I want to help people lead happier, smarter lives. I do this by understanding how our psychology interacts with design, especially when it comes to money, investing, spending and randomness. I enjoy programming (R) and performing research, though I’m not amazing at them. I’m interested in academic research if I can apply it to the real world.
Director of Investing & Behavior Finance, Betterment
I’m currently Director of Behavioral Finance and Investing at Betterment, where I integrate behavioral finance and passive investment management to help customers achieve their goals. Betterment is the most behaviorally informed investing platform available – everything from our interface to our portfolios are intelligently designed to make good behavior automatic, and bad behavior difficult. As a result, Betterment’s customers have the lowest behavior gap I know of – i.e. they don’t reduce their returns because of trading.
- Use behavioral finance to develop and improve our advice and investment process
- Provide educational resources on investing and optimal behavior
- Collaborate with leading researchers in behavioral finance and economics to learn what works for our clients, and validating our unique
- Communicate our investments views and strategies.
- Manage Betterment’s investment strategy, including quantitative asset allocation and individual client portfolio optimization.
Behavioral Finance Specialist, Barclays Wealth
I specialized in developing and implementing commercial applications of behavioral finance, decision making, and behavioral economics. This included an advice & suitability framework, a psychometric diagnostic tool, and associated IT build and training program for advisors.
MSc in Decision Science from the London School of Economics.
BA (Distinction) in Economics from Boston University
I research into what drives, and how to prevent harmful financial behavior. This includes how to increase savings behavior, reduce speculation and increase planning by them more affectively powerful.
The Meerkat Effect (link)
We find that investors increase their portfolio monitoring following both positive and daily negative market returns, behaving more like hyper-vigilant meerkats than head-in-the-sand ostriches. This pattern persists for logins not resulting in trades and weekend logins when markets are closed. Moreover, an investor personality trait–neuroticism – attenuates the pattern of portfolio monitoring suggesting that market–driven variation in portfolio monitoring is attributable to psychological factors.
Second order beliefs and the individual investor (link)
We show that investors’ second-order beliefs—their beliefs about the return expectations of other investors—influence investment decisions. Investors who believe others hold more optimistic stock market expectations allocate more of their own portfolio to stocks even after controlling for their own risk and return expectations. However, second-order beliefs are inaccurate and exhibit several well-known psychological biases. We observe both the tendency of investors to believe that their own opinion is relatively more common among the population (false consensus) and that others who hold divergent beliefs are considered to be biased (bias blind spot).
Comparisons of risk attitudes across individuals (link)
In comparing risk attitudes across individuals we usually aim to determine whether one can reliably measure a difference in risk attitudes between two individuals, the magnitude of that difference, and what factors should be controlled for to ensure comparisons are meaningful. These comparisons critically depend on the method of risk attitude measurement and elicitation used, and a clear understanding of what the modeled risk attitude represents. Individual risk attitudes are fragile and very specific to domain and framing effects, and thus comparisons should always be made within the same elicitation method.
I enjoy speaking to academic classes and industry conferences, and do it often. If you want to invite me, please use http://www.21.co/dpegan
I’ve spoken as a guest lecture at Columbia University, New York University, the London School of Economics, London Business School, University College of London, and the University of Pennsylvania.
I tend to speak about applying quantitative finance in the real world. I avoid theory as much as possible.
I’m sometimes asked to talk about FinTech, commercial applications of behavioral finance, and algorithmic advice. I even offer forecasts sometimes.