Savingforanapartment - Revision history

Miln02 at 01:04, 23 January 2023

2023-01-23T01:04:47Z

Miln02 at 00:40, 23 January 2023

2023-01-23T00:40:36Z

Miln02 at 23:48, 22 January 2023

2023-01-22T23:48:55Z

Miln02 at 23:00, 22 January 2023

2023-01-22T23:00:14Z

Miln02 at 22:52, 22 January 2023

2023-01-22T22:52:29Z

Miln02: Created page with "Introduction =Problem definition= Jon has finally graduated to be an engineer and has found his first job. As he is living with his parents and doesn’t own his apartment,..."

2023-01-22T22:01:36Z

Created page with "Introduction =Problem definition= Jon has finally graduated to be an engineer and has found his first job. As he is living with his parents and doesn’t own his apartment,..."

New page

Introduction

=Problem definition=

Jon has finally graduated to be an engineer and has found his first job. As he is living with his parents and doesn’t own his apartment, he made the decision to start saving so he can buy an apartment in the next 15 years. He already has 100.000 USD that he has saved so far just sitting in his bank account, so he will use that as an initial investment, and after that he will invest a fixed amount of 10.000 USD at the beginning of every year. He now must make a very important decision. Where should he invest his money? After doing some research, he focused on choosing between four different options:

1. Deposit money in the bank.

2. Purchase USA Treasury notes 5Y

3. Invest in NASDAQ.

4. Invest in Tesla.

=Method=

The problem was solved using Monte Carlo simulation and Excel as an calculation environment.

=Model=

=Results=

=Conclusion=

=Code=

[[User:Miln02|Miln02]] ([[User talk:Miln02|talk]]) 23:01, 22 January 2023 (CET)

@@ Line 65: / Line 65: @@
 * End portfolio value in USD: Average, Median, Percentiles 5,25,75,95.
-* Total yield in USD - Difference between total invested money and average end portfolio value.
+* Total yield in USD - Difference between average end portfolio value and total money that's invested from outside.
 * Graph comparing total invested money and average end portfolio value during time.
-* Number of crisis periods
+* Number of crisis periods.
 == Working with simulation  ==
-The first sheet in the excel is Overview page which has three main parts. Short instruction for using the simulation, table for adding input parameters and results overview. Input parameters are set up with the values that I used for my simulation, but Initial investment, Annual investment, Crisis probability, and Bank annual interest rate can be changed here and the simulation will be updated. There is also the option to change the Mean and Standard Deviation for the three volatile portfolios directly in the data sheets. The results overview contains main metrics of simulated results for all four scenarios. The sheets colored in red contain calculations, while the sheets in green contain data from Yahoo Finance and calculations of Mean and Std Dev. If you change the dataset there, the new mean and std dev will be calculated and simulation will be automatically updated with new results.
+The first sheet in the excel is Overview page which has three main parts. Short instruction for using the simulation, table for adding input parameters and results overview. Input parameters are set up with the values that I used for my simulation, but Initial investment, Annual investment, Crisis probability, and Bank annual interest rate can be changed here and the simulation will be updated. There is also the option to change the Mean and Standard Deviation for the three volatile portfolios in the data sheets. Those can be changed by directly adding the values, or by changing the dataset and values will be again automatically calculated. The results overview contains main metrics of simulated results for all four scenarios. The sheets colored in red contain calculations, while the sheets in green contain data from Yahoo Finance and calculations of Mean and Std Dev.
 =Results=
@@ Line 118: / Line 118: @@
 Std dev - $17,129
-% - $279,746
+Percentiles 5% - $279,746
-% - $295,877
+Percentiles 25% - $295,877
-% - $319,393
+Percentiles 75% - $319,393
-% - $335,247
+Percentiles 95% - $335,247
 Total yield - $68,044
@@ Line 190: / Line 190: @@
 Median - $107,767
-Std dev -$6,838,684
+Std dev - $6,838,684
 Percentiles 5% - $13,187
@@ Line 203: / Line 203: @@
 =Conclusion=
 =Sources=

@@ Line 49: / Line 49: @@
 '''NASDAQ'''
 The Nasdaq Composite Index covers more than 3,000 stocks, which makes them more riskier than government bonds, but still less volatile than investment in the individual stock.
 For the calculations of mean and standard deviation, the simulation uses historic yield data starting from 2010. For the crisis, mean and standard deviation are calculated from only historic data where value is lower than Mean-2*Standard Deviation from whole dataset values.
@@ Line 55: / Line 56: @@
 '''TESLA'''
 Tesla is multinational automotive company which has been popular investing option in the recent past. As this scenario assumes investment in only one stock, it's the most volatile one.
 For the calculations of mean and standard deviation, the simulation uses historic yield data starting from 2010. For the crisis, mean and standard deviation are calculated from only historic data where value is lower than Mean-2*Standard Deviation from whole dataset values. As there was only one month like this, the mean is that value and std dev is set as 0.1%.
@@ Line 69: / Line 71: @@
 == Working with simulation  ==
-The first sheet in the excel is Overview page which has three main parts. Short instruction for using the simulation, table for adding input parameters and results overview. Input parameters are set up with the values that I used for my simulation, but Initial investment, Annual investment, Crisis probability, and Bank annual interest rate can be changed here and the simulation will be updated. There is also the option to change the Mean and Standard Deviation for the three volatile portfolios directly in the calc sheets. The results overview contains main metrics of simulated results for all four scenarios. The sheets colored in red contain calculations, while the sheets in green contain data from Yahoo Finance and calculations of Mean and Std Dev. If you change the dataset there, the new mean and std dev will be calculated and simulation will be automatically updated with new results.
+The first sheet in the excel is Overview page which has three main parts. Short instruction for using the simulation, table for adding input parameters and results overview. Input parameters are set up with the values that I used for my simulation, but Initial investment, Annual investment, Crisis probability, and Bank annual interest rate can be changed here and the simulation will be updated. There is also the option to change the Mean and Standard Deviation for the three volatile portfolios directly in the data sheets. The results overview contains main metrics of simulated results for all four scenarios. The sheets colored in red contain calculations, while the sheets in green contain data from Yahoo Finance and calculations of Mean and Std Dev. If you change the dataset there, the new mean and std dev will be calculated and simulation will be automatically updated with new results.
 =Results=
 =Conclusion=

