Stockbot Inventory Forecasting

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Stock Price Prediction Using Python & Machine Learning

hello everyone and welcome to this video,on the Python programming language and,machine learning so in this video I'm,going to show you how to predict the,closing stock price of a corporation or,specifically Apple Inc using an,artificial neural network now currently,I'm on Google's website called collab,research Google comm because it makes it,really easy to get started programming,in Python meaning you don't have to,install Python into your computer you,can just go online to this website and,then like and using your Google Account,and get started writing your Python code,so let's go ahead and get started,writing our Python program now so the,first thing that you're going to want to,do is click on file and then click on,new Python 3 notebook where a new tab,will open up for you and a new cell and,within this cell I like to put a,description and comments about what the,program is about or what it's going to,do so let's go ahead and do that now I'm,going to type description alright so,this program uses an artificial,recurrent neural network called long,short term memory or LS TM for a short,and we're gonna use this LS TM to,predict the closing stock price of a,corporation and again that corporation,being Apple Inc ok and we're going to do,this using the past 60 day stock price,okay now let me go ahead and give you a,summary about LS tiems now like I said,before L STM stands for a long,short-term memory and it is an,artificial recurrent neural network,architecture used in the field of deep,learning and unlike standard feet for,neural networks LS TM has feedback,connections it can not only process,single data points such as images but,also entire sequences of data such as,speech or video and this definition is,coming directly from Wikipedia which of,course I know it's not a reliable source,but it gives you in a very good idea,about a specific topic or subject all,right now LS teams are widely used for,sequence,prediction problems and have proven to,be extremely effective and the reason,they work so well is because LS TM is,able to store past information that is,important and forgive the information,that is not important so with all that,being said let's go ahead and start,coding,so the first thing I want to do is click,up top here I'm going to click the code,button to create a new cell and in this,cell I want to import the libraries that,we're going to be using throughout this,program so I'm going to import math next,I want to import pandas underscore data,reader as web then I'm going to import,numpy as MP and I'm going to import,pandas as PD then from SK learn dot,pre-processing I'm going to import,min/max scalar and from Kira's top,models I'm going to import sequential,and from Kira's dot layers I'm going to,import dense and lsdm alright next I'm,going to import mat flight live dot PI,plot SPL T and I want to use a specific,style so I'm going to type your t dot,style dot use and we're gonna use the,538 style so let's run this cell by,clicking this

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Stockbot app demo - Shopify

install the atlas shown a billing plan,page I'm going to collect the free trial,you get all the features in the free,trial for 14 days the first thing I do,is stop quad sends a low stock email,report so I said my email then I choose,when I wanted to see the email either in,the morning evening Monday's only or,even hourly and daily morning,the hourly sends you freshly low stock,products within the past hour then I,click Save then I had third thing I do,is I set the threshold I can set the,threshold for the entire store so any,variant that goes below inventory ten,will be included in the low stock email,report I can also set alert or in,specific products by searching for the,product names so cap card $50 gift card,I said a threshold of 50 so any variant,of the $50 gift card that goes below 50,well being told on the loss of email,report I can also set a low thresholds,on individual variants so for example,the small blue variant I said a,threshold of 25 so right now there are,two alerts 25 for the variant and 50 for,this product if I want the rest of the,products to be checked against ovarian,threshold of 10 then I click this,checkbox so now these two products will,be checked against these two thresholds,25 50 and dialog threshold of 10 will be,applied to the remaining products in,their store just by clicking this,checkbox now we have some advanced,features you can set an alert on a,collection click here it also all the,collections say you have a drop shipping,arrangement with a vendor,and he supplies you for a particular,collection you can set an alert,threshold for that collection and here,you go so any variant for the under that,collection that goes below 25 will be,emailed directly to this email but,important thing to notice any collection,a lot of set here will override will,ignore the alerts that you the threshold,reset of the previous page so if you,want total coverage if you want all,products to be covered pending our said,a collection alert like this for all the,collections in your store,okay and now if you click on the,real-time web report you can see all the,low stock products currently based on,the threshold very upset it takes a bit,of time but here you go all these,products based on because they are all,less than 10 or 25 or 50 and you can,also download this file as a CSV and,open it in Excel and the really cool,feature we have is forecasting,thresholds setting thresholds allows you,to receive an email after the product,has gone low stock the forecasting we,tell you before the product goes low,start by forecasting all the variance,sales and telling you which of them are,under stopped based on our forecast so,to give you an example we are,forecasting that in the next 20 days,this variant will sell 120 Valjean it's,past sales but the current inventory is,only 20 so you don't stock per 100 which,means you are potentially going to lose,revenue of thousand dollars because,you're under stock by hundred,you just have to reorder 500 because we,

