What we’re reading (11/12)
“Why Buying The Biggest Stock-Market Losers Can Be A Winning strategy” (MarketWatch). “[I]t’s human nature to chase performance — favoring those stocks that are doing the best and avoiding those whose recent returns are at the bottom. But history teaches us that the contrarians are on to something. Consider a hypothetical portfolio that each month owned the 10% of stocks with the worst performance over the prior month. Since 1926, according to data compiled by Dartmouth’s Ken French, this portfolio produced an annualized gain of 13.2%. That’s 8.9 annualized percentage points better than a second portfolio that owned the decile of stocks with the prior month’s best returns. The source of this so-called short-term reversal effect, according to a consensus of researchers, is overreaction by investors: They exaggerate both the good news surrounding a stock that is performing well and the bad news about a stock that is losing. It therefore doesn’t take much for a stock that is losing to beat expectations and for a winning stock to fall short — thereby causing the prior loser to beat the prior winner.”
“FanDuel To Debut Prediction Market App To Fend Off Competitors” (Bloomberg). “FanDuel, the US online gambling division of Flutter Entertainment Plc, is launching its own prediction market product, which will allow it to open up in states where traditional sports betting is illegal and deal with competitive pressure from new startup exchanges in the space. The company plans to introduce a new mobile app in December, FanDuel Predicts, where users can bet on the outcome of sports and economic indicators, the company announced on Wednesday at the same time that it released quarterly financial results that fell short of analysts’ expectations.”
“Do Gamblers Invest Differently?” (Joachim Klement). “People who are at higher risk of problem gambling also tend to trade more in stock markets. So a propensity to gamble translates into investment behaviour. And we know that people who trade more tend to have worse returns due to transaction costs and other frictions that eat away at the returns. Hence, in real life, people who are naturally inclined to gamble should also have lower returns. Most people trade less in a low-volatility market, which means that as long as markets remain calm, their returns should be better. But for the most extreme gamblers, it doesn’t matter whether the market is low volatility or high volatility. They will always trade a lot. They truly are compulsive gamblers, no matter the environment they are in.”
“Streaming Prices Are Soaring—And Consumers Are Still Paying” (Wall Street Journal). “In recent weeks, the streaming platforms HBO Max, Hulu and Disney+ all hiked prices for at least some of their services. Netflix did so in January, Peacock unveiled increases in July, and Apple TV detailed its latest bump in August. Paramount said Monday it would raise the price of Paramount+ early next year…Despite the price hikes, households aren’t significantly recalibrating their subscription habits.”
“Artificial Intelligence, Competition, And Welfare” (Susan Athey and Fiona Scott Morton). “We study how market power in artificial intelligence (AI) shapes wages and welfare in open-economy general equilibrium by treating AI as a priced, imported factor…When AI reduces unit costs and increases variety, it will not pull U from non-tradables, instead it will displace workers from the AI-using sector and lower wage due to diminishing returns in alternative sectors. Strategic upstream pricing of AI then harms welfare through unit-cost (usage fees) and variety (access fees) channels, with income leakage abroad.”
