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How to estimate return of investment over all outcomes? [closed]
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First question here. Please let me know if I can add or edit the question.
Investing in new industries is often times speculation, a lottery. I am curious to know what the odds would look like.
I want to understand how the risk will impact the return of investment.
So far I have $$((1+i)/(1+s))^t * Y $$
Where
- ... $i$ is yearly growth of a new industry.
- ... $t$ is the investment period.
- ... $s$ is the opportunity cost.
- ... $Y$ is the probability of success (i.e, reaching said yearly growth).
The idea is that with assumed $s,t$, we have two variables, $i, Y$ left which we can plot in a two dimensional graph. Which would return something like
the following image, where results > 1 (new investment is good) is green and results < 1 is red (opportunity cost is higher).
I believe this states that an investment with 30% growth and 15% chance of success over ten years is equal to a 7% investment over ten years.
I suppose, what I am asking, is given $i,s,t$, how to estimate the return of investment over all outcomes? Could I, for example, take $$sum_Y=0^\100((1+i)/(1+s))^t * Y * p$$
I ran into the situation when I wrote a blog post about crypto investments, feel free to check it out here.
probability finance
asked Jul 18 at 17:01
camazing
62
closed as unclear what you're asking by lulu, Mostafa Ayaz, Trần Thúc Minh TrÃ, max_zorn, amWhy Jul 19 at 10:55
Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
add a comment |Â
up vote
1
down vote
favorite
First question here. Please let me know if I can add or edit the question.
Investing in new industries is often times speculation, a lottery. I am curious to know what the odds would look like.
I want to understand how the risk will impact the return of investment.
So far I have $$((1+i)/(1+s))^t * Y $$
Where
- ... $i$ is yearly growth of a new industry.
- ... $t$ is the investment period.
- ... $s$ is the opportunity cost.
- ... $Y$ is the probability of success (i.e, reaching said yearly growth).
The idea is that with assumed $s,t$, we have two variables, $i, Y$ left which we can plot in a two dimensional graph. Which would return something like
the following image, where results > 1 (new investment is good) is green and results < 1 is red (opportunity cost is higher).
I believe this states that an investment with 30% growth and 15% chance of success over ten years is equal to a 7% investment over ten years.
I suppose, what I am asking, is given $i,s,t$, how to estimate the return of investment over all outcomes? Could I, for example, take $$sum_Y=0^\100((1+i)/(1+s))^t * Y * p$$
I ran into the situation when I wrote a blog post about crypto investments, feel free to check it out here.
probability finance
asked Jul 18 at 17:01
camazing
62
closed as unclear what you're asking by lulu, Mostafa Ayaz, Trần Thúc Minh TrÃ, max_zorn, amWhy Jul 19 at 10:55
Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
Not clear what you are hoping for here. Is it your intent to calibrate the parameters of your model to actual market prices? If so, then (tautologically) the investment is simply fair. Alternatively, do you want to calibrate your model to some sort of preconceived notions you have about the market? If so, what are those notions? The main point being: you need to make some assumptions in order to build a model. The clearer you can be about those assumptions, the better your model will be.
– lulu
Jul 18 at 17:09
Can you clarify your question? As I said, absent some more information on what you are willing to assume about the industry (or specific companies) you have in mind, there's really nothing that can be said.
– lulu
Jul 18 at 17:22
Voting to close the question as it is unclear what you are asking. If you can, please edit your post for clarity.
– lulu
Jul 18 at 17:33
Welcome to MSE. The site seems to work better for precise questions with a clear answer but I can tell what ball park you're in and I've given you some pointers.
– Robert Frost
Jul 18 at 18:39
Thanks for responses! I tried to clarify the question to be more direct. Given comments this is where I am at. I can feel that my suggestion is incorrect and possibly impossible in a real world scenario. If the outcome was decided by a dice with uniform random distribution then it holds (I believe), but that I would need better assumptions about the probabilities of each success bracket.
– camazing
Jul 19 at 11:16
add a comment |Â
up vote
1
down vote
favorite
up vote
1
down vote
favorite
First question here. Please let me know if I can add or edit the question.
Investing in new industries is often times speculation, a lottery. I am curious to know what the odds would look like.
I want to understand how the risk will impact the return of investment.
So far I have $$((1+i)/(1+s))^t * Y $$
Where
- ... $i$ is yearly growth of a new industry.
- ... $t$ is the investment period.
- ... $s$ is the opportunity cost.
- ... $Y$ is the probability of success (i.e, reaching said yearly growth).
