Standard Chartered is turning to data mining techniques in a bid to bolster its ability to model illiquid products, ahead of new market risk capital rules that punish markets suffering patchy liquidity and gaps in trade data. The lender is building a central repository to host all of its trade data, which Albert Chung, the bank’s head of market risk analytics, Asia, for group market risk models, hopes will allow its risk and finance teams to share a “single golden source of data”. Such efforts Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content. To access these options, along with all other subscription benefits, please contact [email protected] or view our subscription options here: http://subscriptions.risk.net/subscribe You are currently unable to print this content. Please contact [email protected] to find out more. You are currently unable to copy this content. Please contact [email protected] to find out more.
info ##bank is building a repository to host all of its trade data , aiming to create a “ single golden source ” . The bank plans to use the data to improve its ability to analyze illiquid products in preparation for the impending high risk capital rules that penalise markets for patchy liquidity and incomplete trade data . The bank is also developing algorithms that combine historical data to create synthetic time series for use where products suffer from a liquidity gap .