The Tokyo-based management consultancy and research firm said the “NRI/IU Crypto-Asset Index Family” – created in coordination with Intelligence Unit LLC (IU) – will be available through NRI’s financial information database, IDS, to domestic and overseas institutional investors, financial information vendors and crypto exchanges.
Nomura Research Institute (NRI) will launch a benchmark rank and compare Japanese cryptocurrency assets on Friday.
The benchmark is intended to pull together information specific to the Japanese cryptocurrency market, including data on crypto-yen pairs and closing values, all in local time.
A benchmark index is a standard allowing traders to evaluate the performance of their portfolio or of a particular asset against the broader market.
“The increasing investment needs for crypto assets have, in turn, led to a high demand for a benchmark to appraise those investments,” the company said in a release.
The NRI/IU benchmark will support bitcoin, ether, litecoin, bitcoin cash and XRP. It is calculated using the MVIS index platform, with cryptocurrency data supplied by CryptoCompare.
“Strong demand from institutional investors is contributing to the growth of crypto-asset funds, and well-diversified products like index funds are attractive as alternative investments,” said Akihiro Niimi, IU CEO, in a statement. “We will bridge the traditional financial world and the crypto-asset world by providing institutional grade crypto-asset benchmarks, further establishing the status of crypto-assets as alternative investments.”
In September, CF Benchmarks became the first cryptocurrency index provider to be licensed in Europe after the U.K.’s financial watchdog gave it a BenchMark Administrator (EU BMR) license, allowing institutions to use its indices in any European financial products.
Nasdaq launched an AI-powered index of the top-100 best performing cryptocurrencies for Wall Street traders in October.
Nomics Machine-Learning Tool Offers 7-Day Price Forecast on Top 100 Cryptos
Data provider Nomics is using machine learning to predict the future prices of cryptocurrencies like bitcoin.Launched Thursday, the 7-Day Asset Price Prediction feed will give an outlook on future crypto prices based on purpose-built algorithms and the firm’s API, Nomics CEO Clay Collins told CoinDesk in an interview.
“There are a lot of poor signals out there that are getting a lot of clicks and we thought we could do a net positive for the space by just leveling up the quality of predictions”, Collins said.
The Nomics forecaster isn’t a standalone, investment-grade product, Collins added, but can help inform crypto investors based on curated exchange data.
The free tool currently lists 100 of the top cryptocurrencies by market cap. Collins said assets with longer histories and better data sources tend to lead to better predictions overall.
A subset of artificial intelligence, machine learning uses computer algorithms combined with data inputs to predict future events. Interestingly, machine learning services should get better given how these systems learn from past data and predictions.
Under the hood, the tool inputs “aggregate pricing data” from major exchanges that Nomics scrapes and cleans. That data is then fed into a purpose-built algorithm to spit out seven-day predictions in both a spot price and percentage change from the current price.
“LSTMs are relatively new in the machine-learning space, and financial data is notoriously difficult to predict, but we were able to get fairly reasonable predictions, and we are fully transparent about their historical accuracy”, Nomics CTO Nick Gauthier said in a statement.
Of course, price predictions in any market, particularly crypto, can be exceedingly difficult to pin down.
Collins said the team wanted to add a touch of professionalism with its data-guided predictions. In the spirit of transparency, Nomics will also include a 30-day mean error rate with the new feature.
“We don’t know when weird things are going to happen”, Collins said. “If the Yale endowment said they were going to allocate 30 percent in bitcoin – well, our models are not going to know that.”