# data[].attributes.body
Here you can add your questions to the different sections and we'll collate responses and incorporate them into the 2 hour webinar, or follow up e-mail.

# data[].attributes.headline
Summer '19, Q1, both companies are Ltd, why 30% discount is applied. Also, why the redundancy is taken after the PE ratio applied. Thanks 

# data[].attributes.subject
Summer '19, Q1, both companies are Ltd, why 30% discount is applied. Also, why the redundancy is taken after the PE ratio applied. Thanks 

# data[].attributes.body
Should you pick questions to do first based on comfortability over a topic/marks or should you go a-e

# data[].attributes.body
can you explain please the difference gearing ratios and when to use which ones

# data[].attributes.headline
In the notes it is outlined high gearing=high risk and therefore investors expect higher returns for the same investment in comparison to a co. not as highly geared.

# data[].attributes.subject
In the notes it is outlined high gearing=high risk and therefore investors expect higher returns for the same investment in comparison to a co. not as highly geared.

# data[].attributes.body
Can you explain why this is? Is it because debt is cheaper, so when a return is achieved it would be cheaper than a return achieved and having equity as the return required to give back?

# data[].attributes.body
Is the only reason debt is cheaper than equity because interest is tax deductible?
and if a co. is to pay out dividends these wouldnt be tax deducitble.
But dividends dont have to be paid out and interest on debt is a fixed cost. So surely having to pay out something (tax deductible or not) is more expensive than not (dividends - assuming not preference shares backed i guess)

# data[].attributes.body
Can you please run through examples of this please to gain a better understanding

# data[].attributes.body
If rounding to '000, what decimal point should you use

# data[].attributes.body
can you go through the div discounted values per solution not sure how they are getting the disc value
disc value for 2019 per solutions seems to be disc only for 1 yr?

Can you also run through the earnings based approach and explain the formulae's further please

# data[].attributes.headline
Factors to consider when deciding which model to use when valuing a company

# data[].attributes.subject
Factors to consider when deciding which model to use when valuing a company

# data[].attributes.body
Can you go through the PAT per solution please

# data[].attributes.body
How much knowledge is required for expectations theory?