Frequently Asked Questions

How does the Haugen Model Work?

Our expected return factor model interfaces (1) a comprehensive set of characteristics that profile each stock with (2) estimates of how these characteristics (factors) will “pay-off” in the next month. Using a proprietary statistical process, we simultaneously determine the pay-off history of each factor. The updated histories are used to make pay-off projections for the next month. Going into a month, given a stock’s current exposure and our pay-off projections, we calculate the component of return that is expected to come from each factor. Summing across all factors, we then compute each stock’s overall expected return.

Our profile includes factors or characteristics that relate to risk, liquidity, profitability, cheapness in price, technical history, plus analysts ratings and earnings estimates.

What Stock Universes does the Model Use?

Our total universe is over 7,500 stocks.  This consists of the largest – by market capitalization - 3,750 U.S and Canadian stocks, the largest 3,000 European stocks, and the largest 1,500 stocks in Japan .   In addition, we add any stocks in the region's major indices not already included by market cap. Finally, we add requested stocks from our clients.

How often are the Expected Returns generated?

For the United States , we run the model at the end of the month and on every Monday.  If any of these days are a holiday, the run is performed on the previous trading day.

For Europe and Japan , we perform two runs: one on the 5th and one on the 20th.  If either of these days is on a holiday, the run is done on the closest trading day instead.

Do you keep track of Corporate Actions such as mergers and acquisitions?

Absolutely.  Each day we check for acquisitions, mergers, delistings, ticker changes, name changes, and several other identifier changes.  You can be assured that the runs are done with only active companies, and that the files we send you will have the correct tickers / identifiers.

How do you handle new companies?

For all 71 factors to be "firing", we need to have at least 3 years of data.  But when a company such as Google becomes large enough that it needs to be added to the model, but is lacking 3 years of data, we mark the reports we send you to let you know that we have an expected return for the company, but it's not based on all 71 factors yet.

Who are Haugen’s Clients?

Our clients include institutional and individual money managers, banks, insurance companies, as well as pension and endowment funds. Our clients implement investment styles that include large-cap, mid-cap, small-cap, value, growth, core, hedge, market neutral, enhanced index, global and international stock portfolios.

We are currently working on services for individual investors.

How can clients use the Haugen Model?

We have three ways in which we work with clients.  With stage one service, you get all the alphas from a selected region ( U.S., Europe, and / or Japan ).  (See above for the schedule of runs).  After each run, we send files with expected returns, payoffs, exposures, and expected return for the benchmark.  With stage II service, you get the model and compiled code in-house.  That way if you prefer to have fresh alphas on another day of the week than Monday, you can run it in-house.  Additionally, you get a model based on a certain trading day window.  So instead of the end-of-month window that comes standard, you could also have a database based on 10^th to 10^th trading day windows.  This database is unique and distinct in that none of our other clients have your selected range.  This enables you to get distinct alphas that are different from, but just as powerful as, the end-of-month’s data.  Finally, with stage III service, you get everything in addition to the source code.  With it, you can make minor or major modifications to the model as you see fit.

What makes Haugen different from other quantitative services?

We provide the tools and experience that eventually take our clients to a position where they are an independent quantitative money manager, running their own unique, proprietary investment process. Rather than mass-produce a signal that is delivered to many portfolio managers, we work closely with our client base on research to improve their predictive power and methods to improve their operational efficiency.

 What evidence is there to support the results?

We have many reports that detail our performance, including a 40-year survey showing how the model would have done, as well as decile performance reports and cumulative return graphs.  In addition, we provide a file of our historical alphas online so that you may test and verify the power of our model.