Stock Comparison: LRFC vs TZUP

Comparison Date : 2026-11-04

LRFC, TZUP 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 LRFC TZUP
MACD golden cross 63% (8×) 58% (12×)
MA20/MA60 golden cross — —
RSI oversold recovery 0% (5×) 80% (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
Financial Services
Asset Management
Communication Services
Advertising Agencies

Last Price

Last 2 Month line
19.08
4.55

Market Cap

47.54M
47.79M

Dividend Yield

8.04
-

P E

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

E P S

Earnings Per Share
1.45
0

52W Change

Last year
-19.55%
23.66%

Key Price & Prediction 2026-11-04

Resistance

Key Price Level
19
↧0(0%)
18
↧13(286%)

Support

Key Price Level
18
↥-1(-5%)
7
↥2(44%)

Stop Loss

Short & Medium Term
18
-1(-5%)
10
5(110%)

Q_Bullish forecast

Quarterly Prediction
21
17

Q_Base forecast

Quarterly Prediction
18
13

Q_Bearish forecast

Quarterly Prediction
16
9

A_Bullish forecast

Annual Prediction
23
22

A_Base forecast

Annual Prediction
18
15

A_Bearish forecast

Annual Prediction
14
5

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
BUY
BUY

RSI(14)

Relative Strength Index
BUY
BUY

ATR(14)

Average True Range
0.34
1.73

CCI(20)

Commodity Channel Index
SELL
SELL

SAR(20)

Parabolic Stop and Reverse
BUY
SELL

ADX(14)

Average Directional Index
NEUTRAL
BUY

OBV(20)

On-Balance Volume
NEUTRAL
SELL

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.