SearchSearchSearchOct 28, 2024
5 min read
Blockchains are decentralised and immutable digital ledgers where all transactions are entirely transparent. This factor has led to potential use cases of blockchains in various industries worldwide. But simply putting things on-chain doesn’t solve business problems - analysing and comprehending the data recorded in a blockchain is crucial for identifying the trends and performance of a particular blockchain and making future decisions backed by data. This process, known as on-chain analytics, can also be critical for predictive modelling in the crypto market.
Important drivers behind the traditional predictive models that one sees today include statistical strategies and emerging technologies. Data, which is the most pivotal input for predictive modelling, needs to be analysed in minute detail to create accurate models. Other tools and techniques like machine learning algorithms, data visualisation tools, or statistical software can also help with on-chain analytics.
On-chain data of blockchains is analysed by popular blockchain data analytics platforms like Token Terminal and Glassnode. ICR’s crypto scoring and ranking product is also a useful tool for studying various DeFi tokens, smart contract platforms, digital currencies, and utility tokens using major on-chain data indicators.
On-chain data indicators are important for on-chain analytics, but are also crucial for making a fundamental analysis of a blockchain.
While on-chain analytics focuses extensively on data patterns and indicators to make data-driven predictive models, on-chain analysis emphasises the fundamental performance of a blockchain through recorded data indicators.
On-chain analysis provides a comprehensive picture of a blockchain, both fundamentally and technically. On-chain indicators like market cap, circulating supply, transaction volume, and others are essential for working out the potential and current functioning of a blockchain. An on-chain analysis also leverages the data that is recorded on the blockchain, which is its distinguishing feature because the data is completely transparent and immutable.
On-chain analysis is done to derive a fundamental or intrinsic value of a crypto. It is similar to how investors study a company's quarterly report and balance sheet before studying its stock price. Just like 'daily active users' is one of the key metrics to measure a company, say Instagram's success, similarly, depending on the utility of the crypto, it must be possible to measure its success by identifying certain key metrics.
Thus, on-chain analysis is highly impactful in guessing market sentiments and investment decisions.
Here are some of the most essential metrics for performing an on-chain analysis:
Predictive modelling is already prevalent in traditional financial markets to improve efficiencies and minimise risks. In other avenues, such as weather forecasting, predictive modelling is also done widely based on historical data and trends. Hence, it is proven that trusted, safe, and large amounts of data are needed to create the best predictive models.
Blockchain networks fill all three criteria for data. With immutability and decentralisation as underlying factors, a blockchain can deliver the most committed data that cannot be tampered with.
At the same time, with thousands of nodes (or devices) that validate transactions in blockchains, the sampling sizes of on-chain indicators can be quite large. The presence of cryptographic signatures in blockchain protocols also makes on-chain data extremely safe and reliable!
As we've explained in this blog, on-chain analytics is certainly a catalyst for predictive modelling in the blockchain sector. Such models have many viable applications in crypto, including predicting the price movements of crypto tokens. Predictive modelling can also be used to discover new innovative domains that blockchain projects can explore. All things considered, on-chain analytics and predictive modelling can disrupt crypto!
Dive into the various facets of crypto and blockchain, only with India Crypto Research!
The information provided in this blog is based on publicly available information and is intended solely for personal information, awareness, and educational purposes and should not be considered as financial advice or a recommendation for investment decisions. We have attempted to provide accurate and factual information, but we cannot guarantee that the data is timely, accurate, or complete. 1 Finance Private Limited or any of its representatives will not be liable or responsible for any losses or damages incurred by the Readers as a result of this blog. Readers of this blog should rely on their own investigations and take their own professional advice.
