Stock Comparison: LRFC vs QNCX

Comparison Date : 2026-11-04

QNCX, LRFC 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 QNCX LRFC
MACD golden cross 50% (18×) 63% (8×)
MA20/MA60 golden cross 40% (5×) —
RSI oversold recovery 75% (8×) 0% (5×)

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
Asset Management

Last Price

Last 2 Month line
33.16
19.08

Market Cap

47.65M
47.54M

Dividend Yield

-
8.04

P E

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

E P S

Earnings Per Share
-0.54
1.45

52W Change

Last year
9.64%
-19.55%

Key Price & Prediction 2026-11-04

Resistance

Key Price Level
44
↧10(30%)
19
↧0(0%)

Support

Key Price Level
21
↥-12(-36%)
18
↥-1(-5%)

Stop Loss

Short & Medium Term
27
-6(-18%)
18
-1(-5%)

Q_Bullish forecast

Quarterly Prediction
41
21

Q_Base forecast

Quarterly Prediction
33
18

Q_Bearish forecast

Quarterly Prediction
25
16

A_Bullish forecast

Annual Prediction
50
23

A_Base forecast

Annual Prediction
35
18

A_Bearish forecast

Annual Prediction
18
14

Technical Analysis Signals 2026-11-04

MA(20,100)

Moving Avg(20,100)
BUY
NEUTRAL

MACD(12,26,9)

Moving Average Convergence Divergence
SELL
BUY

BOLL

Bollinger Bands
middle:ma20
BUY
BUY

RSI(14)

Relative Strength Index
BUY
BUY

ATR(14)

Average True Range
3.41
0.34

CCI(20)

Commodity Channel Index
BUY
SELL

SAR(20)

Parabolic Stop and Reverse
SELL
BUY

ADX(14)

Average Directional Index
BUY
NEUTRAL

OBV(20)

On-Balance Volume
SELL
NEUTRAL

STOCH(K line)

Stochastic Oscillator
Neutral
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.