Use the International Stock Market database from "Excel Databases.xls" on Blackboard. Use Excel to develop a multiple regression model to predict the Nikkei by the DJIA, the Nasdaq, the S&P 500, the Hang Seng, the FTSE 100, and the IPC. Assume a 1% level of significance. Which independent variables are significantly contributing to predict the Nikkei? Choose all that apply. O S&P 500 O Nasdaq O IPC O DJIA O FTSE 100 O Hang Seng
Use the International Stock Market database from "Excel Databases.xls" on Blackboard. Use Excel to develop a multiple regression model to predict the Nikkei by the DJIA, the Nasdaq, the S&P 500, the Hang Seng, the FTSE 100, and the IPC. Assume a 1% level of significance. Which independent variables are significantly contributing to predict the Nikkei? Choose all that apply. O S&P 500 O Nasdaq O IPC O DJIA O FTSE 100 O Hang Seng
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Concept explainers
Compound Probability
Compound probability can be defined as the probability of the two events which are independent. It can be defined as the multiplication of the probability of two events that are not dependent.
Tree diagram
Probability theory is a branch of mathematics that deals with the subject of probability. Although there are many different concepts of probability, probability theory expresses the definition mathematically through a series of axioms. Usually, these axioms express probability in terms of a probability space, which assigns a measure with values ranging from 0 to 1 to a set of outcomes known as the sample space. An event is a subset of these outcomes that is described.
Conditional Probability
By definition, the term probability is expressed as a part of mathematics where the chance of an event that may either occur or not is evaluated and expressed in numerical terms. The range of the value within which probability can be expressed is between 0 and 1. The higher the chance of an event occurring, the closer is its value to be 1. If the probability of an event is 1, it means that the event will happen under all considered circumstances. Similarly, if the probability is exactly 0, then no matter the situation, the event will never occur.
Question
| DATE | DJIA | NASDAQ | S&P 500 | NIKKEI 225 | HANG SENG | FTSE 100 | IPC | |||
| 9-Feb | 8270.87 | 1591.56 | 869.89 | 87.63 | 1658.5 | 5774.95 | 1351.73 | |||
| 9-Jan | 8000.86 | 1476.42 | 825.88 | 97.73 | 1856.39 | 6375.22 | 1616.08 | |||
| 8-Dec | 8776.39 | 1577.03 | 903.25 | 89.49 | 1820.22 | 6033.18 | 1436.55 | |||
| 8-Nov | 8829.04 | 1535.57 | 896.24 | 86.68 | 1850.86 | 7041.92 | 1612.58 | |||
| 8-Oct | 9336.93 | 1720.95 | 968.75 | 107.68 | 2319.76 | 8780.95 | 2284.53 | |||
