Rajesh Dua chutiye .

True

Just look for Andrew Ng's courses. I'm sure it will change your mind

Thank you for your response i will watch it after watching alot of video

I am glad to see someone tried it while using only past data. The conclusion you make is what I would concur with just by simple reasoning. There should be a need for another factor at least to hope to get some sort of accuracy. Unless there is a repeated pattern to be found somewhere due to a factor we are unaware of. Like patterns in roulette due to flaws making the results not quite random. Something that has surely been caught onto, and is probably now verified for at casinos.

Actually this model will accurately tell you the range of values that the stock has high probability of trading in. Example if model prediction is 180 with rmse of 5 then there is 65% chance that it will close between 175 - 185 range, and there is 95% chance that it will close between 170 - 190 range given that stock returns are randomly distributed and it follows standard normal distribution. If someone knows the range maybe they can wait for the stock to hit either high or low before taking trade or they can deploy option strategies based on the information they got from the model.

@@ishanawasthi1975 good point!!! 👍

How can use multiple data as a input to classify which stock to pick ? from high to low. let's say I input 10 datasets at once & it classifies top 3. (just for project purpose)

His model is literally overfitting with the absurd accuracy

I see your point: if you seeded any number within 1 standard deviation form the previous day to predict today's price, then zooming out to a large timeframe you could get a very similar chart. You brought up a good point and seem to be knowledgeable on this topic, so what would you do to implement a better forecast model ? Suggestions are appreciated, thanks!

@@diegotrazzi It's not possible. Assuming a sufficiently efficient market, if it were possible to forecast asset prices then people would take advantage and trade on such information. Price actions would then disappear.

@@weimondo NOT TRUE that's a total fallacy - the whole insane and inane premise that you cannot predict the future to find for example - a cycle in the market that no one knows about it and make a profit off of it b/c everyone will eventually learn it and use it thus incorporating into the market therefore it is not longer a predictor - this whole premise is so absurb as to make even the term "laughing stock" blush - all you have to do is NOT tell someone else what you discovered and the prediction holds - take for example the Scandavian Finance professor in the 90s that discovered an 80% accurate super cycles that was so freakishly exact like to 1 or 2 day out of every 2 months ish in finding the total and absolute highs and lows of almost everything that occured every 2-3 months - but being a brainwashed bonehead - tells the whole world about it - it was then put onto every Media in the world like Nightly Business Report - the euro continents finance channel and all the finance channels in the USA - it stilll took 2 MONTHS to have it incorporated by rest of the world but in mean time predicted every major and sometimes even minor turns in the USA stockmarket (never mind every other stockmarket index on the planet ) - now despite the fact that that is MORE than enough to make a few billion dollars and retire - keep in mind had he not been a brainwashed bonehead and had he kept this info secret it would never have been known and never incorporated into the stockmarket at all.... is this not common sense - FEEL FREE TO NOT REPLY BACK GEEZZZZ

@Diego Trazzi There is the question that everyone in trading market are looking for! Who knows?

@@dweh I guess CITADEL LLC knows about it pretty well.

Hahahahaahahahahhaahhaha

Hi! I agree with you. I'm new to this so I'd like to know if you see a way to deal with this problem so you can better predict the time series. Thanks!

Why predicting several steps? Why not predicting simply if it goes up or down in the next several steps? Is it not easier for a model to predict that?

@@Otvazhnii Maybe not easier to get the acurate direction, but a lot more useful 😄

Thank you very much !

Bro tell me what is the best value for epoch and batch size

there is no best value found yet on planet earth, you have to try different combinations. @@SahilKhan-td6rv

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I'm an amateur making terrible picks and I really need assistance.

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@@greenquake11931 'BRIDGET MARY TUROW"".

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I noticed this too...

Exactly what I thought. I have noticed many KZfaq’s make some mistakes here and there too. I think they should be more professional to rely on.

Hey you seem like an expert . Can you please guide me as I have been really wanting to get into trading and finance using machine learning. I would really appreciate it if you could give me resources that could get me industry ready to create complex algorithms that can help me out.

Thank you Christos !

Can i get a video on how to combine the technical indicators to this pls? I am thinking of doing this as my final year project

I am trying to make the same including the optimal time to buy and sell the stock . Give me tips if you have any .

What's his contact details ?

Would be fairly easy to verify the accuracy, you should do it

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What if I want to predict the for the date that is not in my train dataset i.e I would use my whole dataset as training dataset and would create a module 2 predict the future price?

Yea that's true, I used a similar model projecting EURUSD but the spread between actual and projected averaged 100pips which is a nono

Any luck?

i started to research python+tensorflow, but i sadly didnt have time to stick to it. (i am just a hobby programmer)... BUT i appreciate you asking❗😁

Same doubt, anyone please share any resources about it?

@@anujsrivastava5316 If you find solution, Kindly mention

Hi guys, Did you find a way to do the multivariate?

Excellent comment thank you. There is indeed "data leakage" in this model.

you have to scale train and test data with the same parameters.. otherwise you distort results

@@robertweber475 yes but you can do that with scaling on train data first and using the same trained scaler on the test data

@@ekinrota1638 yes, that would be possible

@Jeremy Tran Jeremy is correct. The presentation is wrong and needs to be edited.

why we take range as 60. Can you please explain

How to fetch prices of Indian stocks

Why do you imagine that?

can you elaborate on what you mean, please?

​@@daspittin9954 Looking through the code, I see that he did a fit_transform on the entire dataset, then used that same scaler model to transform the test set back; he should have only used the training set when he fit the original scaler model; not both training and test, its akin to someone writing an exam, and giving them hints as to what the answers are (when estimating the predictions), but not providing the actual answers

How would one correct this error, in terms of the code?

