#HO VA TEN : LE THI CAM LY
#LOP: 24NH1
#MSSV: 2454020045
#BAI THI CUOI KY
#PHAN TICH CAC CHI SO TAI CHINH
#SO LUONG MAU : 234
# CHI SO : VNI, VN30, S&P 500
#MA HOA CAC CHI SO
setwd("~/Downloads")
options(width = 200)
options(scipen = 3)
dulieu=read.csv("Du_lieu_R_VNI_VN30_SP500(2).csv",header = TRUE)
save(dulieu,file = "dulieu.rda")
attach(dulieu)
is.data.frame(dulieu)
## [1] TRUE
print(dulieu)
## STT Ngay VNI VN30 SP500
## 1 1 11/09/2026 1795.21 1936.69 7656.98
## 2 2 10/09/2026 1829.23 1976.82 7591.70
## 3 3 09/09/2026 1827.12 1967.64 7636.36
## 4 4 08/09/2026 1830.44 1968.52 7673.52
## 5 5 07/09/2026 1821.64 1963.01 7718.60
## 6 6 04/09/2026 1853.08 1984.89 7747.71
## 7 7 03/09/2026 1827.72 1961.57 7666.60
## 8 8 28/08/2026 1832.12 1982.96 7631.47
## 9 9 27/08/2026 1831.56 1979.23 7686.14
## 10 10 26/08/2026 1821.32 1970.01 7711.76
## 11 11 25/08/2026 1791.41 1936.15 7730.99
## 12 12 24/08/2026 1788.78 1942.00 7675.70
## 13 13 21/08/2026 1768.12 1927.79 7677.28
## 14 14 20/08/2026 1734.24 1887.06 7652.86
## 15 15 19/08/2026 1726.69 1875.73 7674.37
## 16 16 18/08/2026 1732.02 1876.14 7641.16
## 17 17 17/08/2026 1727.46 1877.68 7707.98
## 18 18 14/08/2026 1729.08 1876.81 7691.76
## 19 19 13/08/2026 1765.63 1909.23 7745.06
## 20 20 12/08/2026 1793.18 1936.46 7785.76
## 21 21 11/08/2026 1773.41 1922.53 7798.99
## 22 22 10/08/2026 1776.77 1925.18 7748.50
## 23 23 07/08/2026 1768.06 1911.09 7728.20
## 24 24 06/08/2026 1764.78 1902.79 7753.11
## 25 25 05/08/2026 1776.46 1916.88 7757.64
## 26 26 04/08/2026 1777.23 1927.35 7709.96
## 27 27 03/08/2026 1762.84 1917.69 7723.55
## 28 28 31/07/2026 1735.78 1872.07 7736.52
## 29 29 30/07/2026 1744.66 1886.27 7600.50
## 30 30 29/07/2026 1704.68 1849.12 7489.72
## 31 31 28/07/2026 1680.62 1824.35 7437.63
## 32 32 27/07/2026 1669.01 1806.50 7316.15
## 33 33 24/07/2026 1686.11 1829.36 7428.78
## 34 34 23/07/2026 1699.38 1845.32 7413.18
## 35 35 22/07/2026 1668.53 1826.90 7411.98
## 36 36 21/07/2026 1730.56 1881.32 7408.30
## 37 37 20/07/2026 1743.51 1887.32 7498.96
## 38 38 17/07/2026 1787.45 1931.65 7509.20
## 39 39 16/07/2026 1804.24 1941.65 7443.28
## 40 40 15/07/2026 1782.12 1916.05 7457.69
## 41 41 14/07/2026 1806.63 1946.06 7533.77
## 42 42 13/07/2026 1800.54 1939.84 7572.40
## 43 43 10/07/2026 1828.34 1970.82 7543.59
## 44 44 09/07/2026 1840.70 1987.11 7515.34
## 45 45 08/07/2026 1853.70 1998.44 7575.39
## 46 46 07/07/2026 1848.25 1995.91 7543.64
## 47 47 06/07/2026 1843.50 1991.11 7482.71
## 48 48 03/07/2026 1862.08 2002.56 