Behavioural Models

Setting the Context: In a previous post, I had gone over the basics of different types of theories underlying Portfolio Management. Now, since these theories stem from the Traditional Finance perspective, I felt it was apropos to introduce a couple of theories which come under the realm of Behavioural Finance.

Right, so let’s jump into it!

(I) Behavioural Portfolio Theory

The Behavioural Portfolio Theory was developed by two guys named Shefrin and Statman in the year 2000. Since investors generally have varied goals, with each goal having it’s own levels of risk and return expectations, what this theory proposes is constructing different sub-portfolios for each of the client’s goals.

For instance, let’s say Layla has 3 goals: (a) To fund her college education after 3 years (b) To buy a house after 8 years and (c) To buy a beach side property after 10 years. Each of these goals will have different risk tolerances and return expectations. Let’s assume Layla absolutely needs 9% return on her investments in order to achieve her most pivotal aspirations. So, we invest part of her portfolio in low-risk assets to achieve this aspirational-level of return, post that the remainder of the portfolio is invested in higher-risk (higher return) assets.

In the BPT we basically construct a pyramid like structure, with different layers corresponding to different goals. The bottom of the pyramid is allotted to lower-risk, safer and more diversified assets in order to meet the most pivotal goals requiring an aspirational level of return with minimum risk. Whereas the more “yeah, good to have a beach house” kind of goals form the top layer of the pyramid and the allotted portfolios have greater risk exposure and more concentrated positions.

The BPT focuses on maximising wealth, with the main focus on meeting the aspirational-level of return with the lowest risk possible.

(II) Behavioural Asset Pricing

This theory is essentially the Capital Asset Pricing Model (CAPM) with an added premium called the “Sentiment Premium”. The way this component is calculated is, we analyse the different estimates put forward by analysts about a particular security or an asset, the greater the dispersion that exists amidst the analyst’s estimates, the higher the sentiment premium.

And that’s what the Behavioural Asset Pricing Theory is all about!

(III) Adaptive Markets Hypothesis

The Adaptive Market Hypothesis (AMH) was put forth by an MIT professor called Andrew Lo in 2004. It mainly emphasises on the fact that there is no single strategy that can work THE BEST in the investment environment. Rather strategies and decision making need to continually adapt, innovate and evolve in order to survive (see this as the application of Darwin’s proposition of “Survival of the Fittest” in the investment framework).

The main goal here, isn’t about maximising or optimising to get the best possible result, it’s more about adapting well enough to the environment, in order to survive. The main process behind AMH is listed below:

• Generally investors go through a trial and error period to find the strategies that work.
• Once these are found, more and more people start adopting them, until one day excess returns cannot be achieved via the once novel strategy. Because now, this information is out there, priced into the market.
• Then, we move back to step one and the cycle repeats.

Essentially, in order to survive in the world of active management, you need to continually adapt, change and innovate according to the market milieu.

To summarise AMH: Investors don’t go crazy trying to find the most optimal solution to meet their investment goals. Rather they go ahead with the best possible solution given the limitations (lack of perfect information, limited cognitive processing ability, biases, etc) to reach their mini-milestones, which in turn brings them closer to meeting their main goals.