Get started
VIET NAM DAIRY PRODUCTS JOINT STOCK COMPANYVIET NAM DAIRY PRODUCTS JOINT STOCK COMPANYVIET NAM DAIRY PRODUCTS JOINT STOCK COMPANY

VIET NAM DAIRY PRODUCTS JOINT STOCK COMPANY

No trades
See on Supercharts
Overview Financials News
Ideas
Discussions Technicals Forecast Seasonals

VNM trade ideas

Vinamilk: VNM (Fair value & slow growth)● Vietnam Dairy Products Joint Stock Company (VNM) was established in 1976. The Company has its main business in processing, production, trade, import and export of dairy products and other nutritious ones, under the model of a joint stock company since 2003. VNM is the biggest dairy company with a market share of over 50% in Vietnam dairy industry. VNM's products are exported to 57 countries. ● Milk consumption per capita in Vietnam was only 28 liters in 2021, lower than Thailand (35 liters) and Singapore (45 liters). VS each person in Vietnam consumes around 42.5 liters of beer annually. ● I believe every VNM investor should hold a glass of vinamilk instead glass of beer or soft drink to have a better life. Sun 10/03/2024
HOSE:VNMLong
by MIchaelTran
3
Long-term opportunity to buy value and growth stocks in VinamilkBased on the monthly chart, Vinamilk has been forming a bearish Elliott wave 5 for many years now. The current position is supported by the demand zone I've marked in blue (second from the bottom), but there is no support from the rising trendline yet. Therefore, the market is likely to continue its decline in the near future to level 5 before embarking on a new growth cycle. The 45-52k zone presents a good opportunity to accumulate long-term holdings before breaking out of the untested supply zone I've marked in blue at the top, around 136-150k. Once the peak is reached, I will analyze the new Elliott wave pattern for you. Stay tuned!
HOSE:VNMLong
by TieuLongFX
Locimport pandas as pd import ta.volatility as vol # Load stock price data into a pandas DataFrame df = pd.read_csv('stock_prices.csv') # Calculate Bollinger Bands df , df , df = vol.bollinger_hband(df ), vol.bollinger_mavg(df ), vol.bollinger_lband(df ) # Filter stock price movements that are above the upper Bollinger Band df = df > df # Filter stock price movements that are below the lower Bollinger Band df = df < df # Print the filtered stock price movements print(df [df | df ])
HOSE:VNMLong
by nghiaquan68a8df94c24adf4f9d