PARALLEL MARKETS To PUT (Finance and Banking)

PARALLEL MARKETS

A government-tolerated alternative to the official foreign exchange market, such as a black market. Some countries unofficially acknowledge the benefits of such a market by allowing the market to exist openly.

PARITY CONDITIONS

More exactly called international exchange rate parity conditions, parity conditions are fundamental economic relationships that help to explain exchange rate movements. There are five key relationships among spot exchange rates, forward rates, inflations rates, and interest rates.

Parity Condition	Relationship in Exhibit 87
Purchasing Power Parity	A
Fisher Effect	B
International Fisher Effect	C
Interest Rate Parity	D
Forward Rates as Unbiased Predictor of Future Spot Rates	E

Exhibit 88 displays that under a freely floating exchange rate system, future spot exchange rates are theoretically determined by differing national rates of inflation, interest rates, and the forward premium or discount on each currency. Parity conditions are for any percentage change, or difference in rates. Hypothetical data used in the exhibit are as follows:

1.	Currency rates:
	a. Spot Rate (indirect)	Sj = ¥104/$
	b. Forward Rate (one year)	F = ¥100/$
	c. Expected Spot Rate	S2 = ¥100/$
	d. Expected change in S:	S1-S2 = 10-4-100 = 4% S2 = 100 = 4 %
	e. Forward premium on yen:	104 – 1QQ = 4% 1 QQ – ^ rn
2.	Expected rate of inflation:
	a. Japan	2%
	b. United States	6%
	c. Difference	4%
3.	Interest on 1-year Government	Security
	a. Japan	1%
	b. United States	5%
	c. Deference	4%

EXHIBIT 88

International Parity Conditions

PAR VALUE

1. For a country’s currency, the value set by a government, by agreement or regulation, on its currency in terms of other currencies. At Bretton Woods, other currencies were assigned par values in terms of the U.S. dollar.

2. For a stock, the dollar amount assigned each share of stock in the company’s charter. For preferred issues and bonds, the value on which the issuer promises to pay dividends.

PEGGED EXCHANGE RATES

An exchange rate system under which a country establishes a fixed exchange rate with another major currency and, as a result, values of pegged currencies move together over time. For example, Kuwait pegs its currency to a mix of currencies that roughly represent the composite of currencies used by its trading partners to buy its oil.

PERFORMANCE BOND

Previously referred to as margin, funds that must be deposited as a collateral by a customer with his or her broker, by a broker with a clearing member, or by a clearing member with the Clearing House. The performance bond helps to ensure the financial integrity of brokers, clearing members, and the Exchange as a whole.

PERFORMANCE BOND CALL

Previously referred to as margin call, a demand for additional funds because of adverse pricemovement.

PESETA

Monetary unit of Spain, Andorra, Balearic Island, and Canary Islands. PESO

The currency of the following countries: Argentina, Chile, Columbia, Cuba, Dominican Republic, Mexico, Republic of Philippines, and Uruguay.

PLAIN-VANILLA

Often called generic, a security, especially a bond or a swap, issued with standard features. PLAIN-VANILLA SWAPS

A plain-vanilla swap is a bank-intermediated interest rate swap. Typically, in this type of swap, a BBB-rated U.S. corporation is paired with an AAA-rated foreign bank. The BBB corporation wants to borrow at fixed rates but is discouraged from doing so by the high rates attached to its low rating. The company can borrow in the floating-rate market, however. The AAA foreign bank wants to borrow at floating rates, as its assets are tied to the London Interbank Offer Rate (LIBOR). The bank normally pays at LIBOR to obtain lendable funds. It is able to borrow at fixed rates, which are better than those the corporation could get. When the swap is planned, the bank borrows at fixed rates in the Eurobond market, and the BBB corporation borrows at floating rates. With this done, the two then swap rates on their respective loans. The corporation entices the bank into doing this by discounting the floating rate to the bank by LIBOR minus 0.25%. In return, the bank gives the BBB corporation a fixed rate that is better than the one the corporation could acquire on its own.

EXAMPLE 98

Assume the BBB firm can borrow at a fixed rate of 12.5%.

1. AAA bank issues 11% fixed-rate debt.

2. BBB firm taps floating-rate market at LIBOR plus 0.5%.

3. BBB firm swaps its floating rate to bank at LIBOR minus 0.25%.

4. AAA bank swaps its 11% fixed rate to BBB firm.

The net result is the BBB firm saves 150 basis points and passes 75 of them on to the AAA bank; the bank saves 25 basis points on the normal floating rate.

POINT

One percent (%).

POINTS QUOTATION

A forward rate quotation expressed as only the number of decimal points.

POLITICAL RISK

Also called sovereign risk, political risk implies unwanted consequence of political activity. It is commonly interpreted as (usually host) government interference with business operations. But political changes that are gradual and progressive and neither unexpected nor difficult to anticipate do not constitute political risk. Political risk means potential actions by a host government that would threaten the value of an MNC’s investment. It is the risk associated with political or sovereign uncertainty. Clearly, political factors are a major determinant of the attractiveness for investment in any country. Examples of political risk are government expropriation of property, currency conversion restrictions, and import barriers. Countries viewed as likely candidates for internal political upheaval or with a pronounced trend toward elimination of the private sector will be unattractive to all investors, foreign and domestic alike. There is no reason to believe that local investors will be systematically optimistic regarding their country’s future. When political risks increase significantly, such investors will attempt to diversify from the home market as rapidly as will foreigners. As a result, prices will fall until someone will be satisfied to hold the securities of a risky country. Political instability, limited track records, poor statistics all make gauging risk a risky business. Several companies try to evaluate the risk in some of the countries that are receiving the most attention from foreign investors:

• Euromoney Magazine’s Country Risk Ratings, published twice a year, are based on a measure of different countries’ access to international credit, trade finance, and political risk and the country’s payment record. The rankings are generally confirmed by political risk insurers and top syndicate managers in the Euromarkets. See Exhibit 89.

