05/06/2024
In previous years, Guerdon Associates has investigated how the risk profiles of ASX-listed entities relate to their executives’ remuneration. Two pertinent examples include a 2014 article that looked at how share price volatility related to vesting outcomes (see HERE), and a 2022 article that inquired into the relationship between the betas of ASX 100 constituents and their at-risk pay (see HERE).
Following on from these earlier articles, we examined how ASX 200 companies’ risk profiles – as measured by both beta and share price volatility – relate to the amount of incentive pay CEOs receive as equity. As a forerunner to this analysis, we will also shed light on the risk profiles and equity-based remuneration structures that are typical of ASX 200 companies.
For those that like to skip to the ending, we found that the riskiest companies do not pay CEOs with equity. This should not be a surprise. To attract and retain a CEO for a business with a highly uncertain future, payment in cash may be the only solution.
But that is not all. For those who would like to read the whole story, and get a kick out of the maths, read on.
Background
We use the following abbreviations:
- STI: Short-Term Incentive
- LTI: Long-Term Incentive
- LTE: Long-Term Equity
- TFR: Total Fixed Remuneration
- TR: Total Remuneration
STI and LTI plans are performance-contingent, whereas LTE plans only require continued service. The term “equity-based incentive” refers to the sum of equity-based STI, LTI, and LTE (while LTE does not factor in performance, it still “incentivises” executive retention). TFR refers to the sum of base salary, superannuation, and non-monetary benefits, while TR is the sum of TFR, STI, LTI, and LTE.
All equity-based remuneration is reported based on the maximum incentive opportunity at fair value (discounting for dividends forgone). The following terminology is used when analysing equity-based incentive structures:
- The equity portion of STI refers to maximum fair-value equity STI divided by maximum fair-value total STI;
- The equity portion of TR refers to maximum fair-value equity remuneration divided by maximum fair-value TR; and
- The equity “leverage” over TFR refers to maximum fair-value equity remuneration divided by fair-value TFR.
In this article, we solely consider remuneration plans for ASX 200 executive directors, focusing on CEOs. Only three companies in our remuneration data sample (n=144) had non-CEOs as the highest-ranking executive director with available remuneration data. For simplicity, we refer to the entire sample as “CEOs”.
For each constituent’s daily log-returns Ri and the daily log-returns of the ASX 200 index Rm (based on capitalisation-weighted share prices of the index), the beta is given by β = Covariance(Ri, Rm) / Variance(Rm). It measures the extent to which an individual stock varies in correspondence with the overall index.
Each constituent’s volatility is given by σi = √Variance(Ri), measuring their stock’s level of variability without reference to the market. Both betas and volatilities are calculated using all trading days over the 3-year period spanning from 1 July 2020 to 30 June 2023, and daily log-returns are based on close price. Volatilities are annualised.
When reporting statistical significance results, we follow the convention of a 5% significance level, meaning that we tolerate a risk of committing Type I errors (false positives) of up to 5%. We use the following significance codes for P-values:
0.05 ≤ P < 0.1 |
0.01 ≤ P < 0.05 |
0.001 ≤ P < 0.01 |
P < 0.001 |
. |
* |
** |
*** |
Exploratory Data Analysis
Only one company in the sample (n=197) had a negative beta (-0.054), indicating that this company had a very mild tendency to move against the index, rather than upward/downward together with the index. All other companies in the sample had a positive beta, meaning that they tended to move upward/downward with the index.
The summary statistics in Table 1 indicate that the overall distribution of betas is centred around one, with 50% of betas falling between 0.774 and 1.222, indicating that most stocks tend to move together with the index with a comparable level of volatility to the index. The nearly equidistant positioning of the quartiles, and the similarity of median and mean, suggest that the betas are symmetrically distributed.
Table 1: Summary statistics for 3-year beta and volatility of ASX 200 constituents
|
Minimum |
First Quartile |
Median |
Mean |
Third Quartile |
Maximum |
Beta |
-0.054 |
0.774 |
0.981 |
1.018 |
1.222 |
3.004 |
Volatility |
0.166 |
0.262 |
0.318 |
0.352 |
0.424 |
0.823 |
The average stock volatility of 35.2% is higher than the index volatility of 13.7%, which also happens to be lower than the minimum stock volatility of 16.6%. This indicates that the individual constituents’ share prices are more volatile than the capitalisation-weighted share price of the index.
