Not exact matches
Our confidence in
Euclidean's investment philosophy comes from using machine learning to study the history of public companies and their market
values.
Because of the relative attractiveness of our portfolio, as highlighted on the following page, and the context of how
value and growth investing cycles have worked over time, we expect to deliver attractive long - term results to
Euclidean's investors.
Now we bring our focus back to
Euclidean's approach to systematic
value investing, which was formed using machine learning.
For this reason, and in the context of how
value and growth investing cycles have worked over time, we expect to deliver attractive long - term results to
Euclidean's investors.
At
Euclidean, we have always referenced this data in context of the challenges that
value strategies face given that there have been (and will continue to be) high profile investments that turned out to be
value traps.
We greatly
value the privilege of managing a portion of your assets and want you to be an informed
Euclidean Investor.
Euclidean's systematic approach to
value investing is not influenced by these biases and avoids the
value - destroying mistakes that accompany them.
Time and again, it seems that this divergence between price and
value becomes wide enough for
Euclidean to invest with a reasonable margin of safety and, we believe, puts the probability of long - term success on our side.