Big Data & Capital Markets – You’ve Seen Nothing Yet

Amara’s Law states we overestimate a technology’s effect in the short-run and underestimate it in the long run.  This is happening with the proliferation of “big data” announcements in the capital markets space.  Big Data’s quasi-definition currently relates to identifying patterns in unstructured data.  The best example is that of Sentiment Analysis (twitter feeds, social media, etc..) being cited as a price movement indicator. This model of ‘big data’ is only a short-term arbitrage opportunity.

Sentiment Analysis is a small step in the right direction, but the big money to be made will come with the monitoring of embedded devices.  This concept is called the “Internet of Things” (or IoT).  Although I find it optimistic, some groups have predicted 30 billion devices will be monitored via the Internet in the next 7 years.  As the number of inter-connected devices continues to skyrocket,  the winners will be those that can quickly interpret the terabytes of unstructed data.

Why will this have a dramatic effect on capital markets?  Take the Sentiment Analysis example and apply this to a world of connected devices.  Let’s apply this to a market like gasoline futures.  Instead of waiting for the US Energy Department to release the weekly inventory report, unstructured pump-level data is now sent across the internet from 10,000 gas stations and 50 refineries.  The data is constantly collected and analyzed using deep visualization techniques.  A data analyst and modeler look at real-time consumption trends for  arbitrage opportunities and create a algorithm to predict future-state consumption patterns.  This algorithm is now used utilized to trade futures and equities (oil refiners, agricultural producers, etc..) and fed into a larger algorithm for retail consumption.  Trading and investment now becomes a command and control activity of monitoring activity and adjusting algorithms for non-quantitative factors.

Unstructured data is a key predictor of future economic activity.  No longer will analysts need to rely on qualitative sentiment indicators like Manufacturing Purchasing Index and Consumer Confidence that claim to be forward indicator (but are really emotional glances at the rear-view mirror.) In an IoT world, analysts use aggregated data to identify real-world trends. ( Note:  Like discussions with with my local Costco manager who noted that in late 2007 consumers had moved heavily into buying basis foodstuffs [eggs, fruit] and away from higher-end items such as furniture and electronics).

Big Data may also create mini-futures and micro-exchanges via commoditization of goods and services.  If you have the infrastructure to reliable monitor and predict supply and demand of goods and services, then providing a mini-contract helps eliminate risk.  Providing a method for hedge funds and/or traders to serve as risk brokers via buyers and sellers of a good or services helps overcome asymetric information.  Previously, only inside buyers and sellers in a market had this information.  Unstructured data would allow other risk takers to enter a market and help in price discovery and long term market stability.

Like the title mentions,  we have seen very little of the potential of Big Data analysis in the capital markets….but it is coming and sooner than you think.

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Kinetic Investment – Part 3 of III

Why Change? Why Now?

There are many reasons to lean into the Kinetic Investment Environment but the most compelling reason is differentiation.  This environment complements your most important resource, People, and challenges them to build a creative investment environment.  The Kinetic Environment also fits with more stringent operational and risk protocols via templates and heatmaps.

The Path To A Kinetic Environment – Leveraging Existing Infrastructure

While the quickest path to a Kinetic Environment is the replacement of existing tools and technologies, most firms are not in a position to decommission large swaths of investment technology.  The good news is that existing investments can be leveraged with modest outlays.  Most firms have a solid foundation in database and data warehouse technologies.  These can easily be integrated with advanced analytics and dashboard technology.

From 2013 onwards

In the age of information arbitrage, simplification is power.  This simplification is achieved visually.  The investment team evolves to include financial modeling, data, and content skills.  The end product is a cohesive rule-based investment architecture that is theme-dependent and managed by a highly motivated, interactive team.  It’s not the 1980’s anymore.  It’s time to align the investment environment with the needs of modern information arbitrage.  

Kinetic Investment – Part 2 of III

What is the Kinetic Investment Environment?

To understand the Kinetic Investment Environment, you have to view an investment environment in terms of the 4P’s. Let’s start out with the first P, Performance.  Performance in a kinetic environment is all about creating the biggest brain possible.  A multi-sensory interactive Trade Room serves as the eyes and executive center of an investment environment.   The room is one big tactile, visual display.  Wave your hand, point to a ticker, and point to the wall.  The latest economic news and tick data is posted to the trade wall.  The more brains the better as the Trade Room is designed to leverage a team’s collective brain power. 

The second P, Process, is all about the visual engineering of a repeatable and rigorous process.  Visual engineering uses advancements in data warehouses, analytic engines, and visual dashboards.  Need to understand risk in a portfolio….pull up a color-coded heatmap showing Component VaR.  Want to understand how a change in interest rates affects dollar duration?  Pull up a 3-D visual model of simulated yield curve.  If a portfolio position starts to blink red, drill-down into details about correlation.

Changes are not just about the power of visual dashboards.  It’s about using tools in a consistent manner.  Templates are mandatory during the evaluation of a new investment and serve as the basis for ongoing portfolio management.  Because the templates are objects, underlying data, algorithm code, and analytics are stored together in a trade data warehouse.  Meta-data is also maintained and searchable so that trade objects can be referenced, duplicated, and stress-tested.

The third and most important P is for People.  People generate, evaluate, synthesize, and curate investment ideas.  The old school need for only PMs and Investment Analysts on a team is dead.  In a kinetic environment, financial analysis is complemented by pattern analysis across massive data streams and combined into visual analytics.  This new investment team includes skills in data analysis, modeling, simulation, and content presentation.  Risk and compliance are incorporated as front-end activity via visual dashboards.

The last P of the Kinetic Environment is Philosophy.  Although complex technologies are used, the philosophy is simple.  It’s about telling a good story.   The people and technology translate collective data points into a cohesive visual story.  The story can be recited from analyst to CIO and from investment committee to investor.

 

 

Kinetic Investment – Part I of III

From 1980 To Today

 1980 was a year of momentous changes for Wall Street investment firms and trading desks.  A spreadsheet app named Visicalc was creating “Screen Envy” across firms as early adopters created a buzz with the analytical prowess of personal computing.   The U.S. federal deficit was $900B.  Dallas was the top-rated television show.  The Star Wars sequel, The Empire Strikes Back, captured the minds and wallets of audiences worldwide.

 Fast forward thirty-three years.  The U.S. federal deficit is $17T.  Dallas’s next generation is back on TV and five additional Star Wars movies have been released.  So much has changed.  However, the basic look and feel of an investment environment remains as it did in the early 1980’s…..until today.

 We are now at flex point that can shape the 4P’s (performance, process, people, and philosophy) for the next generation of trading environments.  This intersection accounts for the evolution of computer technology, big data, the human-computing interface, and algorithmic trading.   I call this vision the Kinetic Investment Environment.

Private Fund – Go To Market Kit

In addition to a Pitch Book, every Private Fund should have these documents always updated and ready to go out in a Fedex and/or zip file:

1. Due Diligence Q&A Template
2. Attribution Analysis
3. Business Continuity Plan
4. Tearsheet (including drawdown/drawup analysis)
5. Private Placement Memorandum
6. Subscription Document
 
Optional:  Monthly/Quarterly market commentary and/or investor letters
 
If you have the net after-tax returns, any after-tax analysis is also extremely helpful.