You need to solve the Matrix in given research papar. You need to analyse trends and create graphs based on those trends. I will attach some calculations i did, which might help.(They need modifications as well). I need proper solution. Thanks.
Category: MathLab
Write a short report – no more than six pages – in which you should:
Develop a way to characterise and quantify the stability of the bogie, both considering the safety of the vehicle and the comfort of the passengers.
Show how changing the parameters of the simulation affects the stability of the bogie.
Find or estimate appropriate values for the wheelbase, masses and moments of inertia (the default values are just guesses), justifying your choices, and determine suitable spring stiffness values that maximise stability.
Source for vehicle simulator (Matlab files) are attached.
Structure & Presentation
Six pages may seem very limited, but in industry there is often a demand for brief, even one-or-two page reports that summarise research and make a recommendation. Academic papers typically aim to be 6-8 pages, including everything. The challenge, therefore, is to use the given space wisely without sacrificing clarity.Pages should be numbered. Main report (not including title/cover page, references and appendices, if any) should be no more than six pages. (A table of contents is not required.)
A short abstract (one paragraph) that describes the problem, outlines the approach, and summarises the key conclusions.
Clear structure: Introduction / Methodology / Results & Discussion / Conclusions
Fonts, line spacing and paragraph styles should be consistent. Text in figures, tables and equations should be readable and not overly large. Non-symbols in equations should not be in italics. Units should not be in italics. Do not use bold or underline for emphasis.
All tables and figures should be numbered and have descriptive captions. Tables are not figures. Graphs and charts and images and sketches and photos, etc., are all figures.
Equations, ideally (but not necessarily), should be numbered also, at the right⇢(1)
Space is limited and should not be wasted. Choose carefully what results should be presented. Figures should not be squashed down just to squeeze more in (and should never be stretched – this looks awful). Consider whether multiple figures can instead be merged, and add legends/annotation to identify curves and explain key features.
Avoid first person and narrative.
Results & Interpretation
The main purpose of this coursework is data analysis. There are multiple input parameters that can be varied, and multiple output data values that can be plotted. There are multiple ways to interpret the data. There is no single correct solution.Define – and justify! – a way to quantify vehicle stability, i.e., which are the most critical output data and how can you reduce these to a simple number?
Determine – with justification! – a set of input parameters that maximise stability.
This is not a Matlab exercise. It may be easier to analyse the data in Matlab and plot the results in Excel, but it is possible to use Excel for analysis and it is possible to use Matlab for plotting.
Marks awarded based on how convincing the arguments are.
Instructions
MATLAB toolboxes, which need to be installed when you install MATLAB:
Econometrics Toolbox
• Financial Toolbox
• Risk Management Toolbox
• Statistics and Machine Learning Toolbox
Word limit: 2,000 words, not including references section and appendix.
Download three data sets:
Data set 1.
Using Bloomberg or Yahoo Finance, download daily stock price data (adjusted closing price) for any four U.S. companies for the period 31/12/10-30/12/22.
Data set 2.
Using Bloomberg or Yahoo Finance, download monthly stock price data (end-of- month, adjusted closing price) for any four U.S. companies for the period 2010:12- 2022:12.
Data set 3.
Using the Bank of England’s statistics database, download monthly data (end-of- month) on the GBPUSD spot exchange rate (1998:01-2021:06) and the GBPUSD one- month forward exchange rate (1998:01-2021:06).
When you have downloaded your data, answer the following questions using MATLAB for all computations. Submit a PDF document that contains your answers to the questions. In your answers you should include basic information on the data used and brief comments for each answer, along with tables of numerical results and graphs where relevant. You should also include a references section. In an appendix to this PDF document please include the MATLAB code that you used to compute your results. The references section and appendix are not included in the word count.
Questions
Q1. Pick one of the stocks from data set 1 and compute the natural logarithm of the price series for this stock. Use the Box-Jenkins methodology to estimate an appropriate time series model for the log-price series and investigate the forecasting ability of the model.
Q2.
(a) Using appropriate hypothesis tests, analyse whether the natural logarithm of GBPUSD spot exchange rate from data set 3 is consistent with the random walk model.10%
(b) Using the natural logarithm of the GBPUSD spot and forward exchange rates from data set 3, test the forward rate unbiasedness (FRU) hypothesis.10%
Q3. Using data set 2 and assuming a one-year investment horizon, no borrowing, and no short sales, investigate the optimal portfolio weights for a portfolio of the four stocks and a single risk-free asset (use any sensible values for the coefficient of risk aversion and risk-free rate).
20%
Q4. Using data set 1:
(a) Use the RiskMetrics or Historical Simulation approach to compute the one-day ahead return-VaR for one of the stocks over the period 03/01/22-30/12/22 and conduct backtesting.15%
(b) Use the RiskMetrics or Historical Simulation approach to compute the one-day ahead return-VaR for an equally weighted portfolio of the four stocks over the period 03/01/22-30/12/22 and conduct backtesting.15%
**** data set 1&2 will be attached also the seminars solved questions and marking rubric please follow them , it has enough information *****
Theres a matrix given in the following file(ill attach ss of the matrix) which you need to solve. After solving the equation you need to draw the velocity calculated from matrix on mathlab,
Instructions
Word limit: 2,000 words, not including references section and appendix.
Download three data sets:
Data set 1.
