
v4 Marketplace Price History
(V4M)Date | Open price* | Upper Price | Lower Price | Close price** | Vol |
|---|---|---|---|---|---|
No data | |||||
Where can you buy V4M
About V4M historical price data
The V4M price history tracker allows cryptocurrency investors to conveniently monitor the performance of their investments. You can easily view the opening, highest, and closing prices of V4M over time, as well as the trading volume. In addition, you can instantly check the daily percentage change to easily identify days with higher volatility.
According to our V4M price history data, its value surged to an all-time high of over $0.000076 in 1970-01-22. On the other hand, the lowest point in the V4M price trajectory (often referred to as the “V4M all-time low”) occurred in 1970-01-22. Anyone who purchased V4M during that period would currently enjoy an impressive profit of $0.000035.
By design, the total supply of V4M will reach 1,000,000,000. As of now, the circulating supply of V4M is approximately 1,000,000,000.
All prices shown on this page come from trusted data provider LBank. When reviewing your investments, it is recommended not to rely on a single data source, as values may differ between providers.
Our historical Bitcoin price dataset includes 1-minute, 1-day, 1-week, and 1-month data (open/high/low/close/volume). These datasets have been rigorously tested to ensure consistency, integrity, and accuracy. The design is specifically for trading simulations and backtesting, available for free download and updated in real time.
V4M historical data examples
Here are some uses of V4M historical data in V4M trading
Traders use historical data to analyze trends and movements in the V4M market. They use charts and other visual tools to identify trends and determine when to enter or exit the market. One way to gain an advantage in this dynamic market is to visualize and analyze historical market data. To achieve this, historical data can be stored in GridDB and analyzed using Python scripts with various libraries, such as Matplotlib, Pandas, Numpy, and Scipy for data visualization.
Historical data can also be used to predict future market trends. By analyzing past market behavior, traders can identify recurring patterns and make informed predictions about the direction of the V4M market. By using LBank’s V4M historical dataset, traders can obtain minute-by-minute data such as open, high, low, and close prices for V4M. These data can then be used to define and train price prediction models, helping users make informed trading decisions.
By obtaining historical data, traders can assess the risks of investing in V4M. They can also determine the volatility of V4M, allowing them to make sound investment decisions.
Historical data is also useful in portfolio management. By tracking investments over the long term, traders can identify underperforming assets and adjust portfolios to maximize returns.
In addition, users can choose to download V4M historical cryptocurrency OHLC (open, high, low, close) data to train their own V4M trading bots, achieving outstanding performance in the market. With these tools and resources, traders can deeply study V4M’s historical data, gain valuable insights, and potentially improve their trading strategies.
How to analyze V4M candlestick chart data

V4M candlestick charts display time on the horizontal axis and price data on the vertical axis, similar to line and bar charts. A candlestick may have two different colors: green or red. A green candle indicates a price increase during the considered period, while a red candle indicates a price decrease.
The simple structure of candlestick charts can provide users with a wealth of information. For example, technical analysis may use candlestick chart data to identify potential trend reversals.
According to V4M historical data, when the V4M market shows bearish or bullish trends, conservative investors may choose to use capital-protected products such as Flexible and Locked to capture the trend at that time.
When V4M is in a sideways trend, using Open Futures and selecting a bullish product to take advantage of a slight upward trend, or choosing a bearish product to profit from a mild downward trend, may lead to better performance.

