Final Report on Individual Simulation Investment Simulation Report for FNCE 625
Question
Task: How did the individual simulation Investment Simulation Report contribute to understanding asset trends and decision-making processes in Investment Simulation Report management, and what were the key findings and recommendations?
Answer
Introduction
The Investment Simulation Report project simulations main goal was to study Investment Simulation Report scenarios, using Trading View using trading indicators. My focus was to explore and analyse asset trends, to identify suitable entry and exit levels which will help risk management and maximize returns on Investment Simulation Report. This analysis focuses on stock portfolio decision which provides valuable insights relating to overvaluation and fair price entry levels. The Trading View platform allows for free analysis using a wide range of indicators that can be modified to suite investor requirements. The simulation helped improve understanding of assets price movements thus helping improve my risk to reward management skills (Aguirre et al., 2020). As I performed deeper project analysis, I gained a better understanding of the movements within the market thus allowing me to design more effective risk management strategies. This project has delivered an important learning experience where I have been able to identify Investment Simulation Reports strategies that help reduce strain and minimize devaluation risks.
Objectives of the Report
This report helps plot key Investment Simulation Report levels which can be used to assess asset risk and identify potential profits expected from an Investment Simulation Report. This allowed me to develop low risk strategies by identifying crucial support and resistance levels for various portfolios analysed during the simulation. In addition to this it also helps determine how effective the technical indicators are at analysing the portfolio thus shaping my Investment Simulation Report decisions (Lanbouri & Achchab, 2020). This report outlines key lessons learned during the simulations and areas that may require further investigation to further improve portfolio analysis. This report aims to present my experience and views relating to the simulation Simulation which can be used in future to analyse Investment Simulation Report plans while also addressing Investment Simulation Report risks and mitigation approaches that can be used to enhance Investment Simulation Report returns.
Ill. Highlights Analysis
The simulation revealed several key points such as Trading View being an important charting tool that is instrumental towards examining assets and outlining the resistance and support levels which can be used as effective entry and exit levels. The Linear Regression Channel and MCAD were chosen due to them quickly pointing out market trends and levels which can allow investors to use minimum efforts towards determining suitable entry and exit levels.
The portfolio analysis highlighted three main categories within the portfolio assets namely those that are overpriced, under-priced, and high-risk assets. Stocks such as Amazon (AMG), American Express (AXP), and Google (GOOGL) were classified as overpriced. These stocks require significant retracement to lower levels before buyers can invest on them. On the contrary portfolio stocks like Boston Bear Company (SAM) have achieved the desired entry level which a promising projection that the stock will increase in value in the coming months.
Risk management plays a pivotal role on effective decision making and high risk stocks such as Home Street (HMST) have been classified as inappropriate for Investment Simulation Reports. By eliminating some of the low performing stocks the portfolio can be improved to maximizing profits and also more importantly minimizing Investment Simulation Report risk (Lee et al., 2021).
This simulation Simulation demonstrates the importance of performing in-depth market analysis and research which helps with, risk assessment and detailed decision relating to stock Investment Simulation Report levels as well as potential Investment Simulation Report periods thus offering a clearer overview relating to stock market Investment Simulation Report.
IV. Decision-Making Process
The Investment Simulation Report decision making process involved analysing the chosen assets using Trading view a free charting website. The two chosen trading indicators namely the linear regression(period – 100) and MACD (setting 26-52-9) were selected to identify the current asset trend as well as identify potential support and resistance points based on which entry and accumulation trades can be executed.
Charting Program/ website
Asset historical Charting was performed on trading view which offers a free account limiting users to 2 indicators. The charting website provides provide live asset prices which allows for instant and accurate analysis of assets.
Analysis and charting timeframe
Long term Investment Simulation Reports require retaining an Investment Simulation Report for a minimum of 52 weeks or 1 year making the weekly and monthly analysis timeframe most suitable for long term Investment Simulation Reports. This plots the current asset valuation thus allowing investors to make more accurate entry levels.