The idea is that with assumed $s,t$, we have two variables, $i, Y$ left which we can plot in a two dimensional graph. Which would return something like
the following image, where results > 1 (new investment is good) is green and results < 1 is red (opportunity cost is higher).
I believe this states that an investment with 30% growth and 15% chance of success over ten years is equal to a 7% investment over ten years.
I suppose, what I am asking, is given $i,s,t$, how to estimate the return of investment over all outcomes? Could I, for example, take $$sum_Y=0^\100((1+i)/(1+s))^t * Y * p$$
I ran into the situation when I wrote a blog post about crypto investments, feel free to check it out here.
probability finance
asked Jul 18 at 17:01
camazing
62
First question here. Please let me know if I can add or edit the question.
Investing in new industries is often times speculation, a lottery. I am curious to know what the odds would look like.
I want to understand how the risk will impact the return of investment.
So far I have $$((1+i)/(1+s))^t * Y $$
Where
- ... $i$ is yearly growth of a new industry.
- ... $t$ is the investment period.
- ... $s$ is the opportunity cost.
- ... $Y$ is the probability of success (i.e, reaching said yearly growth).
The idea is that with assumed $s,t$, we have two variables, $i, Y$ left which we can plot in a two dimensional graph. Which would return something like
the following image, where results > 1 (new investment is good) is green and results < 1 is red (opportunity cost is higher).
I believe this states that an investment with 30% growth and 15% chance of success over ten years is equal to a 7% investment over ten years.
I suppose, what I am asking, is given $i,s,t$, how to estimate the return of investment over all outcomes? Could I, for example, take $$sum_Y=0^\100((1+i)/(1+s))^t * Y * p$$
I ran into the situation when I wrote a blog post about crypto investments, feel free to check it out here.
probability finance
asked Jul 18 at 17:01
camazing
62
edited Jul 19 at 11:20
asked Jul 18 at 17:01
camazing
62
asked Jul 18 at 17:01
camazing
62
asked Jul 18 at 17:01
camazing
62
62
closed as unclear what you're asking by lulu, Mostafa Ayaz, Trần Thúc Minh TrÃ, max_zorn, amWhy Jul 19 at 10:55
Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
closed as unclear what you're asking by lulu, Mostafa Ayaz, Trần Thúc Minh TrÃ, max_zorn, amWhy Jul 19 at 10:55
Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
Not clear what you are hoping for here. Is it your intent to calibrate the parameters of your model to actual market prices? If so, then (tautologically) the investment is simply fair. Alternatively, do you want to calibrate your model to some sort of preconceived notions you have about the market? If so, what are those notions? The main point being: you need to make some assumptions in order to build a model. The clearer you can be about those assumptions, the better your model will be.
– lulu
Jul 18 at 17:09
Can you clarify your question? As I said, absent some more information on what you are willing to assume about the industry (or specific companies) you have in mind, there's really nothing that can be said.
– lulu
Jul 18 at 17:22
Voting to close the question as it is unclear what you are asking. If you can, please edit your post for clarity.
– lulu
Jul 18 at 17:33
Welcome to MSE. The site seems to work better for precise questions with a clear answer but I can tell what ball park you're in and I've given you some pointers.
– Robert Frost
Jul 18 at 18:39
Thanks for responses! I tried to clarify the question to be more direct. Given comments this is where I am at. I can feel that my suggestion is incorrect and possibly impossible in a real world scenario. If the outcome was decided by a dice with uniform random distribution then it holds (I believe), but that I would need better assumptions about the probabilities of each success bracket.
– camazing
Jul 19 at 11:16
add a comment |Â
Not clear what you are hoping for here. Is it your intent to calibrate the parameters of your model to actual market prices? If so, then (tautologically) the investment is simply fair. Alternatively, do you want to calibrate your model to some sort of preconceived notions you have about the market? If so, what are those notions? The main point being: you need to make some assumptions in order to build a model. The clearer you can be about those assumptions, the better your model will be.
– lulu
Jul 18 at 17:09
Can you clarify your question? As I said, absent some more information on what you are willing to assume about the industry (or specific companies) you have in mind, there's really nothing that can be said.
– lulu
Jul 18 at 17:22
Voting to close the question as it is unclear what you are asking. If you can, please edit your post for clarity.
– lulu
Jul 18 at 17:33
Welcome to MSE. The site seems to work better for precise questions with a clear answer but I can tell what ball park you're in and I've given you some pointers.
