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Now That You Have Unlimited Access To Real-Time Data, Here’s How It Should Govern Your Decision Making As A Broker
At first glance, stock trading seems like gambling: no one understands how the market appears to move, and a few lucky traders make profits while the others face losses. In reality, there is a lot of science and analytics behind the scenes that help some stock brokers get an advantage over others. In particular, how brokers use real-time data makes a significant difference.
Only professional stock brokers working with institutional brokerages had access to live market feed, stock indices, and other datasets at one point in time. With the advent of the internet, however, the common man can look up any critical information they require to trade. With this potentially unlimited access to real-time data, you should also know how to understand and interpret these numbers to execute trades successfully as a trader.
Real-Time Stock Trading Data: What the Numbers Mean
1. Asset Prices and Market Movement
The asset price is often viewed as the first sign of how well that entity performs in the market. Most of the time, if the value increases, it signifies that the company is performing well. You may not understand the various factors that influence the price to go up or down, but you can interpret the end result.
Prices fluctuate every minute, even if by amounts as small as a third decimal changes. Within a day, there are four fundamental values of every stock or asset price that matter: the value at the start of the trading hours (opening price), the value at the end of the day (closing price), and the highest and lowest prices it reached during the day. Analyzing these numbers for similar assets across a time interval gives you a broad picture of the overall market movement.
2. Impact on Trade Volume
Certain types of traders like arbitrageurs capitalize on minuscule price variations because their advantage lies in the trade volume. These traders execute deals for tens of thousands of securities so that even the increase of a few cents can give them a fortune.
Real-time data on trade volume gives you other useful information as well. For example, if you see a sudden surge in the amount of a particular stock being sold, it is an indication that the company has probably done poorly, and hence, the stock price will fall. In summary, the volume data gives you an idea of how much you should scrutinize the stock price’s upward (or downward) movement.
3. Portfolio Analysis
Every stock market trader has a portfolio, which refers to their collection of investments, be it stocks, bonds, mutual funds, commodities, or cash equivalents. The earnings and losses from every asset class of your portfolio are what give you your overall profits. In general, not all markets perform equally well or poorly at the same time; you will always have some assets whose prices rise and others whose prices fall.
Real-time data on the performance of your portfolio lets you decide if you need a restructuring of your assets. One simple way to check the robustness of your portfolio is to run a Python correlation program on your portfolio. Correlation is a number between negative 1 and 1 that measures how closely your assets are linked or move together. So, the lower the correlation value, the more diverse your portfolio is, and hence, the lesser the overall risk.
Volatility is a term that refers to how much the price of an underlying varies with time; it can be measured daily, weekly, or over any period you choose. The higher the volatility of the price, the more the fluctuation, which means that your chances of getting a higher profit and a higher loss both go up. A more volatile stock can experience more significant variations in real-time data in a short time.
Typically, if you are risk-loving, you would focus your attention on the volatile stocks, hoping that their price soars quickly, after which you sell them. In general, the market is most volatile in the first hour after the trading day starts (usually 9:30 AM to 10:30 AM EST), and in the final hour before the day ends (usually 3:00 PM to 4:30 PM EST). These hours are when financial news and other external factors that took place the previous evening or over the course of the day tend to influence stock prices.
With today’s technology, traders can use third-party tools and features to analyze real-time data to perform further complex calculations and analysis. Here are a couple of examples.
The Use of Algorithmic Trading
While the numbers change every second across multiple markets, it is not possible for humans to monitor this enormous amount of data. In today’s world, computers and machines execute most of the trading orders precisely because they can handle large datasets.
Using algorithmic trading, all you need to do as a trader is to set the parameters and market conditions when you want to sell or buy a particular amount of some security. The system keeps track of the market movement and prices and, when the situation is attained, automatically completes the trade.
Sometimes, the instantaneous values of real-time data may not make sense, but they may form a meaningful trend or pattern over time. Instead of merely following the real-time numbers, computers and software tools process the values over time and predict how the market will move at some point in the future (next hour, day, or week).
With these forecasts, you can also be prepared for potential future scenarios that your competitors may not expect. Simulation programs give you an edge, but the results must be taken with a pinch of salt since the real market can always throw surprises.
Data is the New Gold
Data is now considered by most companies to be one of the most potent assets they have. However, to unleash the true potential of data, you should know how to process and interpret it as well. With this real-time data that you obtain from stock market trading activities, you can maximize your efforts to make profits by making the best decisions at every stage.