The Nexus of Forces in Action – Use-Case 21: Investments and Asset Management

 

Summary

The ability to analyze multiple channels (including various social media, trade feeds), requiring terabytes of data processing enabled by cloud, for making better investment decisions.

Primary Industry Sectors

Financial services

Business Value

Improving ROI – by making better investment decisions using complete, quality, and timely information made available. The ability to aggregate, analyze, and transform data has become key to institutional investors’ ability to compete. Better data accuracy and data integration are critical. Cost-effective large-scale data storage. Cost-effective data aggregation service. Rapid data analytic dashboard processing.

Key Business Functions

Investments opportunity research, managing investments, vehicle performance, risk

Primary Actors

Trade analyst (quant), asset portfolio manager

Secondary Actors

Financial data analyst

Machine Actors

Financial stock trading analytics, financial market social behavior analytics, real-time data aggregation and analysis, social networks, messaging, integration, financial modeling analysis, AI

Key Technologies

Social, big data, cloud

Main Scenarios

Key scenarios include qualitative and quantitative analysis, portfolio rebalancing, and managing risk. Many of the publicly traded companies and their leadership teams provide feeds (twitter feeds, blog posts, etc.), which many times provide indications about their performance and plans. Such inputs help investments personnel in making investments decisions.

Key Data

Master Data

Investments portfolio

Current Observations Data

Company stock price, trading volume, news feeds

Historical Data

Past stock performance, company history

Query Data

Data sought by asset portfolio managers and trade analysts to make investment decisions based on companies’ feeds

Action Taken Data

Investment decisions: buy/sell/hold

Real Business Examples

Statpro

Financial portfolio analytics dashboard from big data. Development of a data aggregator service in the financial service asset management industry. (See the Statpro website.)

Data Aggregation

Service to asset managers, brokers and bankers, custodians and administrators, hedge funds and multi-managers, pension funds and private wealth. (See Andrew Peddar’s article in Wall Street and Technology.)

Making Investment Decisions from Big Data

See Chris Flood’s article in the Financial Times on acute big data challenges facing asset managers.

Predicting Client Behavior

See Paul Garel-Jones’ article in Computer Weekly on how the financial services sector uses big data analytics to predict client behavior.

Additional Considerations

Existing Interoperability Standards

There are many data exchange standards in the asset management space; e.g., those of the Society for Worldwide Interbank Financial Telecommunication (SWIFT).

Investment Book of Records (IBOR) is a good-practice technique for data aggregation (see the Pentagon IBOR White Paper).

The Financial Information eXchange (FIX) protocol is an electronic communications protocol initiated in 1992 for international real-time exchange of information related to the securities transactions and markets. With trillions of dollars traded annually on the NASDAQ alone, financial service entities are investing heavily in optimizing electronic trading and employing DMA to increase their speed to financial markets. Managing the delivery of trading applications and keeping latency low increasingly requires an understanding of the FIX protocol.

Comments on Context

The use of non-financial trend data in the analysis service may include general market trends, social network behavior, and trends.

Preconditions

  • Access to financial funds data.
  • Quality of data is critical to the service performance.
  • Data aggregator services can accelerate the preparation of multiple data sources that need to operate typically in high-speed transactional environments.