PowerPoint Presentation Dr Aziz Hayat Department of Finance Deakin University ‹#› 1 b. Normal rule of thumb Solution: within 1 SD of the mean (For normal dist. ~ 68% of returns obs.) -> high Kurtosis...

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PowerPoint Presentation Dr Aziz Hayat Department of Finance Deakin University ‹#› 1 b. Normal rule of thumb Solution: within 1 SD of the mean (For normal dist. ~ 68% of returns obs.) -> high Kurtosis Within 2 SD of the mean (For normal dist. ~ 95% of returns obs.) Within 3 SD of the mean (For normal dist. ~ 99.7% of returns obs.) -> high Kurtosis ‹#› b. Returns and Sumproduct function in Excel Calculate continuously compounded returns and the number of observations of the returns in the following ranges using sumproduct function Solution: See Excel Mean -1SD Mean +1SD Mean - 2SD Mean + 2SD Mean - 3SD Mean + 3SD ‹#› c. Random number from Normal distribution: Return distribution Draw 1000 random numbers from normal distribution with mean= 1% and SD=0.1%. Solution: In the assignment, use n=size of the returns data, mean=sample mean of the returns data, SD= standard deviation of the returns data. Method1: Using Data Analysis tool-pack in Excel Method2: Using µ+σz(0,1) = µ+σNORM.S.INV(Rand()) ‹#› Histogram for Distribution shape Draw histogram from simulated data done in previous slide. Solution: See Excel. ‹#› d. Try it ‹#› e. Hypothesis testing Ho: µ =0 (mean return to be zero) H1: µ > 0, (mean return to be positive) Until part e. you can get done within a week time. The next two week lectures will cover part f. and g. of the assignment. Due to technical nature and that the assignment is to be done individually, the assignment is not that big. Hopefully, you will agree with it once you finished the assignment. ‹#› Report submitted in word document will be marked. Please submit a report in word document and not the Excel workings. You can take picture of Excel workings where necessary to present in the report. For e.g. and are calculated in Excel as follows. Note rows are hidden to due space limit. Report shall contain enough information so the reader can replicate what you have shown. ‹#› MAF384 – FINANCIAL MODELLING MAF760 – International Finance Trimester 1, 2019 ASSIGNMENT 1 The total mark of this assignment is 100, which comprises 20% of the assessment for this unit. Due date: 11:59 pm AEST 7 April 2019 Submission Instructions: • This is an individual assignment. • Only one assignment per student needs to be submitted online in Cloud Deakin. • The electronic copy of the assignment has to be uploaded to CloudDeakin by the due date. If you experience any problem in uploading the document, please contact the IT Service Desk between Monday to Friday 8am-8pm or Weekends 11am-5pm or CALL Internal phones: 888, Geelong 03 5227 8888, Melbourne 03 9244 6888, Warrnambool 03 5563 3888 Off-campus 1800 463 888 or International +61 3 5227 8888 Write-up instructions: • You are to hand in a (word) document that lists the number and part of each question (e.g. a., b.(I.)) followed by your answer. Do not repeat the question. Use size 11 font. • Make sure that your assignment is well presented. Provide the appropriate Excel output and graphs in your assignment report. Make sure that all your graphs and tables are clearly labelled. • Contact a staff member if you have any further queries regarding the assignment. http://www.deakin.edu.au/its/servicedesk/index.php http://www.deakin.edu.au/its/servicedesk/index.php Foreign exchange rate distribution, and forecasting You have recently been employed as a financial analyst to advise on the trading strategy for investing in the Australian dollar in a major Investment bank in Australia. You have been trained in the importance of foreign exchange rate forecasting stemming from the fact that the outcome of the bank’s decision taken now is contingent upon the value of the exchange rate prevailing sometime in the future, which you aim to forecast with utmost accuracy. The bank’s decisions pertain to a variety of activities, including speculation, hedging, investment, financing, pricing and strategic planning. Your forecast also feeds into the Technical Analysis and Mechanical Trading Rules Department of the bank which reports buy and sell signals. Your first assignment is to perform a thorough analysis using the foreign exchange rate between Australian and the US, S(USD/AUD). You note that the exchange rate is expressed in the indirect quotation from the Australian perspective. Using your skills, knowledge, training, and experience perform the following tasks: a. Draw continuously compounded returns of S(USD/AUD) graphically which can extract information on the distributional characteristics of the returns. What kind of distribution features you find. b. Using 68–95–99.7 normal rule of thumb, provide evidence that the distribution of the returns of S(USD/AUD) is different from the normal. c. Compare artificially (normally) created returns data with that of the actual returns with a valid graphical presentation. What characteristics of the returns do you look for to gauge differences in the two returns? d. What is your assessment for the directional move of S(USD/AUD) the next day based on your intuition and then based on a valid statistic? e. How would you convince your team to advise the client on whether to invest or not to invest in S(USD/AUD) for the next 30 days? Your argument must be based on an acceptable hypothesis testing procedure. f. What can you say about the efficiency of the FX market? Base your discussion on the following task: • Estimate the following models for S(USD/AUD): i. ???? = ?? + ????, Random Walk Model (RWDM) ii. ???? = ?? + ??????−1 + ????, Autoregressive of order 1 (AR(1)) model Note: Use last 100 trading days’ data: first 90 observations for estimation window and the last 10 observations for the holdout period. • Compute the individual forecasts and composite forecasts of S(USD/AUD) from the above models in the holdout period. Use regression method for weights in composite forecasts. Present the forecasting accuracy measures of MAE, MSE, and RMSE for forecasts. Report the best model for the forecast. g. Perform a risk assessment analysis for the next 100 days for the USD1 million invested in AUD in terms of 1% VaR with historical, parametric, and simulated methods. What are the risk implications for your investments on a daily basis? h. Video presentation. (Not more than 2 minutes) • What implications do you draw about the International Finance’s key variable exchange rate for its distributional characteristics and its market efficiency? Data source: http://www.rba.gov.au/statistics/historical-data.html#exchange-rates. The sample period is beginning in January 2003 to current. The data frequency is daily. Marking rule: Refer to the marking rubric for details on how this assessment will be marked Hints: Continuously compounded returns are defined as the ratio of log(et/et-1)*100, where e is the exchange rate. In part b, you can use the “SUMPRODUCT( )” function in Excel to look for the observations that are within certain range. Use Microsoft Excel for computations. --------------------END OF ASSIGNMENT------------------ http://www.rba.gov.au/statistics/historical-data.html#exchange-rates
Answered Same DayApr 01, 2021MAF760Deakin University

