In this week's set of videos, we're going to talk about forecasting, and introduce what is forecasting, and how one would use it. Then we'll begin to explore moving averages and models based on moving averages. I still have with me Hose. So Hose, maybe you could tell us a little bit about forecasting and how you measure whether or not a forecast is good or bad. So there are common statistical measures that you always should take a look, R-square, Root mean square. So there are those common ones that you can identify it and measure if a model is working. We'll be covering those in this class. Right. But there are also some other ones that are more common or hard, or something that you, may be from the statistical point of view, you can know half that measure, but you can intuitive, or more is the modal working? If the forecast working, are you getting returns on your model? If it's helpful, it'll give you any insight or signals that you can take and make a decision based on that. So those are other ways to measure if your forecast is working or not. So that's an excellent point. Statistics takes us so far, but we also need to apply our human intelligence or intuition to the problem to see whether or not our forecasts are valid or not. So Hose, can you tell me a little bit about how moving averages are used in finance. Sure. So from my experience, moving averages are very useful. In sort of a long-term abuse, so when you want to identify maybe one year data or more than one year is very insightful. You can see where it's going monthly, six months data. Very insightful depending on whether you use KS. From my particular use case, when you go down to one meaner done and start going down that part, and all the way down to milliseconds, and nanoseconds, then moving averages don't tend to be as useful or you are not able to apply it. So that's interesting. So moving averages are good when the period is a little bit longer, but when we get down to the microsecond level, it's not as useful. Correct. Okay. So this week, we'll be doing forecasts and hope you enjoy this week's lectures.