– Robert Frost
Jul 18 at 18:39
Thanks for responses! I tried to clarify the question to be more direct. Given comments this is where I am at. I can feel that my suggestion is incorrect and possibly impossible in a real world scenario. If the outcome was decided by a dice with uniform random distribution then it holds (I believe), but that I would need better assumptions about the probabilities of each success bracket.
– camazing
Jul 19 at 11:16
Not clear what you are hoping for here. Is it your intent to calibrate the parameters of your model to actual market prices? If so, then (tautologically) the investment is simply fair. Alternatively, do you want to calibrate your model to some sort of preconceived notions you have about the market? If so, what are those notions? The main point being: you need to make some assumptions in order to build a model. The clearer you can be about those assumptions, the better your model will be.
– lulu
Jul 18 at 17:09
Not clear what you are hoping for here. Is it your intent to calibrate the parameters of your model to actual market prices? If so, then (tautologically) the investment is simply fair. Alternatively, do you want to calibrate your model to some sort of preconceived notions you have about the market? If so, what are those notions? The main point being: you need to make some assumptions in order to build a model. The clearer you can be about those assumptions, the better your model will be.
– lulu
Jul 18 at 17:09
Can you clarify your question? As I said, absent some more information on what you are willing to assume about the industry (or specific companies) you have in mind, there's really nothing that can be said.
– lulu
Jul 18 at 17:22
Can you clarify your question? As I said, absent some more information on what you are willing to assume about the industry (or specific companies) you have in mind, there's really nothing that can be said.
– lulu
Jul 18 at 17:22
Voting to close the question as it is unclear what you are asking. If you can, please edit your post for clarity.
– lulu
Jul 18 at 17:33
Voting to close the question as it is unclear what you are asking. If you can, please edit your post for clarity.
– lulu
Jul 18 at 17:33
Welcome to MSE. The site seems to work better for precise questions with a clear answer but I can tell what ball park you're in and I've given you some pointers.
– Robert Frost
Jul 18 at 18:39
Welcome to MSE. The site seems to work better for precise questions with a clear answer but I can tell what ball park you're in and I've given you some pointers.
– Robert Frost
Jul 18 at 18:39
Thanks for responses! I tried to clarify the question to be more direct. Given comments this is where I am at. I can feel that my suggestion is incorrect and possibly impossible in a real world scenario. If the outcome was decided by a dice with uniform random distribution then it holds (I believe), but that I would need better assumptions about the probabilities of each success bracket.
– camazing
Jul 19 at 11:16
Thanks for responses! I tried to clarify the question to be more direct. Given comments this is where I am at. I can feel that my suggestion is incorrect and possibly impossible in a real world scenario. If the outcome was decided by a dice with uniform random distribution then it holds (I believe), but that I would need better assumptions about the probabilities of each success bracket.
– camazing
Jul 19 at 11:16
add a comment |Â
1 Answer
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One of the most basic ways of incorporating probability into a forecast is to use the concept of expected value. This is given by the probability of the outcome multiplied by the value of the outcome.
All of your probabilities must add up to $1$ to have a valid expected value.
So if you invest £$1,000$ in Trump Properties and it has the following outcomes with their associated probabilities:
25% of the time it will rise with the market at an average of 5% per annum
25% of the time it will underperform market growth and maintain its value
50% of the time it will lose 10% of its value per year
Note that $25%+25%+50%=1$ which means that these alternatives account for all possibilities.
Then your expected outcome in any given year is:
$£1,000times ((.25times1.05) + (.25times 1) + (.5times .9))=£962.50$
This is a loss of £$37.50$
In any given year you expect to have $96.25%$ of what you started with, a loss of $3.75%$. If you wanted to calculate the expected return over a period of years then you can raise this number to the power of the number of years. So over $5$ years, Trump properties would turn every £$1$ into $0.9625^5approxeq£0.826$ and your £$1000$ would be $approxeq $£$826$
A couple of principles:
- For growth of $x%$ over $n$ years, take $(1+x)^n-1$ (where $5%=0.05$)
- You should evaluate any investment against the opportunity cost of some alternative investment. e.g. if you just bought land it would be fairly safe to say its value would increase at $5%$ per annum long-term so anything less than that is a loss. Economically speaking, this is called the opportunity cost of investing in what you choose to invest in.
