Determine the average exchange rate for the last year

Reference no: EM131074980

Project- Exchange rate forecasting

This project is for groups of two to four students, preferably three. (You cannot do this alone or in a group larger than four). As much as possible I will rely on you to form your own groups. Please let me know as early as possible who is in your group. Group will be randomly created for any class member that is not in a group by Wednesday, May 25.

Part 1.

Select three foreign currencies, at least one of which must be from list A and another from list B below. (Those lists indicate currencies that are either "free floating" or "floating" per the IMF classification.) The third may be any other currency of your choice, including those on lists A and B.

1. Obtain daily exchange rates for each currency (relative to the US dollar) for the last year.
2. Determine the average exchange rate for the last year.
3. Determine the daily percentage change in the exchange rate for each currency (i.e., the daily return on each currency).
4. For each currency, calculate the standard deviation of daily returns.
5. Comment on the recent strength of each currency (comparing the one-year average exchange rate with the exchange rate on May 23) and on the volatility of each currency.

Part 2.

Forecast the exchange rate for the three currencies selected in part 1 relative to the U.S. dollar in 15 days and one month (30 days) from May 23, 2016. In other words, forecast what the exchange rate will be for each currency on June 7 and June 22, 2016

Use the following forecasting techniques:

1. random walk (all three currencies, both 15- and 30-day forecast)
2. moving average (all three currencies, both 15- and 30-day forecast)
3. auto-regression (all three currencies, both 15- and 30-day forecast)
4. purchasing power parity (all three currencies, both 15- and 30-day forecast)
5. international fisher effect (all three currencies, both 15- and 30-day forecast)
6. unbiased forward rate (all three currencies, 30-day forecast only)
7. structural model (one currency, 30-day forecast only)
8. weighted average (all three currencies, both 15- and 30-day forecast)
9. expert forecast (all three currencies, 30-day forecast only)

Part 3.

For each currency, based on the exchange rate on May 23 and the weighted average forecasts,

1. recommend whether an investor hoping to profit from the 15-day change in the exchange rate alone should buy or sell the foreign currency today, and

2. recommend whether an investor hoping to profit from the 30-day change in the exchange rate alone should buy or sell the foreign currency today.

Your group should submit:

(1) forecasts for each currency using each method with enough backup information (equations and sources) to determine how you obtain and calculate the forecast;

(2) a brief written explanation if necessary to support the quantitative forecasts (For example, you should articulate reasons for your choice of variables in the structural model, and for choice of weights in the weighted average.);

(3) an explanation of reasoning behind the "expert" forecast; and

(4) the purchase/sale recommendations for each foreign currency for each investment horizon.

All group members will receive the same grade on this project. It will be up to you to allocate work among the members of the group. Grades reflect correct application of the forecasting techniques and whether recommendations are consistent with the weighted average forecast. (Grades do not depend on how accurate the forecasts are or whether an investor would actually realize a profit by following the trading recommendations.)

List A - Free floating

Australia (dollar)	Euro	Norway (krone)	Sweden (krona)
Canada (dollar)	Japan (yen)	Poland (zloty)	United Kingdom (pound)
Chile (peso)	Mexico (peso)	Somalia (shilling)

List B - Floating

Afghanistan (afghani)	Indonesia (rupiah)	Mozambique (metical)	Sierra Leone (leone)
Albania (lek)	Israel (new shekel)	New Zealand (dollar)	South Africa (rand)
Brazil (real)	Kenya (shilling)	Papua New Guinea (kina)	Tanzania (shilling)
Columbia (peso)	Korea (South) (won)	Paraguay (guarani)	Thailand (baht)
Georgia (lari)	Madagascar (ariary)	Peru (sol)	Turkey (lira)
Ghana (cedi)	Malawi (kwacha)	Philippines (peso)	Uganda (shilling)
Hungary (forint)	Mauritius (ouguiya)	Romania (leu)	Ukraine (hryvnia)
Iceland (króna)	Moldova (leu)	Serbia (dinar)	Uruguay (peso)
India (rupee)	Mongolia (tögrög)	Seychelles (rupee)	Zambia (kwacha)

Internet sites that may provide information useful in forecasting:

Pacific Exchange Rate Service, UBC, fx.sauder.ubc.ca/ (historical exchange rates - daily, weekly, monthly averages; Canadian dollar forward rates)

OANDA website,www.oanda.com/currency/historical-rates/(historical exchange rates - daily),

US Federal Reserve, Board of Governors databases, www.federalreserve.gov/econresdata/default.htm(historical US data - mostly banking data)

Federal Reserve Economic Databases (FRED), 8th Federal Reserve District, research.stlouisfed.org/fred2/ (historical US data in a variety of areas including, trade (some country specific), GDP, inflation, employment, etc.)

European central bank statistics,www.ecb.int/stats/html/index.en.html (interest rates and other statistics for the Euro area)

Other country's central banks, links available at https://www.bis.org/ (statistical data for the county, e.g., interest rates, GDP, reserves and etc.)

IMF's World Economic Outlook database,https://www.imf.org/external/pubs/ft/weo/2014/01/weodata/index.aspx(historical and forecasted economic data for IMF members, e.g., inflation rates)

IMF member economic data summaries, linked throughdsbb.imf.org/Pages/SDDS/CountryList.aspx and dsbb.imf.org/Pages/GDDS/CountryList.aspx (current economic data for IMF members and links to original sources)

Commercial banks in a country may have information about interest rates and forward rates.

Currency dealers sometimes quote forward rates (or forward premia or discounts - in either percent or basis points). See e.g. www.fxstreet.com/rates-charts/forward-rates/.

If you would like to see some forecasts generated by others, see e.g. https://www.forecasts.org/, which uses "artificial intelligence" techniques (could mean statistical methods or non-statistical methods such as "neural nets").

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CIA World Fact Book,www.cia.gov/cia/publications/factbook/geos/gh.html (general information about countries)

Lots of other sources of information exist. (A smaller number provide the information at no cost and without requiring registration.) If you locate one that seems particularly useful, send me the link so I can include it.

Reference no: EM131074980

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