Chosen indicators:
The Linear regression channel (period 100)
This is an important charting indicator as it helps plot the regression line as well as deviation points which can be used as a reference level for entry and accumulation. It also provides a relatively clear idea of the current asset trends which allows for entries at the right support levels. In addition to offering support levels that are likely to see the asset bounce to higher levels, it also provides accurate resistance levels which can be used as Book profit levels. For this exercise I have opted to use a regression channel consisting of three diversion points. The weekly -2 deviation points acts as the first Investment Simulation Report level while the monthly -3 acts as the accumulation level. The same principle applies to book profits levels where half the assets profits are booked at the weekly +2 deviation level while the remaining is booked at or above the monthly +3 deviation level.
MACD (Moving Average Conversion diversion)
The MACD indicator has boon chosen due to its ability to identify potential asset price reversal levels. The MACD setting have been adjusted to 26, 52, and 9 so as to help reduce false signals thus helping increase entry and exit level accuracy. The MACD histogram will play a crucial role towards determining trend reversals where the dark histogram colours will indicate strong trends whereas light colours will indicate the start of a potential trend reversal.
Combined indicator signals
To gain more accurate entry and exit points, both indicators signals will have to correspond. For example if an asset price is on a down trend, I will have to wait for the MACD signal to first display a light red histogram candle. Once the light candle has been confirmed I would then need to counter check and confirm that the asset price has fallen to or below the weekly -2 deviation points of the linear regression channel. Entry will only be confirmed once the asset price has reached the -2 deviation level or below which would signal the first Investment Simulation Report level. I would then need to reach the monthly -2 deviation level as the accumulation level where additional assets can be added (Banik et al., 2022).
The same would principle would apply with the book profit level where 50% of the asset profits would be booked at the weekly+2 deviation level and the remaining 50% would be booked at or above the monthly +3 deviation level.
Current asset levels, entry levels and potential profit book levels.
|
Asset |
Last price |
Weekly - 2 Deviation level |
Monthly -2 deviation level |
Analysis |
|
AMZ |
178.85 |
117 |
85 |
Over Valued – Amazon is currently trading just below the weekly take profit level. The asset will require to retrace by between 35-40% from its current price so as to be an attractive Investment Simulation Report position |
|
AXP |
225.96 |
154.5 |
137 |
Over Valued – AXP is currently trading above the weekly take profit level. The asset will require to retrace by between 30-35% from its current price so as to be an attractive Investment Simulation Report position |
|
COST |
734.8 |
550 |
460 |
Over Valued – COST is currently trading at the weekly take profit level. The asset will require to retrace by between 25-30% from its current price so as to be an attractive Investment Simulation Report position |
|
DOOR |
131.59 |
83 |
54 |
Over Valued – DOOR is currently trading above the weekly take profit level. The asset will require to retrace by between 35-40% from its current price so as to be an attractive Investment Simulation Report position |
|
GOOGL |
150.77 |
115 |
91 |
Over Valued – GOOGL is currently trading just below the weekly take profit level. The asset will require to retrace by between 25-30% from its current price so as to be an attractive Investment Simulation Report position |
|
HMST |
15.07 |
4 |
1 |
High Risk – HMST has lost 80-90% of its value over the past 2 years making its high risk Investment Simulation Report. This stock has been able to bounce from its lows which were 4.2 and currently trading at 15. It’s advisable to consider this stock as high risk and only invest a small amount of the portfolio when the stock falls to or below 4.2. Investment Simulation Report but be considered on a longer time frame of 5-10 years and risk management measures must be taken in case the stock is not able to recover from its slump |
|
MA |
481.67 |
400 |
350 |
Over Valued – MA is currently trading above the weekly take profit level. The asset will require to retrace by between 20-25% from its current price so as to be an attractive Investment Simulation Report position |
