Modern Alternative Data for Today’s Investor

Modern Alternative Data for Today’s Investor

Alternative data is information gathered from non-traditional data sources that may offer hidden or additional market insights.

First, it is useful to quickly review what traditional data is. Traditional data, or economic statistics, quantitatively describes an economy or company in the past. Data is presented in a time series form and is collected from a sample universe or surveys. Examples of such are: the unemployment rate, consumer price index, and retail sales. Traditional data is usually produced by one or more statistical organizations, such as governmental (Bureau of Economic Analysis) or organizational (Purchasing managers index) and released to the public at pre-defined dates and times. Traditional data could also be in the form of financial statements and company reports.

Alternative data provides intelligence that is exclusive and generally offers real time measurements. It allows the user to make forecasts and determine risks that cannot be derived from traditional datasets. It tends to draw from obscure datasets that professionals in the finance and investment circles don’t immediately see as useful for their investment decisions. The use of alternative data has always been employed, to some degree, in the professional money management industry as managers are constantly in search of a competitive edge for excess returns. Peter Lynch, the legendary portfolio manager who managed Fidelity’s Magellan mutual fund in the 1980s, tied his investment philosophy to observing shoppers at the mall to see what they were buying. Portfolio managers always made it a point to interview a company’s suppliers to gain foresight into its prospects. Alternative data is not new, but today’s technology has transformed this area of analysis from one that was very labor intensive into data that is much easier to obtain.

Modern alternative data is the output that allows the user to tap into today’s data economy to gain powerful insights.

Examples of such insights are:

Consumer — Transactional data from credit card companies can be acquired and analyzed to produce shopping and spending patterns by region, type of good, and type of consumer.

Internet-Connected Technology — Internet-connected devices and sensors measure everything from the transportation of goods to vehicle and foot traffic.

Business to Business — As more companies put data at the heart of their decision process, they implicitly measure parts of the economy in real time.

Logistics – Telematics (think of how your cell phone’s gps communicates with navigation apps) and machine reading of shipping manifests are enabling real time insights on the movements of goods.

High Technology — The cyber economy is intermediated by thousands of technology companies. Each has insights on consumer behavior (Amazon?).

Construction — Satellite imagery provides aerial views of high construction areas. Permit or pre-permit data can signal industry growth (shrinkage).

Natural Resources — Satellites, UAVs (drones), radar and proprietary technologies enable faster, more detailed insights in the resource sectors.

Agriculture — Sensors in crops, fields, and equipment offer insights into the health of an agricultural region.

As the global economy becomes more and more digitalized, the mining of the signals buried in this data has revolutionized the use of alternative data and has elevated its importance for today’s investor.

Washington Trust Bank believes that the information used in this blog was obtained from reliable sources, but we do not guarantee its accuracy. Neither the information nor any opinions expressed constitutes a solicitation for business or a recommendation of the purchase or sale of securities or commodities.

About The Author

Brian is a Vice President and Senior Portfolio Manager who manages the fixed-income investment process for Wealth Management & Advisory Services clients by providing sophisticated investment counsel and portfolio risk control strategies. Brian is the bank’s primary fixed-income strategist and oversees the strategy, implementation and trading of all fixed-income securities for both private and institutional capital. Brian also holds a Chartered Financial Analyst designation. He has more than 20 years of portfolio management and institutional investment experience. Brian's significant expertise in fixed income is a key to our clients’ financial success, as he positions them to both safe and well positioned portfolios.