Using ARIMA to Predict Bitcoin Prices in Python in 2023🔴

[@adrianjaoszewski2631]

The graph looks only so impressive because there are multiple models which only forecast one single value. The real deal is doing a relatively long forecast based on an ARIMA model. Twenty (or so) ARIMA Models each fitted on a subset of real data and forecasting only one step are exactly as useful as taking the last value and adding a random number to it.

[@sagarpadhiyar3666]

Hey Ritvik, you haven't checked the stationarity and seasonality of the data or it is not necessary for price prediction? You have done prediction for test data. How do predictions for unseen data or future data? Do we have to run for loop for combined trained and test data for making predictions of unseen data?

[@FinancialProgrammingwithRitvik]

Yes, Very good point. I didn't mention it as it might make the video more lengthy and confusing for beginners. But Yes, we will do all the relevant tests before performing the model in a real world analysis.

[@nangkhanh2546]

When running for loop, you add test data to training data and you run ARIMA model then the result absolutely great. However, it just like tell the computer learn by heart the data and tell it show the test data again

[@FinancialProgrammingwithRitvik]

Thanks for the valuable feedback

[@PuneetThawani]

What the hell ? your model is extremely over fitted to the entire dataset because in the 'for' loop you keep appending test data to training data. Test your model on UNSEEN data and see how well it generalizes. Wouldn't all of us be billionaires right now if you showed us a 97% accurate prediction model ? 😂😂😂😂

[@FinancialProgrammingwithRitvik]

Good point! I agree it needs to be architectured better for a production level model. I made this video not to give an easy money making solution to my audience but to explain different parts of ARIMA model 😂 But always, thanks for the feedback

[@camstuart]

Great video, I was happy to subscribe! I did find that when running the statsmodel package suggests to change the import to: "from statsmodels.tsa.arima.model import ARIMA" (so arima.model instead of arima_model) but this causes some errors with the line 'yhat = list(output[0])[0]' when training. Do you mind having a look?

[@FinancialProgrammingwithRitvik]

I will check it out and thanks for the sub

[@matejmak9225]

@@FinancialProgrammingwithRitvik Hello sir I have the same problem is there any solution for that ? Thank you for answear and excellent video :)

[@rensbq7080]

on the print results part i never get ARIMA Results why?

[@AGhosh-sb8lf]

I can't understand the part where you have append the training data in the function with actual_test_value and how I can predict future price i.e. price after 1 week with this approach?

[@巴塔-z5q]

Genius

[@FinancialProgrammingwithRitvik]

Thanks :)

[@emilycherkassky3507]

Thanks!

[@FinancialProgrammingwithRitvik]

Welcome!

[@shireeshkumar6631]

Good content thank you

[@FinancialProgrammingwithRitvik]

Thanks for the appreciation :)

[@antonismarinidis12]

Really helpful tutorial. One question, when you try to predict future values that are not exist yet, what do you use at the part of actual_test_value = testing_set[i] training_set.append(actual_test_value)" because for the future we do not have "actual values". I used the model_predictions[i] as appending to the training_set (which actually the training_set is the actual whole data) and I get a straight line as a result at my graph which is not that good. any solutions? thank you in advance.

[@dandeaton3601]

Same here … 😢

[@junaidseedat7852]

same here...

[@razimoosa7028]

You might be getting a straight line because the model is predicting the price based on the same input features. Maybe for e.g. "you added input feature /actual value '200' to the data, the model will predict the price e.g. '250', now for next future day the input appended is same i.e. actual value '200' and hence model predicts again '250'. With this logic the model keeps on predicting '250' and you get a straight line as output. I believe you need to check the input features you're appending to the data set.

[@SakshamGunj]

bro he is misguiding that's why he didn't replied to this comment.

[@urvashiarya8811]

hlo Sir goodevening I have been working on Nifty bank prediction using ARIMA in python since jan '23 . being from Commerce background everything seems a little bit difficult but i really want to do this . Now I am stuck at a point where I am getting straight line predictions . I don't know what to do . I have tried everything but all in vain. Please suggest me what to do next

[@FinancialProgrammingwithRitvik]

It happens with everyone. Try some other model apart from ARIMA. You may like my fpProphet. I have made a video it that as well.