| 8-Sep | 10850.66 | 2091.88 | 1164.74 | 118.69 | 2678.44 | 10077.78 | 2554.66 | |||
| 8-Aug | 11543.55 | 2367.52 | 1282.83 | 121.78 | 2929.61 | 10569.58 | 2700.02 | |||
| 8-Jul | 11378.02 | 2325.55 | 1267.38 | 127.03 | 2834.06 | 10912.45 | 2814.32 | |||
| 8-Jun | 11350.01 | 2292.98 | 1280 | 138.12 | 3182.05 | 11797.14 | 3059.82 | |||
| 8-May | 12638.32 | 2522.66 | 1400.38 | 132.27 | 3304.82 | 12020.49 | 2886.28 | |||
| 8-Apr | 12820.13 | 2412.80 | 1385.59 | 124.23 | 2970.75 | 11561.18 | 2996.44 | |||
| 8-Mar | 12262.89 | 2279.10 | 1322.7 | 125.67 | 3029.8 | 11534.82 | 2757.18 | |||
| 8-Feb | 12266.39 | 2271.48 | 1330.63 | 127.03 | 3094.02 | 11869.34 | 2721.47 | |||
| 8-Jan | 12650.36 | 2389.86 | 1378.55 | 137.03 | 3566.91 | 12853.11 | 2706.25 | |||
| 7-Dec | 13264.82 | 2652.28 | 1468.36 | 141.48 | 3680.01 | 13202.62 | 2744.68 | |||
| 7-Nov | 13371.72 | 2660.96 | 1481.14 | 146.86 | 4059.75 | 13710.23 | 2887.75 | |||
| 7-Oct | 13930.01 | 2859.12 | 1549.38 | 145.66 | 3493.38 | 13292.91 | 2824.73 | |||
| 7-Sep | 13895.63 | 2701.50 | 1526.75 | 142.62 | 3066.91 | 12744.42 | 2795.17 | |||
| 7-Aug | 13357.74 | 2596.36 | 1473.99 | 142.31 | 2868.1 | 12683.95 | 2738.32 | |||
| 7-Jul | 13211.99 | 2546.27 | 1455.27 | 148.36 | 2785.83 | 13271.05 | 2918.1 | |||
| 7-Jun | 13408.62 | 2603.23 | 1503.35 | 147.16 | 2638.3 | 13213.43 | 2979.65 | |||
| 7-May | 13627.64 | 2604.52 | 1530.62 | 144.26 | 2597.52 | 12833.75 | 2650.22 | |||
| 7-Apr | 13062.91 | 2525.09 | 1482.37 | 144.55 | 2534.49 | 12491.48 | 2643.28 | |||
| 7-Mar | 12354.35 | 2421.64 | 1420.86 | 148.38 | 2476.25 | 11972.75 | 2381.06 | |||
| 7-Feb | 12268.63 | 2416.15 | 1406.82 | 145.38 | 2617.79 | 12379.44 | 2533.66 | |||
| 7-Jan | 12621.69 | 2463.93 | 1438.24 | 144.57 | 2567.06 | 12175.05 | 2442.83 | |||
| 6-Dec | 12463.15 | 2415.29 | 1418.3 | 141.71 | 2403.98 | 11926.86 | 2268.27 | |||
| 6-Nov | 12221.93 | 2431.77 | 1400.63 | 139.99 | 2372.8 | 11727.62 | 2145.5 | |||
| 6-Oct | 12080.73 | 2366.71 | 1377.94 | 138.07 | 2251.33 | 11229.61 | 1969.79 | |||
| 6-Sep | 11679.07 | 2258.43 | 1335.85 | 137.52 | 2240.08 | 11323.31 | 1942.88 | |||
| 6-Aug | 11381.15 | 2183.75 | 1303.82 | 134.09 | 2175.71 | 10981.88 | 1810.7 | |||
| 6-Jul | 11185.68 | 2091.47 | 1276.66 | 135.75 | 2101.99 | 10851.78 | 1804.9 | |||
| 6-Jun | 11150.22 | 2172.09 | 1270.2 | 137.92 | 2016.67 | 10740.7 | 1699.2 | |||
| 6-May | 11168.31 | 2178.88 | 1270.09 | 149.8 | 2148.93 | 11033.48 | 1870.23 | |||
| 6-Apr | 11367.14 | 2322.57 | 1310.61 | 146.92 | 2070.09 | 10464.16 | 1805.45 | |||
| 6-Mar | 11109.32 | 2339.79 | 1294.87 | 137.66 | 2039.02 | 10244.06 | 1820.84 | |||
| 6-Feb | 10993.41 | 2281.39 | 1280.66 | 139.92 | 2029.29 | 10324.87 | 1837.52 | |||
