Why are we giggling like a small child in a candy store? Because at least one of these groups is guaranteed to be embarrassingly wrong, and there’s a pretty good chance that both groups will end the year scrambling for excuses as to why their crystal ball was, well, cloudy.
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Valuation Based Equity Market Forecasts: Q2 2014
We endorse the decisive evidence that markets and economies are complex, dynamic systems which are not reducible to linear cause-effect analysis over short or intermediate time frames. However, the future is likely to rhyme with the past.
Keep ReadingValuation Based Equity Market Forecasts – Q2 2014
Any analysis that relies on the past to offer guidance about the future makes the strong assumption that the future will in fact resemble the past. We have no guarantee that this will be the case. Many optimistic analysts…
Keep ReadingArticle in Taxes & Wealth Management
The Miller Thompson / Reuters monthly Taxes and Wealth Management newsletter carried an article we authored on the relationship between portfolio volatility and retirement planning.
Keep ReadingWhy Skill Never Prevails in Your NCAA March Madness Office Pool
As quants and sports fans we often find ourselves analyzing statistics from the sports world. And seeing as college basketball dominates the sports landscape for the next few weeks, it’s no surprise we are inspired to write about the NCAA Men’s Basketball Tournament, aka March Madness.
Keep ReadingThe Black Box: Eyewitness Testimony and Investment Models
Multiple discovery suggests that the most valuable, achievable advances in a field are often being examined simultaneously – yet independently – by many people at the same time. It stands to reason that on these occasions, leaps in logic can often occur at the same time by independent parties.
Keep ReadingNFL Parity, Sample Size and Manager Selection
We’ve been discussing issues around statistical significance – most notably, what makes a tested model’s results significant and therefore likely to perform in a consistent fashion when implemented in real time. In our last article we discussed what constitutes robustness in the context of testing a trading model.
Keep ReadingFaber’s Ivy Portfolio: As Simple as Possible, But No Simpler
We’ve been discussing sources of performance decay, degrees of freedom, and the implied statistical significance of systematic trading strategies, so I was pleased when some recent articles triggered an idea for a related case study.
Keep ReadingTowards a Simpler Palate
The current article series deals with the concept of performance decay, which occurs when the performance of a systematic trading strategy is materially worse in application than it appeared during testing. We dealt with the concept of arbitrage in our last post, drawing a parallel with the phenomenon of ‘multiple discovery’ in science.
Keep ReadingSources of Performance Decay
Above all, the greatest fear in empirical finance is that the out of sample results for a strategy under investigation will be materially weaker than the results derived from testing. There is absolutely no doubt that a meaningful portion of observed out-of-sample performance decay is the result of arbitrage; that is, others discovering and concurrently exploiting the same anomaly.
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