[@BiffBifford]

Ritvik, I wish you all the best for you and your family in the coming year and express my gratitude for your hard work and highly educational videos. Thank you from Rainy California, and best wishes!

[@FinancialProgrammingwithRitvik]

Thanks a ton

[@laughtoutclips]

hello can u make a option trading simulator for Indian stock.. (Nifty50)

[@FinancialProgrammingwithRitvik]

Will try soon.

[@arunasrancevas6095]

If I iunderstand correctly the code makes a prediction for time already passed?? How can it make prediction for the future? Thanks, sir

[@FinancialProgrammingwithRitvik]

We need to incorporate more things in the model to make it for the real world

[@arunasrancevas6095]

@@FinancialProgrammingwithRitvik I don't remember, does it predict one day into the future or not yet?

[@ummeyfarwa3429]

Plz uploaded full code cryptocruuncy price prediction machine learning using python

[@FinancialProgrammingwithRitvik]

Will upload soon

[@ThanhPham-ic3rz]

Can you sent me the google colab file, please? Thank you so much!

[@FinancialProgrammingwithRitvik]

Hi, all new members have got the access by now. Pardon, I couldn't provide the access for last one week as I am completely engaged in a medical emergency of my father. To compensate, all these new members would have 1 month free access. Thanks for understading.

[@moto.argentina]

I did everything as in the video but I have an error in yhat = list(output[0])[0] --> 'numpy.float64' object is not iterable

[@FinancialProgrammingwithRitvik]

It's difficult to understand the query here. I recommend you to get the google drive access and copy and paste my code and check line by line where is the mistake.

[@moto.argentina]

@@FinancialProgrammingwithRitvik After many hours I was able to solve the error in this way yhat = output[0]

[@yavuz4837]

I always thought that predicting stocks or krypto currencies' prices using time series was impossible because there are a lot of variables that we can not control or teach the model. it will never be perfect and I think every true prediction of stocks or krypto currencies values is a one time only fortune. it is luck I mean. there are too many variables that we can't control and it is impossible to get the prediction right all the time. am I wrong ritvik?

[@Uddu29200]

Iam getting an error near the model predictions [:-1] can u help me ?

[@FinancialProgrammingwithRitvik]

What's the error?

[@34boy97]

I did a prediction of BTC and I got of mape of 0.18 did I made any mistake ?

[@FinancialProgrammingwithRitvik]

Difficult to say. MAPE may varying significantly depending on the time period.

[@furinfo5158]

plz dont invest in crypto especialy waqar zaka group or u will be destroying ur life

[@m.shiqofilla4246]

Sir thanks for the explanation, wanna ask one thing, can you plot the prediction of the stock price of the next 30 days? I mean not prediction in the test set, i want the prediction of the stock of the new days (next 30 days), is that possible to do? Thank you please answer it sir....

[@FinancialProgrammingwithRitvik]

Will try

[@JarHen]

I am happy there are people sharing passion with such preparation, congratulations on your great community support!

[@FinancialProgrammingwithRitvik]

Thanks :)

[@SairamEslavath-k1m]

hello ritvik, can we able to take multiple columns to feed it

[@FinancialProgrammingwithRitvik]

Yes, we can train the model with multiple features as well.

[@eric32145]

Sir it would be really helpful if u could share the code online

[@FinancialProgrammingwithRitvik]

Please follow the steps here to get my Google Drive access: kzbin.info/door/yMifqUrSntvvrrGMaVPkrwcommunity?lb=UgwZRm2WrR2BqVk_ho54AaABCQ

[@carters6138]

Merry Christmas ❤️buddy

[@FinancialProgrammingwithRitvik]

Same to you :)

[@daxitsoni9524]

Why you didn't check stationarity of the data ?

[@FinancialProgrammingwithRitvik]

Yes, Very good point. I didn't mention it as it might make the video more lengthy and confusing for beginners. But Yes, we will do all the relevant tests before performing the model in a real world analysis.

[@mehediazad1780]

We know : mape = mean(|(actual value - predicted valued)| / actual value) but you did : mape = mean(|(predicted valued - actual value)| / actual value) I saw there is a little difference between the results. like mape = mean(|(actual value - predicted valued)| / actual value) = 0.025083830299512718 mape = mean(|(predicted valued - actual value)| / actual value) = 0.02543963108417206 which one is correct? btw. thank you so much for the video.

