Stock Comparison: FMY vs MAXN

Comparison Date : 2026-11-04

FMY, MAXN 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 FMY MAXN
MACD golden cross 52% (23×) 20% (20×)
MA20/MA60 golden cross 29% (7×) 33% (3×)
RSI oversold recovery — 20% (10×)

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
Financial Services
Asset Management
Technology
Solar

Last Price

Last 2 Month line
11.15
0.21

Market Cap

50.93M
50.8M

Dividend Yield

7.44
-

P E

Price-to-Earnings Ratio
6.28
N/A

E P S

Earnings Per Share
0
0

52W Change

Last year
1.6%
-98.71%

Key Price & Prediction 2026-11-04

Resistance

Key Price Level
11
↧0(0%)
5
↧4(1905%)

Support

Key Price Level
10
↥-1(-9%)
2
↥1(476%)

Stop Loss

Short & Medium Term
11
0(0%)
4
3(1429%)

Q_Bullish forecast

Quarterly Prediction
11
8

Q_Base forecast

Quarterly Prediction
11
3

Q_Bearish forecast

Quarterly Prediction
10
-1

A_Bullish forecast

Annual Prediction
12
12

A_Base forecast

Annual Prediction
10
2

A_Bearish forecast

Annual Prediction
10
-6

Technical Analysis Signals 2026-11-04

MA(20,100)

Moving Avg(20,100)
SELL
NEUTRAL

MACD(12,26,9)

Moving Average Convergence Divergence
NEUTRAL
NEUTRAL

BOLL

Bollinger Bands
middle:ma20
SELL
SELL

RSI(14)

Relative Strength Index
SELL
SELL

ATR(14)

Average True Range
0.23
0.43

CCI(20)

Commodity Channel Index
SELL
BUY

SAR(20)

Parabolic Stop and Reverse
SELL
BUY

ADX(14)

Average Directional Index
NEUTRAL
BUY

OBV(20)

On-Balance Volume
SELL
SELL

STOCH(K line)

Stochastic Oscillator
Neutral
Approaching 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.