How to predict stock price fluctuations in the stock market?
In the stock market, you have to make more precise decisions about stock trading, it is difficult to understand what leads to changes in supply and demand in the stock market and makes some buyers and some sellers share. To explain this behavior, various theories have been formed, by studying which we can better predict stock price fluctuations in the stock market.
There is a wide range of investors in the stock market in terms of jobs, education and experience. Each group, according to their expertise, chooses specific methods for analyzing the stock market and companies' stocks and buys and sells stocks. Stock prices can change at any time due to changes in supply and market demand.
According to Gold Cafe , if the number of buyers of a share is more than the number of sellers, ie the demand to buy a share is more than the supply for sale, the price of that share will increase and vice versa. It is very easy to understand supply and demand and the resulting price changes; But what is difficult is to understand what leads to changes in supply and demand in the stock market and causes some to want or buy a particular share and others to turn away or sell it. Various theories have been developed to explain this behavior.
1- Historical theory
In historical theory, the past tense is used to calculate the standard deviation of dividends and then used as a forecast for the future. Although the level of stock price volatility changes over time, this method will be useful if there is no clear trend in price volatility. The best forecast may be based on recent fluctuations.
2- Time series theory
The second theory to predict stock price volatility is to use the time series of volatility patterns in previous periods. Note this explanation; The standard deviation of daily share returns is determined based on recent months. Then, based on the time series trend, these standard deviations are used to estimate the standard deviation of the daily returns of the stock in the next month. This method is different from the first method; This is because he has been using the information for more than a month.
Forecasting may be based on a balanced procedure; Like 50% multiplied by last month's standard deviation plus 25% multiplied by standard deviation in the previous two months plus 15% multiplied by the standard deviation in the previous three months plus 10% multiplied by the standard deviation in the previous four months. This method adds more weight to recent data, but allows data from four months ago to affect the forecast. Weights and the number of past periods with the least prediction error are usually used.
However, various economic and political factors can cause stock price fluctuations to change abruptly; Therefore, even the most accurate time series models do not necessarily accurately predict stock price volatility.
3- Implicit standard deviation
The third theory for predicting stock price volatility is to calculate the implicit standard deviation according to the pricing model of a share option. The mere purchase of a share depends on factors such as the relationship between the share price and the agreed purchase price, the number of days before the expiration date and the predicted fluctuation of the share price change. There is a formula for estimating mere purchasing power based on a variety of factors.
Except in cases of predicted fluctuations, the true value of these factors is known; However , it is possible to calculate the predicted level of fluctuation , given the actual use of the option that investors pay for that share . Those market participants who want to predict volatility over a 30-day period will consider buying an option with 30 days left until it expires. This measure reflects the projected fluctuation of shares in a 30-day period by investors who trade stocks. Participants use this criterion to predict stock price volatility.
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