This is the most common comment you could ever read on web courses. I’m sure your teacher explained well, you were just bored and didn’t pay attention. Here you have 4 hours for everything you need to know and you can stop and start whenever you want. It’s easier. But don’t discredit other people because you have not been able to keep up with them.
I wonder why almost everyone feels the same about the schools.they kepp u 4 years in a box and u act like a piggy bank to them.it is realy sad .I am already in that box.this guy deserves a ton of money not my teachers.
50min in and am already in love with the style of teaching. Errors are left in the vid as well as the logical process of debugging them, everything he mentions are backed up by examples. Superb content
to whom it can be of use: if you're stuck because of a KeyError 'DISCA', that is because the original stock list has had some change. You can solve it by using a try/except block when doing the the iteration for the final_dataframe = final_datafrme.append(.....) . Just put all of that inside the try block, and then do an except KeyError, and handle the eroor
haven't used a try/except before, can you please elaborate on how to use the except? I have the same issue Edit: I just put everything in the try block like you said and put except KeyError: break, is this what you did?
thank you so much for this course!!! I started my coding journey with Free Code Camp, I now work full time as a developer. This topic is on my to do list!!!
I don't comment often but this guy is an amazing teacher. He explained everything in such good detail. It helped me as I need a deep understanding of a topic to grasp it completely. Keep up the great work.
So far I have only used my python knowledge to program basic games, automation widgets and a few data scrappers but this... My head just exploded with curiosity!🤯 Thank you so much!
Excellent course, NIck!! I enjoyed very much the "real life" approach that included the footage of tracking down bugs. Thanks for not editing that out!
@2:09:00 you can use the code below to ensure you have a valid number by looping until the user has inputted a numerical value. Thanks for the great video! while True: try: portfolio_size = float(input("Enter the size of your portfolio: $")) break except ValueError: print("Please enter a valid numerical value in $")
I worked on it for a full month using the Interactive Brokers API in python and watched a bunch of videos focusing on day trading indicators etc to try and code the bot. In the end, I hadn't accounted for the commission the brokerages take (about $5 per trade which adds up especially if you're not trading with a lot) and this eventually started discouraging me a little. If anyone does run into the same problem, I would look into leverage which is riskier but easier to overcome tis problem. Risk analysis is also crucial (setting stop losses, take profits).
Still watching and learning the topics, so far so good, thanks a lot for generous offering this great course and I look forward to seeing this extended topic with advanced techniques and link to specific brokers' API like IB, Futu, etc. Thanks again for your great teaching!!
Excellent course for someone new to Algo Trading. It’s precise and well designed course. I would like to see something more along lines of simulating real time strategies like VWAP, TWAP. This one is more of pre-trade analytics. Nonetheless I liked it and strongly suggest to anyone new to Algo trading space!
Thank you that you didn't edit video, these debugging/looking for error processes actually make things more clear. And teach how to deal with such cases. And thank you for this video at all, it's great!
Loving the materials! I might add that Pandas and Numpy actually has builtin methods better suited than math and scipy libraries for some operations. For example, numpy.floor() can be used instead of math.floor() final_dataframe['Number of Shares to Buy'] = np.floor(position_size/final_dataframe['Price']) or df.rank() can be used instead of scipy.stats.percentileofscore() for time_period in time_periods: hqm_dataframe[f'{time_period} Return Percentile'] = hqm_dataframe[f'{time_period} Price Return'].rank(method='max', pct=True).mul(100)
@@adiletdaniyarov5737 HQM Scores from momentum strategy, momentum_percentiles = [f'{time_period} Return Percentile' for time_period in time_periods] hqm_dataframe['HQM Score'] = hqm_dataframe[momentum_percentiles].mean(axis=1) RV Score from valuations: rv_dataframe['RV Score'] = rv_dataframe[[i for i in metrics.values()]].mean(axis=1) :)
@@irvin1241 Im sure most colleges that have a business school within them will have a course or two on python or R that’s centered around finance. The course Im taking next semester is a minicourse to fill out my credit requirement so it’s probably not as in depth as youre looking for. The best place to start would probably be just googling the “python finance college course” and seeing what colleges offer that you’d be willing to pay for. Of course, if youre good at learning things on your own I cant recommend Kaggle enough. Its free and has alot of stuff that you can pull from. Good luck!
