To keep my skills sharp, I recently started looking at the online landscape for freelancers, and among all the options, Upwork was recommended as one of the best marketplaces for freelancers and clients. So I set up my account and narrowed down some projects that I found interesting and wouldn’t take too long to complete.

The project I will cover in this post, as the title indicates, involves the study of price movements between Bitcoin and three crypto mining stocks: MARA, RIOT, and CLSK.

Disclaimer: I did not work on this project with the client who posted it on Upwork. The work presented here is purely mine and for my own entertainment. The datasets are publicly available – the research is entirely my work.

1. Data Link to heading


  • Bitcoin (BTC-USD, or BTC in short)
  • MARA
  • RIOT
  • CLSK

Type: OHLCV data (Open, High, Low, Close, Volume).

Timeframe: from 02 January 2020 to 23 May 2024.

Frequency: daily observations.

N.B.: BTC trades 24/7 while the crypto stocks follow regular market hours, so no weekends. This means that the data for Bitcoin needs to be adjusted to not take into account weekends. I have omitted the code used for the pre-processing phase, to focus primarily on the analysis itself, but I can make it available upon request.

2. Analysis scope Link to heading

Primary analysis scope: investigate the relationship between closing price of Bitcoin and the closing price of the three crypto mining stocks. Additionally, repeat the exercise for with the (OHLC) price average of the three stocks.

Secondary analysis scope: analyse the effect of Bitcoin up days on the three stocks. Similarly, analyse the effect of Bitcoin down days on the three stocks.

N.B.: Up days mean that the Close price was higher than the Open price for that day. Vice versa, down days are the ones where the Close price was lower than the Open price. Based on the interval under analysis, there is no observation where Bitcoin was flat, it was either Up (green) or Down (red) days.

3. Analysis Link to heading

For the primary analysis, standard line and scatter plots were implemented to get a feel of the data. In Fig. 1. you can see the time series over the entire timeframe for BTC. In Fig. 2 you can see the same for the three stocks. From Figure 1. we see that BTC doesn’t really follow the same patterns as the three crypto mining stocks, while the three stocks move very closely together.

Potential scope for more research: not related to the scope of the current tasks, but the closeness of the three stocks could perhaps be modelled under a Vector Autoregressive (VAR) model, and potentially exploit anomalies via pairs or trio trading.

BTC entire horizon

Figure 1. BTC


Figure 2. MARA | RIOT | CLSK

Following, the scatter plots in Fig. 3; Fig. 4; and Fig. 5, show a positive and weak correlation between BTC and the stocks. From the graphs we notice that all three stocks are positively correlated, yet the correlation is not strong. Repeating the exercise with the average of Open, High, Low, and Close price yields nearly identical results.

BTC MARA scatter

Figure 3. BTC MARA correlation

BTC RIOT scatter

Figure 4. BTC RIOT correlation

BTC CLSK scatter

Figure 5. BTC CLSK correlation

The weak correlation is validated in the secondary analysis where the directional impact of BTC is analysed against the crypto stocks. Before delving into the secondary analysis, I need to note that unlike BTC, the three stocks occasionally show flat days. A flat day is a day when the Open price is equal to the Close price. This will be relevant in explaining why when I compute the statistics of up/down days of the three stocks, up + down percentage doesn’t equal 100% but slightly less.

To meet the goals of the secondary analysis, I opted for a simple scoring mechanism that checks on day $ 𝑑 $ if Bitcoin is $ 𝑒𝑝 (πΆπ‘™π‘œπ‘ π‘’>𝑂𝑝𝑒𝑛) $: check each of the stocks and note if it’s $ 𝑒𝑝 $ or $ π‘‘π‘œπ‘€π‘› (πΆπ‘™π‘œπ‘ π‘’<𝑂𝑝𝑒𝑛) $. If it’s not $ up $ or $ down $, then it’s $ π‘“π‘™π‘Žπ‘‘ (𝑂𝑝𝑒𝑛=πΆπ‘™π‘œπ‘ π‘’) $.

The summary statistics have been collected in Table 1. and Table 2.

Bitcoin up days (total: 565)

Up days (%)Down days (%)Flat (%)

Table 1. Bitcoin up days

Bitcoin down days (total: 541)

Up days (%)Down days (%)Flat (%)

Table 2. Bitcoin down days

4. Conclusions and insights Link to heading

From Table 1. we see that the three stocks will generally follow the same direction when BTC is up. This matches what is shown in the scatter graphs, with RIOT showing the highest percentage of up days among the three. This could be interpreted as a weak BUY/LONG signal in a trading strategy.

From Table 2. we see that the three stocks will generally follow the same direction when BTC is down. Similarly to Table 1., RIOT shows the highest percentage of down days among the three stocks. This could be interpreted as a weak SELL/SHORT signal.

From the two tables above one could make the argument that when BTC is up, the three stocks are very likely going to be up but not very strongly, or in other words, there is also an abundance of days when the stocks tanked. This makes sense because there are other factors that enter stock price. On the other hand, when BTC is down, in relative terms to the up days, there’s a stronger argument to go short on the stocks because of the wider gap between Down days (%) and Up days (%).

What about other cryptocurrencies? Link to heading

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