Swiss franc currency
Swiss franc is the chosen currency for this project.
- Look at the 25-30-year history of the exchange rates relative to US dollar (and if necessary relative to other major world currencies). Identify any significant changes (currency crisis, devaluations/ revaluation. depreciation/appreciation etc.) Briefly describe those events. In your description indicate what currency regimes that a country was following prior and after every significant event. Monthly or annual data can be used, but graphs of exchange rate changes around significant events could present daily/weekly data, if necessary.
- Obtain end of the month exchange rates covering the last 36 months ending October 2022 for a currency relative to the U.S. dollar. Prepare a graph of that exchange rate history that shows the amount of your currency required to purchase one U.S dollar. Using reliable sources and data explain the exchange rate pattern (including economic situation in the country, any political changes (if relevant), central bank actions, etc.)
- Predict where the exchange rate will be in one year (October 2023). You will need other data including inflation and interest rates. (you should try several different methods of forecast: for example, PPP prediction (test if PPP holds. and use the model to forecast the rate,) try to predict one year forward rate based on IRP, use Efficient Market approach, or even Technical approach. Discuss your forecast results.
- The paper should be three to five pages plus graphs and exhibits with all references cited. Please, submit your Excel file too.
Sample Solution
regards to the osmosis of pieces into lumps. Mill operator recognizes pieces and lumps of data, the differentiation being that a piece is comprised of various pieces of data. It is fascinating to take note of that while there is a limited ability to recall lumps of data, how much pieces in every one of those lumps can change broadly (Miller, 1956). Anyway it’s anything but a straightforward instance of having the memorable option huge pieces right away, somewhat that as each piece turns out to be more natural, it very well may be acclimatized into a lump, which is then recollected itself. Recoding is the interaction by which individual pieces are ‘recoded’ and allocated to lumps. Consequently the ends that can be drawn from Miller’s unique work is that, while there is an acknowledged breaking point to the quantity of pieces of data that can be put away in prompt (present moment) memory, how much data inside every one of those lumps can be very high, without unfavorably influencing the review of similar number>
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