• International Country Risk Guide, published by International Business Communications, Ltd., a London company, offers a composite risk rating, as well as individual ratings for political, financial, and economic risk. The political variable—which makes up half of the composite index—includes factors such as government corruption and how economic expectations diverge from reality. The financial rating looks at such things as the likelihood of losses from exchange controls and loan defaults. Finally, economic ratings consider such factors as inflation and debt-service costs.

• Rating by Economist Intelligence Unit, a New York-based subsidiary of the Economist Group, London, is based on such factors as external debt and trends in the current account, the consistency of the government policy, foreign-exchange reserves, and the quality of economic management.

• Data Book (quarterly), published by Thompson BankWatch, Inc., 61 Broadway, New York, NY 10006, provides a Thompson country rating assessing overall political and economic stability of a country in which a bank is domiciled.

EXHIBIT 89

Euromoney Magazine’s Country Risk Ratings, September 2000 (continued)

			Total
			Score
Sep-00	Mar-00		Weighting: 100
1	1	Luxembourg	99.02
2	2	Switzerland	96.89
3	4	United States	94.25
4	3	Norway	94.24
5	6	Netherlands	92.90
6	5	Denmark	92.77
7	11	Germany	92.77
8	8	France	92.33
9	7	Austria	92.29
10	12	United Kingdom	91.54
11	9	Finland	91.38
12	10	Sweden	91.12
13	14	Japan	90.70
14	15	Singapore	90.04
15	16	Ireland	89.71
16	13	Belgium	89.63
17	17	Canada	89.10
18	18	Australia	88.01
19	20	Spain	87.29
20	19	Italy	87.11
21	21	Iceland	86.72

			Debt in
Political	Economic	Debt	Default or	Credit
Risk	Performance	Indicators	Rescheduled	Ratings
25	25	10	10	10
24.38	25.00	10.00	10.00	10.00
25.00	21.89	10.00	10.00	10.00
24.94	19.30	10.00	10.00	10.00
23.90	20.42	10.00	10.00	10.00
24.66	18.27	10.00	10.00	10.00
23.09	19.95	10.00	10.00	9.79
24.52	18.27	10.00	10.00	10.00
24.34	18.01	10.00	10.00	10.00
23.69	18.63	10.00	10.00	10.00
24.63	16.92	10.00	10.00	10.00
23.52	18.23	10.00	10.00	9.69
23.65	18.65	9.50	10.00	9.38
23.51	18.41	10.00	10.00	9.58
22.39	19.07	10.00	10.00	9.58
23.42	16.53	10.00	10.00	9.79
23.07	17.84	10.00	10.00	8.75
23.75	16.24	10.00	10.00	9.17
22.69	16.60	10.00	10.00	9.17
23.03	14.93	10.00	10.00	9.38
22.61	16.14	10.00	10.00	8.44
19.91	18.71	10.00	10.00	8.54

EXHIBIT 89

Euromoney Magazine’s Country Risk Ratings, September 2000 (continued)

				Total	Political	Economic	Debt	Debt in Default or	Credit
				Score	Risk	Performance	Indicators	Rescheduled	Ratings
Sep-00	Mar-00		Weighting:	100	25	25	10	10	10
22	22	New Zealand		85.27	21.42	14.54	10.00	10.00	9.38
23	23	Portugal		83.25	22.21	13.72	10.00	10.00	8.75
24	24	Taiwan		80.65	20.46	14.95	9.87	10.00	8.75
25	25	Greece		78.66	20.13	13.35	10.00	10.00	6.25
26	27	Hong Kong		77.42	18.22	15.95	10.00	10.00	7.08
27	26	Cyprus		76.62	18.18	13.49	9.76	10.00	7.50
28	29	United Arab Emirates		75.59	18.07	14.59	9.98	10.00	6.88
29	30	Bermuda		73.67	18.67	13.71	10.00	10.00	8.96
30	28	Kuwait		73.28	16.35	15.45	9.64	10.00	6.67
31	33	Malta		72.89	18.40	14.20	9.95	10.00	7.08
32	31	Israel		72.68	16.56	13.70	9.74	10.00	6.88
33	32	Slovenia		68.93	17.43	12.31	5.66	10.00	7.29
34	38	Saudi Arabia		68.27	16.74	10.85	9.79	10.00	4.38
35	34	Qatar		68.14	16.10	12.20	8.50	10.00	5.31
36	35	Brunei		66.84	16.40	18.44	10.00	10.00	0.00
37	40	Korea South		66.28	17.50	12.43	9.05	10.00	5.83
38	36	Oman		66.17	15.57	10.27	9.49	10.00	5.00
39	41	Chile		65.83	18.24	10.39	8.67	10.00	6.88
40	42	Hungary		65.24	17.06	10.78	8.35	10.00	6.04
41	39	Bahrain		65.20	15.22	10.56	10.00	10.00	3.75
42	43	Poland		63.59	16.56	9.92	9.26	10.00	6.25
43	44	Czech Republic		63.14	17.11	9.96	8.94	10.00	6.46
44	45	Malaysia		61.11	15.86	10.08	8.88	10.00	5.42
45	48	China		59.75	15.64	9.46	9.58	10.00	5.83
46	49	Mexico		59.68	15.68	9.28	8.81	10.00	4.58