7503.85
## 49 49 02/07/2026 1866.35 2009.04 7537.43
## 50 50 01/07/2026 1867.21 2013.35 7483.24
## 51 51 30/06/2026 1860.01 1995.71 7483.23
## 52 52 29/06/2026 1854.97 2004.29 7499.36
## 53 53 26/06/2026 1871.91 2008.57 7440.43
## 54 54 25/06/2026 1863.07 2004.62 7354.02
## 55 55 24/06/2026 1878.02 2010.15 7357.49
## 56 56 23/06/2026 1869.04 1995.12 7358.22
## 57 57 22/06/2026 1857.91 1980.13 7365.46
## 58 58 19/06/2026 1824.53 1963.57 7472.79
## 59 59 18/06/2026 1830.47 1967.22 7500.58
## 60 60 17/06/2026 1806.20 1957.17 7420.10
## 61 61 16/06/2026 1807.94 1960.19 7511.35
## 62 62 15/06/2026 1799.31 1962.48 7554.29
## 63 63 12/06/2026 1791.65 1944.36 7431.46
## 64 64 11/06/2026 1798.61 1947.28 7394.30
## 65 65 10/06/2026 1803.71 1960.97 7266.99
## 66 66 09/06/2026 1793.05 1951.92 7386.65
## 67 67 08/06/2026 1790.53 1936.81 7405.73
## 68 68 05/06/2026 1838.90 1986.28 7383.74
## 69 69 04/06/2026 1831.55 1982.29 7584.31
## 70 70 03/06/2026 1819.01 1974.60 7553.68
## 71 71 02/06/2026 1826.47 1972.99 7609.78
## 72 72 01/06/2026 1844.54 1989.71 7599.96
## 73 73 29/05/2026 1863.49 1997.06 7580.06
## 74 74 28/05/2026 1863.67 1999.82 7563.63
## 75 75 27/05/2026 1874.43 2022.46 7520.36
## 76 76 26/05/2026 1884.18 2027.90 7519.12
## 77 77 25/05/2026 1886.03 2021.72 7473.47
## 78 78 22/05/2026 1877.13 2010.93 7445.72
## 79 79 21/05/2026 1896.89 2027.51 7432.97
## 80 80 20/05/2026 1913.23 2028.94 7353.61
## 81 81 19/05/2026 1912.93 2027.45 7403.05
## 82 82 18/05/2026 1927.94 2046.37 7408.50
## 83 83 15/05/2026 1921.60 2050.58 7501.24
## 84 84 14/05/2026 1925.46 2068.62 7444.25
## 85 85 13/05/2026 1898.37 2043.51 7400.96
## 86 86 12/05/2026 1901.10 2053.97 7412.84
## 87 87 11/05/2026 1895.50 2040.51 7398.93
## 88 88 08/05/2026 1915.37 2074.06 7337.11
## 89 89 07/05/2026 1909.01 2079.10 7365.12
## 90 90 06/05/2026 1891.20 2053.41 7259.22
## 91 91 05/05/2026 1874.85 2032.30 7200.75
## 92 92 04/05/2026 1854.06 2014.62 7230.12
## 93 93 29/04/2026 1854.10 2022.75 7209.01
## 94 94 28/04/2026 1875.84 2041.40 7135.95
## 95 95 24/04/2026 1853.29 2011.42 7138.80
## 96 96 23/04/2026 1870.36 2024.74 7173.91
## 97 97 22/04/2026 1857.30 2025.41 7165.08
## 98 98 21/04/2026 1833.48 2007.08 7108.40
## 99 99 20/04/2026 1837.11 2009.04 7137.90
## 100 100 17/04/2026 1817.17 1988.11 7064.01
## 101 101 16/04/2026 1819.83 1979.19 7109.14
## 102 102 15/04/2026 1800.65 1961.60 7126.06
## 103 103 14/04/2026 1775.65 1946.55 7041.28
## 104 104 13/04/2026 1758.96 1925.66 7022.95
## 105 105 10/04/2026 1750.00 