This is to be expected, in part due to the variance-reducing effects of averaging, and since the constituents will often move in different directions, leading to lower index volatility by cancellation of upward and downward movements.
Using FY2023 executive director remuneration data for the ASX 200 constituents (n=144), we looked at how many of these companies delivered incentives (i.e., STI, LTI, and LTE) in equity. The remuneration data set consisted entirely of CEOs, except for two companies with an executive chair and one company with a CFO as the highest-ranking executive director with available data. We refer to the sample as “CEOs” for simplicity. We found that 136 company CEOs (94.4%) in the sample of 144 had equity-based incentives, leaving 8 companies that provide the CEO with no equity incentives.
We also looked at the distribution of companies providing the CEO with equity-based STI plans (e.g., deferred shares). Table 2 summarises the frequency of different CEO cash/equity splits for STI, with 0% equity and 50% equity being particularly common, at 30.6% and 29.9% of ASX 200 companies’ CEOs respectively. Only 2.8% of companies had a fully equity-based STI. Note that the ranges “0% to 50%” and “50% to 100%” are exclusive of the endpoints, making each category in the table non-overlapping.
Table 2: Proportion of CEO STI delivered as equity for ASX 200 constituents in FY2023
|
0% |
0% to 50% |
50% |
50% to 100% |
100% |
Count |
44 |
40 |
43 |
13 |
4 |
Percent |
30.6% |
27.8% |
29.9% |
9.0% |
2.8% |
Regression Analysis
We employed logistic regression (detailed in the Methodology section) to examine whether ASX 200 companies with CEO equity-based incentives had a different risk profile from those with cash-only incentives. This was done by regressing a binary response variable, representing the presence of equity in variable pay, against the beta and stock volatility of each company.
Note that logistic regressions do not provide an R-squared (R2) statistic to measure goodness-of-fit of the model, so we only report R-squared for linear regressions.
Both logistic regressions gave a significant result. The regression against beta (p=0.006) had a negative slope (-3.279), indicating that companies with lower beta were more likely to have equity-based incentives. The regression against volatility (p=0.0382) also had a negative slope (-5.276), giving a similar conclusion. Overall, these results suggest that higher-risk companies may be more averse to providing variable pay as equity relative to less risky companies.
Figures 1 and 2 illustrate the equity portion of total remuneration (i.e., Equity STI + Equity LTI + LTE all divided by TR) plotted against beta and stock volatility, respectively. These plots highlight how companies without equity-based pay (having zero for the equity portion) tend to have slightly higher risk, reinforcing the regression results. In addition, Figure 1 shows that all equity-free companies except for one had a beta higher than one, indicating above-market volatility.
Figure 1: Equity portion of CEO total remuneration against 3-year beta
Figure 2: Equity portion of CEO total remuneration against 3-year stock volatility
Figure 3 highlights that ASX 200 constituents’ CEOs with equity-based incentives had both lower beta and lower stock volatility on average, relative to constituents without equity incentives. Equity-free companies had an average beta of 1.329, while companies with equity incentives averaged 1.009. This further reinforces earlier conclusions regarding the association of risk with the presence of CEO equity remuneration, while highlighting that companies with equity incentives more closely follow market trends, with an average beta of approximately one.
Figure 3: Average 3-year beta and 3-year stock volatility for ASX 200 constituents’ CEOs with/without equity-based incentives
For the companies that had equity incentives, neither the equity portion of TR, nor the equity leverage over TFR, were found to be significantly related to 3-year beta or stock volatility. The P-value and R-squared of each associated linear regression is shown in Table 3. This implies that while the “presence” of equity in at-risk pay was found to be linked with both beta and stock volatility, the “amount” of equity had no strong association with either.
Table 3: P-value and multiple R-squared for each simple linear regression of CEO equity portion/leverage of TR/TFR against 3-year beta/volatility (only considering companies’ CEOs that had equity-based incentives in FY23)
|
3-year Beta |
3-year Stock Volatility |
Equity Portion of TR |
P=0.246 (R2=0.010) |
P=0.428 (R2=0.005) |
Equity Leverage over TFR |
P=0.413 (R2=0.005) |
P=0.514 (R2=0.003) |
To compare the risk profiles of different companies based on the level of equity-based STI, the risk measures (beta and volatility) were regressed against a categorical variable representing the level of STI provided in equity, based on the categories in Table 2, with “0%” equity treated as the baseline. The results for the beta regression are shown in Table 4, and those for the volatility regression are shown in Table 5.
