ECA-100 Class C

Similarity Matrices

Similarity matrices are square matrices (e.g., 100 x 100 in ECA-100) that describe closeness among of cryptocurrencies. Each element of a matrix represents the similarity between two cryptocurrencies in terms of directions and scales of their price log returns. Similarities are evaluated by well-known quantitative measures.

ECA-100:C1 : Collinear Matrix

ECA-100:C2 : Covariance Matrix

ECA-100:C3 : Correlation Coefficient Matrix

ECA-100 is the first real time streaming product that offers both event and time series analytics in cryptocurrency (and finance). ExxaBlock is a pioneer in large-scale real time streaming event analytics in finance. ECA-100 supports cache API for direct access to ECA-100 cache servers with low-latency, constant-jitter connectivity and high-throughput I/O computation. Through dedicated or shared connections to the servers, customers can perform time-sensitive and/or high-throughput computational tasks. Concise Binary Object Representation (CBOR) is used to minimize the network communication overhead caused by message encoding, decoding, and transmission. Compared to JSON text messages, CBOR messages require 70% less size in ECA-100.

ECA-100 is available on public clouds, private clouds, and customer on-premise data centers. ECA-100 can also be integrated into customer systems.

To view our real time streaming quotes view our beta link below:

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