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The index signals that the decline in home prices is in Notable Seasonality We've entered a traditionally difficult period of the year. US equities have had terrible seasonality during the second half of September. The mean result is even worse. Moreover, the losses were even more significant in the past couple of decades. The yield curve has been inverted, credit spreads widened, and the labor market cooled down.

Their lead time from cycle peak to the next recession has been historically a few months. However, the process has been ongoing already. Moreover, the leading indicators could be even late this time as GDP already contracted in the The Market Is The Economy! According to Lakshman Achuthan's data, there has always been a recession on the back of two quarters of negative growth in the past 75 years.

Moreover, our analysis reveals that every NBER recession in the US also triggered a double-digit decline during that same period. Third, most of the information in the markets is not quantifiable with the tools at our disposal. By restricting themselves to hard numbers, scientific investors sometimes miss what qualitative investors see clear as day. Franco Modigliani, of the Modigliani-Miller theorem, was puzzled that so many firms paid dividends.

Investors have known since the days of Ben Graham that dividends impose discipline on corporate managers, keeping them from doing too many stupid things. Soft qualities such as culture and incentives matter, even if you can't easily assign numbers to them or model them in a closed-form solution. There are good reasons be skeptical of the things that come out of finance researchers' mouths, but it's a big mistake to completely dismiss them.

I'd go as far as to say evidence-driven investing is the best approach for the majority of investors, because it's based on an efficient learning strategy. Many investors pick a terrible learning strategy: personal experience. Experience is unreliable; colored by emotions and the zeitgeist, it captures a period that's short by the standards of history. Investors traumatized by the Great Depression learned that stocks are dangerous and should be avoided; investors who rode the bull markets of the s and s learned that stocks are unstoppable engines of wealth.

Both learned the hard way that personal experience is a flawed teacher. A better strategy is to learn from history, so you don't repeat the mistakes past generations made. Scientific investing, at its best, is about engaging the data honestly, with the intention of learning something new, hopefully something discordant with previously held beliefs. Science as it's currently practiced has plenty of flaws, but it's still the most reliable method of acquiring the truth that I know of.

What are the fruits of science as it pertains to investing? There's a lot of nonsense, but also a great deal of sense: Factors are important, and most investors should focus on investing in them. Factor Investing Unless you like to open the occasional dusty academic tome, chances are you're not intimately familiar with factor investing. It's really not as esoteric as it sounds.

You've heard of style investing--small cap versus large cap, or value versus growth. If you've ever tilted to a particular style, you've engaged in factor investing. Style investing is a kind of factor investing, dealing with only two factors: size large-small and value value-growth. A working definition of a factor is an attribute of an asset that both explains and produces excess returns. Factor investing can be thought of as buying these return-generating attributes rather than buying asset classes or picking stocks.

None of this is new. The original factor theory, dating back to the s, is the capital asset pricing model, or CAPM, which predicts that the only determinant of an asset's expected return is how strongly its returns move or, in technical terms, covary with the market's. The strength of the relationship is summarized in a variable called beta. A beta of 1 indicates that for each percentage point the market moves, an asset's price moves in the same direction by a percentage point.

CAPM predicts asset returns are linearly related to market beta. However, since the s, academics have known that stock returns don't seem to be related to beta. This finding spurred many fruitless or convoluted attempts to explain how market efficiency could be squared with a world in which CAPM didn't work. More importantly, the relationships were smooth; the smaller or more value-laden the stock, the higher its return. Fama and French interpret the smoothness of the relationship as indicating the market is rationally "pricing" these attributes, which implies that size and value strategies enjoy higher expected returns for being riskier.

Further research has uncovered more stock factors, including momentum, quality, and low volatility, in nearly every equity market studied. They also display the same smooth relationship: The stronger the factor attribute, the higher the excess returns. The interpretation of these factors depends on whether you believe the market is efficient.

In an efficient market, they must be connected to risk. However, if the market is not perfectly rational, some may represent quantitative strategies that exploit mispricings to produce excess returns. I don't believe value, quality, momentum, and low-volatility strategies work because they are riskier.

The strategies were exploited by investors before academics triumphantly published them in journals as "discoveries. This does not mean that all factors earn profits by identifying mispricings. Some attributes, such as illiquidity, are associated with higher returns because they obviously represent risk. So factor investing encompasses two different approaches: Rational factor theory, which deals with the rewards that accrue to different types of risk and how the market prices them.

Factor investing in this context is about finding the optimal portfolio of factor risks. Factor investing as commonly understood by practitioners, which is the identification of simple quantitative strategies associated with excess returns. Though it's been around for decades, factor investing has only in the past decade gained adherents.