47	54	Thailand	59.55
48	37	Bahamas	59.46
49	47	Mauritius	59.08
50	51	South Africa	57.71
51	46	Tunisia	57.48
52	75	Barbados	57.32
53	50	Uruguay	56.79
54	52	Egypt	56.36
55	55	Estonia	55.69
56	53	Morocco	55.11
57	57	Argentina	54.97
58	60	Trinidad & Tobago	54.18
59	58	India	53.75
60	67	Costa Rica	53.42
61	59	Latvia	53.11
62	66	Slovak Republic	52.95
63	56	Philippines	52.81
64	65	Turkey	52.74
65	64	Panama	52.20
66	62	Botswana	51.83
67	69	Brazil	51.31
68	63	El Salvador	51.12
69	61	Lithuania	50.79
70	70	Croatia	49.67
71	68	Colombia	48.88
72	71	Fiji	47.38
73	76	Guatemala	47.31
74	73	Lebanon	46.85
75	74	Jordan	46.32
76	78	Venezuela	43.85
77	77	Dominican Republic	43.84
78	90	Jamaica	42.70

14.89	8.55	8.44	10.00	4.79
16.50	6.03	10.00	10.00	5.31
14.16	11.44	8.90	10.00	5.00
13.85	9.51	9.41	10.00	4.79
13.87	10.00	8.80	10.00	5.21
15.62	10.71	9.43	10.00	6.56
14.19	9.41	8.83	10.00	4.79
14.48	9.21	9.19	9.90	4.79
13.85	9.31	9.61	10.00	5.63
12.76	9.27	8.55	10.00	4.38
12.81	9.58	7.68	10.00	3.13
14.10	10.95	9.10	10.00	5.00
13.79	7.90	9.11	10.00	3.96
13.07	10.88	9.20	10.00	3.54
12.84	8.56	9.62	10.00	5.42
12.86	8.57	8.76	10.00	4.38
13.23	7.61	8.75	10.00	4.38
14.07	8.54	8.74	10.00	2.08
12.02	9.34	8.54	10.00	4.38
15.14	9.93	9.82	10.00	0.00
12.49	8.66	7.51	9.96	2.29
10.98	9.63	9.29	10.00	4.58
12.54	8.28	9.49	10.00	3.96
11.69	8.49	9.14	7.67	4.58
11.26	7.13	8.64	10.00	3.96
10.12	9.18	9.68	10.00	3.75
9.77	8.84	9.33	10.00	3.13
10.33	7.29	8.62	10.00	2.50
11.22	7.96	7.56	8.49	3.44
10.71	6.85	8.72	10.00	1.67
10.25	8.81	9.45	9.19	1.25
7.73	8.76	8.74	10.00	2.19

EXHIBIT 89

Euromoney Magazine’s Country Risk Ratings, September 2000 (continued)

								Debt in
				Total	Political	Economic	Debt	Default or	Credit
				Score	Risk	Performance	Indicators	Rescheduled	Ratings
Sep-00	Mar-00		Weighting:	100	25	25	10	10	10
79	85	Bolivia		42.52	8.54	7.10	8.08	10.00	2.81
80	84	Bulgaria		42.51	10.46	6.69	8.23	10.00	1.88
81	88	Kazakhstan		42.46	9.28	6.65	9.21	10.00	2.29
82	86	Paraguay		41.31	9.74	7.01	9.45	10.00	1.88
83	80	Iran		40.64	8.99	7.09	9.25	10.00	1.25
84	82	Belize		40.61	10.81	5.30	8.82	10.00	3.13
85	79	Sri Lanka		39.81	9.37	5.82	9.08	10.00	0.00
86	91	Seychelles		39.71	9.14	6.32	9.14	10.00	0.00
87	94	Macau		39.59	14.15	12.75	0.00	0.00	5.63
88	125	Maldives		39.22	9.64	8.23	9.03	10.00	0.00
89	92	Peru		39.12	10.63	7.50	9.15	1.25	3.33
90	93	Syria		38.95	9.67	6.62	7.96	10.00	0.00
91	116	Honduras		38.77	8.00	7.12	8.13	10.00	1.25
92	136	Dominica		38.60	7.39	9.98	9.08	10.00	0.00
93	115	Indonesia		38.48	7.98	5.96	6.65	8.65	0.63
94	87	Vietnam		38.36	9.82	6.01	8.64	9.96	1.88
95	133	Russia		37.88	8.02	6.65	8.62	8.26	0.42
96	99	Algeria		37.71	8.27	6.77	7.94	8.90	0.00
97	72	Ghana		37.64	8.57	6.61	7.92	10.00	0.00
98	89	Kenya		37.64	7.41	7.37	8.61	10.00	0.00
99	102	Gambia		37.63	7.85	7.67	9.43	10.00	0.00
100	120	Macedonia (FYR)		37.37	6.30	7.67	8.18	10.00	0.00
101	83	Papua New Guinea		37.17	8.49	5.33	8.74	10.00	2.29
102	103	Azerbaijan		36.94	8.42	6.72	9.22	10.00	0.00