[@FinancialProgrammingwithRitvik]

Both are correct, it all depends on our interpretation and analysis we are doing.

[@ajays1031]

It is predicted future price or historical price ?

[@FinancialProgrammingwithRitvik]

Yes, it's predicting future prices. I have shown it on historical data

[@shivamkashyap1877]

sir please upload videos for data how to used from different platform or others

[@aishworyann4928]

sir i am facing an issue while running that numpy.float64 object is not iterable in yhat = list(output[0])[0] could you please give me a solution to this

[@aishworyann4928]

also i am using streamlit so can you please help me out sir in this

[@ibfaka1726]

Thanks once again for yet another captivating financial programming video. This is a video every crypto trader should watch to equip himself for financial gains.

[@FinancialProgrammingwithRitvik]

Much appreciated!

[@rationalist8016]

kindly share the code plz

[@FinancialProgrammingwithRitvik]

I save my codes in my google drive that I share with my subscribers. You can copy and paste it :)

[@bhupathireddy1663]

I am getting the predictions as a straight line no matter what values I take for p, d, q. Is it because of the stationarity of the data?

[@FinancialProgrammingwithRitvik]

Yes, we need to work on all biases before finalizing the code for real world applications such as Multicollinearity, Stationarity, heteroscedasticity, etc.

[@YensyCiprianS]

Is there any way to use this forecasting to analyze huge data and predict 5 or 15 min movements in a certain day? and if so, how can I do it, just to learn and compare with real market

[@FinancialProgrammingwithRitvik]

Prediction is possible, yet we would need to work on reliability on it. We can use the same model or any AI based models for the prediction.

[@thefourluckyones889]

how can i increase the lenght o the model prediction? like a prediction of a week instead of a day

[@BhumikaBhandari-x8x]

Which model is the best for time series predication? Is it LSTM, ARIMA or Prophet?

[@FinancialProgrammingwithRitvik]

It depends on the instrument we are predicting. Cryptos like Bitcoin will have a complete different answer than Bonds.

[@varunkuntal9175]

Thanks a lot for really helpful tutorial! I have a doubt as why are you training ARIMA model in a for loop for every iteration of test data. So if you are building a rolling model, it should be rather done every time new data point arrives, we can do train test split and train ARIMA model once instead of doing it for every iteration of test data.

[@FinancialProgrammingwithRitvik]

I agree

[@yes-yogaearthstories1404]

Ritvik, Great Work! :))) I had ARIMA during my BSc but obviously we never saw a computer so now i cna catch up.

[@FinancialProgrammingwithRitvik]

I am glad :)

[@visunashokkumar1782]

yhat section output[0] float is not itterable

[@vedanksingh6073]

Is it a 1 day ahead prediction or what? Means the prediction is of what time spam?

[@dicloniusN35]

what about Stationarity ? AIC tooo big, i think better to do auto_arima before, for choosing params

[@FinancialProgrammingwithRitvik]

Yes, Very good point. I didn't mention it as it might make the video more lengthy and confusing for beginners. But Yes, we will do all the relevant tests before performing the model in a real world analysis.

[@BenMoussaFayssal]

Great video

[@FinancialProgrammingwithRitvik]

Thanks :)

[@relax8638]

Sir can't we predict the next days price?

[@FinancialProgrammingwithRitvik]

What's the error you are getting?

[@relax8638]

@@FinancialProgrammingwithRitvik I'm only able to predict to the extent of test data and I'm stuck at predicting the next day's price

[@bhupathireddy1663]

is the data from yfinance reliable ? and if there are any other libraries like yfinance please do suggest.

[@FinancialProgrammingwithRitvik]

Yes, pricing data is reliable as per my past experience, however, if you want to explore more financial data providers API, then I have made an entire playlist on it. Just check it out and you will see how much data is available in the market for free.

[@16oshe]

por favor compartir el código

[@FinancialProgrammingwithRitvik]

Hola. Por favor, siga los pasos aquí: kzbin.info/door/yMifqUrSntvvrrGMaVPkrwcommunity?lb=UgwZRm2WrR2BqVk_ho54AaABCQ

[@ahmadlakunle9607]

Thanks so much sir, this is straight forward Just a question please, what if I’m trying to pass multiple crypto asset instead of just bitcoin. Say 10 different assets how do i call it using yfinance?

