How to Calculate Trading Volume
The second reason why trading volume figures lose their analytical value is that they are more pronounced not in the stock markets, but rather in futures markets. However, in these markets, daily trading volume figures are announced close to the closing or at the end of these days, which is a significant drawback, especially for shorter-term investors. On the other hand, Istanbul Stock Exchange and warrants bring a different perspective to a state of contradiction. According to widely accepted technical analysis principles, if investors do not see a surge in trading volumes during breakout moments, they begin to hesitate to enter a position with concerns that these breakouts could turn into bull traps or traps. While this theory, which should yield correct results most of the time, needs to be known that the condition of trading volumes occurring before price movements, meaning it is a leading indicator. You can quickly and most effectively benefit from some technical indicators that include trading volume figures in their calculations, such as OBV, Chaikin, MFI, etc. However, even these indicators may not be useful for you, especially in futures markets.
What Are the Correct Investment Principles
Trading volume figures and information are accepted as the total number of contracts bought and sold during the day. For every buyer, there is always a seller. However, this may not be useful in futures markets. In short, here, every buyer and every seller assumes they are doing the right thing. It should be known at this point that it is not trading volumes that move the market. Whether it is stocks, Istanbul Stock Exchange, or futures and options, the investment principles to be applied to achieve stable returns in the markets are globally the same. However, it should be known that these principles are so simple that investors, believing that this simplicity does not contain the sophistication to achieve their goals, seek solutions in flashy, colorful, and complex systems. At these stages, they search in software that can almost make coffee, in inescapable algorithms with tips from others, in outlandish analysis systems, and in their much-trusted but historically untested predictive abilities.
