The Challenge

Whether trading Cash or Derivatives products in Equities, Fixed Income, FX or Commodities, trading desks today are increasingly - if not overwhelmingly - data driven environments. Interpreting the large and expanding volumes of transactional and pricing data available in the post-MiFID environment is now a critical capability. Quantitative models and techniques are fundamental - not just for developing and running trading algorithms, but also for creating the insights that drive broader sales and trading strategies.

Quantitative Analysts use a variety of tools and techniques to turn large data sets into actionable intelligence. Transactional and pricing data from within the firm is combined with market data from a variety of external sources and analysed using complex and constantly evolving techniques. As a result, Quant teams are among a firm’s most challenging and demanding users of technology and are often the trailblazers who stretch the boundaries of the tools and infrastructure available to them.

A common challenge for Investment banks is that traditional legacy environments remain inflexible. As a result, it is often too slow or too expensive to justify creating new environments, incorporating large new data sets, deploying new tools or accessing temporary burst processing power simply to prove - or disprove - a new premise or test innovative new models. This in turn stifles innovation, creativity and business opportunity.

The Solution

The Google Cloud Platform (GCP) is a highly secure environment unhindered by the traditional confines of legacy infrastructure, storage and computing power. As an established provider of advice, consultancy and Cloud solutions to Investment banks, Appsbroker is uniquely positioned to make Google’s Cloud an accessible and productive environment for Quant Development and Analysis.

GCP has practically unlimited flexibility and scalability, so new environments can be spun up on-demand with no requirement for dedicated and under-utilised technology infrastructure. Within the GCP environment, familiar development tools and techniques are all utilised and vastly extended by the power of Google’s advanced analytical tools; and can serve as the entry point into its class-leading Machine Learning and Artificial Intelligence technologies.

The Appsbroker Quant Laboratory harnesses the power of GCP, providing services, essential tools and standardised components together with provisioning and management services to quickly and effectively get you up and running in the cloud:

Customised connectivity and data pipelines to ingest and aggregate in-house and external data sources including prices, quotes, trades, reference data, news & research

GCP and scalable storage services including BigQuery and BigTable

Standardised Data models for aggregation of cross-asset quotes, transactions, time series and reference data sets

Standardised Time Series queries and analytics

Familiar development environments pre-configured with R / Python tooling

GCP Big Data Analytical and Machine Learning Tools
-  BigQuery, DataFlow, Cloud ML,

Presentation, Visualisation & BI tools
-  Google Data Studio, Periscope, Tableau, Qlikview

Straightforward provisioning and management of secure GCP environments

Audit trail and approval process around all provisioning requests

Budget and cost control for provisioned environments


 
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