Financhill
Back

PICC Property and Casualty Stock Price Chart

7 Powerhouse Stocks to Buy and Hold Forever

Get it now.
Sell
50

PPCCF
PICC Property and Casualty

Last Price:
1.31
Seasonality Move:
-2.48%

7 Day Trial

ALL ACCESS PASS

$ 7

Will Crypto Make People Rich Again Starting April 2024?

Details on how to profit here.
  • The current trend is relatively stagnant and PPCCF is experiencing slight buying pressure.

PICC Property and Casualty Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 1.31 Sell
20-day SMA: 1.31 Sell
50-day SMA: 1.31 Buy
200-day SMA: 1.19 Buy
8-day EMA: 1.31 Buy
20-day EMA: 1.31 Buy
50-day EMA: 1.29 Buy
200-day EMA: 1.2 Buy

PICC Property and Casualty Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 0 Buy
Relative Strength Index (14 RSI): 95.09 Buy
Chaikin Money Flow: 0 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (1.31 - 1.31) Sell
Bollinger Bands (100): (1.15 - 1.31) Buy

PICC Property and Casualty Technical Analysis

Technical Analysis: Buy or Sell?
8-day SMA:
20-day SMA:
50-day SMA:
200-day SMA:
8-day EMA:
20-day EMA:
50-day EMA:
200-day EMA:
MACD (12, 26):
Relative Strength Index (14 RSI):
Bollinger Bands (25):
Bollinger Bands (100):

Technical Analysis for PICC Property and Casualty Stock

Is PICC Property and Casualty Stock a Buy?

PPCCF Technical Analysis vs Fundamental Analysis

Sell
50
PICC Property and Casualty (PPCCF) is a Sell

Is PICC Property and Casualty a Buy or a Sell?

PICC Property and Casualty Stock Info

Market Cap:
29.14B
Price in USD:
1.31
Share Volume:
0

PICC Property and Casualty 52-Week Range

52-Week High:
1.31
52-Week Low:
1.06
Sell
50
PICC Property and Casualty (PPCCF) is a Sell

PICC Property and Casualty Share Price Forecast

Is PICC Property and Casualty Stock a Buy?

Technical Analysis of PICC Property and Casualty

Should I short PICC Property and Casualty stock?

* PICC Property and Casualty stock forecasts short-term for next days and weeks may differ from long term prediction for next month and year based on timeline differences.