103	107	Romania	36.62
104	100	Lesotho	36.42
105	98	St Lucia	35.91
106	118	Kyrgyz Republic	35.76
107	110	Equatorial Guinea	35.69
108	95	Bangladesh	34.96
109	96	Senegal	34.28
110	164	Uzbekistan	34.15
111	137	Yemen	33.99
112	101	Uganda	33.73
113	112	Zimbabwe	33.43
114	105	Cape Verde	33.06
115	134	Ukraine	33.06
116	97	Gabon	33.03
117	81	Swaziland	32.92
118	131	Cambodia	32.90
119	106	Nepal	32.72
120	123	Cote d’lvoire	32.47
121	114	St Vincent & the Grenadines	32.14
122	108	Nigeria	32.09
123	129	Pakistan	31.99
124	119	Burkina Faso	31.95
125	132	Turkmenistan	31.81
126	109	Malawi	31.66
127	147	Samoa	31.28
128	130	Ethiopia	30.95
129	140	Belarus	30.74
130	139	Mongolia	30.64
131	144	Armenia	30.47
132	121	Grenada	30.41
133	155	Georgia	30.40
134	135	Solomon Islands	30.39

8.17	5.32	8.89	10.00	0.83
8.47	6.74	8.54	10.00	0.00
9.98	4.57	8.69	10.00	0.00
8.05	8.13	8.59	10.00	0.00
4.19	9.88	8.93	10.00	0.00
7.73	5.48	9.24	10.00	0.00
6.28	7.03	8.22	10.00	0.00
6.76	6.35	9.43	10.00	0.00
7.57	5.86	8.38	9.95	0.00
6.77	6.68	8.95	7.72	0.00
4.22	5.04	7.88	10.00	0.00
6.33	4.95	8.89	10.00	0.00
6.05	5.68	9.26	9.61	0.00
6.86	8.42	8.42	8.26	0.00
9.09	8.96	0.00	10.00	0.00
3.81	9.40	8.80	10.00	0.00
6.24	5.38	8.96	10.00	0.00
5.84	6.56	7.29	8.70	0.00
7.53	4.27	7.70	10.00	0.00
4.88	6.20	8.48	10.00	0.00
6.36	4.87	8.61	10.00	0.94
6.27	4.65	8.85	10.00	0.00
5.98	5.96	7.32	10.00	0.94
4.99	5.55	7.73	10.00	0.00
7.75	0.87	8.52	10.00	0.00
4.79	7.62	7.41	9.80	0.00
5.77	3.24	9.82	10.00	0.00
6.10	3.68	8.71	10.00	1.25
6.22	3.44	8.91	10.00	0.00
8.09	1.46	8.71	10.00	0.00
4.19	6.05	9.26	10.00	0.00
6.86	0.79	9.25	10.00	0.00

EXHIBIT 89

Euromoney Magazine’s Country Risk Ratings, September 2000 (continued)

				Total Score	Political Risk	Economic Performance	Debt Indicators	Debt in Default or Rescheduled	Credit Ratings
Sep-00	Mar-00		Weighting:	100	25	25	10	10	10
135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159	146 127 126 117 153 142 113 145 111 157 141 152 104 150 149 138 122 171 158 154 124 156 168 148	Albania Vanuatu Cameroon Madagascar Ecuador Moldova Tanzania Mozambique Togo Bhutan Benin Guyana Mali Chad Mauritania Zambia Guinea Myanmar Nicaragua Sudan Niger Micronesia (Fed. States) Central African Republic Djibouti Haiti		30.38 30.02 29.74 29.48 29.28 29.24 28.89 28.63 28.63 28.53 28.51 28.27 28.15 27.79 27.19 27.04 26.77 26.35 26.34 25.45 25.43 25.24 25.13 24.63 24.32	5.40 6.19 5.64 3.90 3.90 4.90 4.96 4.60 5.46 6.19 4.00 6.69 4.66 3.04 3.52 3.86 5.02 5.03 4.71 2.41 2.67 13.06 2.86 3.30 2.71	4.56 0.92 5.52 5.66 5.34 2.42 6.12 5.48 3.61 0.71 3.69 3.79 3.52 3.51 5.33 6.35 3.19 3.24 5.76 3.33 3.17 0.93 4.27 0.91 0.69	9.49 9.58 7.73 7.87 7.94 8.37 6.63 6.31 7.69 9.22 8.64 6.10 8.02 8.73 5.66 6.57 8.04 7.19 4.29 8.82 8.26 0.00 8.11 9.17 9.40	10.00 10.00 7.72 9.37 10.00 10.00 8.79 8.84 9.19 10.00 10.00 10.00 9.99 9.82 10.00 9.32 9.62 10.00 8.72 10.00 9.89 10.00 9.00 10.00 10.00	0.00 0.00 0.00 0.00 0.00 0.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.25 0.00 0.00 0.00 0.00 0.00 0.00

