In our previous post we ran two investing strategies based on Apple’s last twelve months price-to-earnings multiple (LTM P/E). One strategy bought Apple’s stock when its multiple dropped below 10x and sold when it rose above 20x. The other bought the stock when the 22-day moving average of the multiple crossed above the current multiple and sold when the moving average crossed below. In both cases, annualized returns weren’t much different than the benchmark buy-and-hold, but volatility was, resulting in significantly better risk-adjusted returns.
In our last post on valuation, we looked at whether Apple’s historical mutiples could help predict future returns. The notion was that since historic price multiples (e.g., price-to-earnings) reflect the market’s value of the company, when the multiple is low, Apple’s stock is cheap, so buying it then should produce attractive returns. However, even though the relationship between multiples and returns was significant over different time horizons, its explanatory power was pretty low.
Stock analysts are usually separated into two philosophical camps: fundamental or technical. The fundamental analyst uses financial statements, economic forecasts, industry knowledge, and valuation to guide his or her investment process. The technical analyst uses prices, charts, and a whole host of “indicators”. In reality, few stock analysts are purely fundamental or technical, usually blending a combination of the tools based on temperament, experience, and past success. Nonetheless, at the end of the day, the fundamental analyst remains most concerned with valuation, while the technical focuses on price action.
Don’t hold your breath. We’re taking a break from our deep dive into diversification. We know how you couldn’t wait for the next installment. But we thought we should revisit our previous post on investing strategies to mix things up a bit. Recall we investigated whether employing a 200-day moving average tactical allocation would improve our risk-return proflie vs. simply holding a large cap index like the S&P500.
What we learned when we calculated rolling twenty-year cumulative returns was that the moving average strategy outperformed the S&P 500 76% of the time.
Yield curve predictions are hitting the headlines again here, here, and here, though they’re not quite front page. The alarm bells are ringing since the probability of a recession appears to have increased meaningfully in the past few months. We look at the data to try to infer whether a recession is around the corner.
So what is it that has ruffled everyone’s feathers? The NY Fed’s yield curve model estimates the probability of a recession in the next twelve months at an exceedingly precise 27.
A recession a year from now?
As we saw in the last post, when we run a model with a 6-month look forward, it does a fairly reasonable job in predicting a recession, assuming we use a threshold closer to recession base rate. In this post, we look at 12-month look forward and then use the best of the two look forward models to test it on out-of-sample data.
Where did we go wrong?
Not another model!
As we saw in the last post, one iteration of the yield curve – the spread between 10-year and 3-month Treasuries – doesn’t generate a great model of recession probabilities. Part of this is that recessions are not that common, so we’re trying to find the veritable needle. Another problem is picking the right threshold to say the model is prediciting a greater likelihood of the economy being recession.
All models are wrong
Build the model
In the last post, we discussed the yield curve, why investors focus on it, and looked at one measure of the curve – the spread between 10-year and 3-month Treasury yields. In this post, we build a model that tries to quantify the probability that the economy is in recession based on the 10-year/3-month spread.
All models are wrong
A first question to ask is what kind of model should we build?
Introduction
What is a yield curve? (Skip if you already know!)
Show me the data! (Start here if don’t want the background)
Investing pundits like to quote the yield curve as a nearly infallible indicator for the next recession. But what do the data say? And which yield curve should you use? In this multi-part series we try to answer these questions in as straightforward (though not necessarily simple) a manner as possible.