|
MSFT |
428.75 |
335 |
270 |
Over Valued – MA is currently trading below the weekly take profit level. The asset will require to retrace by between 20-25% from its current price so as to be an attractive Investment Simulation Report position |
|
NDVA |
942.87 |
455 |
80 |
Over Valued – NDVA is currently trading above the weekly take profit level. The asset will require to retrace by between 45-50% from its current price so as to be an attractive Investment Simulation Report position |
|
RY |
99.38 |
83.5 |
77 |
Over Valued – RY is currently trading close the weekly take profit level. The asset will require to retrace by between 45-50% from its current price so as to be an attractive Investment Simulation Report position |
|
SAM |
307 |
290 |
113 |
Fairly PRICE – SAM is currently trading at the weekly -2 Diversion level. The asset is ready for first Investment Simulation Report and accumulation if price falls to 113. This provides potential to secure 35-40% profit when the price reaches the +2 deviation level from its current position |
|
TRIP |
28.56 |
12 |
5 |
Over Valued – TRIP is currently trading above the weekly take profit level. The asset will require to retrace by between 55-60% from its current price so as to be an attractive Investment Simulation Report position |
|
V |
283.26 |
245 |
215 |
Over Valued – RY is currently trading close the weekly take profit level. The asset will require to retrace by between 15-20% from its current price so as to be an attractive Investment Simulation Report position |
|
WMT |
60.85 |
52 |
47.5 |
Over Valued – RY is currently trading close the weekly take profit level. The asset will require to retrace by between 15-20% from its current price so as to be an attractive Investment Simulation Report position |
Analysis Observation and Advice
The portfolio analysis clearly shows that the majority of stocks are currently over valued except for SAM which is currently trading at a fair Investment Simulation Report entry price. HMST has been observed to loss 80-90% of its value since 2022 which makes it a high risk Investment Simulation Report that is likely to remain under valued for 5 to 10 years or even remain at the lower valuation for longer periods. This makes HMST high risk and not a recommended stock to invest on for a medium term outlook. The valuation of the other portfolio Assets require to fall between 30-40% in order to deliver a fair entry price which will reduce the risk of the investor. Investment Simulation Report at the current overvalued value can result in investor capital being trapped resulting in unnecessary waiting and stress. In Addition V and WMT have been observed to offer a profit range of between 15-20% which make them unsuitable Investment Simulation Report stocks due to their lower swing ranges as opposed to other stocks which offer 30-50%.
From the analysis it is advised that portfolio Investment Simulation Report be made on the following assets:
• AMZ - Amazon.com Inc.
• AXP - American Express Company
• COST - Costco Wholesale Corporation
• DOOR - Masonite International Corporation
• GOOGL - Alphabet Inc. (formerly Google Inc.)
• MA - MasterCard Incorporated
• MSFT - Microsoft Corporation
• NDVA - Endava plc
• RY - Royal Bank of Canada
• SAM - The Boston Beer Company, Inc.
• TRIP - TripAdvisor, Inc.
Bibliography
Aguirre, A.A.A., Medina, R.A.R. & Méndez, N.D.D., 2020. Machine learning applied in the stock market through the Moving Average Convergence Divergence (MACD) indicator. Investment Simulation Report Management & Financial Innovations, 17(4), pp.44 retrieved from https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/14191/I MFI_2020_04_Aguirre.pdf.
Banik, S. et al., 2022. LSTM based decision support system for swing trading in stock market. Knowledge-Based Systems, 239, pp.1-45 retrieved from https://arxiv.org/pdf/2401.06139.pdf.
Lanbouri, Z. & Achchab, S., 2020. Stock market prediction on high frequency data using long-short term memory. Procedia Computer Science, 175, pp.603-608 retrieved from https://pdf.sciencedirectassets.com/280203/1-s2.0-S1877050920X00135/1-s2.0-S1877050920317877/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEFwaCXVzLWVhc3QtMSJHMEUCIBVRTvwd7u6xqLfaQJQIM1irad2mJY%2B199R5vK IBT4foAiEAsmB8ZS%2FzYhJ9U1R%2.
Lee, M.C., Chang, J.W., Hung, J.C. & Chen, B.L., 2021. Exploring the effectiveness of deep neural networks with technical analysis applied to stock market prediction. Computer Science and Information Systems, 18(2), pp.401-418 retrieved from https://doiserbia.nb.rs/img/doi/1820-0214/2021/1820-02142100002L.pdf.
