Algorithmic stock trading—aka "algo-trading"—uses machine learning algorithms to make stock market trades faster than a human could, calculating the best time, price, and amount to trade in an instant.
Portfolio management is the management of investments to meet long-term financial objectives.
Today, machine learning models and external data are used in order to help companies and individuals better manage, diversify, and maintain their assets and take on less risk for higher reward.
Today, machine learning models and external data are used in order to help companies and individuals better manage, diversify, and maintain their assets and take on less risk for higher reward. Portfolio management models and use cases include any collection of investment instruments like shares, mutual funds, bonds, FDs and other cash equivalents, etc.
Hedge fund investments use several different strategies to achieve returns in both domestic and international markets. They are often aggressively managed and trade in land, real estate, stocks, derivatives, currencies, etc. markets.
The most lucrative hedge funds also have a diverse portfolio—which means investors need to analyze large amounts of data to make investment decisions.
Fighting money laundering is a complicated task with substantial costs and risks, including—but not limited to—regulatory, reputational, and financial crime risks. Money laundering can be difficult to track, with many false alerts making detection even more challenging. But new technology, such as artificial intelligence (AI) and big data, can increase detection rates and keep your firm safe.