Stock Comparison: IZM vs NSYS

Comparison Date : 2026-11-04

NSYS, IZM are showing a bullish 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 NSYS IZM
MACD golden cross 45% (22×) 50% (14×)
MA20/MA60 golden cross 60% (5×) 0% (3×)
RSI oversold recovery 88% (8×) 57% (7×)

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
Medical Devices
Technology
Electronics & Computer Distribution

Last Price

Last 2 Month line
11.3
0.66

Market Cap

23.55M
23.46M

Dividend Yield

-
-

P E

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

E P S

Earnings Per Share
0
0

52W Change

Last year
-45.29%
-20.32%

Key Price & Prediction 2026-11-04

Resistance

Key Price Level
13
↧1(9%)
1
↧0(0%)

Support

Key Price Level
9
↥-2(-18%)
0
↥0(0%)

Stop Loss

Short & Medium Term
10
-1(-9%)
0
0(0%)

Q_Bullish forecast

Quarterly Prediction
12
1

Q_Base forecast

Quarterly Prediction
9
0

Q_Bearish forecast

Quarterly Prediction
7
0

A_Bullish forecast

Annual Prediction
14
1

A_Base forecast

Annual Prediction
8
0

A_Bearish forecast

Annual Prediction
5
0

Technical Analysis Signals 2026-11-04

MA(20,100)

Moving Avg(20,100)
NEUTRAL
BUY

MACD(12,26,9)

Moving Average Convergence Divergence
BUY
SELL

BOLL

Bollinger Bands
middle:ma20
NEUTRAL
BUY

RSI(14)

Relative Strength Index
SELL
BUY

ATR(14)

Average True Range
0.75
0.12

CCI(20)

Commodity Channel Index
BUY
SELL

SAR(20)

Parabolic Stop and Reverse
SELL
BUY

ADX(14)

Average Directional Index
NEUTRAL
BUY

OBV(20)

On-Balance Volume
BUY
BUY

STOCH(K line)

Stochastic Oscillator
Approaching 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.