Answer To: PowerPoint Presentation Dr Aziz Hayat Department of Finance Deakin University ‹#› 1 b. Normal rule...

Lovenesh answered on Apr 05 2021
153 Votes
2003–2006 Historical Daily Exchange Rates of the Australian Dollar Against:
Data
    HISTORICAL DAILY
EXCHANGE RATES OF THE AUSTRALIAN DOLLAR AGAINST:                                                                    Rolling Avg 30 day Return
    Series ID    FXRUSD                    Mean    0.01%
    02-Jan-2003    0.5634        30 day rolling return            Std    0.0049        Total Count    4073
    03-Jan-2003    0.5629    -0.09%
    06-Jan-2003    0.5696    1.18%                                                    Reference Range
    07-Jan-2003    0.5745    0.86%                Mean + 1SD    0.51%        No of observation    2212        Inference :     NOT NORMAL        < 68%
    08-Jan-2003    0.5737    -0.14%                Mean - 1 SD    -0.48%        % of observation    54.31%
    09-Jan-2003    0.5773    0.63%
    10-Jan-2003    0.5759    -0.24%                Mean +2 SD    1.00%        No of observation    3425        Inference :     NOT NORMAL        <95%
    13-Jan-2003    0.5835    1.31%                Mean - 2 SD    -0.98%        % of observation    84.09%
    14-Jan-2003    0.5863    0.48%
    15-Jan-2003    0.5868    0.09%                Mean +3SD    0.51%        No of observation    3018        Inference :     NOT NORMAL        < 99.7 %
    16-Jan-2003    0.5869    0.02%                Mean-3SD    -1.47%        % of...
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