160	128	Tonga	24.01
161	163	Laos	23.99
162	143	Namibia	23.65
163	176	Suriname	23.11
164	162	Sierra Leone	23.06
165	161	Dem. Rep. of the Congo (Zaire)	22.87
166	—	Eritrea	22.18
167	159	Congo	22.03
168	151	Rwanda	21.13
169	167	Angola	20.97
170	—	Burundi	20.81
171	166	Guinea-Bissau	20.04
172	165	New Caledonia	19.96
173	—	Marshall Islands	19.44
174	174	Antigua & Barbuda	19.43
175	169	Libya	19.30
176	172	Tajikistan	17.76
177	160	Sao Tome & Principe	16.67
178	—	Bosnia-Herzegovina	15.82
179	173	Liberia	15.30
180	175	Yugoslavia (Fed. Republic)	14.81
181	170	Somalia	14.76
182	177	Cuba	10.67
183	178	Iraq	9.04
184	179	Korea North	4.72
185	180	Afghanistan	2.81

8.64	1.06	0.00	10.00	0.00
6.06	0.00	7.04	10.00	0.00
10.29	7.58	0.00	0.00	0.00
7.36	3.22	0.00	10.00	1.25
2.62	2.96	6.62	9.97	0.00
2.35	2.61	7.01	10.00	0.00
1.33	0.64	9.31	10.00	0.00
3.66	3.44	5.75	9.19	0.00
1.52	0.77	9.55	8.40	0.00
3.30	3.29	4.44	8.42	0.00
2.29	0.62	7.01	10.00	0.00
4.19	2.56	2.47	9.93	0.00
12.86	3.67	0.00	0.00	0.00
12.19	1.00	0.00	0.00	0.00
4.61	2.87	0.00	10.00	0.00
9.20	8.19	0.00	0.00	0.00
3.09	4.42	8.99	0.00	0.00
2.41	0.65	0.00	10.00	0.00
3.38	3.25	8.16	0.00	0.00
3.91	0.85	0.00	10.00	0.00
1.99	1.73	0.00	10.00	0.00
2.29	0.74	0.00	10.00	0.00
3.80	5.81	0.00	0.00	0.00
2.36	5.80	0.00	0.00	0.00
2.98	0.85	0.00	0.00	0.00
0.00	1.56	0.00	0.00	0.00

A. Methods for Dealing with Political Risk

To the extent that forecasting political risks is a formidable task, what can an MNC do to cope with them? There are several methods suggested.

• Avoidance—Try to avoid political risk by minimizing activities in or with countries that are considered to be of high risk and by using a higher discount rate for projects in riskier countries.

• Adaptation—Try to reduce such risk by adapting the activities (for example, by using hedging techniques).

• Diversification—Diversity across national borders, so that problems in one country do not risk the company.

• Risk transfer—Buy insurance policies for political risks. Most developed nations offer insurance for political risk to their exporters. Examples include: in the U.S., the Eximbank offers policies to exporters that cover such political risks as war, currency inconvertibility, and civil unrest. Furthermore, the Overseas Private Investment Corporation (OPIC) offers policies to U.S. foreign investors to cover such risks as currency inconvertibility, civil or foreign war damages, or expropriation. In the U.K., similar policies are offered by the Export Credit Guarantee Department (ECGD); in Canada, by the Export Development Council (EDC); and in Germany, by an agency called Hermes.

PORTFOLIO DIVERSIFICATION

The rationale behind portfolio diversification is the reduction of risk. The main method of reducing the risk of a portfolio is the combining of assets which are not perfectly positively correlated in their returns.

EXAMPLE 99

Consider the following two-asset portfolio:

Stock	Return	Risk	Correlation
Wal-mart (US)	18.60%	22.80%	0.20
Smith-Kline (UK)	16.00%	24.00%

By changing the correlation coefficient, the benefits of risk reduction can be clearly observed, as shown in Exhibits 90 and 91.

EXHIBIT 90

Portfolio Analysis

Weight of	Weight of	Expected
Wal-mart in	Smith-Kline	Return	Expected Risk
Portfolio	in Portfolio	(percent)	(percent)
1.00	0.00	18.60%	22.80%
0.95	0.05	18.47%	21.93%
0.90	0.10	18.34%	21.13%
0.85	0.15	18.21%	20.41%
0.80	0.20	18.08%	19.77%
0.75	0.25	17.95%	19.22%
0.70	0.30	17.82%	18.78%

0.65	0.35	17.69%	18.44%
0.60	0.40	17.56%	18.22%
0.55	0.45	17.43%	18.11%
0.50	0.50	17.30%	18.13%
0.45	0.55	17.17%	18.27%
0.40	0.60	17.04%	18.52%
0.35	0.65	16.91%	18.89%
0.30	0.70	16.78%	19.36%
0.20	0.80	16.52%	20.60%
0.25	0.75	16.65%	19.94%
0.20	0.80	16.52%	20.60%
0.15	0.85	16.39%	21.35%
0.10	0.90	16.26%	22.17%
0.05	0.95	16.13%	23.06%
0.00	1.00	16.00%	24.00%

EXHBIT 91

Portfolio Analysis: Risk and Return Two Asset Portfolio

PORTFOLIO INVESTMENTS

1. Investing in a variety of assets to reduce risk by diversification. An example of a portfolio is a mutual fund that consists of a mix of assets which are professionally managed and that seeks to reduce risk by diversification. Investors can own a variety of securities with a minimal capital investment. Since mutual funds are professionally managed, they tend to involve less risk. To reduce risk, securities in a portfolio should have negative or no correlations to each other.