[@FinancialProgrammingwithRitvik]

We need to write a for loop for that and store the data when it comes.

[@ahmadlakunle9607]

@@FinancialProgrammingwithRitvik example?

[@tylerdonaldson2804]

So over fitted, haha

[@FinancialProgrammingwithRitvik]

Yes, :D I understand. That's why I said in the beginning that it is just an educational video on now to use ARIMA :)

[@thecomparefactory4601]

Great work buddy

[@FinancialProgrammingwithRitvik]

Thank you so much for your appreciation :)

[@optimalsolutionprogramming1299]

Very helpful video! Thank you for posting.

[@FinancialProgrammingwithRitvik]

You're very welcome!

[@mrvindictive2940]

how do you increase the length of the model prediction so you are able to predict the price for the next day?

[@FinancialProgrammingwithRitvik]

We would need daily data and then run the model.

[@UZAIROfficial]

@@FinancialProgrammingwithRitvik Can you tell me how I can extend this for next 10 days

[@dandeaton3601]

Amazing thank you so much! I notice that stats model has recently changed ARIMA, does it mean any code changes are required? I also couldn't work out how to amend the code to handle an MA value of > 0. I get error messages about convergence ...

[@FinancialProgrammingwithRitvik]

I would need to check it.

[@dandeaton3601]

@@FinancialProgrammingwithRitvik I got it working ! But then began to wonder how useful my “creation” was in the real world … I.e I couldn’t forecast out multiple time intervals into the unknown as I wouldn’t be able to re-informing the training dataset each time :(

[@saadashraf1293]

The prices till 2022 are already known, How can i use 100% of the data as training data and predict the future values??? Here we are prediciting already known values. How to predicit future values?

[@pisanchungchamroenkit7694]

Thank you Ritvik, easy to understand and very useful!!!

[@FinancialProgrammingwithRitvik]

Glad it was helpful!

[@harshitanath9705]

Why we have chosen the order of ARIMA =(4,1,0)?

[@ajinkyaadhotre5336]

Its a random choice

[@mohammadkhan5387]

with this arima model can we implement it into other asset classes? Of course, changing the Arima model or would this code automatically choose the best-fit Arima model for stock X?

[@FinancialProgrammingwithRitvik]

Yes, it can be used for any tradable securities, however, it is just a basic model and might have some limitations. Please do thorough research before putting real money on it.

[@mohammadkhan5387]

@@FinancialProgrammingwithRitvik thanks for the reply much appreciated. I am a new follower of your KZbin account and I have seen many channels and I can say that you have some high quality content. I am a trader and currently doing my masters in finance from RMIT university Australia. But just learnt basic coding at uni with R studios. I can see you have a python course so if I take that course would I be able to make a model myself like the one you made like how advance is it what I mean to ask ? Thanks Mohammad khan

[@FinancialProgrammingwithRitvik]

@@mohammadkhan5387 Thanks for your interest in my work. Yes, in that course you will learn to make the models on your own. In fact, sessions 4 and 5 are just about exploring some projects and how to optimize/automate them using Python. I guarantee you won't regret your decision to enrol for the course: fpritvik.com/python

[@narrrrdy]

Very simple explanation to understand the application of ARIMA model. You da best.

[@FinancialProgrammingwithRitvik]

Thanks :)

[@kevinlefebvre9838]

thank you for this great content. i am studying for CMT and this is very helpful, thanks!

[@FinancialProgrammingwithRitvik]

My pleasure :)

[@telifhakki8745]

i am getting error this here . What is the reason ? bro code : plt.figure(figsize=(15,9)) plt.grid(True) date_range = df[to_row:].index plt.plot(date_range, model_predictions[:-1], color = 'blue', marker = 'o', linestyle = 'dashed', label = 'BTC predicted Price') plt.plot(date_range, testing_data, color = 'red', label = 'BTC Actual Price') plt.title('Bitcoin Price Prediction') plt.xlabel('Date') plt.ylabel('Price') plt.legend() plt.show()

[@alexandr8153]

Thanks for your video. Is there any way to get your code from your videos?

