed over time. Furthermore, for some trailing timeframes, you can view the average P/E and standard deviation.

Normalized vs (μ , σ)
28 August 2025 · P/E Ratio: 38.12
28 August 2025 · P/E Ratio: 38.12 · 1Y Average: 36.38 · 1 Std Dev range: [35.43 , 37.33] · 2 Std Dev range: [34.48 , 38.28]
28 August 2025 · P/E Ratio: 38.12 · 5Y Average: 30.25 · 1 Std Dev range: [26.70 , 33.80] · 2 Std Dev range: [23.15 , 37.35]
28 August 2025 · P/E Ratio: 38.12 · 10Y Average: 23.71 · 1 Std Dev range: [17.97 , 29.46] · 2 Std Dev range: [12.23 , 35.20]
28 August 2025 · P/E Ratio: 38.12 · 20Y Average: 18.66 · 1 Std Dev range: [13.85 , 23.47] · 2 Std Dev range: [9.04 , 28.29]
Methodology

The Average P/E (μ) and the Standard Deviation (σ) are calculated excluding 20% outliers (i.e. over a range of values excluding 10% of observations from the top and 10% from the bottom of the dataset). Additionally, P/E values greater than 70 or lower than 1 are logarithmically normalized to reduce distortions.

A P/E between (μ - σ) and (μ + σ) is considered "Fair", over a specific timeframe.
A P/E greater than (μ + σ) is defined "Overvalued", greater than (μ + 2σ) is defined "Expensive".
A P/E less than (μ - σ) is defined "Undervalued", less than (μ - 2σ) is defined "Cheap".

Forward Return Evaluation

It is possible to estimate potential future returns using statistical models based on historical data and market patterns.

These forecasts are purely a statistical exercise and should never be relied upon as the basis for defining one’s investment strategy. They serve only as an analytical tool to explore possible scenarios, not as a guarantee of future performance.
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80% Prediction Return(%) 80% Prediction Return(%) 80% Prediction Return(%)
Period Lower Median Upper R² Lower Median Upper R² Lower Median Upper R²
1 Years -25.89 1.61 29.11 0.0834 -44.59 -6.84 30.91 0.1569 -28.99 11.16 51.31 0.0002
5 Years 2.25 10.22 18.19 0.5010 -19.83 -7.18 5.47 0.5834 11.41 21.67 31.93 0.4468
10 Years 14.36 16.77 19.18 0.2598 -8.69 -2.96 2.77 0.8474 18.37 21.03 23.69 0.1330
20 Years 3.65 7.94 12.23 0.5879 3.65 7.94 12.23 0.5879
Combined regression models Current PE → Forward Return model Trailing → Forward Return model
•Weak correlation (R² < 0.2) - •Good correlation (R² >= 0.7)

The following sections walk you through each model, starting with the initial data and leading to the final parameters achieved.

Current P/E vs Forward Return Model

This chart illustrates the historical relationship between the market’s Price-to-Earnings (P/E) ratio and the subsequent returns over the following years. The horizontal axis shows the P/E ratio observed at a given point in time, while the vertical axis displays the annualized return over the subsequent period (e.g., 10 years).

P/E RATIO vs Forward Return
Scatter plot and stats
Based on the last 30 years, when available
Forward 1Y
Forward 5Y
Forward 10Y
Forward 20Y
38.12
Current P/E Ratio (x₀)
-6.84
Expected Forward 1Y Return (y₀)
[-44.59 , 30.91]
80% Prediction Interval
0.1569
R²
Estimates based on a linear model with the last 30 years of data (when available). Function: y = a + b·x → y = 36.5027 + (-1.137)·x | RSE = 22.7802 | tcrit (80%) = 1.645
38.12
Current P/E Ratio (x₀)
-7.18
Expected Forward 5Y Return (y₀)
[-19.83 , 5.47]
80% Prediction Interval
0.5834
R²
Estimates based on a linear model with the last 30 years of data (when available). Function: y = a + b·x → y = 32.2129 + (-1.0334)·x | RSE = 7.6155 | tcrit (80%) = 1.645
38.12
Current P/E Ratio (x₀)
-2.96
Expected Forward 10Y Return (y₀)
[-8.69 , 2.77]
80% Prediction Interval
0.8474
R²
Estimates based on a linear model with the last 30 years of data (when available). Function: y = a + b·x → y = 28.8245 + (-0.8338)·x | RSE = 3.4471 | tcrit (80%) = 1.645
38.12
Current P/E Ratio (x₀)
7.94
Expected Forward 20Y Return (y₀)
[3.65 , 12.23]
80% Prediction Interval
0.5879
R²
Estimates based on a linear model with the last 30 years of data (when available). Function: y = a + b·x → y = 22.2362 + (-0.375)·x | RSE = 2.579 | tcrit (80%) = 1.645

Trailing vs Forward Return Model

This chart illustrates the relationship between trailing (past) returns and forward (subsequent) returns across various time ranges. Each point represents a specific period in the past, showing how past performance has (or hasn’t) correlated with future outcomes. By analyzing different time frames, the chart highlights the degree of persistence —or mean reversion— in investment returns over time.

