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I believe there are many investors like me who love to invest in companies that pay dividends. Naturally, we hope that companies we invest in would have growing dividends. So, the question is**"How can we differentiate companies that will have growing dividends from others?"**

In an attempt to find an answer to this question, I will perform a series of analyses in this and upcoming articles.

Today, I will focus on two metrics that are commonly thought to be useful in forecasting if a company is capable of distributing the same or higher dividends in future. They are**Debt-to-equity Ratio** and
**Operating Cashflow** (referred to as DER and OC from hereon). In particular, I would like to see how DER and OC in year X influences the dividend per share (DPS) in year X+1.

**Debt-to-equity Ratio's influence in numbers**

Based on the data I have collected from the internet about companies listed in the Singapore stock exchange, P(positive DPS change) is 64.1%. That is, out of 1054 companies that are paying dividends in year X, and with DER information, 676 are paying dividends the same or higher in year X+1. This is the baseline. That is, without using companies' fundamental data, if we randomly pick, we have a 64.1% chance of picking a growing dividends company. The goal is to increase this probability.

Let's see if DER can help.

P(positive DPS change | increased DER) is 61.2%. That is, out of 503 companies that are paying dividends and has increased DER in year X, 308 are paying the same or higher dividends in year X+1.

P(positive DPS change | reduced DER) is 66.8%. That is, out of 551 companies that are paying dividends and has reduced DER in year X, 368 are paying the same or higher dividends in year X+1.

For those who are a fan of p-value statistics, the chi-square test p-value is 0.0603.

**Debt to Equity Ratio's influence in English**

Basically, it means that a company with a reduced DER this year will have a better chance of paying the same or higher dividends next year compared to a company with increased DER (66.8% vs 61.2%). However, this statement has a 6% chance of being false.

Next, let's look at OC.

**Operating Cashflow's influence in numbers**

P(positive DPS change) is 64.7%. That is, out of 1223 companies that are paying dividends in year X and has OC information, 791 are paying dividends the same or higher in year X+1. You might be wondering why the baseline is slightly different from DER. This is because I do not have the OC and/or DER figures for all companies.

P(positive DPS change | increased OC) is 68.9%. That is, out of 531 companies that are paying dividends, and increased OC in year X, 366 are paying the same or higher dividends in year X+1.

P(positive DPS change | reduced OC) is 61.4%. That is, out of 692 companies that are paying dividends, and reduced OC in year X, 425 are paying the same or higher dividends in year X+1.

The p-value of chi-square test statistics is 0.0065.

**Operating Cashflow's influence in English**

Basically, it means that a company with an increased OC this year will have a better chance of paying the same or higher dividends next year compared to a company with reduced OC (68.9% vs 61.4%). The chance of the previous statement being false is low (0.65%).

**Conclusion**

Essentially, the results suggest that OC change is a better metric than DER change in forecasting next year's dividends. In fact, with a p-value of 0.06 for DER change, we would normally conclude that "DER change is not useful in forecasting dividends for next year".

It would be interesting to look at how the combination of them would perform though.

**More**

Some readers might be wondering why I am using change instead of absolute value, especially for DER since it is a ratio and hence comparable across all companies. Well, actually I did, and I will be sharing the results in the next article because I did not want to crowd this article.

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By evankoh posted on 10 Feb 2016 - 3,284 views

I believe there are many investors like me who love to invest in companies that pay dividends. Naturally, we hope that companies we invest in would have growing dividends. So, the question is

In an attempt to find an answer to this question, I will perform a series of analyses in this and upcoming articles.

Today, I will focus on two metrics that are commonly thought to be useful in forecasting if a company is capable of distributing the same or higher dividends in future. They are

Based on the data I have collected from the internet about companies listed in the Singapore stock exchange, P(positive DPS change) is 64.1%. That is, out of 1054 companies that are paying dividends in year X, and with DER information, 676 are paying dividends the same or higher in year X+1. This is the baseline. That is, without using companies' fundamental data, if we randomly pick, we have a 64.1% chance of picking a growing dividends company. The goal is to increase this probability.

Let's see if DER can help.

P(positive DPS change | increased DER) is 61.2%. That is, out of 503 companies that are paying dividends and has increased DER in year X, 308 are paying the same or higher dividends in year X+1.

P(positive DPS change | reduced DER) is 66.8%. That is, out of 551 companies that are paying dividends and has reduced DER in year X, 368 are paying the same or higher dividends in year X+1.

For those who are a fan of p-value statistics, the chi-square test p-value is 0.0603.

Basically, it means that a company with a reduced DER this year will have a better chance of paying the same or higher dividends next year compared to a company with increased DER (66.8% vs 61.2%). However, this statement has a 6% chance of being false.

Next, let's look at OC.

P(positive DPS change) is 64.7%. That is, out of 1223 companies that are paying dividends in year X and has OC information, 791 are paying dividends the same or higher in year X+1. You might be wondering why the baseline is slightly different from DER. This is because I do not have the OC and/or DER figures for all companies.

P(positive DPS change | increased OC) is 68.9%. That is, out of 531 companies that are paying dividends, and increased OC in year X, 366 are paying the same or higher dividends in year X+1.

P(positive DPS change | reduced OC) is 61.4%. That is, out of 692 companies that are paying dividends, and reduced OC in year X, 425 are paying the same or higher dividends in year X+1.

The p-value of chi-square test statistics is 0.0065.

Basically, it means that a company with an increased OC this year will have a better chance of paying the same or higher dividends next year compared to a company with reduced OC (68.9% vs 61.4%). The chance of the previous statement being false is low (0.65%).

Essentially, the results suggest that OC change is a better metric than DER change in forecasting next year's dividends. In fact, with a p-value of 0.06 for DER change, we would normally conclude that "DER change is not useful in forecasting dividends for next year".

It would be interesting to look at how the combination of them would perform though.

Some readers might be wondering why I am using change instead of absolute value, especially for DER since it is a ratio and hence comparable across all companies. Well, actually I did, and I will be sharing the results in the next article because I did not want to crowd this article.

Like

0 likes

0 comments

Next Article > < Previous Article

Growing Dividends - Does Debt-to-equity ... The John Neff Screener

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Share Your Portfolio Selectively

Our portfolios are very personal and sensitive information. While many users have generously shared them publicly, many more are not comfortable with opening up their portfolio and share with just anyone who visits sgxcafe.com. This is totally understandable. Even I only share my portfolio partially (portfolio is displayed without exact values). Hence, I have recently added a followers/following mechanism ...

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Since the introduction of the new stock screener, I have received numerous requests to add more metrics and/or to add more ways to build the constraints so that different strategies can be easily implemented using the new screener. Hence the number of metrics have grown, from the initial 30 to the current 60+ different metrics covering both technicals and fundamentals. The number of ways to build the ...

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