- Your future pounds will be worth less than today's pounds. If you wanted to discount for inflation of $x%$ perannum over $n$ years then by the same token take $(1+x)^n$ and divide your end-result by that number.
answered Jul 18 at 18:33
Robert Frost
3,8821036
1
Hi Robert. Thanks for your answer! I had combined your principles (2) and (3) into one statement, using growth of one asset class and discounting it back with opportunity cost. I changed the terms to better reflect that. I do not understand (1) however. I was under the understanding that you multiplied Investment with (1+x)^n. Could you please explain? Additionally, I believe I came to an answer with your pointer. I can use the above mentioned formula, without the sum part, and through separate analysis calculate the probability for each Y, bracket of success. Would this be correct?
– camazing
Jul 19 at 11:26
@camazing sorry I had transposed the difference which I've now fixed. I'm just saying if the final figure is $100% + g%$ of the starting amount then subtract 100% to see $g$
– Robert Frost
Jul 19 at 11:46
add a comment |Â
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
One of the most basic ways of incorporating probability into a forecast is to use the concept of expected value. This is given by the probability of the outcome multiplied by the value of the outcome.
All of your probabilities must add up to $1$ to have a valid expected value.
So if you invest £$1,000$ in Trump Properties and it has the following outcomes with their associated probabilities:
25% of the time it will rise with the market at an average of 5% per annum
25% of the time it will underperform market growth and maintain its value
50% of the time it will lose 10% of its value per year
Note that $25%+25%+50%=1$ which means that these alternatives account for all possibilities.
Then your expected outcome in any given year is:
$£1,000times ((.25times1.05) + (.25times 1) + (.5times .9))=£962.50$
This is a loss of £$37.50$
In any given year you expect to have $96.25%$ of what you started with, a loss of $3.75%$. If you wanted to calculate the expected return over a period of years then you can raise this number to the power of the number of years. So over $5$ years, Trump properties would turn every £$1$ into $0.9625^5approxeq£0.826$ and your £$1000$ would be $approxeq $£$826$
A couple of principles:
- For growth of $x%$ over $n$ years, take $(1+x)^n-1$ (where $5%=0.05$)
- You should evaluate any investment against the opportunity cost of some alternative investment. e.g. if you just bought land it would be fairly safe to say its value would increase at $5%$ per annum long-term so anything less than that is a loss. Economically speaking, this is called the opportunity cost of investing in what you choose to invest in.
- Your future pounds will be worth less than today's pounds. If you wanted to discount for inflation of $x%$ perannum over $n$ years then by the same token take $(1+x)^n$ and divide your end-result by that number.
answered Jul 18 at 18:33
Robert Frost
3,8821036
1
Hi Robert. Thanks for your answer! I had combined your principles (2) and (3) into one statement, using growth of one asset class and discounting it back with opportunity cost. I changed the terms to better reflect that. I do not understand (1) however. I was under the understanding that you multiplied Investment with (1+x)^n. Could you please explain? Additionally, I believe I came to an answer with your pointer. I can use the above mentioned formula, without the sum part, and through separate analysis calculate the probability for each Y, bracket of success. Would this be correct?
– camazing
Jul 19 at 11:26
@camazing sorry I had transposed the difference which I've now fixed. I'm just saying if the final figure is $100% + g%$ of the starting amount then subtract 100% to see $g$
– Robert Frost
Jul 19 at 11:46
add a comment |Â
up vote
0
down vote
One of the most basic ways of incorporating probability into a forecast is to use the concept of expected value. This is given by the probability of the outcome multiplied by the value of the outcome.
All of your probabilities must add up to $1$ to have a valid expected value.
So if you invest £$1,000$ in Trump Properties and it has the following outcomes with their associated probabilities:
25% of the time it will rise with the market at an average of 5% per annum
25% of the time it will underperform market growth and maintain its value
50% of the time it will lose 10% of its value per year
Note that $25%+25%+50%=1$ which means that these alternatives account for all possibilities.
Then your expected outcome in any given year is:
$£1,000times ((.25times1.05) + (.25times 1) + (.5times .9))=£962.50$
This is a loss of £$37.50$
In any given year you expect to have $96.25%$ of what you started with, a loss of $3.75%$. If you wanted to calculate the expected return over a period of years then you can raise this number to the power of the number of years. So over $5$ years, Trump properties would turn every £$1$ into $0.9625^5approxeq£0.826$ and your £$1000$ would be $approxeq $£$826$
A couple of principles:
- For growth of $x%$ over $n$ years, take $(1+x)^n-1$ (where $5%=0.05$)
- You should evaluate any investment against the opportunity cost of some alternative investment. e.g. if you just bought land it would be fairly safe to say its value would increase at $5%$ per annum long-term so anything less than that is a loss. Economically speaking, this is called the opportunity cost of investing in what you choose to invest in.
