Customize Consent Preferences

We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.

The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... 

Always Active

Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.

No cookies to display.

Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.

No cookies to display.

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.

No cookies to display.

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

No cookies to display.

Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.

No cookies to display.

Long-Term Real Dynamic Investment Planning

By Russell J. Gerrard, Munir Hiabu, Jens Perch Nielsen & Peter Vodička

When long-term savers plan for retirement they need to know their investment prospects in terms of real income (Merton, 2014). While inflation has traditionally been considered as a complication in financial analysis and financial practise, we obtain enhanced predictability and model fit if the real returns are targeted in conjunction with earnings-by-price minus inflation as predictor. For this latter case, we propose an investment strategy of updating the simple classical Merton proportion as we go along. This simple strategy is very close to the complicated theoretically optimal solution but has comparably much lower parameter uncertainty.

Source @Papers