| 6-Jan | 10864.86 | 2305.82 | 1280.08 | 136.5 | 1918.66 | 9646 | 1685.12 | |||
| 5-Dec | 10717.50 | 2205.32 | 1248.29 | 125.61 | 1942.99 | 9490.98 | 1627.2 | |||
| 5-Nov | 10805.87 | 2232.82 | 1249.48 | 118.87 | 1879.79 | 9413.49 | 1479.4 | |||
| 5-Oct | 10440.07 | 2120.30 | 1207.01 | 118.36 | 1984.42 | 9652.19 | 1490.35 | |||
| 5-Sep | 10568.70 | 2151.69 | 1228.81 | 113.63 | 1949.17 | 9746.37 | 1353.07 | |||
| 5-Aug | 10481.60 | 2152.09 | 1220.33 | 106.54 | 1927.06 | 9366.65 | 1376.06 | |||
| 5-Jul | 10640.91 | 2184.83 | 1234.18 | 104.15 | 1827.1 | 9142.46 | 1259.04 | |||
| 5-Jun | 10274.97 | 2056.96 | 1191.33 | 104.66 | 1782.11 | 9098.04 | 1211.94 | |||
| 5-May | 10467.48 | 2068.22 | 1191.5 | 104.65 | 1783.94 | 9089.81 | 1127.03 | |||
| 5-Apr | 10192.51 | 1921.65 | 1156.85 | 109.24 | 1729.81 | 9281.12 | 1140.06 | |||
| 5-Mar | 10503.76 | 1999.23 | 1180.59 | 112.78 | 1802.76 | 9600.89 | 1243.08 | |||
| 5-Feb | 10766.23 | 2051.72 | 1203.6 | 109.39 | 1740.82 | 9221.95 | 1193.78 | |||
| 5-Jan | 10489.94 | 2062.41 | 1181.27 | 111.68 | 1830.55 | 9162.32 | 1164.34 | |||
| 4-Dec | 10783.01 | 2175.44 | 1211.92 | 104.79 | 1821.7 | 9130.15 | 1094.63 | |||
| 4-Nov | 10428.02 | 2096.81 | 1173.82 | 100.91 | 1683.15 | 8568.45 | 1007.95 | |||
| 4-Oct | 10027.47 | 1974.99 | 1130.2 | 99.49 | 1682.63 | 8369.66 | 975.11 | |||
| 4-Sep | 10080.27 | 1896.84 | 1114.58 | 101.64 | 1669.73 | 8074.64 | 906.4 | |||
| 4-Aug | 10173.92 | 1838.10 | 1104.24 | 101.27 | 1564.33 | 8065.1 | 890.57 | |||
| 4-Jul | 10139.71 | 1887.36 | 1101.72 | 109.97 | 1575.17 | 8032.19 | 894.2 | |||
| 4-Jun | 10435.48 | 2047.79 | 1140.84 | 102.77 | 1552.7 | 8126.01 | 875.08 | |||
| 4-May | 10188.45 | 1986.74 | 1120.68 | 106.54 | 1532.17 | 7967.62 | 891.59 | |||
| 4-Apr | 10225.57 | 1920.15 | 1107.3 | 112.69 | 1627.42 | 8192.45 | 950.59 | |||
| 4-Mar | 10357.70 | 1994.22 | 1126.21 | 103.45 | 1788.16 | 8479.88 | 924.09 | |||
| 4-Feb | 10583.92 | 2029.82 | 1144.94 | 102.15 | 1671.89 | 7969.92 | 880.17 | |||
| 4-Jan | 10488.07 | 2066.15 | 1131.13 | 99.62 | 1619.86 | 8014.26 | 782.69 | |||
| 9-Feb | 8270.87 | 1591.56 | 869.89 | 87.63 | 1658.5 | 5774.95 | 1351.73 |
Transcribed Image Text:Use the International Stock Market database from "Excel Databases.xls" on Blackboard. Use Excel to develop a multiple regression model to predict the Nikkei by the DJIA, the
Nasdag, the S&P 500, the Hang Seng, the FTSE 100, and the IPC. Assume a 1% level of significance.
Which independent variables are significantly contributing to predict the Nikkei? Choose all that apply.
O S&P 500
Nasdaq
O IPC
O DJIA
O FTSE 100
O Hang Seng
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