- Your future pounds will be worth less than today's pounds. If you wanted to discount for inflation of $x%$ perannum over $n$ years then by the same token take $(1+x)^n$ and divide your end-result by that number.
answered Jul 18 at 18:33
Robert Frost
3,8821036
1
Hi Robert. Thanks for your answer! I had combined your principles (2) and (3) into one statement, using growth of one asset class and discounting it back with opportunity cost. I changed the terms to better reflect that. I do not understand (1) however. I was under the understanding that you multiplied Investment with (1+x)^n. Could you please explain? Additionally, I believe I came to an answer with your pointer. I can use the above mentioned formula, without the sum part, and through separate analysis calculate the probability for each Y, bracket of success. Would this be correct?
– camazing
Jul 19 at 11:26
@camazing sorry I had transposed the difference which I've now fixed. I'm just saying if the final figure is $100% + g%$ of the starting amount then subtract 100% to see $g$
– Robert Frost
Jul 19 at 11:46
add a comment |Â
up vote
0
down vote
up vote
0
down vote
One of the most basic ways of incorporating probability into a forecast is to use the concept of expected value. This is given by the probability of the outcome multiplied by the value of the outcome.
All of your probabilities must add up to $1$ to have a valid expected value.
So if you invest £$1,000$ in Trump Properties and it has the following outcomes with their associated probabilities:
25% of the time it will rise with the market at an average of 5% per annum
25% of the time it will underperform market growth and maintain its value
50% of the time it will lose 10% of its value per year
Note that $25%+25%+50%=1$ which means that these alternatives account for all possibilities.
Then your expected outcome in any given year is:
$£1,000times ((.25times1.05) + (.25times 1) + (.5times .9))=£962.50$
This is a loss of £$37.50$
In any given year you expect to have $96.25%$ of what you started with, a loss of $3.75%$. If you wanted to calculate the expected return over a period of years then you can raise this number to the power of the number of years. So over $5$ years, Trump properties would turn every £$1$ into $0.9625^5approxeq£0.826$ and your £$1000$ would be $approxeq $£$826$
A couple of principles:
- For growth of $x%$ over $n$ years, take $(1+x)^n-1$ (where $5%=0.05$)
- You should evaluate any investment against the opportunity cost of some alternative investment. e.g. if you just bought land it would be fairly safe to say its value would increase at $5%$ per annum long-term so anything less than that is a loss. Economically speaking, this is called the opportunity cost of investing in what you choose to invest in.
- Your future pounds will be worth less than today's pounds. If you wanted to discount for inflation of $x%$ perannum over $n$ years then by the same token take $(1+x)^n$ and divide your end-result by that number.
answered Jul 18 at 18:33
Robert Frost
3,8821036
One of the most basic ways of incorporating probability into a forecast is to use the concept of expected value. This is given by the probability of the outcome multiplied by the value of the outcome.
All of your probabilities must add up to $1$ to have a valid expected value.
So if you invest £$1,000$ in Trump Properties and it has the following outcomes with their associated probabilities:
25% of the time it will rise with the market at an average of 5% per annum
25% of the time it will underperform market growth and maintain its value
50% of the time it will lose 10% of its value per year
Note that $25%+25%+50%=1$ which means that these alternatives account for all possibilities.
Then your expected outcome in any given year is:
$£1,000times ((.25times1.05) + (.25times 1) + (.5times .9))=£962.50$
This is a loss of £$37.50$
In any given year you expect to have $96.25%$ of what you started with, a loss of $3.75%$. If you wanted to calculate the expected return over a period of years then you can raise this number to the power of the number of years. So over $5$ years, Trump properties would turn every £$1$ into $0.9625^5approxeq£0.826$ and your £$1000$ would be $approxeq $£$826$
A couple of principles:
- For growth of $x%$ over $n$ years, take $(1+x)^n-1$ (where $5%=0.05$)
- You should evaluate any investment against the opportunity cost of some alternative investment. e.g. if you just bought land it would be fairly safe to say its value would increase at $5%$ per annum long-term so anything less than that is a loss. Economically speaking, this is called the opportunity cost of investing in what you choose to invest in.
