Talking Numbers: Technical Versus Fundamental Recommendations
H/T George Pearkes
The Hebrew University of Jerusalem
Apollo Global is no longer the “king of distress”: Josh Harris
Bar-Ilan University, Israel
The Hebrew University of Jerusalem
This version: August 20, 2015
This study assesses the economic value of technical and fundamental recommendations simultaneously featured on “Talking Numbers,” a CNBC and Yahoo joint broadcast. Technicians display stock-picking skills, while fundamentalists reveal no value. In particular, technicians overwhelmingly outperform fundamentalists in predicting returns over horizons of three to nine months and moreover they produce large alpha with respect to the Fama and French (1993) and momentum benchmarks. Considering market indexes, Treasuries, commodities, and various equity indexes, both schools of recommendation generate poor forecasts. Overall, the evidence shows that proprietary trading rules could, at best, enhance investments in single stocks, while returns on broader assets are unpredictable.
Talking Numbers: Technical Versus Fundamental Recommendations – Introduction
This paper employs a novel dataset from “Talking Numbers” to assess the economic value of technical and fundamental recommendations covering a comprehensive list of assets. Hosted by CNBC and Yahoo Finance, “Talking Numbers” is a media broadcast simultaneously featuring fundamental and technical recommendations before and during the market open. Dual recommendations are made by highly experienced analysts representing prominent institutions. This unique setup featuring synchronized recommendations, multiple assets, and the presence of leading professionals, offers important insights in assessing the value of financial analysis.
For one, we establish a natural experiment to contrast technical and fundamental analyses and gauge the real time value of dual recommendations. Our experiments are robust to several biases characterizing analysts’ forecasts. To wit, as the bar to participate in the show is high, analysts are less prone to career concerns, and, moreover, the simultaneous broadcast eliminates potential cross-herding between analysts. Next, analysts’ recommendations span individual stocks and broader assets, including Treasuries, commodities, domestic and foreign market indexes, and various equity indexes. During the broadcast, both schools of thought are essentially exposed to the same public information. Thus, comparing performance enables one to assess the extent to which technicians and fundamentalists efficiently process the flow of public information.
Our analysis is reasonably robust to data mining concerns. Indeed, to our knowledge, we are the first to visit the fundamental and technical recommendations broadcasted in “Talking Numbers,” and moreover, we explicitly study technical recommendations rather than technical rules, which are at the core of the literature on technical analysis. Finally, analyst’ recommendations feature the largest stocks (e.g. Apple, Google, Exxon Mobil), liquid commodities (e.g. gold, oil), main exchange rates (e.g. the US dollar), major bonds (e.g. the U.S. ten-year notes), major indices (e.g. the various Dow Jones indexes), and prominent sectors (e.g., Technology, Real Estate, Pharmaceutical). In addition, our experiments are comprehensive employing 1000 dual recommendations on 262 stocks and 620 dual recommendations on the other assets. Thus, our findings are general enough and are less prone to liquidity concerns.
Figure 1 highlights the major empirical evidence for technical and fundamental stock recommendations during the sample period from November 2011 to December 2014. Plotted are the Cumulative Abnormal Returns (CARs) starting from the recommendation broadcast (Panels A and B) and the cumulative payoffs generated by four spread portfolios (Panel C) undertaking long (short) positions in stocks with buy (sell) recommendations. In particular, we consider buy-minus-sell and strong buy-minus-sell, both technical and fundamental, spread portfolios.
The evidence shows that technicians display rather impressive stock-picking skills, while fundamentalists provide no value, whatsoever. To illustrate, observe from Panel A that the ninemonth CARs of the strong sell, sell, hold, buy, and strong buy technical recommendations are ?8.85%, ?2.74%, ?0.02%, 1.74%, and 7.92%, respectively. In contrast, Panel B shows that CARs attributable to fundamental analysis do not align with the type of recommendation. If anything, sell recommendations generate higher CAR than the buy recommendations.
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