Stock Comparison: GOOG vs ORCL

Comparison Date : 2026-11-04

GOOG, ORCL are showing a bearish technical setup.

Based on end-of-day indicators (RSI, MACD, moving averages, volume). Not investment advice.

VS VS

How these signals performed on each stock 20 trading-day horizon, since 2024-01-01

Signal GOOG ORCL
MACD golden cross 66% (29×) 59% (17×)
MA20/MA60 golden cross 75% (4×) 60% (5×)
RSI oversold recovery 43% (7×) 62% (13×)

Win rate with number of historical occurrences in parentheses. A single occurrence is not evidence. Returns are gross of transaction costs. Full market-wide results: backtest.php. Not investment advice.

Basic Stock Information 2026-11-04

Sector

Industry
Communication Services
Internet Content & Information
Technology
Software - Infrastructure

Last Price

Last 2 Month line
278.27
126.19

Market Cap

1.97T
407.98B

Dividend Yield

0.52
1.37

P E

Price-to-Earnings Ratio
18.18
34.15

E P S

Earnings Per Share
9.55
6

52W Change

Last year
-3.67%
25.64%

Key Price & Prediction 2026-11-04

Resistance

Key Price Level
311
↧32(11%)
152
↧25(20%)

Support

Key Price Level
245
↥-33(-12%)
100
↥-26(-21%)

Stop Loss

Short & Medium Term
294
15(5%)
139
12(10%)

Q_Bullish forecast

Quarterly Prediction
308
141

Q_Base forecast

Quarterly Prediction
275
112

Q_Bearish forecast

Quarterly Prediction
247
91

A_Bullish forecast

Annual Prediction
338
163

A_Base forecast

Annual Prediction
273
105

A_Bearish forecast

Annual Prediction
217
64

Technical Analysis Signals 2026-11-04

MA(20,100)

Moving Avg(20,100)
SELL
SELL

MACD(12,26,9)

Moving Average Convergence Divergence
SELL
SELL

BOLL

Bollinger Bands
middle:ma20
SELL
SELL

RSI(14)

Relative Strength Index
BUY
SELL

ATR(14)

Average True Range
9.9
8.08

CCI(20)

Commodity Channel Index
BUY
SELL

SAR(20)

Parabolic Stop and Reverse
SELL
SELL

ADX(14)

Average Directional Index
SELL
NEUTRAL

OBV(20)

On-Balance Volume
BUY
BUY

STOCH(K line)

Stochastic Oscillator
Oversold
Oversold

These predictions are generated using a combination of technical analysis, fundamental factors, market sentiment indicators, and machine learning models trained on historical price data. Probabilities represent the likelihood of reaching the target price within the specified timeframe based on our models. All predictions are for informational purposes only and should not be considered as financial advice.