1928.23 6967.38
## 106 106 09/04/2026 1736.68 1915.01 6886.24
## 107 107 08/04/2026 1756.55 1931.01 6816.89
## 108 108 07/04/2026 1677.54 1840.96 6824.66
## 109 109 06/04/2026 1674.99 1836.25 6782.81
## 110 110 03/04/2026 1684.04 1837.43 6616.85
## 111 111 02/04/2026 1694.82 1852.99 6611.83
## 112 112 01/04/2026 1702.93 1861.84 6582.69
## 113 113 31/03/2026 1674.49 1829.59 6575.32
## 114 114 30/03/2026 1662.54 1811.92 6528.52
## 115 115 27/03/2026 1672.80 1821.53 6343.72
## 116 116 26/03/2026 1644.63 1791.25 6368.85
## 117 117 25/03/2026 1658.19 1814.73 6477.16
## 118 118 24/03/2026 1614.77 1770.16 6591.90
## 119 119 23/03/2026 1591.17 1741.05 6556.37
## 120 120 20/03/2026 1647.81 1797.99 6581.00
## 121 121 19/03/2026 1699.13 1854.19 6506.48
## 122 122 18/03/2026 1713.83 1868.84 6606.49
## 123 123 17/03/2026 1710.29 1873.65 6624.70
## 124 124 16/03/2026 1693.21 1852.99 6716.09
## 125 125 13/03/2026 1696.24 1853.60 6699.38
## 126 126 12/03/2026 1709.61 1859.80 6632.19
## 127 127 11/03/2026 1728.34 1889.94 6672.62
## 128 128 10/03/2026 1676.73 1836.96 6775.80
## 129 129 09/03/2026 1652.79 1780.71 6781.48
## 130 130 06/03/2026 1767.84 1904.19 6795.99
## 131 131 05/03/2026 1808.51 1942.76 6740.02
## 132 132 04/03/2026 1818.27 1956.53 6830.71
## 133 133 03/03/2026 1813.14 1959.35 6869.50
## 134 134 02/03/2026 1846.10 2010.75 6816.63
## 135 135 27/02/2026 1880.33 2061.75 6881.62
## 136 136 26/02/2026 1879.64 2069.82 6878.88
## 137 137 25/02/2026 1860.91 2049.64 6908.86
## 138 138 24/02/2026 1867.62 2050.85 6946.13
## 139 139 23/02/2026 1860.14 2039.80 6890.07
## 140 140 13/02/2026 1824.09 2018.64 6837.75
## 141 141 12/02/2026 1814.09 2016.47 6909.51
## 142 142 11/02/2026 1796.85 2000.90 6861.89
## 143 143 10/02/2026 1754.03 1951.58 6881.31
## 144 144 09/02/2026 1754.82 1947.75 6843.22
## 145 145 06/02/2026 1755.49 1943.60 6836.17
## 146 146 05/02/2026 1782.56 1969.27 6832.76
## 147 147 04/02/2026 1791.43 1988.19 6941.47
## 148 148 03/02/2026 1813.40 1997.69 6941.81
## 149 149 02/02/2026 1806.50 2004.31 6964.82
## 150 150 30/01/2026 1829.04 2029.81 6932.30
## 151 151 29/01/2026 1814.98 2018.98 6798.40
## 152 152 28/01/2026 1802.91 1997.13 6882.72
## 153 153 27/01/2026 1830.50 2019.88 6917.81
## 154 154 26/01/2026 1843.72 2032.28 6976.44
## 155 155 23/01/2026 1870.79 2077.76 6939.03
## 156 156 22/01/2026 1882.73 2082.35 6969.01
## 157 157 21/01/2026 1885.44 2080.38 6978.03
## 158 158 20/01/2026 1893.78 2085.61 6978.60
## 159 159 19/01/2026 1896.59 2094.24 6950.23
## 160 160 