Stock Comparison: MFC vs PPL

Comparison Date : 2026-11-04

MFC, PPL 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 MFC PPL
MACD golden cross 67% (15×) 57% (21×)
MA20/MA60 golden cross — 60% (5×)
RSI oversold recovery — 83% (6×)

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
Insurance - Life
Utilities
Utilities - Regulated Electric

Last Price

Last 2 Month line
44.78
35.71

Market Cap

52.99B
26.66B

Dividend Yield

3.99
3.02

P E

Price-to-Earnings Ratio
15.04
26.92

E P S

Earnings Per Share
4.1
1.82

52W Change

Last year
28.45%
28.44%

Key Price & Prediction 2026-11-04

Resistance

Key Price Level
47
↧2(4%)
37
↧1(3%)

Support

Key Price Level
42
↥-2(-4%)
34
↥-1(-3%)

Stop Loss

Short & Medium Term
43
-1(-2%)
34
-1(-3%)

Q_Bullish forecast

Quarterly Prediction
45
33

Q_Base forecast

Quarterly Prediction
43
31

Q_Bearish forecast

Quarterly Prediction
42
30

A_Bullish forecast

Annual Prediction
47
35

A_Base forecast

Annual Prediction
44
31

A_Bearish forecast

Annual Prediction
40
28

Technical Analysis Signals 2026-11-04

MA(20,100)

Moving Avg(20,100)
BUY
BUY

MACD(12,26,9)

Moving Average Convergence Divergence
BUY
BUY

BOLL

Bollinger Bands
middle:ma20
BUY
BUY

RSI(14)

Relative Strength Index
BUY
BUY

ATR(14)

Average True Range
0.75
0.56

CCI(20)

Commodity Channel Index
BUY
SELL

SAR(20)

Parabolic Stop and Reverse
BUY
BUY

ADX(14)

Average Directional Index
NEUTRAL
BUY

OBV(20)

On-Balance Volume
BUY
SELL

STOCH(K line)

Stochastic Oscillator
Neutral
Approaching Overbought

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.