Macroeconomic data is often noisy, contradictory and lagging. These limitations render the data difficult to integrate into a robust quantitative investment strategy that generates excess returns. This paper outlines a new approach to macro investing that removes these inherent limitations in...

Investors are periodically challenged with this question: with funds ready to invest, but faced with a market that is generally perceived to be expensive, is it better to wait for a market correction before investing? Many investors are certain that a correction must be around the corner, and...

Growth-Trend (GT) timing from Philosophical Economics is a brilliant timing strategy which only signals a bear market when both the trend in the unemployment (UE) rate and the SP500 index are bearish. As a result, it captures most market downturns while switching to cash in less than 15% of the...

What would you do if you were invited to play a game where you were given $25 and allowed to place bets for 30 minutes on a coin that you were told was biased to come up heads 60% of the time? This is exactly what we did, gathering 61 young, quantitatively trained men and women to play this...

The paper is focused on an ex-post investment performance analysis. Firstly, we create a suite of return, risk, return to risk and benchmark related measures with immediate real life applications in mind. We define and describe these measures and provide real data examples where appropriate....

The Finnish National Election Study of 2003 revealed that in Finland most voters do not identify with parties and are self-described as independents. In this article it is asserted that partisan attachments affect Finnish parties’ optimal positions despite the large amount of independents. To...

Recently, President Obama has proposed that the Department of Education start ranking colleges based on “value.” School rankings have, for some time, formed an important component of students’ decisions on which institutions to attend. However, as we illustrate in this paper, such rankings...

Volatility forecasts play a central role among equity risk measures. Besides traditional statistical models, modern forecasting techniques, based on machine learning, can readily be employed when treating volatility as a univariate, daily time-series. However, econometric studies have shown that...