Sentences with phrase «simple statistical model»

Butler Philbrick Gordillo and Associates» argue in Valuation Based Equity Market Forecasts — Q1 2013 Update that «there is substantial value in applying simple statistical models...

There's a growing body of research that suggests that simple statistical models outperform expert judgements even when the experts are provided with the output of the model.

In a recent study, Mathias Trachsel (Dept. of Biology, University of Bergen) and Atle Nesje (Dept. of Earth Science, University of Bergen and Uni Research Climate) used simple statistical models to assess and quantify the relative importance of summer temperature and winter precipitation for annual mass balances of eight Scandinavian glaciers.

These projections — available through 2008 at the Philadelphia Fed's Real Time Data Center — have generally been more accurate than forecasts from simple statistical models.

Butler Philbrick Gordillo and Associates» argue in Valuation Based Equity Market Forecasts — Q1 2013 Update that «there is substantial value in applying simple statistical models to discover average estimates of what the future may hold over meaningful investment horizons (10 + years), while acknowledging the wide range of possibilities that exist around these averages.»

As we know from Andrew McAfee's Harvard Business Review blog post, The Future of Decision Making: Less Intuition, More Evidence, and James Montier's 2006 research report, Painting By Numbers: An Ode To Quant, in context after context, simple statistical models outperform expert judgements.

Two years ago I developed a simple statistical model that tries to predict the outcome of general elections from local election results.

The graphic outlines, from left, interrelated variables in a simple statistical model, a neural network model with populations of neurons that capture the same structure, and a variant of the neural network collapsed into a more realistic overlapping configuration.

-LSB-...] capitalization - to - gross national product, and the equity q ratio, all three examined together in The Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models).

For more on market value - to - GNP see my earlier posts Warren Buffett Talks... Total Market Value - To - Gross National Product, Warren Buffett and John Hussman On The Stock Market, FRED on Buffett's favored market measure: Total Market Value - to - GNP, The Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models.

The relationship is much less predictive than the other models I've considered on Greenbackd over the last month or so (see, for example, the Shiller PE, Buffett's total market capitalization - to - gross national product, and the equity q ratio, all three examined together in The Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models).

See Warren Buffett and John Hussman On The Stock Market, FRED on Buffett's favored market measure: Total Market Value - to - GNP, The Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models)

Once you find a good ratio, you have to apply that to the stocks without a fear of failure although it may not seem very profitable, but you will find that it if you try to cherry pick those ideas, they underperform the screen and the reason for that is because the experts tend to underperform these simple statistical models and use their discretion to override these models too often.

The best explanation I have seen for wariness at various points in the market is Butler Philbrick Gordillo's in The Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models:

Super Crunchers is a more full version of James Montier's 2006 research report, Painting By Numbers: An Ode To Quant, providing several more anecdotes in support of Montier's thesis that simple statistical models outperform the best judgements of experts.

Further, decision makers who, when provided with the output of the simple statistical model, wave off the model's predictions tend to make poorer decisions than the model.

In such an instance, I'd be inclined to take a position because I favor the simple statistical model over qualitative factors and my own judgement.

In the figure below, Dr Gavin Schmidt, director of the NASA Goddard Institute for Space Studies, uses a simple statistical model to estimate what the global temperature record (black line) would be like in the absence of El Niño or La Niña influences (red line).

Groisman et al. (1999) developed a simple statistical model of the frequency of daily precipitation based on the gamma distribution.

Report co-author Robert Fildes, a forecast researcher, developing a simple statistical model that delivers better results when compared with previous climate forecasts, i.e. by adding certain data he has been able to match his figures more accurately with a historic forecast.

«If the climate model was as good as it is possible to be, my simple statistical model should not have added any value.

But new research indicates the physical reality may not bend so neatly to this simple statistical model.