Trailing vs Forward Return
Scatter plot and stats
Based on the last 30 years, when available
1Y Returns
5Y Returns
10Y Returns
20.91
Current Trailing 1Y Return (x₀)
11.16
Expected Forward 1Y Return (y₀)
[-28.99 , 51.31]
80% Prediction Interval
0.0002
R²
Estimates based on a linear model with the last 30 years of data (when available). Function: y = a + b·x → y = 10.8458 + (0.015)·x | RSE = 24.3574 | tcrit (80%) = 1.645
19.90
Current Trailing 5Y Return (x₀)
21.67
Expected Forward 5Y Return (y₀)
[11.41 , 31.93]
80% Prediction Interval
0.4468
R²
Estimates based on a linear model with the last 30 years of data (when available). Function: y = a + b·x → y = 11.3725 + (0.5173)·x | RSE = 6.201 | tcrit (80%) = 1.645
21.40
Current Trailing 10Y Return (x₀)
21.03
Expected Forward 10Y Return (y₀)
[18.37 , 23.69]
80% Prediction Interval
0.1330
R²
Estimates based on a linear model with the last 30 years of data (when available). Function: y = a + b·x → y = 19.1294 + (0.0886)·x | RSE = 1.5311 | tcrit (80%) = 1.645

Trailing P/E Ratio Stats

The following table provides a comprehensive analysis of the Price-to-Earnings (P/E) ratio over different trailing time periods. It includes key statistical measures such as the average P/E ratio, variance, and an evaluation of the current price relative to historical trends.

The data allows to assess market valuation over various time horizons, helping to identify potential overvaluation or undervaluation trends. The time intervals range from short-term (1 year) to long-term (20 years when available), offering a broad perspective on market conditions.

28 August 2025 · P/E Ratio: 38.12 · Last Periods metrics
Show all periods
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Range
Analysis
Period Average P/E
(μ)		 Std Dev
(σ)		 Std Dev Range
[ μ-2σ · μ-σ , μ+σ · μ+2σ ]		 vs Current P/E
( 38.12 )		 Deviation
vs μ		 Valuation
Last 1Y 36.38 0.95 [34.48 · 35.43 , 37.33 · 38.28]
+1.83 σ
Overvalued
Last 2Y 34.74 1.79 [31.15 · 32.94 , 36.53 · 38.32]
+1.89 σ
Overvalued
Last 3Y 32.13 3.66 [24.82 · 28.48 , 35.79 · 39.45]
+1.64 σ
Overvalued
Last 4Y 31.22 3.33 [24.55 · 27.89 , 34.56 · 37.89]
+2.07 σ
Expensive
Last 5Y 30.25 3.55 [23.15 · 26.70 , 33.80 · 37.35]
+2.22 σ
Expensive
Last 6Y 28.73 3.98 [20.76 · 24.74 , 32.71 · 36.69]
+2.36 σ
Expensive
Last 7Y 27.13 4.88 [17.37 · 22.25 , 32.01 · 36.88]
+2.25 σ
Expensive
Last 8Y 25.67 5.24 [15.19 · 20.43 , 30.92 · 36.16]
+2.37 σ
Expensive
Last 9Y 24.54 5.51 [13.53 · 19.03 , 30.04 · 35.55]
+2.47 σ
Expensive
Last 10Y 23.71 5.74 [12.23 · 17.97 , 29.46 · 35.20]
+2.51 σ
Expensive
Last 11Y 22.70 5.76 [11.18 · 16.94 , 28.46 · 34.22]
+2.68 σ
Expensive
Last 12Y 21.90 5.81 [10.28 · 16.09 , 27.70 · 33.51]
+2.79 σ
Expensive
Last 13Y 21.04 5.76 [9.52 · 15.28 , 26.80 · 32.57]
+2.96 σ
Expensive
Last 14Y 20.26 5.89 [8.47 · 14.37 , 26.15 · 32.04]
+3.03 σ
Expensive
Last 15Y 19.75 5.98 [7.79 · 13.77 , 25.73 · 31.71]
+3.07 σ
Expensive
Last 16Y 19.24 5.70 [7.84 · 13.54 , 24.95 · 30.65]
+3.31 σ
Expensive
Last 17Y 18.80 5.59 [7.62 · 13.21 , 24.39 · 29.98]
+3.46 σ
Expensive
Last 18Y 18.55 5.24 [8.08 · 13.32 , 23.79 · 29.03]
+3.74 σ
Expensive
Last 19Y 18.57 4.98 [8.61 · 13.59 , 23.55 · 28.53]
+3.93 σ
Expensive
Last 20Y 18.66 4.81 [9.04 · 13.85 , 23.47 · 28.29]
+4.05 σ
Expensive

S&P 500 Information Technology Sector Trend

Trend is evaluated considering the price of the XLK Etf and its 200/50-day moving averages (SMA).

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Trend Indicator Valuation Margin
Long Term Price vs SMA200 +13.54% 28 Aug
Short Term Price vs SMA50 +2.68% 28 Aug
The 200-day moving average is a long-term indicator that takes into account the average price of a stock over the past 200 trading days. It is considered a significant level of support or resistance, meaning that when the stock price is above the 200-day moving average (i.e. margin vs moving average is positive), it is generally viewed as bullish, while when it is below, it is viewed as bearish.
The 50-day moving average, on the other hand, is a shorter-term indicator that measures the average price of a stock over the past 50 trading days. It is also viewed as a significant level of support or resistance and can be used to identify shorter-term trends.