This project is all about bitcoins. It uses an online database that tracks the daily prices of many cryptos and it aims to examine the impact of different factors on bitcoin prices.
I like this midterm report very much. It resembles a published research report. More specifically, the formatting is flawless; the plots explain the data fairly well. I especially like the idea of reframing the project into a classification problem focusing on the sign of day-to-day return of bitcoin.
A few places to improve upon. I had a hard time consuming Figure 5 – which row/column should I be looking at? Also, the report fails to explain what is "bitcoin price adjusted". How is it adjusted? Why does the adjusted prices correlate much more with other variables?
The explanatory analysis looks rushy. And, if "Clearly, such model does not generalize with our data set", then why only use this one model in the first place? Figure 6 and 7 looks quite out-of-place. What do they suppose to imply?
This project is all about bitcoins. It uses an online database that tracks the daily prices of many cryptos and it aims to examine the impact of different factors on bitcoin prices.
I like this midterm report very much. It resembles a published research report. More specifically, the formatting is flawless; the plots explain the data fairly well. I especially like the idea of reframing the project into a classification problem focusing on the sign of day-to-day return of bitcoin.
A few places to improve upon. I had a hard time consuming Figure 5 – which row/column should I be looking at? Also, the report fails to explain what is "bitcoin price adjusted". How is it adjusted? Why does the adjusted prices correlate much more with other variables?
The explanatory analysis looks rushy. And, if "Clearly, such model does not generalize with our data set", then why only use this one model in the first place? Figure 6 and 7 looks quite out-of-place. What do they suppose to imply?