Wei-Shen joined WatersTechnology in June 2016, becoming the publication’s first full-time Asia-based reporter. Based out of Hong Kong, she writes for both Waters and Inside Data Management magazines, as well as the four subsites of WatersTechnology.com—Sell-Side Technology, Buy-Side Technology, Inside Reference Data and Inside Market Data. Prior to joining WatersTechnology, she was a journalist at Star Media Group in Malaysia. She has a Bachelor of Commerce degree in Accounting and Finance from the University of Auckland.
Development of machine learning and natural-language processing is now turning to languages other than English to keep a better eye on traders and the market. But how easy is it to teach a machine a new tongue?
Buy-side participants are now more aware of the risks associated with FX settlement, and are getting more involved in managing them.
Automated hedging service aims to jump-start liquidity at start-up venues, using proprietary mechanics to minimize slippage and boost profitability.
As interest in cryptocurrency trading refuses to wither, despite a bearish year, traders are increasingly calling for institutional-grade tooling from traditional markets to further develop the asset class.
Subject to regulatory approval, the newly created digital asset investment bank plans to launch a custody solution in April.
The data provider recently launched a platform aggregating BRI data.
An industry initiative to start a new US exchange promises much, but it may struggle to deliver without a clearer purpose.
CoinFLEX users will be able to use trading tools provided by Trading Technologies.
From the data battle between the SGX and India to the ASX green-lighting its clearing blockchain project, Wei-Shen Wong looks back on topics that made headlines this past year.
The performance and risk measurement specialist is also using machine learning to help drill into value-at-risk calculations.
Processing corporate actions is usually the last workflow to be automated, mainly due to the complexities involved and the weakness of underlying data. Wei-Shen Wong explains how this has changed over the last few years and what challenges remain.