Stock Comparison: COEP vs GLST

Comparison Date : 2026-11-04

COEP is showing a bullish technical setup; GLST is 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 COEP GLST
MACD golden cross 38% (16×) —
MA20/MA60 golden cross 50% (4×) —
RSI oversold recovery 67% (3×) —

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
Healthcare
Biotechnology
Financial Services
Shell Companies

Last Price

Last 2 Month line
16.4
6.56

Market Cap

27.92M
28.35M

Dividend Yield

-
-

P E

Price-to-Earnings Ratio
N/A
N/A

E P S

Earnings Per Share
0
0

52W Change

Last year
15.28%
-35.84%

Key Price & Prediction 2026-11-04

Resistance

Key Price Level
13
↧-3(-18%)
12
↧5(76%)

Support

Key Price Level
7
↥-9(-55%)
0
↥-6(-91%)

Stop Loss

Short & Medium Term
9
-7(-43%)
9
2(30%)

Q_Bullish forecast

Quarterly Prediction
14
13

Q_Base forecast

Quarterly Prediction
11
3

Q_Bearish forecast

Quarterly Prediction
7
-2

A_Bullish forecast

Annual Prediction
18
20

A_Base forecast

Annual Prediction
12
0

A_Bearish forecast

Annual Prediction
4
-11

Technical Analysis Signals 2026-11-04

MA(20,100)

Moving Avg(20,100)
BUY
SELL

MACD(12,26,9)

Moving Average Convergence Divergence
NEUTRAL
SELL

BOLL

Bollinger Bands
middle:ma20
BUY
SELL

RSI(14)

Relative Strength Index
BUY
SELL

ATR(14)

Average True Range
0.85
1.49

CCI(20)

Commodity Channel Index
SELL
SELL

SAR(20)

Parabolic Stop and Reverse
BUY
SELL

ADX(14)

Average Directional Index
BUY
SELL

OBV(20)

On-Balance Volume
SELL
BUY

STOCH(K line)

Stochastic Oscillator
Oversold
Neutral

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.