2. Investments that are undertaken for the sake of obtaining investment income or capital gains rather than entrepreneurial income which is the case with foreign direct investments (FDI). This typically involves the ownership of stocks and/or bonds issued by public or private agencies of a foreign country. The investors are not interested in assuming control of the firm.

PORTFOLIO THEORY

Theory advanced by H. Markowitz in attempting a well-diversified portfolio. The central theme of the theory is that rational investors behave in a way that reflects their aversion to taking increased risk without being compensated by an adequate increase in expected return. Also, for any given expected return, most investors will prefer a lower risk, and for any given level of risk, they will prefer a higher return to a lower return. Markowitz showed how quadratic programming could be used to calculate a set of “efficient” portfolios. An investor then will choose among a set of efficient portfolios the best that is consistent with the risk profile of the investor.

Most financial assets are not held in isolation but rather as part of a portfolio. Therefore, the risk-return analysis should not be confined to single assets only. What is important is the expected return on the portfolio (not just the return on one asset) and the portfolio’s risk.

A. Portfolio Return

The expected return on a portfolio (r_p) is simply the weighted average return of the individual sets in the portfolio, the weights being the fraction of the total funds invested in each asset:

where

r_j = expected return on each individual asset Wj = fraction for each respective asset investment n = number of assets in the portfolio

E Wj =

j =1

EXAMPLE 100

A portfolio consists of assets A and B. Asset A makes up one-third of the portfolio and has an expected return of 18%. Asset B makes up the other two-thirds of the portfolio and is expected to earn 9%. The expected return on the portfolio is:

Asset	Return (rj)	Fraction (Wj)	wjrj
A	18%	1/3	1/3 x 18% =	6%
B	9%	2/3	2/3 x 9% =	6%
			rp =	12%

B. Portfolio Risk

Unlike returns, the risk of a portfolio (op) is not simply the weighted average of the standard deviations of the individual assets in the contribution, for a portfolio’s risk is also dependent on the correlation coefficients of its assets. The correlation coefficient (p) is a measure of the degree to which two variables “move” together. It has a numerical value that ranges from -1.0 to 1.0. In a two-asset (A and B) portfolio, the portfolio risk is defined as:

where

o_A and o_B = standard deviations of assets A and B

w_a and w_b = weights, or fractions, of total funds invested in assets A and B pAB = the correlation coefficient between assets A and B.

Incidentally, the correlation coefficient is the measurement of joint movement between two securities.

C. Diversification

As can be seen in the above formula, the portfolio risk, measured in terms of o is not the weighted average of the individual asset risks in the portfolio. We have in the formula a third term (p), which makes a significant contribution to the overall portfolio risk. What the formula basically shows is that portfolio risk can be minimized or completely eliminated by diversification. The degree of reduction in portfolio risk depends upon the correlation between the assets being combined. Generally speaking, by combining two perfectly negatively correlated assets (p = -1.0), we are able to eliminate the risk completely. In the real world, however, most securities are negatively, but not perfectly correlated. In fact, most assets are positively correlated. We could still reduce the portfolio risk by combining even positively correlated assets. An example of the latter might be ownership of two automobile stocks or two housing stocks.

EXAMPLE 101

Assume the following:

Asset	o	w
A	20%	1/3
B	10%	2/3

The portfolio risk then is:

(a) Now assume that the correlation coefficient between A and B is +1 (a perfectly positive correlation). This means that when the value of asset A increases in response to market conditions,so does the value of asset B, and it does so at exactly the same rate as A. The portfolio risk when p_AB = +1 then becomes:

(b) If p_AB = 0, the assets lack correlation and the portfolio risk is simply the risk of the expected returns on the assets, i.e., the weighted average of the standard deviations of the individual assets in the portfolio. Therefore, when p_AB = 0, the portfolio risk for this example is:

(c) If p_AB = -1 (a perfectly negative correlation coefficient), then as the price of A rises, the price of B declines at the very same rate. In such a case, risk would be completely eliminated. Therefore, when p_AB = -1, the portfolio risk is

When we compare the results of (a), (b), and (c), we see that a positive correlation between assets increases a portfolio’s risk above the level found at zero correlation, while a perfectly negative correlation eliminates that risk.

EXAMPLE 102

To illustrate the point of diversification, assume data on the following three securities are as follows:

Year	Security X (%)	Security Y (%)	Security Z (%)
20 x 1	10	50	10
20 x 2	20	40	20
20 x 3	30	30	30
20 x 4	40	20	40
20 x 5	50	10	50
rj	30	30	30
Op	14.1 4	14.1 4	14.1 4

Note here that securities X and Y have a perfectly negative correlation, and securities X and Z have a perfectly positive correlation. Notice what happens to the portfolio risk when X and Y, and X and Z are combined. Assume that funds are split equally between the two securities in each portfolio.

	Portfolio XY	Portfolio XZ
Year	(50% – 50%)	(50% – 50%)
20 x 1	30	10
20 x 2	30	20
20 x 3	30	30
20 x 4	30	40
20 x 5	30	50
rp	30	30
	0	14.14

Again, see that the two perfectly negative correlated securities (XY) result in a zero overall risk.

