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The cryptocurrency market truly established itself when it became possible to invest in cryptocurrencies. This meant that a cryptocurrency could be more than just the result of fancy computer code but an actual tradable commodity. Nowadays it can almost be taken for granted that any avid user of the internet has come across cryptocurrency and/or blockchain technology. The market is growing at an astronomical rate with market cap values that are setting and breaking numerous records. Even with the occasional wobble, the market is still able to command an average of up to $2 billion worth of trade on a daily basis.
There are a number of self-proclaimed experts in the business of cryptocurrency investment on the internet. These individuals claim to have some secret formula to investing in the cryptocurrency business. They have blogs and twitter accounts dedicated to discussing these trading techniques that they say will make for profitable trading. This situation isn’t at all unique to the crypto market. The same can be found in almost any commodity trading market. Most of these analysts use highly speculative models which aren’t necessarily based on numbers and statistics. There is a growing movement within the crypto and blockchain community that is striving to actively use a scientific approach to creating useful crypto investment strategies.
Data Science and Crypto Investment
Data Science and Blockchain Technology are among some of the exciting technological developments that have the potential to shape the modern world. Already, there is a lot of buzz within the tech community that the dawn of a new digital age is imminent where concepts like Artificial Intelligence (AI) and the Internet of Things (IoT) become fully functioning realities. Both Data Science and Blockchain Technology play an important role in this new digital revolution. Away from that, there is a growing intersection between Data Science and Blockchain Technology, especially in the use of the former to conceptualize certain elements pertaining to cryptocurrencies.
The crypto market is highly volatile with a lot of speculative investment activity. Price charts over time show a lot of sharp peaks and troughs indicative of an unstable price environment. For this reason, some mainstream investors have tended to shy away from the market. Analysts are beginning to use a data-driven approach in a bid to make sense of the apparent madness of the cryptocurrency market. The following are some of the focus areas of these data-driven approaches to cryptocurrency investment.
Bitcoin Price Prediction
Python plays a big role in the field of Data Science, Big Data, and Machine Learning. Using basic Python scripts, analysts are able to develop algorithms that study the price of Bitcoin and predict the future price of the cryptocurrency. Bitcoin is the most valuable cryptocurrency in the market and it is no surprise that it is a focus of crypto investment data analysts. A large number of historical Bitcoin price data pulled from numerous exchanges is utilized for this analysis.
Depending on the programming skill of the analysts, they can choose to use an Anaconda interface due to the high level of dependencies that are involved in the study. Anaconda is one of the more popular Python data analysis tools. When all the price data has been collected and coalesced into a single dataframe, the behavior of the Bitcoin is then studied. The next step involves a probabilistic extrapolation that is used to predict the future price of Bitcoin. This same procedure can be used for Ethereum and other altcoins.
Altcoin Price Correlation
With more than 1,300 different altcoins in the market, price correlation is another important parameter when developing cryptocurrency investment strategies. Price correlation refers to the relationship between the prices of two commodities in the same market. It is a useful tool for predictive analysis models that are frequently used in investment analysis. Price correlation answers the question, “is there any relationship between these two assets?” By studying how the price of one asset behaves vis-à -vis another, the analyst can determine the relationship between the two assets.
Investors like to diversify their portfolio across different asset classes and the crypto market is no exception. Large hedge funds are beginning to enter the crypto market, spreading considerable investment sums across a number of altcoins. This increases the level of speculation on these altcoins and causes their prices to behave differently. With price correlation data, analysts can begin to pinpoint which altcoin pairs behave alike in terms of price volatility. Using a number of computer programs and algorithms capable of handling big data, these price correlations can be obtained. The effect is that similar investments are being seen in specific altcoin pairs as crypto price correlation data is becoming more refined.
The Road Ahead
It would be extremely premature to say that these data-driven approaches to crypto investments have successfully been able to understand the market. A lot of it is still theoretical with a great deal of testing and finetuning required. Analysts are still coming to grips with certain nuances that are unique to the crypto market and creating contingencies for such in their programming models.
There are a number of approaches being used for different data analysts. These include Python — Anaconda Interface, Bayesian Regression, and Long Short Term Memory (LSTM) just to mention a few. If successful, these scientific approaches to crypto investment could help investors become more successful in the market.
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Data Science trends that are affecting crypto market was originally published in The Mission on Medium, where people are continuing the conversation by highlighting and responding to this story.
Disclaimer
The views and opinions expressed in this article are solely those of the authors and do not reflect the views of Bitcoin Insider. Every investment and trading move involves risk - this is especially true for cryptocurrencies given their volatility. We strongly advise our readers to conduct their own research when making a decision.