Technology DisruptionTechnology is becoming ever more important for hedge funds looking to gain a competitive advantage, especially in sectors that have been underperforming over the last few years. Technology can enable doing more with less. Hedge funds can optimize and gain quicker access to markets while remaining compliant and cost efficient. In the KPMG survey from last year, an overwhelming 94% of hedge funds said technology will have an impact on their competitive advantage over the next five years. Managers are having to think in new and innovative ways to ultimately remain competitive and attract investors. With this shift, technology is also disrupting and challenging existing processes and sometimes destroying the status quo. We are seeing this trend continue through 2017 as funds test out and deploy new solutions. Sometimes, entire functions are migrated to being delivered as a service and usually by niche providers, who find themselves much nimbler and quicker to adopt these new technologies.
DataFunds are increasingly leveraging alternative data sources in order to find new or deeper market insight. Obscure data, such as raw satellite imagery, can now be converted into tradable information. Sentiment analysis is a methodology that has been around for a while and is becoming an established source of useful information. Similarly, “dark” or “exhaust” data, which is data that has been collected but usually discarded or not put to any particular use, is now becoming more feasible and interesting. New high performance computing solutions using cloud platforms, allow researchers to make use of increasing volumes and complexity of data. This can be mined for new information, analysing risks and opportunities that would have otherwise been overlooked. Using public cloud services even small hedge funds are able to ingest enormous data sets in a matter of seconds and very cost efficiently. Some challenges around big data are complexity, speed, data quality, and noise. Processing such large data sets, without the right technology or data strategy, can be wasteful or produce the wrong results. Additionally, insights from big data are only as accurate as the quality of data itself. If there isn’t proper governance around the quality of data being ingested and the processing, then the value of the outputs can be jeopardized.
Quant StrategiesThe technology, services and data which are ever more easily accessible, are driving interest in quantitative methodologies. We are already seeing an increase in demand for quant work across the spectrum of asset managers in 2017. Even traditional discretionary hedge funds are augmenting their work with quant processes. However, there is always the risk of just jumping on the bandwagon and suffering from inaccurate implementation and misleading back-testing. It is easy to engineer an upward chart with some back-tests. It is much harder to deploy a robust and relevant quant strategy into a trading production environment.
Cognitive CloudWe like the term “Cognitive Cloud”, which is essentially the pulling together of all of the above into a collection of platforms and services which are augmented by artificial intelligence. Artificial intelligence and machine learning are transforming the way some asset managers approach trading. These systems can analyse large amounts of data at speed and improve themselves through such analysis.
Date(s) - 01/01/1970
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