Correlation Analysis of Price/NAV of S-REITs to other factors

REITs have many unique values, from Financial Ratios to Debt values to Market Performance (such as Occupancy Rates etc). In this article, we will be using some statistical measurements to understand the correlation of several factors that a REIT would have, and the Price/Net Asset Value (NAV) of the S-REIT market.

Each of the following graphs shows the individual plot of each REIT, to create a graph that visualises the S-REIT market. Data used is collected and compiled from the StocksCafe REIT screener.

Note: The following analysis is based on observations. Correlation Causation, hence it is not a predictor of future stock movements. Read the Disclaimer for more details. You can also find out more about what the R-squared value means here.

Objective:

To understand the correlation of the other REIT factors to the Price/NAV value.
There are several values that show a correlation between the Price/NAV value of the REIT. Below are some examples:

Price/NAV vs Interest Coverage Ratio

Interest Coverage Ratio (ICR) is one of the financial ratios that displays a correlation with the Price/NAV value.

Graph of Price/NAV vs Interest Coverage Ratio, 28 Aug 2020

With a R-squared value of 0.5251, this displays a relatively strong correlation between the 2 values. Using the y=mx+c equation, the positive m value of 0.1114 means a positive correlation, that a higher Interest Coverage Ratio is correlated to a higher Price/NAV ratio.

This could possibly be explained that since a higher Interest Coverage Ratio means a healthier financial position.

Price/NAV vs Market Cap

Market cap is another one of the financial ratios that displays a correlation with the Price/NAV value.

Graph of Price/NAV vs Market Cap, 28 Aug 2020

With a R-squared value of 0.3488, this displays a reasonable correlation between the 2 values, albeit not as strong as Price/NAV vs Interest Coverage Ratio. Using the y=mx+c equation, the positive m value means a positive correlation, that a higher Market Cap is correlated to a higher Price/NAV ratio.

This could possibly be explained that since higher Market Capitalisation consistent increase in share value and dividend payments

Price/NAV vs Weighted Average Lease Expiry (WALE)

However not all factors are not correlated to the Price/NAV value of the REIT. For example, rental-related values such as WALE and Occupancy Rates do not show a correlation to the Price/NAV value. The following is the graph for Price/NAV to WALE:

Graph of Price/NAV vs Weighted Average Lease Expiry (WALE), 28 Aug 2020

With a very low R-squared value of 0.0651, it does not show a correlation between the 2 values, with values all over the place. Thus, it can be said that there does not seem to be any correlation between WALE and the Price/NAV value.

Price/NAV vs Occupancy Rate

The same can be said with Occupancy Rate, as seen with the graph below:

Graph of Price/NAV vs Occupancy (%), 28 Aug 2020

With a very low R-squared value of 0.06636, it does not show a correlation between the 2 values, with values all over the place. Thus, it can be said that there does not seem to be any correlation between the Occupancy Rate and the Price/NAV value.

The following table shows the Top 10 Singapore REITs with highest Interest Coverage Ratio. For data, please refer to Stocks Cafe REITs Screener.

Kenny Loh is a Senior Consultant and REITs Specialist of Singapore’s top Independent Financial Advisor. He helps clients construct diversified portfolios consisting of different asset classes from REITs, Equities, Bonds, ETFs, Unit Trusts, Private Equity, Alternative Investments and Fixed Maturity Funds to achieve an optimal risk adjusted return. Kenny is also a CERTIFIED FINANCIAL PLANNER, SGX Academy REIT Trainer, Certified IBF Trainer of Associate REIT Investment Advisor (ARIA) and also invited speaker of REITs Sympsosium and Invest Fair. You can join my Telegram channel #REITirement – SREIT Singapore REIT Market Update and Retirement related news. https://t.me/REITirement

This Post Has One Comment

  1. YC

    I think it’s good to put a disclaimer that this is a quick approach and with an assumption that the relationship between 2 variables are linear. R-Squared explains how well the data fits with the model (or line), i.e. coefficient of determination.

Leave a Reply