@@gomes8335 I dont think its a waste of time, as Im not looking to be a full time programmer. I pay for 18 credits per semester, and using a few of them to focus on my interests outside of my major seems pretty worthwhile to me. I’m not a good self-learner like some people and my background in coding isnt that strong. I think it’ll be a cool way to combine a minor interest with my other education and see if I can really take it anywhere. As always, the internet is truely the best teacher when it comes to programming, but not everyone is suited to that path :)
This is awesome! I followed every part of the course and finished all three projects successfully. Thank you so much for providing great quality content!
guys it is a simplified approach that allows to learn to program in python in a playful way. with this course you can try to make the analysis more relevant by integrating other indicators idk
Rather than counting zeros, an easier way to input large numbers with many zeros is to use e-notation: 3e3 (which equals 3 * 10^3, or 3000) 10e6 (equals 10 * 10^6, or 10000000) 8e100 (equals 8 * 10^100, or 80000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000)
There were a few questions I had while watching (I am a noob so sorry if any of them sound dumb): - How do you deploy that? I imagine you wouldn't want it running in Jupyter Notebook. - Is the accuracy-loss of floats safe to ignore? - While the concept of high-quality vs low-quality momentum makes sense, why is momentum a good metric? Isn't it likely that since you rely on data from a year ago, your model identify stocks that have already seen their growth and won't grow more? (Like making you buy at high, instead of low) - Would it be sensible instead of calculating a score to sort all the columns based on different return_percentiles? - Also, when do you know to sell? I know the premise was that we have a team of traders to whom we send our excel files, but while they'd be able to know how many stocks to buy based on our position and the filtering we did, how do they know when to sell?
Great course. Thank you for all the work you put in and your thorough explanation of how it all works together while coding. I haven't been coding python for more than a year and this was a great refresher course into data science and api use
In 58:05 for anyone don't want to use yield, you can use list concatenation for both symbol_groups and symbol_strings symbol_groups = [list(stocks.Ticker)[x:x+100] for x in range(0, len(list(stocks.Ticker)), 100)] symbol_strings = [(',').join(i) for i in symbol_groups]
do u have any tips on how to learn and improve my ability in this area after I complete this video? Tryna prepare myself for work in this field was wondering if you have tips!
52:39 If you stuck with appending series to a dataframe like me, this method(.append) returns a new object, so if you want to see the result, you should assign final_dataframe to new variable and then print it. new_dataframe = final_dataframe.append(pd.Series( [ symbol, price, market_cap, 'N/A' ], index=my_columns ), ignore_index=True ) print(new_dataframe.to_markdown())
Amazing video! Thank you so much for sharing this! Still going through it, but there's an observation I need to make for any beginners that might stumble upon this video: To create a new column with values based on another column(s), using a for loop to iterate through rows and make calculations (as shown in 2:31:11) will be EXTREMELY inefficient on larger datasets. It is better to use Pandas' `apply()` method paired with a `lambda` function, as follows: ``` # create list with time periods time_period = ['One-Year', 'Six-Month', 'Three-Month', 'One-Month'] # create new fields (or update existing ones) based on previous list # and calculate percentile based on Price Return for i in time_period: change_col = f'{i} Price Return' percentile_col = f'{i} Return Percentile' hqm_dataframe[percentile_col] = hqm_dataframe.apply( lambda x: score(hqm_dataframe[change_col], x[change_col]), axis=1) ``` Same method can be applied to calculate HQM Score using Pandas' `mean()` method: ``` hqm_dataframe['HQM Score'] = hqm_dataframe.apply( lambda x: pd.Series([x[f'{time_period[0]} Return Percentile'], x[f'{time_period[1]} Return Percentile'], x[f'{time_period[2]} Return Percentile'], x[f'{time_period[3]} Return Percentile'] ]).mean(), axis=1) ```
@@Jon-bk2bw I had the same question and I think they did on 21st August 2021 but I'm not sure how come users were able to work with it until a couple of months ago.
A great detailed starter course to learn some Python. As a licensed commodity trading advisor (and a software engineer), I would never advise someone to trade this though.
It's June 2024 and it is giving the error "Sandbox environment is disabled for this subscription tier." , API key may have expired. Can you please update the key!
The API no longer works. I dont really understand if what I am saying makes sense, but IEX Cloud is shutting down apparently. Could you please suggest a workaround? Just FYI, what this means is that the access to the API token provided in the video is restricted.
