It’s not often I get the opportunity to write a book review for our fellow teammates and the best authors on our website — Elisabetta Basilico and Tommi Johnsen! If you haven’t read Elisabetta and Tommi’s mountain of blog posts on our site you’ve been hiding under a rock somewhere (or clearly not spending enough time on the Alpha Architect website). I believe that rigorous academic research is the foundation for understanding and implementing successful investing strategies. At the core, I firmly subscribe to the idea of turning academic insights into investment performance. But as many readers know, it is almost impossible to keep up do date on the latest peer-reviewed journal articles and working papers coming out of the financial economics research community, even with Tommi and Elisabetta’s weekly updates on our site. Elisabetta and Tommi solve this problem in their book: Smart(er) Investing: How Academic Insights Propel the Savvy Investor.
What did I like about the book?I like this book because it simplifies my life and helps me get up to speed on areas of the market that matter today and will likely matter in the future. Elisabetta and Tommi have identified a number of cutting-edge investment ideas in the following categories:
- Index Investing
- Factor Investing
- Multi-Asset Investing
- Tail Risk Hedging
- Responsible Investing
- Equity and Rewards Based Crowdfunding
- Big Data and Artificial Intelligence Based Investing
- Women in Finance
- In the Index Investing chapter, they review an article that challenges the anti-passive movement by discussing the research that documents the impact of index investing on active management: it makes it better! For example, active funds have a higher active share and lower shareholder costs in countries where indexers are relatively more prevalent and are less costly to boot.
- In the Multi-Asset Investing chapter, Elisabetta and Tommi review a compilation of more than twenty papers on various aspects of asset allocation including the definition of an asset class; common pitfalls of mean-variance models; a new measure of risk that will determine the probability of maximum drawdowns on a continuous basis; and approaches to rebalancing the multi-asset portfolio.
- In a world where alpha has proven to be scarce, investment professionals believe that AI-based investing will be the next wave of financial innovation. In the Big Data and AI chapter, we review the research on whether new and novel datasets and statistical techniques create value and add alpha. Specifically, we focus on sentiment related datasets covering news, social media, accounting textual information, and macro-economic text.
- What Constitutes Good Investment Research
- A Roadmap to Reading an Academic Article
- Women in Finance