Using Bloomberg or Yahoo Finance, download daily stock price data (adjusted closing price) for any four U.S. companies for the period 31/12/10-30/12/22.
Data set 2.
Using Bloomberg or Yahoo Finance, download monthly stock price data (end-of- month, adjusted closing price) for any four U.S. companies for the period 2010:12- 2022:12.
Data set 3.
Using the Bank of England’s statistics database, download monthly data (end-of- month) on the GBPUSD spot exchange rate (1998:01-2021:06) and the GBPUSD one- month forward exchange rate (1998:01-2021:06).
When you have downloaded your data, answer the following questions using MATLAB for all computations. Submit a PDF document that contains your answers to the questions. In your answers you should include basic information on the data used and brief comments for each answer, along with tables of numerical results and graphs where relevant. You should also include a references section. In an appendix to this PDF document please include the MATLAB code that you used to compute your results. The references section and appendix are not included in the word count.
1
Questions
Q1. Pick one of the stocks from data set 1 and compute the natural logarithm of the price series for this stock. Use the Box-Jenkins methodology to estimate an appropriate time series model for the log-price series and investigate the forecasting ability of the model.
Q2.
(a) Using appropriate hypothesis tests, analyse whether the natural logarithm of GBPUSD spot exchange rate from data set 3 is consistent with the random walk model.10%
(b) Using the natural logarithm of the GBPUSD spot and forward exchange rates from data set 3, test the forward rate unbiasedness (FRU) hypothesis.10%
Q3. Using data set 2 and assuming a one-year investment horizon, no borrowing, and no short sales, investigate the optimal portfolio weights for a portfolio of the four stocks and a single risk-free asset (use any sensible values for the coefficient of risk aversion and risk-free rate).
20%
Q4. Using data set 1:
(a) Use the RiskMetrics or Historical Simulation approach to compute the one-day ahead return-VaR for one of the stocks over the period 03/01/22-30/12/22 and conduct backtesting.15%
(b) Use the RiskMetrics or Historical Simulation approach to compute the one-day ahead return-VaR for an equally weighted portfolio of the four stocks over the period 03/01/22-30/12/22 and conduct backtesting.15%
**** attached are the seminars and marking rubric please follow them , it has enough information *****
Instructions
Word limit: 2,000 words, not including references section and appendix.
Download three data sets:
Data set 1.
Using Bloomberg or Yahoo Finance, download daily stock price data (adjusted closing price) for any four U.S. companies for the period 31/12/10-30/12/22.
Data set 2.
Using Bloomberg or Yahoo Finance, download monthly stock price data (end-of- month, adjusted closing price) for any four U.S. companies for the period 2010:12- 2022:12.
Data set 3.
Using the Bank of England’s statistics database, download monthly data (end-of- month) on the GBPUSD spot exchange rate (1998:01-2021:06) and the GBPUSD one- month forward exchange rate (1998:01-2021:06).
When you have downloaded your data, answer the following questions using MATLAB for all computations. Submit a PDF document that contains your answers to the questions. In your answers you should include basic information on the data used and brief comments for each answer, along with tables of numerical results and graphs where relevant. You should also include a references section. In an appendix to this PDF document please include the MATLAB code that you used to compute your results. The references section and appendix are not included in the word count.
1
Questions
Q1. Pick one of the stocks from data set 1 and compute the natural logarithm of the price series for this stock. Use the Box-Jenkins methodology to estimate an appropriate time series model for the log-price series and investigate the forecasting ability of the model.
Q2.
(a) Using appropriate hypothesis tests, analyse whether the natural logarithm of GBPUSD spot exchange rate from data set 3 is consistent with the random walk model.10%
(b) Using the natural logarithm of the GBPUSD spot and forward exchange rates from data set 3, test the forward rate unbiasedness (FRU) hypothesis.10%
Q3. Using data set 2 and assuming a one-year investment horizon, no borrowing, and no short sales, investigate the optimal portfolio weights for a portfolio of the four stocks and a single risk-free asset (use any sensible values for the coefficient of risk aversion and risk-free rate).
20%
Q4. Using data set 1:
(a) Use the RiskMetrics or Historical Simulation approach to compute the one-day ahead return-VaR for one of the stocks over the period 03/01/22-30/12/22 and conduct backtesting.15%
(b) Use the RiskMetrics or Historical Simulation approach to compute the one-day ahead return-VaR for an equally weighted portfolio of the four stocks over the period 03/01/22-30/12/22 and conduct backtesting.15%
**** attached are the seminars and marking rubric please follow them , it has enough information *****
Modify our sample code planewarpdemo in the matlab sample code section of our course to
generate a higher resolution output than it currently does, for example, by setting the output
(destination) image be comparable in number of rows/cols to the input (source) image. Also,
note that one deficiency of this code is that the user has to “guess” what the shape of the
chosen rectangle is when specifying the output. Write a new version that does not rely on user
input, and that generates a top-down view of the floor plane that is accurate up to a similarity
transformation (rotation, translation and isotropic scale) with respect to the 2D X-Y world
coordinate system in the floor plane Z=0. Hint: how can you relate ground plane X-Y
coordinates to 2D image coordinates in the source and in the destination images, given the
known camera parameters of one or both views? Explain how you are generating your top-
down view. Also, with regard to the resulting output image, what things look accurate and
what things look weird? Could this kind of view be useful for analyzing anything about the
performance of a person as they move around in the room?