at 2:28:12 While implementing the percentiles, I noticed that the data I am receiving has None type in it. So the scipy.stats module throws an error as it cant compare the None type instances. For now I am replacing it with 0. Just for people who face this error you can just add this right before you assign your return percentiles for row in hqm_dataframe.index: for time_period in time_periods: if hqm_dataframe.loc[row,f'{time_period} return'] == None: hqm_dataframe.loc[row,f'{time_period} return']=0
Just as a safety precaution since you never want to trust someone to know what to do you can use a while loop for the input validation: invalid_input = True while invalid_input: try: portfolio_size = input("Enter the value of our portfolio:") val = float(portfolio_size) print(val) invalid_input = False except Exception as exception: print("You must enter an integer")
I am really enjoying learning these techniques and am impressed with your style. Thank you for encouraging others to learn! I'm running into an error in the momentum calculations around percentileofscore implementation, around 2h 30m mark in your video. I am executing the following: for row in hqm_dataframe.index: for time_period in time_periods: change_col = f'{time_period} Price Return' percentile_col = f'{time_period} Return Percentile' hqm_dataframe.loc[row, percentile_col] = score(hqm_dataframe[change_col], hqm_dataframe.loc[row, change_col]) and get the error: TypeError: '
I found a solution to this question in one of the comments. Another user had the same issue and they resolved it by adding this line before the for loops I mentioned: hqm_dataframe.dropna(inplace=True) This drops any rows/columns that return N/A as part of f''{time_period} Price Return' column in the hqm_dataframe
great video, what I really liked is that you showed in a super clear way how to use the requests library in Python and now I do not need to depend on 3rd party wrappers that might not have all functionality! thanks!
The fun thing about pandas, is that you can work with whole columns without loops, e.g: final_dataframe['Number of Shares to Buy'] = final_dataframe.apply( lambda row: math.floor(position_size / row.Price), axis=1)
Easy way to add a cost column to your pandas df: final_dataframe = final_dataframe.apply(lambda x: x['Stock Price'] * x['Number of Shares to Buy'], 1) *** don't forget the ',1', it specifies the axis :)
Hello, for people getting to the Key Error for the stocks, the solve is to delete the 4 stocks that have been delisted from the S&P 500: code example: stocks = stocks[~stocks['Ticker'].isin(['DISCA', 'HFC','VIAC','WLTW'])]
this was awesome and though I've just finished the first part only, I cannot thank you enough for how well you explained each portion of the project. Now only, if I could build up from here!
Just stumbled on this. Thank goodness I got took my trading seriously. Getting into the market surely led to many open doors for me as I've gone to make quadruple of what I put in.
@@Diallo872 For me, I lost money repeatedly because I didn’t know how to go about it till I came across recommendations of Levi Clemans, a seasoned trade analyst and reached out. It’s been a great journey ever since. You can also get across
I have not written this sort of comment before but I feel compelled to. Just wanted to let you know that you’re doing a great job Clemans. You have made a difference in my understanding of the market.
awesome!Fix some problems:Before Calculating Momentum Percentiles,Execute the statement first to clean up invalid data.hqm_dataframe.fillna(value=0, inplace=True)
Just coming across this video now. Make sure, for the first project, you get an up to date list of all stocks found on the S&P 500. At this time there were 4 stocks that no longer are under the listed tickers with the provided csv file.
i cant find this Needd Heeellppp!!! Section 2: Course Configuration & API Basics How to Install Python Cloning The Repository & Installing Our Dependencies Jupyter Notebook Basics The Basics of API Requests
@deqiang tian Thanks and it worked! My steps are a little different 1) I downloaded "Anaconda" and 2) In the Anaconda Prompt I type "pip install panda" "pip install numpy" "pip install jupyterlab".
Yeah, its very unfortunate and discouraging to those who are learning the fact that section 2 is missing from the actual video even thou it is mentioned on all the syllabus for this course that I came across. Several people on the comments are complaining about this and I mean... You could at least edit the video description with basic instructions or with a link to where we can find the missing part of the video. After all that is critical information for those who wants to follow along with your course. Thanks anyway
This is a great course. I learned so much from it. One suggestion: the robust value trading program should exclude the negative PE Ratio stocks first before sorting for the low 50 stocks.
Mrs harriet dixson service is a talk of the town in North Holland Netherlands , I started with a little amount of 1ETH, and she made huge returns, and I have been constantly investing with her
Tell her I referred you I can't hide her contact information from anyone who is interested in investing with her because she has really helped me a lot with my trade, today I am smiling
I don't know much about these or it works, when it comes to trading I have learnt to have an open mind as there are different trading strategies out there.
Awesome video, thanks very much! For the next time, please put the video of the educator not on top of the slides or if in a corner where it does not superimpose on the content.
I just started learning python, it's only been days, but this is my end goal. So I'll be saving this video for later, hopefully it won't be too long before I'm ready for this course.
bro i too want to start with python nd my end goal is gonna be this video. Can you help me where to begin with nd when i will be ready to go with this one
@@zeroXmlbb if you're new to coding, I would start at the basics. Learning functions and variables are a good place to start. If you're like me, and this is your first programming language, I would give myself 3 to 6 months before getting to this level.
I have a few tips for people that may be struggling with setup & other things: As an alternative to setting up & using a local Jupyter notebook, you can use a Google Colab Notebook (colab.research.google.com) with the following imports: import numpy as np import pandas as pd import requests import math !pip install xlsxwriter If any of you are confused about how to get secrets.py, click on the link & press 'Ctrl/Command + S' to save the file. Upload it into your Google Colab, go to the 'Runtime' menu tab, and click 'Restart & Run All' Note that if you use Google Colabs, you may have to re-upload the stocks csv & IEX token file after you leave the browser & come back.
