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Published byNorma Foss Modified over 2 years ago

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1. Expected sales/expenses These expectations are the same on each day of the year because we are dissecting annual sales/expenses into those expected at day 1 and unexpected 1. Expected sales/expenses These expectations are the same on each day of the year because we are dissecting annual sales/expenses into those expected at day 1 and unexpected 2. Unexpected sales/expenses (i.e., cash flow news about the current period sales and expenses) These change over the year because of the cumulative effect of news on each of the 252 days 2. Unexpected sales/expenses (i.e., cash flow news about the current period sales and expenses) These change over the year because of the cumulative effect of news on each of the 252 days B. Discount rate news (i.e., news that changes the expected rate of return) B. Discount rate news (i.e., news that changes the expected rate of return) C. Cash flow (i.e., sales and expense) news Unexpected return arriving on each day 1 to 252 A. Expected return at time 0 Does not map to either expected or unexpected sales/expenses. That is the independent variable contains more and more news (as t increases) which has little or nothing to do with sales/expenses of the current period Components of dependent variables 1&2 Components of independent variables A, B, &C Part of ERT NOT Part of ERT

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1. Expected sales/expenses These expectations are the same on each day of the year because we are dissecting annual sales/expenses into those expected at day 1 and unexpected 1. Expected sales/expenses These expectations are the same on each day of the year because we are dissecting annual sales/expenses into those expected at day 1 and unexpected 2. Unexpected sales/expenses (i.e., cash flow news about the current period sales and expenses) These change over the year because of the cumulative effect of news on each of the 252 days 2. Unexpected sales/expenses (i.e., cash flow news about the current period sales and expenses) These change over the year because of the cumulative effect of news on each of the 252 days B. Discount rate news (i.e., news that changes the expected rate of return) B. Discount rate news (i.e., news that changes the expected rate of return) C. Cash flow (i.e., sales and expense) news Unexpected return arriving on each day 1 to 252 A. Expected return at time 0 Does not map to either expected or unexpected sales/expenses. That is the independent variable contains more and more news (as t increases) which has little or nothing to do with sales/expenses of the current period Components of dependent variables 1&2 Components of independent variables A, B, &C Part of ERT NOT Part of ERT Sadka JAR shows that cash flow news is the predominant news component of returns

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Using the notation from the previous slide, I believe dependent variable/daily return coefficient on a given day, τ, can be dissected (by definition) as follows: In order to facilitate a tractable analysis, I will assume that a given day, τ, the expected return component and the unexpected (i.e., cash flow news plus discount rate news) are independent, such that:

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1. Expected sales/expenses These expectations are the same on each day of the year because we are dissecting annual sales/expenses into those expected at day 1 and unexpected 1. Expected sales/expenses These expectations are the same on each day of the year because we are dissecting annual sales/expenses into those expected at day 1 and unexpected B. Discount rate news (i.e., news that changes the expected rate of return) B. Discount rate news (i.e., news that changes the expected rate of return) C. Cash flow (i.e., sales and expense) news Unexpected return arriving on each day 1 to 252 A. Expected return at time 0 Does not map to either expected or unexpected sales/expenses. That is the independent variable contains more and more news (as t increases) which has little or nothing to do with sales/expenses of the current period Components of dependent variable 1 Components of independent variables A, B, &C Part of ERT NOT Part of ERT NO mapping to expected sales/expenses (1)The effect of news accumulates over time such that less and less of daily returns are related to the dependent variables. (2) Mapping declines over the year because more of daily returns are not related to expected sales/expenses. (3) Non-zero end of year coefficient reflects expectations that remain at the end of the year. (4) Daily returns contain little of expected returns when news is bad because expected returns must be positive. (1)The effect of news accumulates over time such that less and less of daily returns are related to the dependent variables. (2) Mapping declines over the year because more of daily returns are not related to expected sales/expenses. (3) Non-zero end of year coefficient reflects expectations that remain at the end of the year. (4) Daily returns contain little of expected returns when news is bad because expected returns must be positive. Sadka JAR shows that cash flow news is the predominant news component of returns Minor effect in our analyses

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Expected dependent variable/daily return coefficient:

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1. Expected sales/expenses These expectations are the same on each day of the year because we are dissecting annual sales/expenses into those expected at day 1 and unexpected 1. Expected sales/expenses These expectations are the same on each day of the year because we are dissecting annual sales/expenses into those expected at day 1 and unexpected B. Discount rate news (i.e., news that changes the expected rate of return) B. Discount rate news (i.e., news that changes the expected rate of return) C. Cash flow (i.e., sales and expense) news Unexpected return arriving on each day 1 to 252 A. Expected return at time 0 Does not map to either expected or unexpected sales/expenses. That is the independent variable contains more and more news (as t increases) which has little or nothing to do with sales/expenses of the current period Components of dependent variable 1 Components of independent variables A, B, &C Part of ERT NOT Part of ERT Now there is a mapping to expected sales/expenses Sadka JAR shows that cash flow news is the predominant news component of returns Minor effect in our analyses Conditional on sign of news Now we are have 2 expectations: (1) if news is turns out to be good and(2) if news turns out to be bad; the idea is along the lines that we expect to sell more ice cream if the summer is hot but we still expect to sell some ice cream if the summer is cool (different expectations according to different conditions).

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Expected dependent variable/daily return coefficient: Variance may also vary with sign (this is P&Ts point and we control for this???) Sadka JAR shows that cash flow news is the predominant component of returns

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Expected Sales revenue –Sales revenue of the current year less responsive to bad news than good news; we expect more beer will be drunk if the summer turns out to be hot than if the summer turns out to be cold Expected Current Sales element of expenses –Similar response for each sub-sample because matched expenses are very difficult to change in the short run; we still have to pay rent and up-keep on the pub Expected Expectations element of expenses –Much higher if the news is bad; e.g., expected write downs are much higher if news is bad….more likely to have to close the pub

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2. Unexpected sales/expenses (i.e., cash flow news about the current period sales and expenses) These change over the year because of the cumulative effect of news on each of the 252 days 2. Unexpected sales/expenses (i.e., cash flow news about the current period sales and expenses) These change over the year because of the cumulative effect of news on each of the 252 days B. Discount rate news (i.e., news that changes the expected rate of return) B. Discount rate news (i.e., news that changes the expected rate of return) C. Cash flow (i.e., sales and expense) news Unexpected return arriving on each day 1 to 252 Does not map to either expected or unexpected sales/expenses. That is the independent variable contains more and more news (as t increases) which has little or nothing to do with sales/expenses of the current period Components of dependent variable 2 Components of independent variables A, B, &C Part of ERT NOT Part of ERT Sadka JAR shows that cash flow news is the predominant news component of returns Minor effect in our analyses (1) Coefficient declines over time because the number of days within the year to which the news relates declines form 252 to 0. (2) Non-zero end of year coefficient reflects changes in expectations about sales and expenses in in future years. (1) Coefficient declines over time because the number of days within the year to which the news relates declines form 252 to 0. (2) Non-zero end of year coefficient reflects changes in expectations about sales and expenses in in future years.

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Unexpected dependent variable/daily return coefficient:

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Unexpected Sales revenue –No difference across samples Unexpected Current Sales element of expenses –No difference across samples Unexpected Expectations element of expenses –Much higher if the news is bad; e.g., expected write downs are much higher if news is bad

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