[@FinancialProgrammingwithRitvik]

You can get a free access of my google drive. Over there, this code is save along with many other codes + study material.

[@iealpha-cqachallenge2897]

Nicely explained

[@FinancialProgrammingwithRitvik]

Thank you so much for your appreciation :)

[@aapriyanka8323]

Hello sir. Thank you for your video. Excellent job. Could you please provide me the code to forecast future one year values. Please help me for my thesis

[@gracesmith7726]

good explanation, thanks! waiting from one month... and video is delivered today keep it up ritvit

[@FinancialProgrammingwithRitvik]

Glad you liked it! Pardon for your wait. I will be more consistent from now on :)

[@shivamkashyap1877]

Thank so much sir

[@alexandr8153]

Is the code from your videos avaliable for downloading somewhere?

[@FinancialProgrammingwithRitvik]

You can get a free access of my google drive. Over there, this code is save along with many other codes + study material.

[@QuanttradingVega]

great video !! can you please share details of instruments used while recording this great video

[@FinancialProgrammingwithRitvik]

I don't have any setup. I just have a webcam and a shoulder mic

[@NickWindham]

Sorcery!

[@FinancialProgrammingwithRitvik]

:)

[@himeshkoli8607]

I have some doubts 1) Dont we need to check if our data is stationary or not? 2) And after if its not stationary we have to take differencing right 3) And if at all it comes stationary we need to feed that value in plot acf and plot pacf to see our MA and AR values i.e p and q values 4) Then we can come to conclusion of our p and q numbers right and then feed them to ARIMA model?? So how did you land those 4,0,1 numbers, they cant be random Please correct/guide me if Im missing something I mean im confused is this video centered for bitcoin users or those guys who wants to know how that code is working?

[@FinancialProgrammingwithRitvik]

No, you are correct. We would need to follow all the steps exactly as you mentioned in the real world analysis. I made the video just to show how we can use ARIMA model. Yes 4,0,1 should not be random. I appreciate your detailed comment :)

[@himeshkoli8607]

@@FinancialProgrammingwithRitvik thank you for clearing... I mean you can also make a detailed video regarding the points I mentioned, people will appreciate it, and also its nice to see different perspectives over a problem.. Have a great day

[@ajinkyaadhotre5336]

The same thought came to my mind why ain't he making the series stationary 😅

[@omaraziz1299]

it is good to check if data is stationary but with time series of financial instruments, the data is almost always non-stationary, especially as we expand the time period.

[@andregab6671]

thank you very much ritvik for your content that you bring to the channel and above all for the niche based on the markets and also for the clear and detailed explanations in the videos

[@FinancialProgrammingwithRitvik]

Thank you so much for your appreciation :)

[@pranitchand]

This is a good approach and I really enjoyed following it, however I am curious how would you account for non-stationary data in the forecast?

[@FinancialProgrammingwithRitvik]

Good question! I will make more videos covering nonstationarities.

[@mohammadkhan5387]

@@FinancialProgrammingwithRitvik i think you would convert that data into stationary then?

[@sarthakhajirnis1908]

You are doing such an amazing job. Waiting for your next videos eagerly! Thanks a lot.

[@FinancialProgrammingwithRitvik]

Thank you so much 😀

[@machan2k6]

Good work Ritvik. your videos and codes are really helpful

[@FinancialProgrammingwithRitvik]

Thanks :)

[@flyhighdp]

What is the use of lagged future prediction?

[@FinancialProgrammingwithRitvik]

I understand. It's just for the educational purpose.

[@sangnp07]

Good work Ritvik. your videos and codes are really helpful

[@FinancialProgrammingwithRitvik]

My pleasure :)

[@williamneri4299]

Excellent topic I wish there was a similar video with Oil prices prediction using stock RSI or CCI indicators! Best of luck for this year

[@FinancialProgrammingwithRitvik]

Noted! Thanks for the suggestion.

[@vsanden]

Thank you Ritvik, i liked the video a lot and found it usefull!

[@FinancialProgrammingwithRitvik]

Thanks for the appreciation :)

[@69nukeee]

Pretty good video! Thanks for sharing :)

[@FinancialProgrammingwithRitvik]

Thanks for watching!