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Stock Market Tools for Discord

what is going on guys welcome back to,trading learning,101 today we're going to talk about some,very,useful tools in the trading learning 101,discord server now i have multiple tools,in this server to help us do our jobs,effortlessly and more easily,so the first one we're going to talk,about is the stock bot,if you go to the bot chart lookup under,the stock talk,other subjects click on this,you could see that there's a stock bot,in here that i keep,talking with now there's a list of,commands,for this stock bot some commands that,you could,use for this stock bot like for an,example,looking up to see which top stocks,are the top stocks for the day i call,this either i,i say i p o p or i,popular so let me type in i pop and this,stock bot,is gonna search through and pull up,all the most popular ticker symbols,for today and you could see popular,symbols and this is scanning this stock,bot,is in a total of 21 455,servers so out of 2100,servers the last 24 hours,these are the most mentioned stocks,in those servers number one is amc,it's been cena 880 times,with the price change the current price,right here,which you could also look for with this,stock bot is you could pull up,multiple different charts so again,i like to say i b now this one you can,range the charts,i think it's from one through ten the,first one we can do is,ic and then the ticker symbol so let's,look up,amc and you can see the stock bot will,pull a chart,from bigcharts.com and this is the,current,one minute chart of amc,i like to use this tool when i'm out and,about and i'm away from my computer,i'll jump into the server and i'll look,up what popular stocks are popping off,and then i'll come into here and i'll,quickly just pull up charts,to get a glance at what's going on,another chart,we could say i see,for the next chart let's look up amc,again,and you can see now this is pulling from,finvis and there's,all kinds of different charts like i,said we'll run through real quickly,and we'll look at them real quick so i,c3,amc the ticker symbol this is amc,this is a daily chart so this is a very,very handy tool for all of us,most definitely utilize this and take,advantage of it,it's at our fingertips i see four,let's look at the spy once again it's a,daily chart but this is pulling up a,different,chart this is from i forget what website,that this is from,chart mill i believe i see,five qqq i think it goes up to seven,if i'm not mistaken this one's from,trading view,it's got a link right there for you i,see,seven gme and there's another chart,right here,very cool tool for all of us to use now,there's a lot more that you could do,with the stock bot,like i've said there's a big list,of commands that you can learn for this,stock bot,so if you type in i commands link to,help,for all commands we'll click on that,link and this website pops up,and look it these are all the different,commands,that you can quickly learn these are all,commands,that you can memorize or even save this,link and i'll shar

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Predicting Stock Prices in Python

what is going on guys welcome back to,the new online channel today we're going,to learn how to predict stock prices,with neural networks in python so let us,get right into it,now before we actually get into anything,here let me tell you first of all this,video is not,investing advice and i'm not just saying,this for legal purposes it is literally,not investing advice in any way you,shouldn't use this model to predict,stock prices because it's not going to,predict stock prices it's going to be in,a recurrent neural network and lstm,network,and it's going to use the last 60 days,let's say the last,n days and it's going to predict one day,into the future it's not going to,project or to,predict into the far future 50 days 60,days two years it's just going to,predict the next day,based on 60 days and you know it might,be better than guessing,it might be but it doesn't have to be so,please don't use this to make investment,decisions at all this is more,about learning how to use recurrent,neural networks more about learning,about machine learning,and neural networks and tensorflow and,python programming than it is,in any way about predicting stock prices,this video is not about predicting stock,prices,it's called predicting stock prices,we're going to try to predict stock,prices but it's not going to be,actually anything that you would want to,use in your investment decisions,now of course if you add a lot of more,sophistication to that model it might,actually turn out to make,decent results but with with what we're,going to,show in this video we're going to see,that it has some effect so we're going,to compare it,uh we're going to compare the,predictions to the actual stock prices,and we're going to see that sometimes,it's quite,good quote-unquote sometimes it's not,good at all,um but all in all this is not something,that you would actually want to use this,is the first step to learning how to,predict stock prices with machine,learning or attempting to predict stock,prices with machine learning,this is not in any way an investing,advice or anything that you would want,to use in your portfolio,so having said all that we can start by,importing some libraries,and loading the data so the first one is,going to be numpy snp,import matplotlib dot pi plot splt,import pandas spd import,pandas data reader as web,import date time,sdt which is a core python module and,then we're also going to see from,sklearn dot,pre-processing import min max,scalar and from tensorflow,tensorflow.keras.models,import the sequential model and then,from,tensorflow tensorflow.keras.layers we're,going to have,dense layers we're going to have drop,out layers,and we're going to have lstm long short,term memory layers,and we need an import here so,if you don't have all of those libraries,installed you need to install them open,up your command line no matter if it's a,linux terminal or a windows command line,and you say pip install numpy,pip install matplotlib,pip install pandas pip instal

