Behavioural Bias Benefits : Beating Benchmarks By Bundling Bouncy Baskets

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)4885-4921
Journal / PublicationAccounting and Finance
Volume61
Issue number3
Online published9 Aug 2021
Publication statusPublished - Sep 2021

Abstract

We consider in detail an investment strategy, titled ‘the bounce basket’, designed for someone to express a bullish view on the market by allowing them to take long positions on securities that would benefit the most from a rally in the markets. We demonstrate the use of quantitative metrics and large amounts of historical data towards decision-making goals. This investment concept combines macroeconomic views with characteristics of individual securities to beat the market returns. The central idea of this theme is to identity securities from a regional perspective that are heavily shorted and yet are fundamentally sound with at least a minimum buy rating from a consensus of stock analysts covering the securities. We discuss the components of creating such a strategy including the mechanics of constructing the portfolio. Using simulations, in which securities lending data is modelled as geometric Brownian motions, we provide a few flavors of creating a ranking of securities to identity the ones that are heavily shorted. An investment strategy of this kind will be ideal in market scenarios when a downturn happens due to unexpected extreme events and the markets are anticipated to bounce back thereafter. This situation is especially applicable to incidents being observed, and relevant proceedings, during the Coronavirus pandemic in 2020–2021. This strategy is one particular way to overcome a potential behavioural bias related to investing, which we term the ‘rebound effect’.

Research Area(s)

  • Big Data, Investment Hypothesis, Market Rebound, Pandemic, Risk Management, Volatility

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).