16/01/2026 1879.13 2080.35 6915.61
## 161 161 15/01/2026 1864.80 2047.48 6913.35
## 162 162 14/01/2026 1894.44 2067.10 6875.62
## 163 163 13/01/2026 1902.93 2089.21 6796.86
## 164 164 12/01/2026 1877.33 2080.24 6940.01
## 165 165 09/01/2026 1867.90 2066.21 6944.47
## 166 166 08/01/2026 1855.56 2074.03 6926.60
## 167 167 07/01/2026 1861.58 2096.76 6963.74
## 168 168 06/01/2026 1816.27 2055.96 6977.27
## 169 169 05/01/2026 1788.40 2028.68 6966.28
## 170 170 31/12/2025 1784.49 2030.63 6921.46
## 171 171 30/12/2025 1766.90 2009.70 6920.93
## 172 172 29/12/2025 1754.84 1990.66 6944.82
## 173 173 26/12/2025 1729.80 1965.97 6902.05
## 174 174 25/12/2025 1742.85 1976.21 6858.47
## 175 175 24/12/2025 1782.82 2023.13 6845.50
## 176 176 23/12/2025 1772.15 2012.87 6896.24
## 177 177 22/12/2025 1751.03 1985.28 6905.74
## 178 178 19/12/2025 1704.31 1933.28 6929.94
## 179 179 18/12/2025 1676.98 1903.47 6932.05
## 180 180 17/12/2025 1673.66 1897.95 6909.79
## 181 181 16/12/2025 1679.18 1909.87 6878.49
## 182 182 15/12/2025 1646.01 1869.84 6834.50
## 183 183 12/12/2025 1646.89 1867.03 6774.76
## 184 184 11/12/2025 1698.90 1924.29 6721.43
## 185 185 10/12/2025 1718.98 1946.98 6800.26
## 186 186 09/12/2025 1747.17 1973.02 6816.51
## 187 187 08/12/2025 1753.74 1983.82 6827.41
## 188 188 05/12/2025 1741.32 1975.50 6901.00
## 189 189 04/12/2025 1737.24 1979.53 6886.68
## 190 190 03/12/2025 1731.77 1971.99 6840.51
## 191 191 02/12/2025 1717.06 1950.12 6846.51
## 192 192 01/12/2025 1701.67 1933.56 6870.40
## 193 193 28/11/2025 1690.99 1923.92 6857.12
## 194 194 27/11/2025 1684.32 1921.18 6849.72
## 195 195 26/11/2025 1680.36 1923.55 6829.37
## 196 196 25/11/2025 1660.36 1909.60 6812.63
## 197 197 24/11/2025 1667.98 1916.36 6849.09
## 198 198 21/11/2025 1654.93 1899.89 6812.61
## 199 199 20/11/2025 1655.99 1897.46 6765.88
## 200 200 19/11/2025 1649.00 1886.20 6705.12
## 201 201 18/11/2025 1659.92 1898.07 6602.99
## 202 202 17/11/2025 1654.42 1893.54 6538.76
## 203 203 14/11/2025 1635.46 1871.54 6642.16
## 204 204 13/11/2025 1631.44 1864.23 6617.32
## 205 205 12/11/2025 1631.86 1872.27 6672.41
## 206 206 11/11/2025 1593.61 1821.60 6734.11
## 207 207 10/11/2025 1580.54 1804.18 6737.49
## 208 208 07/11/2025 1599.10 1824.71 6850.92
## 209 209 06/11/2025 1642.64 1869.60 6846.61
## 210 210 05/11/2025 1654.89 1886.47 6832.43
## 211 211 04/11/2025 1651.98 1897.71 6728.80
## 212 212 03/11/2025 1617.00 1857.64 6720.32
## 213 213 31/10/2025 1639.65 1885.36 6796.29
## 214 214 30/10/2025 1669.57 1925.18 6771.55