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I Asked the OpenAI Chatbot for Investment Advice: The Result Is Unbelievable! (ChatGPT)

open AI is a former Elon Musk headed,company and last week the company,released a new AI chatbot and the new,artificial intelligence engine has been,making headlines as its capabilities are,truly mind-blowing for instance the chat,GPT robot can solve difficult math,problems write poems about almost,anything or scripts or TV shows and it,can write new lines of code or more,generally it is able to engage in,human-like conversations about a wide,range of topics now what I've done is I,started a conversation with the AI,chatbot and I asked it for investment,advice and I can assure you that the,results have been absolutely stunning I,asked it seven questions in total,starting with some very basic questions,and then gradually asking more and more,nuanced questions that truly challenged,the ai's capabilities so what kind of,answers did the AI engine give me and,how do I rate these investment,recommendations,this will be the topic of this video and,so without further Ado let's get started,alright so let's jump right into it I,started the conversation with the robot,with a very light question and pretended,to be new to investing so I asked the,open AI where someone new to investing,should start his educational investing,journey and here's the response that I,received if you're new to investing a,good place to start is by educating,yourself about the basics of investing,and how it works there are many,resources available online that can help,you learn about the different types of,Investments how to evaluate potential,investment opportunities and how to,manage your Investment Portfolio some,good places to start include the,Securities and Exchange commissions,website which has a lot of useful,information and resources for investors,as well as financial news and Analysis,websites like the Motley Fool and,Investopedia you can also consider,talking to a financial advisor or taking,a course on investing to learn more it's,important to do your own research and,understand the risks and potential,reward of any investment before you,decide to put your money into it so what,do I as someone who's been trying to,master the art of investing for many,years think of this response quite,frankly I think the response is quite,amazing I probably agree with almost all,of the recommendations it's important to,understand that ultimately only you are,responsible for your own finances and,your financial successes and failures,the SEC so the Securities and Exchange,Commission provides some of the most,reliable resources that are available,online and many filings are even,provided by the businesses themselves,including their financial statements and,Investopedia too is a great resource to,look up investing terms that you will,inevitably encounter yeah when you are,trying to fight your way through the,investing jargon jungle when it comes to,the motley fools content however which,the AI also recommended I'd be a bit,more cautious as I consider most of,their content more yeah clickbai

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A machine learning approach to stock trading | Richard Craib and Lex Fridman

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Stock Prediction using Machine Learning and Python | Machine Learning Training | Edureka

