But the study also found that institutional investors do not have such a steep learning curve, said researcher Yiming Qian, an associate professor of finance in the Tippie College of Business. In fact, she said institutional investors seem to have no learning curve at all.
“Individual investors who happen to gain a good return on their first purchase are more aggressive in subsequent purchases and their earnings decrease with each purchase,” she said. “But with institutional investors, their earnings do not decrease or increase with subsequent purchases.”
She said the trend with individuals is a result of what is called naïve reinforcement learning, where people who make money on their first trade believe their success was due to their own investment skill and not to outside forces. Confusing luck with ability and armed with a false sense of confidence, they continue buying stocks, only to see their returns dwindle with each purchase.
Qian and her co-researchers analyzed the purchases of more than 31,000 individual investors and more than 1,200 institutional investors who participated in IPO auctions on the Taiwan Stock Exchange between 1995 and 2000. Using trader ID numbers, they were able to track each traders’ purchases in the 84 auctions held during that time, and recorded the earnings for each investor on each transaction.
Overwhelmingly, she said, beginning traders performed worse with experience, earning lower profits or even showing losses with every trade. The study found that from the first IPO auction to the second IPO auction, the average percentage return decreased by 2.9 percent and the average dollar profits decreased by $6,480.
“Individuals became unduly optimistic after receiving good returns in early trading, mistakenly attributing it to their skill instead of to luck or some other part of the external environment,” said Qian. Finally, after 24 auctions, their earnings per trade stopped decreasing, and eventually started going back up again, suggesting they had finally caught on.
Of course, this is completely counter-intuitive to the belief that we get better at something with experience. But Qian said that because of naïve reinforcement learning, we often learn to fail (which also happens to be the title of her paper, “Learning to Fail”). The concept was established by psychology researchers and shows people often fail at something because they learned the wrong lessons from an earlier success. The study from Qian and her co-researchers is one of the first to apply the concept to investing.
In the Taiwan IPO auctions, Qian said learning the wrong lessons led to individual traders becoming more aggressive with each auction, bidding higher prices, and being less selective about the auctions in which they participated.
But she said the data showed the naïve learning effect does not seem to apply to institutional investors.
“Institutional investors do not exhibit any of the patterns for retail investors,” she said. “There’s no return deterioration and no decreased auction selection ability, nor do they bid more aggressively. However, they do not seem to improve either.”
Qian said her research team didn’t examine possible causes for this, but she speculates it might be because institutional traders have more financial and talent resources available for research.
Qian’s paper, “Learning to Fail? Evidence from Frequent IPO Investors,” will be published in a forthcoming issue of the journal Review of Financial Studies. Her co-authors are Yao-Min Chiang of the National Chengchi University in Taiwan; David Hershleifer of the University of California, Irvine; and Ann E. Sherman of DePaul University.
Yiming Qian, 319-335-0934, firstname.lastname@example.org; Tom Snee, 319-384-0010 (office), 319-541-8434 (cell), email@example.com
Yiming Qian | Newswise Science News
Study relating to materials testing Detecting damages in non-magnetic steel through magnetism
23.07.2018 | Technische Universität Kaiserslautern
Innovative genetic tests for children with developmental disorders and epilepsy
11.07.2018 | Christian-Albrechts-Universität zu Kiel
Scientists develop first tool to use machine learning methods to compute flow around interactively designable 3D objects. Tool will be presented at this year’s prestigious SIGGRAPH conference.
When engineers or designers want to test the aerodynamic properties of the newly designed shape of a car, airplane, or other object, they would normally model...
Researchers from TU Graz and their industry partners have unveiled a world first: the prototype of a robot-controlled, high-speed combined charging system (CCS) for electric vehicles that enables series charging of cars in various parking positions.
Global demand for electric vehicles is forecast to rise sharply: by 2025, the number of new vehicle registrations is expected to reach 25 million per year....
Proteins must be folded correctly to fulfill their molecular functions in cells. Molecular assistants called chaperones help proteins exploit their inbuilt folding potential and reach the correct three-dimensional structure. Researchers at the Max Planck Institute of Biochemistry (MPIB) have demonstrated that actin, the most abundant protein in higher developed cells, does not have the inbuilt potential to fold and instead requires special assistance to fold into its active state. The chaperone TRiC uses a previously undescribed mechanism to perform actin folding. The study was recently published in the journal Cell.
Actin is the most abundant protein in highly developed cells and has diverse functions in processes like cell stabilization, cell division and muscle...
Scientists have discovered that the electrical resistance of a copper-oxide compound depends on the magnetic field in a very unusual way -- a finding that could help direct the search for materials that can perfectly conduct electricity at room temperatur
What happens when really powerful magnets--capable of producing magnetic fields nearly two million times stronger than Earth's--are applied to materials that...
The quality of materials often depends on the manufacturing process. In casting and welding, for example, the rate at which melts solidify and the resulting microstructure of the alloy is important. With metallic foams as well, it depends on exactly how the foaming process takes place. To understand these processes fully requires fast sensing capability. The fastest 3D tomographic images to date have now been achieved at the BESSY II X-ray source operated by the Helmholtz-Zentrum Berlin.
Dr. Francisco Garcia-Moreno and his team have designed a turntable that rotates ultra-stably about its axis at a constant rotational speed. This really depends...
08.08.2018 | Event News
27.07.2018 | Event News
25.07.2018 | Event News
14.08.2018 | Information Technology
14.08.2018 | Life Sciences
14.08.2018 | Life Sciences