@@surengrigorian7888 This is the general approach, which you'll have to implement after the step where he implemented the lag structure > scaler.fit(X_train) # scaler model fit to training set only > X_train_scaled= scaler.transform(X_train) > # some code .... > X_test_scaled = scaler.transform(X_test)

I see how this is an unsound practice, but scaling the input data should only make the training a bit more simple. In the end you should get the same result, up to a factor for the weights in the first layer. Plus the difference in scaling is rather low, so it is really not a big deal here.

w michaux can I send you some code to take a look at and maybe give me some pointers on what i can do better. my code runs im just not getting the results i intended and do not know where or why im stuck

If I'm not mistaken it is rmse = np.sqrt( np.mean( (predictions - y_test)**2 ))

@@amidatongassassin nope getting the same error its giving me nan output

but what if i just want tomorrows prediction, shouldn't i be satisfied with that?

I made a mistake on the rmse calculation but have the correct code for it in the description.

But the shape of the predicted graph was uncannily accurate no? Surely something there? Did you watch the entire thing? Just asking and thanks for your post here. Cheers

0.3

Ur brilliant u will sure succeed in share market like warrent Buffett

What do you mean?

@@RoboticusMusic This RNN yields an error of ~16 dollars. If you always predict tomorrow's closing price as yesterday's closing price from 2001 to 2020. You get 0.71 dollar mean absolute error. abs(df.close.diff(1)).mean() == 0.7417740650899958

@@shaw7598 If yesterday's close is $100 and today's close is $101, you're saying predicting that tomorrows close is $100 is accurate on average of how many ticks?

@@RoboticusMusic Nobody is talking about tick data

What if I want to predict the for the date that is not in my train dataset i.e I would use my whole dataset as training dataset and would create a module 2 predict the future price?

Same error here, waiting for answer

get an answer from the comment below, hope it helps. "import yfinance as yf and change the line of code to df = yf.download('AAPL', start='2012-01-01', end=end='2019-12-17'). It seems like yahoo changed their api and these changes broke compatibility with pandas datareader" , and thank you @lucaartz

@@Suheng-dn9cd thank you very much

from datetime import datetime import yfinance as yf yf.pdr_override() symbol = "AAPL" today = pd.to_datetime("today") # Ensures today's date start_date = datetime(2012,1,1) end_date = today # Retrieve historical data df = pdr.get_data_yahoo(symbol, start=start_date, end=end_date) df

​@@Suheng-dn9cd Thank you very much

do you know what else i can write here?

@@oscura15 there's similar question above yours with a different answer you can check that out, but i used data_source = 'stooq' and it works fine

remember to import yfinance as yf

Yeah! There was information leak in this demonstration

Thank you, I will

@@ComputerSciencecompsci112358 I found an error predictions=model.predict(x_test) predictions=scaler.inverse_transform(predictions) Output: Valueerror: Found array with dim 3. Estimator expected

Why?

It can be done. Look up billionaire mathematician Jim Simons

@@nczioox1116 I see this as being more useful for Options

I like the metaphor 👍

​@@nczioox1116 Yes - but the video shows the common missconception about stock price prediction with LSTMs. This model just adds random noise of small amplitude to previous values. It cannot predict anything, its structure is just unsuitable to do so.

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How do you go about this, I will like to know more

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Hola. Acabo de ver este video. Has intentado usar el código para invertir? De ser así, q tal salió todo?

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You will need to use for loop on the last cell he made for predicting next day value. The for loop will help to execute same lines of code for how many days you want to predict in future.

Any guy who has studied computational finance, know that you cant predict stock prices/security prices on previous data. Otherwise, the biggest HFTs would be utilizing machine learning by running a regression on previous data and they would be able to exploit this arbitrage forever and violate the no-risk arbitrage principle.

Can confirm. When I started Machine learning I started with exactly this approach and couldn’t get any useful predictions on any stocks. Back tested all my models in real trading Programms (with no real money) and kept generating losses. I tried out so many different models and amounts of data but nothing worked. I’m currently working with a friend on collecting news data and use a sentiment analysis in combination with stocks to predict them.

William zhang what about Nomi Prins? She uses machine learning

William zhang check out her KZfaq interview on London Real

No black box will ever work. You need a discretionary touch to make it work.

Add it after your Lstm layer in similar way we do for ANN.

++

The thumbnail is an image from the program in this video.

yep but they dont care. they fell for "invest 250€ in amazon for second income" too. you cant help these people

I put the correct code in the description

@@ComputerSciencecompsci112358 thanks! By the way, great video!

Thanks! but thats underestood since he is trying to do some money in youtube insted of getting rich!

Why being so harsh?

@@RogerCarelli Because the author is not telling you the full truth. The model is pretty much as useless as a random guess. You can't use it neither for day trading nor for swing not for any kind of trading or investing. It's useless because it makes an assumption that the next day's return will be the same as the previous. So, it made a prediction for tomorrow. What happens tomorrow? Whatever it was right or wrong, it will take the real return and use it to predict the next day, making the same assumption. And that's for an entire year. In the end, predicted values walking around real ones, showing correct return approximately 50/50. But if you zoom out, show graphs for the entire year, they're pretty close. That creates an illusion that the model works. That's why so harsh.

@@arsenyturin I think you got confused , he is not showing how to create a trading bot, and not showing a forward feed model. This is a very well made example on building simple models, using simple time series.

let's say you need data for the next 30 days, just change the Y to 30, so instead of predicting for 1 day the model will predict for 30 days. This is an alternative and effective solution I guess..

Did you backtest?