the art of forecasting stock prices has,been a difficult task for many of the,researchers and analysts in fact,investors are highly interested in the,research of area of stock price,reduction for a good and successful,investment many investors are keen on,knowing the future situation of the,stock market in such a scenario an,effective prediction system for stock,markets helped traders investors and,analysts by providing support of,information like the future value of,certain stocks hi all I welcome you to,this stock prediction session using,machine learning in this work I present,a record new rule network and long short,term memory or lsdm approach to predict,stock market indices so without much ado,let's get started so on our agenda today,I'm gonna start out by a little,introduction on this piece then I'm,gonna explain to you what an lsdm is and,then we are going to move on straight to,a model before concluding this session,also don't forget to subscribe to us and,hit that Bell icon to never miss an,update from the a Eureka YouTube channel,and if you want to know more on machine,learning data science or any other,related field do not forget to check out,our certification trainings the link to,which I will leave in the description,box below so let's get straight to the,introduction shall we now there's a load,of complicated financial indicators and,also the fluctuation of the stock market,is very very violent however as the,technology is getting advanced the,opportunity to gain a steady fortune,from the stock market is increased and,it also helps experts to find out the,most infinitive indicators to make a,better prediction for those of you who,do not understand stocks stocks are,basically an equity investment that,represents part ownership in a,corporation or a company it entitles you,to a part of that company's earnings and,assets now the prediction of the market,value is of great importance to help,in maximizing the profit of your stock,option purchase while keeping the risk,low and this is important because you,need to invest your money in a stock,which is going to increase in value over,time and not decrease so RN ins or,recurrent neural networks have proven to,be one of the most powerful models for,processing sequential data the long,short term memory is our the most,successful RN and architectures now the,Ellis team introduces the memory cell a,unit of computation that replaces the,traditional artificial neurons in the,hidden layer of the network with these,memory cells networks are able to,effectively associate memories and input,remote in time,hence the suit to grasp the structure of,the data dynamically over time with high,prediction capacity now this is what the,lsdm architecture looks like we have the,forget gate now for the sake of,illustration let's assume that we are,reading words in a piece of text and,want to use lsdm to keep track of,grammatical structures such as whether,the subject is singular or plural if the,subject changes

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Automatically trade stocks to make profit - Bitburner #11

hello and welcome back to some more bit,burners so in the last video i created a,script called get youtube comments that,looks at all my youtube comments from my,bit burner videos and then uh pulls them,across,uh from within the game um so before,recording any videos i usually check,whether there's new comments but since,there isn't uh i'm not gonna be,featuring that from i guess the start of,this video,um,so today's video is going to be focus on,the stock market and how it works and i,guess what sort of functions,uh you can use to uh start trading,automatically,so to get started you go to the city tab,here and then you go to world stock,exchange,obviously your screen wouldn't look like,this when you first start uh mainly,because i went ahead and purchased,everything that i needed,from this world stock exchange,if you've been following this series,quite closely then,you should have enough to actually,purchase everything,within this menu,just so that it looks like this,so going through the accounts the first,account that you're probably going to,purchase is this wse account,and what that one will do is that it's,going to give you access to buy and sell,stocks from within this uh this ui here,the second one is this tix api access,and what this one will do is that's,gonna allow you to buy and sell stocks,from within your scripts,uh third one is the market data tix api,access and what this one will do is it's,gonna give you,access to forecast figures and,volatility figures,and this one will assist us in,i guess deciding whether we're gonna buy,or sell our stocks uh from within our,scripts,and then optionally you can purchase,this 4s market data access and what that,one will do is that it's going to unlock,the uh the ui elements for the,volatility and price forecast figures,as well as unlock the achievement if you,haven't gotten that already,so before going in depth into anything,about this uh stock market in this game,how how the stock market works in this,game,i would first like to mention that if,you know anything about trading or,finances or,investing uh basically the stocks in,this game doesn't behave the same way as,the stocks in the real world,uh so any of your technical analysis,tools or,uh you know moving averages and rsi,indicators you can leave that out the,door because that's no longer necessary,basically the price movements in this,game is determined by one property and,it's called forecast,and this forecast is basically just a,number between zero and one,if the number is less than 0.5 it means,that stock will go down if the number is,greater than 0.5 it means that the stock,will go up it's it's that simple,and then volatility figures affect your,uh i guess the price movement so it's,going to affect your profit chance,every single stock from within this game,is uh has its own ticker code or symbol,it has its own price,volatility figures and then price,forecast,if we expand this we could see here that,a bunch of menu we can buy and sell,st

