Q3 2019 AIAR Vol. 8 Issue 3

In this paper, the authors discuss some of the public misconceptions around artificial intelligence (A.I) and provide suggestions to investment practitioners for incorporating A.I. into their investment strategies. Topics include an introduction to and the basics of A.I., how A.I. impacts the manager selection process, and how investors can incorporate A.I. into their portfolios.
Outcome-orientation signals a major shift from the traditional strategic asset allocation approach to more flexible and diverse approaches tailored to meet investors’ needs. Often being asset class agnostic and riskdriven, alternative investments are naturally well suited to outcome-oriented investments. In this paper, the author identifies four types of outcomes and classifies various alternative strategies into these relevant types of outcomes. This paper also discusses risk management considerations
In this paper, the author analyzes how hedging longevity risk can impact a pension fund’s funding ratio volatility and asset-liability management strategy. The author introduces how they jointly model longevity and investment risks in a stochastic framework and formulates the ALM problem of a pension fund in the context of this framework. He then discusses the impact of hedging longevity risk on the pension fund’s funding level volatility and provides an outlook for future research.
The tokenization of real assets offers a next step in electronic trading. It expands the investible opportunity set by adding real assets – such as real estate or art – to a list of traded asset classes. However, before tokenization can be implemented, a few hurdles need to be cleared, such as regulation, protection of ownership rights, and the taxation of tokens. The author specifically explores how tokenization and blockchain technology will create liquid markets in traditionally illiquid real assets, such as real estate and intangible assets. Additionally, the author explores the challenges to tokenization.
Due to its unique nature, unpredictable investment landscape and burdensome regulatory requirements, equity investment in the China A-share market has proven to be difficult to navigate. For quantitative investors who prefer to invest in a diversified, liquid investment strategy and need easy access to market data and information, building a strategy for China A-shares has been a formidable task. The authors of this paper seek to simplify this perception by displaying the relationship between publicly-available fundamental data and its impact on future returns.
As of June 2018, $1.9 trillion was invested in factor-based strategies – a figure expected to grow to $3.4 trillion in 2022. The authors explore the definition of a “factor”, how factor performance can differ depending on its underlying definition and practical application, and argue that a standard “off-the-shelf” factor portfolio may not necessarily provide the exposure expected by the investor
High-net-worth clients are increasingly looking to direct investments, a strategy gaining popularity with institutional investors. Direct investments appeal to wealthy individuals and family offices because they not only eliminate the management fees charged by investment firms, but also because the investments can align more closely with the values and mindset of the investor. In this paper, the author explores the trends in direct investing and the motivations for private wealth clients, as well as the performance of direct investments relative to public markets and private fund structures.