Finance
Deploy massive compute capabilities to enhance workflows and accelerate time to value
Beat the Market with Unlimited Compute
Emergent factors are beginning to have a huge impact on markets. While often financial analysis involves applying macroeconomic theories and models, studying emergence requires a bottom up approach, simulating the agents and their actions themselves. Reflecting this activity is computationally demanding and often unpredictable. Simulations have to be equipped to deal with entity complexity and dynamic shifting of data.
This agent-based simulation requires processing of huge amount of data. Hadean’s big data processing library, Mesh, is one such application that enables massively distributed computing to optimise big data workflows. It requires no specialist engineering or scaling expertise, putting the handling of big data into the hands of a single data scientist or engineer. It eliminates the need to build, manage and scale big data pipelines that are traditionally built on ecosystems such as Hadoop and Spark.
The Old Way
Traditional high performance computing relies on excessive amounts of middleware, resulting in complex development, expensive ops and high failure rates.
The Hadean Way
Hadean removes all bottlenecks during runtime and allows full-scalability of an infrastructure, eliminating the need for containerisation and middleware.
Benefits
Massive Power and Scale
By leveraging the Hadean Platform, Financial institutions can apply raw compute power to enhance workflows and accelerate time to value across their business
Overcome Technical Talent and Skills Gaps
Hadean eliminates the reliance on distributed systems expertise and DevOps tooling, acting as a force multiplier across engineering teams to build applications of unparalleled levels of performance, reliability and scale
Process Big Data Like Small Data
Mesh puts the handling of Big Data back into the hands of a single data scientist or engineer, similarly to how a “small data” problem is currently using tools like Python or SQL
Unbounded Financial Simulations
Aether Engine enables financial institutions to harness the power of massive scale simulations to model future market scenarios with unparalleled realism and inform risk management
Use Case
Monte Carlo Simulation
A financial services organisation wanted an alternative means to perform a risk analysis across a large portfolio. Mesh was used to run a Monte Carlo simulation to complete a VaR on a financial portfolio.
Related Posts
Scaling Monte Carlo Simulations On Apache Spark
At Hadean, we’re working to lower the barrier to distributed computing by making it simpler and more reliable.
A new Open Source C++ library for Spatial Simulations
The different approaches to representing arbitrary shapes, their impact on performance and why Aether Engine uses Morton regions.
Agent Based Simulation in Volatile Markets
Recent events surrounding GameStop have shown that traditional financial forecasting is ripe for disruption.
Achieve Greater Financial Insight with Hadean
