Stock market projects by digital marketing companies in Delhi NCR

Stock market projects by digital marketing companies in Delhi NCR

Now before we begin writing any actual code or even exploring I want datasets for that matter. It's going to take a few minutes to print a brief overview of this project as a whole. So we're going to talk about first what we're trying to accomplish with this particular project of digital marketing companies in Delhi NCR and how are they going to go about doing it on the rough order in which we're going to implement our tasks. So you don't have to write any of this down and just kind of follow along with me so that you know how we're going to be proceeding through this project.

Project 1

So as I'm sure you gain from the intersection as well as even the title of this tutorial we're going to be building a model that will be used to predict digital marketing companies in Delhi NCR whether a stock price will increase or decrease the next day. So this is crucial we're not going to be building a long term prediction model in which you'll be able to enter a date you know two months three months down the road and see what the price is going to be. This is just going to be used for day trading day and it's going to be based on digital marketing services entirely on this one factor which is going to be the amount of volume exchanged by the end of a certain day.

Now because we're only taking this one's doctrine's consideration and the fact that we're only talking about the difference between the end of the day and the beginning of the next day. This isn't going to be a super complex model. We're really only using this to predict the difference between the end of the days' price and the beginning of the next day price. And that's because we know that the price of digital marketing companies in Delhi NCR and the stock is generally going to be different at the end of the day versus the beginning of the next day.

Project 2

Our goal is to try and figure out whether that difference is positive or negative. So whether or not the price of the stock will go up the next morning or it will go down the next morning. So if all model based on digital marketing companies in Delhi NCR the volume at the end of the day will predict that the stock price will go up then we probably want to sell it right away the next morning because that will result in a net profit for us whereas if we know the stock price is going to go down or at least that's our model predicts we probably want to hold onto that stock and not sell it otherwise we'd be losing money.

Now as I said this isn't going to be a super complex model which means it's probably not even going to be close to percent accuracy. In fact, the best results I've got using a pretty simple model is a little over percent. I think I've reached around percent with some of the stocks. Now you might be looking at that number and saying well that's a garbage number percent accurate is not very good. And you'd be absolutely right. With regards to and machine learning models generally, if we're not even close to percent accurate that's not a good model Astle we want very close to percent accurate or high.

Now in the case with these stock prediction models, I think the very best out there claims to be around percent. But that's a bold claim that just because there are so many factors that go into predicting stocks it's not just based on Passions and numerical data but there are so many other things of world events that affect the prices of stocks. And that's just to name a few factors. So really it's an almost impossible task to get digital marketing companies in Delhi NCR even close to percent accuracy with any stock prediction model no matter how complex you make it. The crux of it all is that the more data you feed in the more things the model has to consider. And so it might become confused past a certain point.

That's why anything over percent accuracy in around percent accuracy really isn't that bad. And honestly, if you were to do this long time with a percent accuracy result then we would probably result in net profits over the long term again. Now that being said I don't claim responsibility for any money bet in this rather using this particular model. Nor do I even recommend you go about using this particular model with only percent accuracy and investing a lot of money into the hopes that this is going to get you rich. The purpose of this tutorial is mostly just to get you into the realm of making stock prediction models and of Rausch process that we would take to build something like this.

So my goal isn't to get close to percent accuracy. It's mostly just to show you the process of building up this model. With regards to stock market prediction. So if at the end of this tutorial you decide you want to use this model. I want to try and make some money using a percent accuracy then I'm not going to discourage you from doing so but I'm certainly not going to encourage you to rely on the percent accuracy figure. This is more used for digital marketing companies in Delhi NCR and the grounds for a or the basis for a better model. OK but with that being said we have a little bit of background into what we're going to be building so let's talk about the order in which we can implement our tasks.