← Older revision		Revision as of 23:48, 22 January 2023
Line 19:		Line 19:
	=Model=		=Model=

		+	The simulation is based on historic data found on Yahoo Finance. The behaviour of four given options is projected for the next 15 years using the historic data, while economic crisis effects are included with ability to set up the probability of such event.

		+	== Input parameters ==

		+	* Initial investment - Amount of USD invested at the beginning of first year.
		+
		+	* Annual investment - Amount of USD invested at the beginning of every following year.

		+	* Crisis probability - Probability that crisis will happen as percentage (no matter if we are simulating by months or years).
		+
		+	* Bank annual interest rate - For bank deposit scenario, in %.
		+
		+	* Standard deviations and means - For volatile scenarios for standard times.
		+
		+	* Standard deviations and means - For volatile scenarios for crisis times.
		+
		+	== Scenarios ==
		+
		+	'''Bank Deposit'''
		+
		+	This is the simplest scenario. Jon is putting his money in the bank savings account. The annual interest rate is fixed and he will receive known amount of money after 15 years. No randomness in included, so no MC was used for this scenario.
		+
		+	'''Treasury notes'''
		+
		+	USA government treasury notes for 5 years are bit more risker for Jon, but they can be more profitable than simple deposits and their payment is guaranteed by the USA government.
		+	For the calculations of mean and standard deviation, the simulation uses historic yield data starting from 2010. For the crisis, mean and standard deviation are calculated from only historic yields that are below 1%.
		+	Since the attribute of the bonds that interest is received annually and the full worth of bond is paid after 5 years, the total value of the portfolio is calculated as the total invested amount after 15 years. The simulations assumes that all earned interest rates and repaid mature bonds are reinvested immediately.
		+	Portfolio is simulated for the 1000 times.
		+
		+	'''NASDAQ'''
		+	The Nasdaq Composite Index covers more than 3,000 stocks, which makes them more riskier than government bonds, but still less volatile than investment in the individual stock.
		+	For the calculations of mean and standard deviation, the simulation uses historic yield data starting from 2010. For the crisis, mean and standard deviation are calculated from only historic data where value is lower than Mean-2*Standard Deviation from whole dataset values.
		+	The total portfolio value is calculated as sum of invested amount and gains. The simulations assumes that all gains are reinvested immediately.
		+	Portfolio is simulated for the 1000 times.
		+
		+	'''TESLA'''
		+	Tesla is multinational automotive company which has been popular investing option in the recent past. As this scenario assumes investment in only one stock, it's the most volatile one.
		+	For the calculations of mean and standard deviation, the simulation uses historic yield data starting from 2010. For the crisis, mean and standard deviation are calculated from only historic data where value is lower than Mean-2*Standard Deviation from whole dataset values. As there was only one month like this, the mean is that value and std dev is set as 0.1%.
		+	The total portfolio value is calculated as sum of invested amount and gains. The simulations assumes that all gains are reinvested immediately.
		+	Portfolio is simulated for the 1000 times.
		+
		+	== Metrics ==
		+
		+	* End portfolio value in USD: Average, Median, Percentiles 5,25,75,95.
		+	* Total yield in USD - Difference between total invested money and average end portfolio value.
		+	* Graph comparing total invested money and average end portfolio value during time.
		+	* Number of crisis periods
		+
		+	== Working with simulation ==
		+
		+	The first sheet in the excel is Overview page which has three main parts. Short instruction for using the simulation, table for adding input parameters and results overview. Input parameters are set up with the values that I used for my simulation, but Initial investment, Annual investment, Crisis probability, and Bank annual interest rate can be changed here and the simulation will be updated. There is also the option to change the Mean and Standard Deviation for the three volatile portfolios directly in the calc sheets. The results overview contains main metrics of simulated results for all four scenarios. The sheets colored in red contain calculations, while the sheets in green contain data from Yahoo Finance and calculations of Mean and Std Dev. If you change the dataset there, the new mean and std dev will be calculated and simulation will be automatically updated with new results.

	=Results=		=Results=

@@ Line 24: / Line 24: @@
 =Code=
+[[File:Savingforanapartment.xlsx]]
 [[User:Miln02|Miln02]] ([[User talk:Miln02|talk]]) 23:01, 22 January 2023 (CET)

@@ Line 15: / Line 15: @@
 =Method=
-The problem was solved using Monte Carlo simulation and Excel as an calculation environment.
+The problem was solved using Monte Carlo simulation and Excel as an calculation environment. MC was chosen because it's widely used and accepted for solving similar investment problems.
 =Model=
 =Results=
 =Conclusion=
 =Code=