- Your future pounds will be worth less than today's pounds. If you wanted to discount for inflation of $x%$ perannum over $n$ years then by the same token take $(1+x)^n$ and divide your end-result by that number.
answered Jul 18 at 18:33
Robert Frost
3,8821036
edited Jul 19 at 11:44
answered Jul 18 at 18:33
Robert Frost
3,8821036
answered Jul 18 at 18:33
Robert Frost
3,8821036
answered Jul 18 at 18:33
Robert Frost
3,8821036
3,8821036
1
Hi Robert. Thanks for your answer! I had combined your principles (2) and (3) into one statement, using growth of one asset class and discounting it back with opportunity cost. I changed the terms to better reflect that. I do not understand (1) however. I was under the understanding that you multiplied Investment with (1+x)^n. Could you please explain? Additionally, I believe I came to an answer with your pointer. I can use the above mentioned formula, without the sum part, and through separate analysis calculate the probability for each Y, bracket of success. Would this be correct?
– camazing
Jul 19 at 11:26
@camazing sorry I had transposed the difference which I've now fixed. I'm just saying if the final figure is $100% + g%$ of the starting amount then subtract 100% to see $g$
– Robert Frost
Jul 19 at 11:46
add a comment |Â
1
Hi Robert. Thanks for your answer! I had combined your principles (2) and (3) into one statement, using growth of one asset class and discounting it back with opportunity cost. I changed the terms to better reflect that. I do not understand (1) however. I was under the understanding that you multiplied Investment with (1+x)^n. Could you please explain? Additionally, I believe I came to an answer with your pointer. I can use the above mentioned formula, without the sum part, and through separate analysis calculate the probability for each Y, bracket of success. Would this be correct?
– camazing
Jul 19 at 11:26
@camazing sorry I had transposed the difference which I've now fixed. I'm just saying if the final figure is $100% + g%$ of the starting amount then subtract 100% to see $g$
– Robert Frost
Jul 19 at 11:46
1
1
Hi Robert. Thanks for your answer! I had combined your principles (2) and (3) into one statement, using growth of one asset class and discounting it back with opportunity cost. I changed the terms to better reflect that. I do not understand (1) however. I was under the understanding that you multiplied Investment with (1+x)^n. Could you please explain? Additionally, I believe I came to an answer with your pointer. I can use the above mentioned formula, without the sum part, and through separate analysis calculate the probability for each Y, bracket of success. Would this be correct?
– camazing
Jul 19 at 11:26
Hi Robert. Thanks for your answer! I had combined your principles (2) and (3) into one statement, using growth of one asset class and discounting it back with opportunity cost. I changed the terms to better reflect that. I do not understand (1) however. I was under the understanding that you multiplied Investment with (1+x)^n. Could you please explain? Additionally, I believe I came to an answer with your pointer. I can use the above mentioned formula, without the sum part, and through separate analysis calculate the probability for each Y, bracket of success. Would this be correct?
– camazing
Jul 19 at 11:26
@camazing sorry I had transposed the difference which I've now fixed. I'm just saying if the final figure is $100% + g%$ of the starting amount then subtract 100% to see $g$
– Robert Frost
Jul 19 at 11:46
@camazing sorry I had transposed the difference which I've now fixed. I'm just saying if the final figure is $100% + g%$ of the starting amount then subtract 100% to see $g$
– Robert Frost
Jul 19 at 11:46
add a comment |Â
Not clear what you are hoping for here. Is it your intent to calibrate the parameters of your model to actual market prices? If so, then (tautologically) the investment is simply fair. Alternatively, do you want to calibrate your model to some sort of preconceived notions you have about the market? If so, what are those notions? The main point being: you need to make some assumptions in order to build a model. The clearer you can be about those assumptions, the better your model will be.
– lulu
Jul 18 at 17:09
Can you clarify your question? As I said, absent some more information on what you are willing to assume about the industry (or specific companies) you have in mind, there's really nothing that can be said.
– lulu
Jul 18 at 17:22
Voting to close the question as it is unclear what you are asking. If you can, please edit your post for clarity.
– lulu
Jul 18 at 17:33
Welcome to MSE. The site seems to work better for precise questions with a clear answer but I can tell what ball park you're in and I've given you some pointers.
– Robert Frost
Jul 18 at 18:39
Thanks for responses! I tried to clarify the question to be more direct. Given comments this is where I am at. I can feel that my suggestion is incorrect and possibly impossible in a real world scenario. If the outcome was decided by a dice with uniform random distribution then it holds (I believe), but that I would need better assumptions about the probabilities of each success bracket.
– camazing
Jul 19 at 11:16