D. Markowitz’s Efficient Portfolio

Dr. Harry Markowitz, in the early 1950s, provided a theoretical framework for the systematic composition of optimum portfolios. Using a technique called quadratic programming, he attempted to select from among hundreds of individual securities, given certain basic information supplied by portfolio managers and security analysts. He also weighted these selections in composing portfolios. The central theme of Markowitz’s work is that rational investors behave in a way reflecting their aversion to taking increased risk without being compensated by an adequate increase in expected return. Also, for any given expected return, most investors will prefer a lower risk and, for any given level of risk, prefer a higher return to a lower return. Markowitz showed how quadratic programming could be used to calculate a set of “efficient” portfolios such as illustrated by the curve in Exhibit 92.

EXHIBIT 92

Efficient Frontier

In Exhibit 93, an efficient set of portfolios that lie along the ABC line, called “efficient frontier,” is noted. Along this frontier, the investor can receive a maximum return for a given level of risk or a minimum risk for a given level of return. Specifically, comparing three portfolios A, B, and D, portfolios A and B are clearly more efficient than D, because portfolio A could produce the same expected return but at a lower risk level, while portfolio B would have the same degree of risk as D but would afford a higher return.

To see how the investor tries to find the optimum portfolio, we first introduce the indifference curve, which shows the investor’s trade-off between risk and return. Exhibit 94 shows the two different indifference curves for two investors. The steeper the slope of the curve, the more risk averse the investor is. For example, investor B’s curve has a steeper slope than investor A’s. This means that investor B will want more incremental return for each additional unit of risk.

EXHIBIT 93

Efficient Portfolio

EXHIBIT 94

Risk-Return Indifference Curves

Exhibit 95 depicts a family of indifference curves for investor A. The objective is to maximize his satisfaction by attaining the highest curve possible.

EXHIBIT 95

Matching the Efficient Frontier and Indifference Curve

By matching the indifference curve showing the risk-return trade-off with the best investments available in the market as represented by points on the efficient frontier, investors are able to find an optimum portfolio. According to Markowitz, investor A will achieve the highest possible curve at point B along the efficient frontier. Point B is thus the optimum portfolio for this investor.

E. Portfolio Selection as a Quadratic Programming Problem

A portfolio selection problem was formulated by Markowitz as a quadratic programming model as follows:

subject to

where

X represents the rate at which a particular investor is just willing to exchange expected rate of return for risk. X = 0 indicates the investor is a risk lover, while X = 1 means he is a risk averter. The resulting solution to the problem would identify a portfolio that lies on the efficient portfolio. If one knows the coefficient of risk aversion, X, for a particular investor, the model will be able to find the optimal portfolio for that investor.

F. The Market Index Model

For even a moderately sized portfolio, the formulas for portfolio return and risk require estimation of a large number of input data. Concern for the computational burden in deriving these estimates led to the development of the following market index model:

where

What this model attempts to do is measure the systematic or uncontrollable risk of a security. The beta is measured as follows:

where

Cov(j r_m) = the covariance of the returns of the security with the market return.

o²_m = the variance (standard deviation squared) of the market return, which is the return on the Standard & Poor’s 500 or Dow Jones 30 Industrials.

An easier way to compute beta is to determine the slope of the least-squares linear regression line (r_;- – rf), where the excess return of the security (r_;- – rf) is regressed against the excess return of the market portfolio (r_m – rf). The formula for beta is:

where M = (r_m – rf), K = (r_;- – rf), n = the number of periods, M = the average of M, and K = the average of K.

The market index model was initially proposed to reduce the number of inputs required in portfolio analysis. It can also be justified in the context of the capital asset pricing model.

G. The Capital Asset Pricing Model (CAPM)

The capital asset pricing model (CAPM) takes off where the efficient frontier concluded with an assumption that there exists a risk-free security with a single rate at which investors can borrow and lend. By combining the risk-free asset and the efficient frontier, we create a whole new set of investment opportunities which will allow us to reach higher indifference curves than would be possible simply along the efficient frontier. The rf mx line in Exhibit 96 shows this possibility. This line is called the capital market line (CML) and the formula for this line is:

which indicates the expected return on any portfolio (r_p) is equal to the risk-free return (rf) plus the slope of the line times a value along the horizontal axis (o_p) indicating the amount of risk undertaken.

EXHIBIT 96

Graph of CAPM

H. The Security Market Line

We can establish the trade-off between risk and return for an individual security through the security market line (SML) in Exhibit 97. SML is a general relationship to show the risk-return trade-off for an individual security, whereas CML achieves the same objective for a portfolio. The formula for SML is:

where

This formula is called the Capital Asset Pricing Model (CAPM). The model shows that investors in individual securities are only assumed to be rewarded for systematic, uncontrollable, market-related risk, known as the beta (b) risk. All other risk is assumed to be diversified away and thus is not rewarded.

The key component in the CAPM, beta (b), is a measure of the security’s volatility relative to that of an average security. For example, b = 0.5 means the security is only half as volatile, or risky, as the average security; b = 1.0 means the security is of average risk; and b = 2.0 means the security is twice as risky as the average risk. The whole term b(r_m – rf)represents the risk premium, the additional return required to compensate investors for assuming a given level of risk.