Table 4: Coefficient estimates and P-values from multiple linear regression of 3-year beta against CEO STI equity level
|
Coefficient |
Standard Error |
P-Value |
Significance |
0% to 50% |
-0.156 |
0.062 |
0.013 |
* |
50% |
-0.159 |
0.061 |
0.010 |
** |
50% to 100% |
-0.091 |
0.090 |
0.311 |
– |
100% |
0.196 |
0.148 |
0.187 |
– |
The regression of beta against STI equity level was found to be collectively significant (p=0.013, R2=0.087), with only the equity levels “0% to 50%” (p=0.013) and “50%” (p=0.010) found to differ significantly from the baseline zero-equity case. The coefficients for these levels were -0.156 and -0.159, indicating that companies with over 0% but at most 50% of STI in equity had a lower beta relative to the equity-free companies. However, companies with more than half of STI given in equity did not differ significantly in beta from equity-free companies.
Table 5: Coefficient estimates and P-values from multiple linear regression of 3-year stock volatility against CEO STI equity level
|
Coefficient |
Standard Error |
P-Value |
Significance |
0% to 50% |
-0.086 |
0.022 |
0.0002 |
*** |
50% |
-0.100 |
0.022 |
8.96E-6 |
*** |
50% to 100% |
-0.067 |
0.032 |
0.039 |
* |
100% |
0.090 |
0.053 |
0.093 |
. |
The regression of stock volatility against STI equity level was also collectively significant (p<0.001, R2=0.194), with all three of the levels “0% to 50%” (p<0.001), “50%” (p<0.001), and “50% to 100%” (p=0.039) found to differ significantly from the baseline zero-equity case. However, companies with fully equity-based STI did not differ significantly in volatility from those with fully cash-based STI.
Figure 4 illustrates that, on average, the riskiest ASX 200 companies were those that either had fully equity-based STI or fully cash-based STI, with both brackets having above-market volatility as indicated by betas above one, and higher-than-average daily return volatilities (refer to Table 1). The other “mid-range” brackets had risk profiles more representative of the overall index, with average betas of approximately one.
Figure 4: Average 3-year beta and 3-year stock volatility for ASX 200 constituents’ CEOs with varying levels of STI delivered as equity
The equity-free companies form a subset of the companies with zero-equity STI, but the converse is not true (not all companies with zero-equity STI would be equity-free overall). The average beta for companies with cash-only STI is 1.121, which is lower than the average of 1.329 for equity-free companies overall. This indicates that many of the companies with cash-only STI provide equity-based LTI or LTE, likely to offset the lack of long-term focus in their STI plans.
Conclusion
Our findings for the ASX 200 over the three-year period spanning from 2020 to 2023 indicate that higher-risk companies, as measured by beta and stock volatility, tend to be more averse to CEO equity-based remuneration compared to less risky companies.
Companies that had CEO equity-based incentives followed the market more closely than those with CEO cash-only incentives.
The companies that deviated the most from the market were those without any equity pay, or those with 100% equity STI, with above-market volatility in both cases.
While the presence of equity in CEO incentive pay seemed to be associated with companies’ risk profiles, the amount provided in equity by those with equity-based plans was not found to be linked with company risk.
Methodology
The “ASX 200” refers to all 199 current constituents of the ASX 200 index, as last rebalanced in March 2024. Financial data over the 3-year period spanning from 1 July 2020 to 30 June 2023 is considered for only these companies, without any adjustments made to account for index rebalancing in prior quarterly periods.
After appropriate data cleaning, the sample consisted of 197 index constituents with available stock market data that were used to compute financial statistics (e.g., beta, volatility), and 144 constituents with remuneration plan data for FY2023.
Logistic regression involves regressing the “log-odds” of a binary response variable against a linear combination of independent variables, like in linear regression. For a binary response variable with “success” probability , the logistic regression model with one independent variable can be expressed as
log[(p/(1-p)] = β0 + β1x
where log is the natural logarithm. The ratio “p/(1-p)” of the success probability over the failure probability is called the “odds”.
The slope coefficient β1 has the interpretation that a unit increase in x is associated with an increase in the log-odds of success by β1, on average. In other words, for a unit increase in x, the odds of success will change by a multiplicative factor of exp(β1).
In our analysis, p would represent the proportion of companies with equity-based incentives, with the independent variable x being either the 3-year beta or the 3-year stock volatility.
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