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Real Time Stock Market Data Analysis with Python - Five Minute Python Scripts

hey guys welcome back to the channel,today I want to do a request from a,subscriber on how we can start using,real-time stock market data in our,Python scripts let's jump right in,jumping over to a text editor the first,thing we need to do is to install a new,package I'm on a Mac so I'll use a,terminal and I'll type in pip 3 install,and then the package is called alpha,Vantage then we'll hit return to install,the package I already have this package,installed and that's where I get this,message but you're sure download will,use this package as an easy way to,access your real time stock market data,next we need to jump over to their,website I just google it and go to the,first link and now we need to go to get,your free API key we'll put in our,information here once you put in your,information and click get free API key,they return an API key to you go ahead,and copy this value and we'll move it,over to our Python script so say API key,is equal to that value once you're,watching this video I'll probably have,already deleted this API key but it's a,very straightforward process to get your,own next we'll import all the packages,that we need so it's import pandas as PD,and then from Alpha Vantage dot time,series we'll import the class time,series lastly we'll import time next,we'll drop down below our API key and,say time series is equal to the time,series parentheses set our keyword,argument of key equal to this variable,right here API key next we'll specify,our output format so we'll put output,format and then we want it as a painted,a different so we'll pass in pandas here,let's set the variables data and then,metadata and we'll set this equal to,time series get entered a we see that we,have a lot of different values here that,we can pull out so daily weekly and,monthly but since we want,minute-by-minute data let's use intraday,will set the symbol so symbol equals and,then we'll pass in a ticket so let's say,we're looking at Microsoft stock comma,and then we'll specify the interval so,interval equals 1 minute and then we,want an output size equal to full let's,drop down and put print data to make,sure it works go back to your command,prompt for terminal and type in Python 3,and then the name of your file so minus,stock stop hi,to execute when we get the result we see,we have minute-by-minute data of the,stock that we specified we'll scroll up,and we see that we have the data for the,open the high low close and volume for,the stock in each minute now that we're,able to pull out the data we're able to,do operations on but first let's talk,about how we can save this data in real,time like how our commenter wanted so,we'll drop down and since this is,already in a Pena's data frame we can,use the function to Excel so let's say I,is equal to 1 and usually I wouldn't,create an infinite while loop but since,our subscriber wants us to happen all,the time let's do that so while I is,equal to 1 or do this function like I,said we already have a panda's data,fr

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ARIMA Models for Stock Price Prediction ❌ How to Choose the p, d, q Terms to Build ARIMA Model (1/2)

hi there welcome back today i want to,talk about how we can,forecast time series with arima,models and in order to understand arima,models,first we need to understand what time,series are,so a time series is basically a sequence,where we record a metric over,regular intervals and in this case we,will talk about stock prices,and forecasting refers to the future,values,that this sequence will take in this,example we're going to go through,a price series that is formed out of,microsoft,bars that include the open high,low and close and a couple of other,features,but we're only going to be using the,close price,because we're going to only use this,feature,to predict the future values and this is,called univariate,time series forecasting now that we know,all of this arima models which is short,for autoregressive,integrated moving average is a,forecasting algorithm,that takes into account previous past,values,to predict future values because it,considers that the information that is,found,in those past values can be indicative,of future values so in short arima,models,explain a time series based on its,past values basically its lags,and its lagged forecast errors so an,arima model,is characterized by three terms and,these are the most important things that,you need to know in order to be able to,fit,an arima model and these are p d,and q alright so p refers to the order,of the autoregressive term d,is the order of differencing in order to,make the time series stationary,and q is the order of the moving average,term,now we're going to go through all of,these three and,i'm going to explain how they are,calculated and how you can actually get,these values,so that they are mapped perfectly to,your specific problem,but as we see from these terms we,realize that what we actually need to,have,in order to be able to fit a narima,model,is a stationary time series,okay so the time series needs to be,stationary you might be wondering what,is stationarity now stationarity refers,to the fact,that the price series in this case is,mean,reverting and as we know most price,series aren't mean reverting because,otherwise it would be super easy for us,to be able to profit from uh from the,stock market because,we would only buy low and sell high or,the opposite okay we would short high,and then buy low,but we know that this is not the case,because,prices don't mean revert usually and the,ones that do are very rare,but what we do know is that the returns,are more likely to mean revert because,they,are distributed randomly around a zero,mean,so coming back to the arima model we,know that now we need,a stationary time series in order to be,modeled by,an arima model but why is that and the,answer lies,in the autoregressive term in,the actual name because it's,autoregressive,it means that the model is a linear,regression,that uses its own lags as predictors,now linear regression as we know works,best,when the features when the predictors,aren't,dependent on each other because if

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