Monthly Stock Returns: One Fat Tail and a Dash of Skewness?
Been thinking a lot about risk and return these days. Even started skimming through Fama's old book "Foundations of Finance." The book is available for free: [...]
Been thinking a lot about risk and return these days. Even started skimming through Fama's old book "Foundations of Finance." The book is available for free: [...]
Clinical intuition and test scores as a basis for diagnosis Klehr, R. Journal of Consulting Psychology, 13, 34-38 An online version of the paper can [...]
We know that valuation metrics such as the CAPE, or Shiller P/E, ratio are correlated with long-term returns (notice we didn't say "predict" long-term returns--that is [...]
Analyst Interest as an Early Indicator of Firm Fundamental Changes and Stock Returns Jung, Wong, Zhang A version of the paper can be found here. Want [...]
Sell Winners Too Early and Hold Losers Too Long Researchers have explored the "disposition effect" for years, which describes how investors are more likely to sell [...]
VIX is currently sitting at the lowest levels since all the way back to 2007, and market valuations are rich. The chart below highlights VIX [...]
We ran some numbers on the large liquid universe of stocks (>2B USD) traded in EAFE countries. In total there are 1086 names in the [...]
Are Mutual Funds Sitting Ducks? S. Shive and H. Yun A version of the paper can be found here. Want a summary of academic papers with [...]
The Cost of Capital for Alternative Investments J Jurek and E Stafford A version of the paper can be found here. Want a summary of academic [...]
Listening to a fascinating talk and associated slide deck on the 'future of technology and the world." h.t. R. Compton http://recode.net/2014/05/30/mary-meekers-annual-rapid-fire-internet-trends-talk-video/ If you are into [...]
We're often asked: Why does value investing work? You guys simply buy crappy high-risk companies. Of course you outperform. I typically agree with claims that [...]
Momentum Has Not Been 'Overgrazed': A Visual Overview in 10 Slides Claude B. Erb A version of the paper can be found here. Want a summary [...]
The (Questionable) Legality of High-Speed 'Pinging' and 'Front Running' in the Futures Markets Greg Scopino A version of the paper can be found here. Want a [...]
When Growth Beats Value: Removing Tail Risk From Global Equity Momentum Strategies Clare, Seaton, Smith, and Thomas A version of the paper can be found here. [...]
Industry Window Dressing Huaizhi Chen, Lauren Cohen, Dong Lou A version of the paper can be found here. Want a summary of academic papers with alpha? [...]
The Predictive Ability of P/E Ratio: Evidence from Australia and New Zealand Basu and O'Shea A version of the paper can be found here. Want a [...]
A recent blog post suggests that value investing in the tech sector is a waste of time. The article tells a compelling story and argues for 2 points: Successful tech stock investing is done when the stocks are dear, not when they are cheap. Tech companies should not get credit for huge piles of cash on their balance sheets. The author then makes the claim that you can't make big money in cheap tech stocks and buying cheap tech doesn't work. We thought the blog post was thought-provoking and it inspired us to conduct a quick empirical analysis to ascertain if there was any truth to the claims.
I've heard some crazy things over the years and I often wondered what percentage of investment managers and advisors have an element of "astrology" to their decision-making process. Nonetheless, I never actually thought someone would use "relationships(s) between astronomical phenomena and events in the human world" to make investment decisions.
Everyone makes mistakes. It’s part of what makes us human. Because humans understand their actions are sometimes flawed, it was perhaps inevitable that the field of psychology would develop a rich body of academic literature to analyze why it is that human beings often make poor decisions. Although insights from academia can be highly theoretical, our everyday life experiences corroborate many of these findings at a basic level: “I know I shouldn’t eat the McDonalds BigMac, but it tastes so good.” Because we recognize our frequent irrational urges, we often seek the judgment of experts, to avoid becoming our own worst enemy. We assume that experts, with years of experience in their particular fields, are better equipped and incentivized to make unbiased decisions. But is this assumption valid? A surprisingly robust, but neglected branch of academic literature, has studied, for more than 60 years, the assumption that experts make unbias decisions. The evidence tells a decidedly one-sided story: systematic decision-making, through the use of simple quantitative models with limited inputs, outperforms discretionary decisions made by experts. This essay summarizes research related to the “models versus experts” debate and highlights its application in the context of investment decision-making. Based on the evidence, investors should de-emphasize their reliance on discretionary experts, and should instead approach investment decisions with systematic models. To quote Paul Meehl, an eminent scholar in the field, “There is no controversy in social science that shows such a large body of qualitatively diverse studies coming out so uniformly in the same direction as this one [models outperform experts].”
Hot hand bias in rhesus monkeys Blanchard, Wilke, and Hayden A version of the paper can be found here. Want a summary of academic papers with [...]
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