This report focuses on some of the prevalent approaches to alternative data being used by hedge fund managers today. It highlights the importance of symbiosis between humans and machines in the effort to gain superior insight.
The 'Data Science in Focus 2020' special report comprises four separate articles listed below, these can be read individually or as a sequence.
By A Paris – Alternative data and data science techniques can help give hedge funds a competitive edge but, it is the symbiotic integration of human and machine which ultimately underpins managers’ success or failure in their use of these techniques.
Using order book data to drive investment decisions was historically the domain of high frequency trading hedge funds. However, as these datasets are being aggregated, harmonised and made searchable, a whole host of hedge funds and investment managers can seek to benefit from insights drawn from order book data to improve their back-testing techniques and enhance their alpha generation capabilities.
As various pharmaceutical companies around the world endeavour to find a workable vaccine against the coronavirus, alternative data could help funds take an investment view on where the value lies in this global race.
The growing computing power witnessed in the past few years has led to data becoming more accessible, often at the touch of a button. Though there are huge benefits to this, the progress also means the danger of information overload is an unfortunate reality. As more alternative datasets become available to hedge fund managers looking for a competitive edge, they need to make sure they take full advantage of any data they purchase while also incorporating any information they share across their internal company channels.