Stock Comparison: DIT vs PNI

Comparison Date : 2026-11-04

DIT, PNI 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 DIT PNI
MACD golden cross 29% (31×) 72% (18×)
MA20/MA60 golden cross 20% (5×) 50% (4×)
RSI oversold recovery 50% (8×) 67% (12×)

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
Consumer Defensive
Food Distribution
Financial Services
Asset Management

Last Price

Last 2 Month line
59.97
6.52

Market Cap

76.49M
76.33M

Dividend Yield

0.61
5.2

P E

Price-to-Earnings Ratio
47.57
N/A

E P S

Earnings Per Share
0
0

52W Change

Last year
-24.95%
-6.71%

Key Price & Prediction 2026-11-04

Resistance

Key Price Level
65
↧5(8%)
6
↧0(0%)

Support

Key Price Level
54
↥-5(-8%)
6
↥0(0%)

Stop Loss

Short & Medium Term
62
2(3%)
6
0(0%)

Q_Bullish forecast

Quarterly Prediction
68
6

Q_Base forecast

Quarterly Prediction
61
6

Q_Bearish forecast

Quarterly Prediction
54
6

A_Bullish forecast

Annual Prediction
74
6

A_Base forecast

Annual Prediction
60
6

A_Bearish forecast

Annual Prediction
47
5

Technical Analysis Signals 2026-11-04

MA(20,100)

Moving Avg(20,100)
SELL
NEUTRAL

MACD(12,26,9)

Moving Average Convergence Divergence
BUY
BUY

BOLL

Bollinger Bands
middle:ma20
SELL
BUY

RSI(14)

Relative Strength Index
SELL
BUY

ATR(14)

Average True Range
1.66
0.11

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
Oversold
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.