[@visunashokkumar1782]

I would like to ask you sir how did your model account for the seasonality ?

[@FinancialProgrammingwithRitvik]

Yes, Very good point. I didn't mention it as it might make the video more lengthy and confusing for beginners. But Yes, we will do all the relevant tests before performing the model in a real world analysis.

[@omaraziz1299]

seasonality in a time series = non-stationary data .... i think that is why he used differencing

[@desproscrypto2034]

great video, can you try to predict forward testing

[@FinancialProgrammingwithRitvik]

We can mae prediction model for it.

[@harigovindp6061]

Loved the way you explained. It was really Helpful

[@FinancialProgrammingwithRitvik]

Thanks :)

[@dianimogadishu1348]

Great Channel. This is the channel I was looking for.

[@FinancialProgrammingwithRitvik]

I am glad to know that :)

[@Gio-ug3ye]

Subscribed! Thanks for the video :)

[@FinancialProgrammingwithRitvik]

Thanks for the sub!

[@carlolattanzi7878]

This is great! Thanks for your knowledge share! ;)

[@FinancialProgrammingwithRitvik]

My pleasure.

[@aarondelarosa3146]

statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have been removed in favor of statsmodels.tsa.arima.model.ARIMA (note the . between arima and model) and statsmodels.tsa.SARIMAX. statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and is both well tested and maintained. It also offers alternative specialized parameter estimators.

[@ganpatipatil7551]

Yes we want to see vedio on the ARIMA 👍

[@FinancialProgrammingwithRitvik]

Noted!

[@aboudiallo5852]

How to add the forcatested valeus at the same fugure with the actual values?

[@FinancialProgrammingwithRitvik]

You mean the same dataframe?

[@aboudiallo5852]

@@FinancialProgrammingwithRitvik yeah

[@burstingblahblah2313]

Cant wait to see the effect after params become optimized!

[@FinancialProgrammingwithRitvik]

Yes, I am excited too :D

[@aasthaarora9879]

Great video , thanks for sharing knowledge

[@FinancialProgrammingwithRitvik]

My pleasure

[@MarioGiordano0]

Fantastic job, i hope in some new contents soon!!!!

[@FinancialProgrammingwithRitvik]

Very soon!

[@enjoymusicbymaks]

Где кнопка бабки, индус

[@omaraziz1299]

Great video man, really appreciate it. One question though, how do I predict the value for the next trading day?

[@aashajawaharlal4855]

Great work!

[@FinancialProgrammingwithRitvik]

Thank you! Cheers!

[@jeremyheath862]

Thanks for all your videos. They are very helpful. Keep up the great work, Ritvik!

[@FinancialProgrammingwithRitvik]

Sure... My pleasure

[@haiyennguyen3394]

Thank you Ritvik, easy to understand and very useful!!!

[@FinancialProgrammingwithRitvik]

Glad it was helpful!

[@longgiaphoang4465]

tui cũng thấy ló useful áa :v

[@suryadesings4486]

All the codes are soo easy to understand and execute

[@FinancialProgrammingwithRitvik]

Thanks for the appreciation :)

[@rameenaali]

Hi,Nice video.I would like to know more theoretical aspects of ARIMA.Please do a video if possible. Also can you do video on how to do CNN based prediction?

[@FinancialProgrammingwithRitvik]

Noted.

[@MrJuanazio]

Very interesting and complete explanation

[@FinancialProgrammingwithRitvik]

Thanks for the appreciation :)

[@prakharpandey4496]

hey Ritvik, great work! i am thinking of predicting crypto data using sentiments in twitter. how can we implent the major thing i am lagging with is how can we preprocess and merge the sentiment data with cryptodata. pls help as i am new and struggling

[@FinancialProgrammingwithRitvik]

Thanks for the suggestion. I will try to cover it in future.

[@mdsahidulislam1480]

Hi Ritvit , Thanks for the video. I can not run the for loop , it shows me 'tuple' object is not capable at " print =(output)"

[@FinancialProgrammingwithRitvik]

It's difficult to understand the issue here. Have you got access to my google drive. If yes, please copy and paste my code and run line by line to check whether you have made any mistakes.