GARCH
Have you ever watched the weather report on TV and heard the meteorologist say there's a chance of rain, but they're not sure how much or when it will come? It's like that with the stock market sometimes. Experts try to predict how much a stock's price will change, but they can't always be sure. That's where something called a GARCH model comes in.
GARCH stands for Generalized Autoregressive Conditional Heteroskedasticity (wow, that's a long word!). What it means is that the model tries to estimate how much the stock price might change by looking at past changes in price. It also takes into account that sometimes the changes can be very big (heteroskedasticity). Think of it like trying to predict how many cookies you'll eat tomorrow for snack time by looking at how many cookies you've eaten in the past, but knowing that some days you eat a lot more than others.
The GARCH model is a way of trying to make better predictions about how much a stock's price will change in the future. It's like a tool that helps experts make better guesses about what might happen in the stock market. But just like the weather report, it's not always perfect, and sometimes even with the best tools, we can't be completely sure what will happen next.
GARCH stands for Generalized Autoregressive Conditional Heteroskedasticity (wow, that's a long word!). What it means is that the model tries to estimate how much the stock price might change by looking at past changes in price. It also takes into account that sometimes the changes can be very big (heteroskedasticity). Think of it like trying to predict how many cookies you'll eat tomorrow for snack time by looking at how many cookies you've eaten in the past, but knowing that some days you eat a lot more than others.
The GARCH model is a way of trying to make better predictions about how much a stock's price will change in the future. It's like a tool that helps experts make better guesses about what might happen in the stock market. But just like the weather report, it's not always perfect, and sometimes even with the best tools, we can't be completely sure what will happen next.