Thus, in words, the CAPM (or SML) equation shows that the required (expected) rate of return on a given security (r_j ) is equal to the return required for securities that have no risk (rf) plus a risk premium required by investors for assuming a given level of risk. The higher the degree of systematic risk (b), the higher the return on a given security demanded by investors. Exhibit 97 shows the graph of the equation, known as the security market line (SML).

EXHIBIT 97

The Security Market Line (SML)

EXAMPLE 103

Assuming that the risk-free rate (r_f) is 8%, and the expected return for the market (r_m) is 12%, then if

POUND

Monetary unit of Great Britain, Cyprus, Egypt, Gibraltar, Republic of Ireland, Lebanon, Malta, Sudan, and Syria.

PREMIUM

1. The price agreed upon between the purchaser and seller for the purchase or sale of an option—purchasers pay the premium and sellers (writers) receive the premium.

2. The excess of one futures contract price over that of another, or over the cash market price.

PRIVATE EXPORT FUNDING CORPORATION

Private Export Funding Corporation (PEFCO) is a private U.S. corporation, established with government support, which helps finance U.S. exports of big-ticket items from private sources. PEFCO purchases at fixed interest rates the medium- to long-term debt obligations of importers of U.S. products. Foreign importer loans are financed through the sale of PEFCO’s own securities. Guarantees of repayment on all of PEFCO’s foreign obligations are provided by the Eximbank.

PUNT

Ireland’s currency.

PURCHASING POWER PARITY (PPP)

Purchasing Power Parity (PPP) states that spot currency rates among countries will change to the differential in inflation rates between countries. There are two versions of this theory.

Absolute PPP: The price of internationally traded commodities should be the same in every country, that is, one unit of home currency should have the same purchasing power worldwide. The absolute version, popularly called the law of one price, is written as

where S = spot exchange rate in direct quotes (i.e., the number of units of home currency that can be purchased for one unit of foreign currency), P_h = the price of the good in the home country, and P_f = the price of the good in the foreign country.

EXAMPLE 104

Suppose that a shoe is selling for 30 pounds in the U.K. and $50 in the U.S. (home). If the exchange rate (direct quotes) is $1.667 per pound, then

or

Thus, the price of the shoe in the U.K. is the same as the U.S. price once we use the exchange rate to the convert the dollar into pounds and compare prices in a common currency.

Relative PPP: The relative version of purchasing power parity says that the exchange rate of one currency against another will adjust to reflect changes in the price levels of the two countries.

Purchasing power parity can be summarized as follows:

Expected spot rate = current spot rate x expected difference in inflation rate Mathematically,

where Sj and S₂ = the spot exchange rate (direct quote) at the beginning of the period and the end of the period, If = foreign inflation rate, measured by price indexes, and I_h = home(domestic) inflation rate.

EXAMPLE 105

If the home currency experiences a 5% rate of inflation, and the foreign currency experiences a 2% rate of inflation, then the foreign currency will adjust by 2.94% (1.05/1.02 = 1.0294). In fact, the foreign currency is expected to appreciate by 2.94% in response to the higher rate of inflation of the home country relative to the foreign country.

If purchasing power parity is expected to hold, then the best prediction for the one-period spot rate, called the purchasing power parity (PPP) rate, should be:

A more simplified but less precise relationship of purchasing power parity is shown as:

Note: Dividing both sides of Equation 2 by S₁ and then subtracting 1 from both sides yields

Equation 3 follows if I_h is relatively small.

Equation 3 indicates that the exchange rate change during a period should equal the inflation differential for that same time period. In effect, PPP says that currencies with high rates of inflation should devalue relative to currencies with lower rates of inflation.

EXAMPLE 106

If the home currency experiences a 5% rate of inflation, and the foreign currency experiences a 2% rate of inflation, the foreign currency should adjust by about 3% (5% – 2% = 3%).

Equation 3 is illustrated in Exhibit 98. The vertical axis shows the percentage appreciation of the foreign currency relative to the home currency, and the horizontal axis measures the percentage higher or lower rate of inflation in the foreign country relative to the home country. Equilibrium is reached on the parity line, which contains all those points at which these two differentials are equal. At point A, for example, the 3% inflation differential is exactly offset by the 3% appreciation of the foreign currency relative to the home currency. Point B, on the other hand, portrays a situation of disparity, where the inflation differential of 3% is greater than the appreciation of 1% in the home currency value of the foreign currency.

EXHIBIT 98

Purchasing Power Parity

Note: (1) If absolute PPP holds, then relative PPP will also hold. But if absolute PPP does not hold, relative PPP still may. This is because the level of S may not equal If II_h, but the change in S could still equal the inflation differential. (2) Empirical evidence has indicated that purchasing power parity holds up well over the long run, but not so well over shorter time periods.

PURCHASING POWER RISK

Also called inflation risk.

1. The failure of assets (financial and real) to earn a return to keep up with increasing price levels. Bonds are exposed to this risk because the issuer will be paying back in cheaper dollars in inflationary times.

2. The domestic counterpart to exchange risk. It involves uncertain changes in the exchange rate between domestic currency and domestic goods and services.

PUT

1. A right (not the obligation) to sell a specific security at a specified price within a designated period for which the option buyer pays the seller (writer) a premium or option price. Contracts on listed puts (and calls) have been standardized at date of issue for periods of three, six, and nine months, although as these contracts approach expiration, they may be purchased with a much shorter life.

2. Bondholder’s right to redeem a bond prior to maturity.