Nice video, but I think it has been edited from the original as now at the 17:00 mark, he states that he's already told us how to set up the environment (and the required files) this is missing. Maybe someone can reply a location to find these? Thanks
People have to remember the point of these videos is to teach you to code a trading algo. He isnt saying that algo will be profitable. That requires some really complex mathematical models like what Jim Simmons and Renaissance do. But these videos are still valuable to learn to build something for its own sake nevertheless.
Another way to skin the cat... You can put inputs in while loops such that the user is repeatedly queried for input until he gives it correctly (i.e. until he gives numeric input). For example: portfolio_size = '' while not isinstance(portfolio_size, float): portfolio_size = input('Enter the numeric value of your portfolio') try: portfolio_size = float(portfolio_size) except ValueError: print('Entry must be numeric') I go this route because assertions, try-except blocks, etc. generally halt execution on errors, requiring you to run the code again. This keeps it going.
Shouldn't stocks with negative P/E and P/B ratio be removed when you are calculating the RV Score? I see that it was done when you take the simpler approach and only use the P/E ratio. Thanks in advance :)
Awesome tutorial, watched the whole thing through to the end. For the next video tutorial, do you want to show us how to write a trading bot that will automate day trading based on these algorithms?
This course is the best on RU-vid and it is better than University degrees. Thank you so much for your contribution to us. Is there any way to contribute to you and paying for a certificate after finishing this course?
BONUS: In this course a free addictive Python course for beginners / intermediate programmers is included, with clear clarifications about everything you may need ♥
@@goober-ll1wx If you can place order 100 times a minute, it's still not illegal. They place 1000 times a min. It's not illegal. It's calculus of day trading, more like minute or even seconds trading.
You can use a while loop with the input: def portfolio_size(): global portfolio_size while True: try: portfolio_size = input('What is your portfolio size?') if isinstance(float(portfolio_size), float): break except ValueError: print('This is not a number')
Some stocks have been delisted, to make the tutorial work you must delete the following stocks from either the stocks dataframe or the original sp_500_stocks.csv file: 'DISCA', 'HFC', 'VIAC', 'WLTW'
I know absolutely nothing about Python… But this is the first video that seems to clearly explain what my brain just can’t seem to wrap itself around. When I designed the investment strategy that I use, it was simple math, well, it was math… But to suddenly take the algo and transfer it into a language that I am not familiar with, seems like the worst possible prostitution of my time… I get it, learn Python then write code and be happy ever after but, but, but, why can’t I do that in English? I can read medical journals on just about any topics, all I need is a dictionary and some extra time, I don’t need to mortgage a significant portion of my time on this planet just to learn something that will be old info by the time I’m done learning it… There’s gotta be a practical way to do that in English! Heck in French or Spanish or Russian or any languages! Geese this is so frustrating!!!!!!!
When you take the user input this could be an option so that it will keep asking until they provide anportfolio_size = input('Enter the value of your Portfolio : ') while True: try: val = float(portfolio_size) print(portfolio_size) break except ValueError as e: print('That"s not a number, please try again') portfolio_size = input('Enter the value of your Portfolio : ') print(portfolio_size)
What I like about your tutorial is that one doesn’t miss out if they start with the third section. Also than you didn’t cut out the bugs and struggle helps people to understand that these stuff belong to a programmers life. Another positive point is that you try to clarify specific financial terms. Overall you did a great job here. One point of improvement is your face cam position on the screen.
This is very great video filled with explanation and experience. Watching it has been a pleasure. Thank you for taking the time and having a student mentality you are appreciated.
You should do one that actually goes through candle data for several stock tickers. That's what seems to be lacking everywhere I go. People always trade on just 1 stock ticker when they go through candle data and do TA strategies. Would be nice to have a tutorial on going through candle data maybe even intraday, and buying specific stocks from a long list of tickers using a % of available funds, or % of portfolio.
Very confused on how i missed this but where does he list the dependencies i need for this? I watched the intro and am new to python, I'm not too sure what environment he is using or how I install everything I need for this course
Hello. If you're installing this on Windows 10, make sure to install the version from the python website and not from the microsoft store, since both of them install python in different locations. As for the dependencies, use the command prompt (don't use the python IDLE), and install the dependencies by typing: pip install Replace dependency-name for the following modules: numpy jupyter pandas requests xlsxwriter Hope this helps you continue
@@tetsuo79 Sir, I can see that you are a kind man. Can you please help me with getting into jupyter notebook please. as I am facing some problem with it.It seems I need some password to access it.
