Can analysts, experts and gurus really give you an investing/trading edge? Should you track the advice of as many as possible? Are there ways to tell good ones from bad ones? Recent research indicates that the average “expert” has little to offer individual investors/traders. Finding exceptional advisers is no easier than identifying outperforming stocks. Indiscriminately seeking the output of as many experts as possible is a waste of time. Learning what makes a good expert accurate is worthwhile.
November 13, 2019 - Animal Spirits, Investing Expertise
What are ways to mitigate biases that interfere with rational investment decision-making? In their September 2019 paper entitled “The Psychology of Financial Professionals and Their Clients”, Kent Baker, Greg Filbeck and Victor Ricciardi describe common psychological biases and suggest ways to overcome them. Based on their knowledge and experience, they conclude that: Keep Reading
November 12, 2019 - Investing Expertise
When media recommend stocks, should investors pay attention? To check, we look at performance of stock recommendations for 2019 from December 2018 articles in several publications. Specifically, we test:
For each source, we form equally weighted portfolios of recommended stocks at the close on 12/31/2018 and hold without rebalancing. For a broader perspective, we form an equally weighted portfolio of all recommended stocks (Overall). Because the sample period is very short, we focus on daily performance statistics, but also look at cumulative returns. We use SPDR S&P 500 (SPY) as a benchmark. Using daily dividend-adjusted prices of the 74 recommended stocks and SPY during 12/31/2018 through October 15, 2019, we find that: Keep Reading
October 16, 2019 - Big Ideas, Investing Expertise
Is there a way that asset managers can share knowledge/data across proprietary boundaries with many researchers to advance development of investment strategies? In their September 2019 paper entitled “Crowdsourced Investment Research through Tournaments”, Marcos Lopez de Prado and Frank Fabozzi describe highly structured tournaments as a crowdsourcing paradigm for investment research. In each such tournament, the organizer poses one investment challenge as a forecasting problem and provides abstracted and obfuscated data. Contestants pay an entry fee, develop models and provide forecasts, retaining model ownership by running calculations on their own hardware/software. Based on this hypothetical tournament setup and their experience, they conclude that:
August 22, 2019 - Investing Expertise
What should investors expect to see in a typical investment advisor’s model portfolio? In their July 2019 paper entitled “Factors and Advisors Portfolios”, Brian Lawler, Andrew Ang, Brett Mossman and Patrick Nolan examine patterns and factor exposures in detailed holdings for a large number of model portfolios from many types of investment advisors. When holdings are funds, they examine contents of the funds. They assess exposures to economic growth, real interest rates and inflation. Within equity holdings, they assess exposures to size, value, momentum, quality and volatility factors. Using holdings of 9,940 model portfolios provided by investment advisors during October 2017 through September 2018, they find that: Keep Reading
August 1, 2019 - Investing Expertise
Would retail investors improve portfolio performance by using robo-advisors to manage holdings they have selected? In their July 2019 paper entitled “Artificial Intelligence Alter Egos:Who benefits from Robo-investing?”, Catherine D’Hondt, Rudy De Winne, Eric Ghysels and Steve Raymond compare performances of portfolios held by each of a large sample of actual individual investors to that of a robo-investor constrained to the stocks and exchange-traded funds (ETF) held by that investor over a rolling 2-year historical window. They consider three robo-investor strategies:
Robo-investors may hold cash, but they may not sell short, with focus on quarterly portfolio rebalancing. They measure portfolio performance monthly and exclude trading frictions. Using common stock/exchange-traded fund (ETF) trading records for 20,622 individual Belgian brokerage accounts during January 2003 through March 2012, they find that:
July 29, 2019 - Investing Expertise
Do short-term trade ideas of professional stock analysts have merit? In their July 2019 paper entitled “Are Analyst Trade Ideas Valuable?”, Justin Birru, Sinan Gokkaya, Xi Liu and René Stulz examine the price impact of analyst trade ideas, which differ from stock ratings in that trade ideas:
They estimate abnormal returns of trade ideas based on an equally weighted portfolios of stocks with similar size, book-to-market ratio and momentum characteristics. For trade idea buy and sell portfolios, they add a new stock at the close on the trading day after idea announcement and rebalance the portfolio on any day a stock is added or removed. Using a manually constructed sample of 4,167 buy ideas and 367 sell ideas from 688 analysts at 77 brokers involving 1,619 unique stocks during 2000 through 2015, they find that: Keep Reading
May 16, 2019 - Bonds, Investing Expertise
Did Bill Gross, the Bond King, generate significantly positive alpha during his May 1987 through September 2014 tenure as manager of PIMCO Total Return Fund (Fund)? In their March 2019 paper entitled “Bill Gross’ Alpha: The King Versus the Oracle”, Richard Dewey and Aaron Brown investigate whether Bill Gross generates excess average return after adjusting for market exposures over this tenure. They further compare evaluation of bond market alpha for Bill Gross to evaluation of equity market alpha for Warren Buffett. Following the explanation given by Bill Gross for his outperformance, their factor model of Fund returns includes three long-only market factors: interest rate (Merrill Lynch 10-year Treasury Index), credit (Barclays U.S. Credit Index) and mortgage (Barclays U.S. MBS Index). It also includes a fourth factor that is long U.S. Treasury 5-year notes and short U.S. Treasury 30-year bonds, with weights set to eliminate coupon and roll-down effects of their different durations. Using monthly returns for the Fund and the four model factors, and monthly 1-month U.S. Treasury bill yield as the risk-free rate during June 1987 (first full month of the Fund) through September 2014 (when Gross left the Fund), they find that: Keep Reading
April 17, 2019 - Aesthetic Investments, Investing Expertise
Given the uniqueness of fine art objects and uncertainties in demand (at auctions), can investors in paintings get accurate estimates of market values of holdings and potential acquisitions? In their March 2019 paper entitled “Machines and Masterpieces: Predicting Prices in the Art Auction Market”, Mathieu Aubry, Roman Kräussl, Gustavo Manso and Christophe Spaenjers compares accuracies of value estimates for paintings based on: (1) a linear hedonic regression (factor model), (2) neural network software and (3) auction houses. For the first two, they employ 985,188 auctions of paintings during 2008–2014 for in-sample training and 104,404 auctions of paintings during the first half of 2015 for out-of-sample testing. Neural network software inputs include information about artists and paintings (year of creation, materials, size, title and markings), and images of the paintings. Using information about artists/paintings and images and auction house estimates and sales prices for the specified 1,089,592 paintings by about 125,000 artists offered through 372 auction houses during January 2008 through June 2015, they find that:
April 10, 2019 - Big Ideas, Investing Expertise
What are common cautions regarding exploitation of academic and practitioner papers on financial markets? To investigate, we collect, collate and summarize our cautions on findings from papers reviewed over the past year. These papers are survivors of screening for relevance to investors of a much larger number of papers, mostly from the Financial Economics Network (FEN) Subject Matter eJournals and Journal of Economic Literature (JEL) Code G1 sections of the Social Sciences Research Network (SSRN). Based on review of cautions in 109 summaries of papers relevant to investors posted during mid-March 2018 through mid-March 2019, we conclude that: Keep Reading
April 9, 2019 - Big Ideas, Investing Expertise
Should investors trust academic equity factor research? In their February 2019 paper entitled “A Census of the Factor Zoo”, Campbell Harvey and Yan Liu announce a comprehensive database of hundreds of equity factors from top academic journals and working papers through January 2019, including a link to citation and download information. They distinguish among six types of common factors and five types of firm characteristic-based factors. They also explore incentives for factor discovery and reasons why many factors are lucky findings that exaggerate expectations and disappoint in live trading. Finally, they announce a project that allows researchers to add published and working papers to the database. Based on their census of published factors and analysis of implications, they conclude that: Keep Reading