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About 2017-06-13T03:14:44+00:00

OUR MISSION IS TO DEMOCRATIZE ACCESS TO ADVANCED INVESTMENT ANALYTICS

HedgeSPA provides a cloud-based core investment platform that protects institutional portfolios against severe portfolio drawdowns, makes asset allocations under reasonable market scenarios and helps select the most likely winning assets in recovering markets.

The Problem

Today, a professional asset manager wishing to access to an investment analytics platform will face many challenges, including exorbitant pricing, high implementation risk, dated technology, waiting overnight for time-sensitive analyses, and refusal by exclusive providers to sell to perceived threats in asset management.

Our Vision

The HedgeSPA Core Investment Platform is unique in the utilization of Artificial Intelligence and Big Data to simulate combinations on an immense volume of fundamental factors. We provide the capabilities of a core investment platform through an easy-to-deploy front-to-back Cloud Computing platform.

Our Mission

We democratize access to advanced investment analytics, by offering a cloud-based core investment platform for all professional asset managers to automate their process to “manufacture” investment products: from asset selection to portfolio rebalancing to decision/execution to reporting/delivery.

OUR GLOBAL OFFICES HAVE HELPED CUSTOMERS WORLDWIDE

SINGAPORE

HedgeSPA Pte. Ltd.

77 Ayer Rajah Crescent #03-36, Singapore 139954

+65 9183-1492

HONG KONG

HedgeSPA Limited

Mailbox #208, Level 5, Cyberport 3 (Core F), Hong Kong

+852 6143-3758

SAN FRANCISCO

Representative Office

164 South Park Street, San Francisco, California 94107, USA

+1 (415) 324-0908

MEET OUR MANAGEMENT

Dr. Bernard Lee
Dr. Bernard LeeFounder & CEO
Dr. Lee was a Managing Director at BlackRock in New York, where he won a prestigious industry award for his investment analytics implementation at BlackRock. Dr. Lee was also a finance professor in the US and Singapore, who has taught or guest-lectured at Columbia, NYU Courant, Stanford Business School and MIT-Tsinghua.
Dr. Kua Chin Hock
Dr. Kua Chin HockCo-Founder & CTO
Before joining HedgeSPA, Dr. Kua gained more than 4 years of experience as an Operations Manager in proprietary trading firms. He completed his doctorate and masters degrees in Mechanical Engineering from Nanyang Technological University under the Singapore-MIT Alliance programme in 2008.

WHAT DIFFERENTIATES US

  • Post-Crisis markets are known for tail risk behavior (i.e. once-in-a-decade crashes more frequent than predicted by the normal distribution) with ‘non-normal’ underlying key market factors.
  • Typical platforms use Monte Carlo simulations to capture the non-linearity of complex instruments that are no longer in vogue among buy-side investors after the Crisis.
  • Monte Carlo simulations rely on the Cholesky decomposition of variance-covariance matrix of key market factors; however, the resulting simulations produce normal markets because nonnormality is not captured by the inputs (i.e. the variance-covariance matrix).
  • The best ‘fat tail’ simulation technology available today can calibrate to a variance-gamma distribution with pre-defined uniform fat tail distributions, which is helpful to describe certain hightail-risk markets such as energy, but will not work well for post-Crisis markets where crashes are driven by ‘messy’, non-uniform fat-tail behavior.
  • Net Result: Other platforms may produce predictions ‘off’ by as much as an order of magnitude!
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TOP RATED ANALYTICS AND INSIGHTS:

Market Research Widely Covered by Financial Press including the BBC

Write-up on Greek Crisis Top-Ranked by Google among over

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results

HOW DO WE STACK UP IN THE PLAYING FIELD?

HedgeSPA

  • Native support for multi-asset, multi-frequency portfolios
  • Tail risk models supported by architecture
  • Factor-based asset selection driven by forward-looking scenarios
  • Ready-for-deployment tail risk scenarios
  • Virtualized deployment with flexible integration in stages
  • Algorithms with real-time performance and battle-tested parameters and heuristics
  • Software-as-a-Service advantage with much lower maintenance

Our Competitors

  • Make up or delete useful data to enforce uniform data frequency
  • At best retrofit tail risk model into legacy architectures
  • Asset selection driven by fundamental data and scenarios
  • Tail-risk scenarios only an ‘after-thought’?
  • On-site deployment only, hard to show benefits before massive integration
  • Overnight batch jobs, rigid parameters
  • Require high-maintenance support from headcount-heavy technology teams

HOW CAN WE HELP?

Harness the Power of Artificial Intelligence, Big Data and Cloud Computing to achieve Investment Outperformance!

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