Is Investing on Robinhood a Great Idea?
With the rise of Fintech (Financial Technology), I wanted to determine just how well investors were at investing on their own on the Robinhood platform. Are people as financially savvy as they think they are by abandoning the traditional ways of hiring a Wealth Management firm to manage and handle their investments and self-invest instead? I wanted to dive deeper to see if they were. As an ex financial advisor myself, there was always the challenge of my millennial generation wanting to make their own investment choices and not take the advice from the “experts”, so I wanted to see exactly how that has panned out.
I gathered a data set from Kaggle that had all of Robinhood’s user counts in every asset on their platform, which surprisingly enough, they report on a regular basis and is public information. Once I loaded my data into Jupyter Notebook, cleaned, condensed, and converted it into a datetime data frame, I began my EDA and my findings were really interesting. I originally wanted to look at Robinhood users as a whole from this past year, but when I started my EDA, I discovered a lot of interesting things pre and post COVID 19, so I decided to redirect my focus on that time frame.
The official declaration date for COVID was March 13, 2020 and from that time onward, the total user amount increased by 122.26%. My COVID 19 time frame went from March 13, 2020 until Jul 17, 2020 when my data ended. In my opinion, the cause for this sudden increase in users was due to the fact that more people wanted to invest and take advantage of the stock market decline in March. We were now in quarantine and people who usually were not aware of the stock market now had the time to be curious and jump in.
Now I wanted to explore the assets that Robinhood users invested in the most so I plotted the top 10 assets by popularity.
Next I wanted to The most popular assets among Robinhood users were:
Stock Name % Change Post COVID $ Change 03/13 - 07/17
1. Aurora Cannabis Inc. 22.00% $9.24 - $11.88
2. Ford 20.78% $5.63 - $6.80
3. General Electric -9.80% $7.84 - $7.07
4. Walt Disney 15.70% $102.52 - $118.65
5. GoPro Inc. 82.56% $2.70 - $4.92
I calculated the percent change from March 13 through July 17 to get my percentages. These percentage changes, besides GE seems to be great looking at it from just a percentage change stand point. But all of the assets, except for Disney has a stock price of under $10 and their returns are very limited from a dollar amount stand point of a capital gain of $1-$2 a share.
Next I want to look at the most profitable assets post COVID 19 and see how they compare to the popular assets.
Stock Name % Change Post COVID $ Change 03/13 - 07/17
1. Moderna 345.00% $21.30 - $94.85
2. DocuSign 153.86% $77.37 - $196.41
3. Zoom 129.00% $107.47 - $246.54
4. Amazon 65.94% $1785.00 - $2961.97
5. Netflix 46.60% $336.28 - $492.99
What I see here is that Robinhood users did not choose the most profitable assets. The percent changes blow the popular assets out of the water and their average capital gain per share is over $300.
After my analysis, I believe that the Robinhood users did not invest in the most profitable assets. The assets that were the most popular were assets that would have be profitable pre COVID 19. Because of the current circumstances, our ‘new normal’ may become a permanent reality and investment strategies must shift. Industries like the car, agriculture, home appliances, and entertainment may all never be what they once were. When investing, you must look at the bigger picture.
With companies now having to shift their business to an almost 100% digital platform, companies like FAANG are on the rise more than ever. FAANG stands for Facebook, Amazon, Apple, Netflix, and Alphabet(Google). Looking into technology companies seems to be the better investment move going forward. Thinking about how our world will forever change because of COVID 19 has to be in the forefront when making business and investment decisions. This is a concept that a lot of people, if not exposed to it, will not think about on their own. As you can see from my findings, self-managed investments without some form of in-depth knowledge about finance and economics will prohibit maximum profits. Just understanding the buy low, sell high method will give your ROI a boost. Smart investing is a proactive process and not a reactive process. If you react to the market, you will always be behind it. Working with a professional or at least someone who understands these concepts will ensure you are maximizing your portfolio growth potential.
I also created an Advanced Auto ARIMA model to predict Amazon prices. Since this post was more about my EDA, I will not go into too much depth about it but I want to share what I built. Please check out my github for the full project and an explanation of my model.
plt.figure(figsize=(8,5))
plt.plot(df.Close, label = 'Training')
plt.plot(df_test.Close, label = 'Testing')
plt.plot(prediction2, label = 'Prediction')
plt.legend(loc = 'Left corner')
plt.show()
prediction2.plot(figsize = (20,5), color = 'red')
df_test.Close.plot(color = 'blue')
plt.title('Predicted Amazon Stock Prices vs. Test Data', size = 24)
from sklearn.metrics import r2_score
df_test['predicted_stock_price'] = prediction2
r2_score(df_test.Close, df_test.predicted_stock_price)
I built multiple models and played around with different parameters. I started with an r2 score of -0.15836897303755193 and went to a 0.7006142667306581. Or a -0.16 to a 0.70. My model went from not accurate at all to being substantially accurate. Overall, I’m pretty happy about the outcome of my model. I want to definitely continue to tweak the parameters to try to enhance it to be able predict volatility as well. I also think that having the market crash in March in my data also contributed to some inaccuracy.