## 215 215 29/10/2025 1685.83 1949.76 6851.97
## 216 216 28/10/2025 1680.50 1949.28 6840.20
## 217 217 27/10/2025 1652.54 1900.76 6822.34
## 218 218 24/10/2025 1683.18 1944.60 6890.59
## 219 219 23/10/2025 1687.06 1945.78 6890.89
## 220 220 22/10/2025 1678.50 1930.88 6875.16
## 221 221 21/10/2025 1663.43 1915.90 6791.69
## 222 222 20/10/2025 1636.43 1870.86 6738.44
## 223 223 17/10/2025 1731.19 1977.14 6699.40
## 224 224 16/10/2025 1766.85 2022.27 6735.35
## 225 225 15/10/2025 1757.95 2009.64 6735.13
## 226 226 14/10/2025 1761.06 2013.69 6664.01
## 227 227 13/10/2025 1765.12 2012.28 6629.07
## 228 228 10/10/2025 1747.55 1980.57 6671.06
## 229 229 09/10/2025 1716.47 1940.89 6644.31
## 230 230 08/10/2025 1697.83 1922.95 6654.72
## 231 231 07/10/2025 1685.30 1909.65 6552.51
## 232 232 06/10/2025 1695.50 1918.97 6735.11
## 233 233 03/10/2025 1645.82 1859.51 6753.72
## 234 234 02/10/2025 1652.71 1859.80 6714.59
dim(dulieu)
## [1] 234 5
names(dulieu)
## [1] "STT" "Ngay" "VNI" "VN30" "SP500"
str(dulieu)
## 'data.frame': 234 obs. of 5 variables:
## $ STT : int 1 2 3 4 5 6 7 8 9 10 ...
## $ Ngay : chr "11/09/2026" "10/09/2026" "09/09/2026" "08/09/2026" ...
## $ VNI : num 1795 1829 1827 1830 1822 ...
## $ VN30 : num 1937 1977 1968 1969 1963 ...
## $ SP500: num 7657 7592 7636 7674 7719 ...
###CAU B
# MA HOA VNI
VNIMH=dulieu$VNI
VNIMH=replace(VNIMH,dulieu$VNI<=1700,1)
VNIMH=replace(VNIMH,dulieu$VNI>1700&dulieu$VNI<=1800,2)
VNIMH=replace(VNIMH,dulieu$VNI>1800,3)
VNI=data.frame(dulieu$VNI,VNIMH)
VNI
## dulieu.VNI VNIMH
## 1 1795.21 2
## 2 1829.23 3
## 3 1827.12 3
## 4 1830.44 3
## 5 1821.64 3
## 6 1853.08 3
## 7 1827.72 3
## 8 1832.12 3
## 9 1831.56 3
## 10 1821.32 3
## 11 1791.41 2
## 12 1788.78 2
## 13 1768.12 2
## 14 1734.24 2
## 15 1726.69 2
## 16 1732.02 2
## 17 1727.46 2
## 18 1729.08 2
## 19 1765.63 2
## 20 1793.18 2
## 21 1773.41 2
## 22 1776.77 2
## 23 1768.06 2
## 24 1764.78 2
## 25 1776.46 2
## 26 1777.23 2
## 27 1762.84 2
## 28 1735.78 2
## 29 1744.66 2
## 30 1704.68 2
## 31 1680.62 1
## 32 1669.01 1
## 33 1686.11 1
## 34 1699.38 1
## 35 1668.53 1
## 36 1730.56 2
## 37 1743.51 2
## 38 1787.45 2
## 39 1804.24 3
## 40 1782.12 2
## 41 1806.63 3
## 42 1800.54 3
## 43 1828.34 3
## 44 1840.70 3
## 45 1853.70 3
## 46 1848.25 3
## 47 1843.50 3
## 48 1862.08 3
## 49 1866.35 3
## 50 1867.21 3
## 51 1860.01 3
## 52 1854.97 3
## 53 1871.91 3
## 54 1863.07 3
## 55 1878.02 3
## 56 1869.04 3
## 57 1857.91 3
## 58 1824.53 3
## 59 1830.47 3
## 60 1806.20 3
## 61 1807.94 3
## 62 1799.31 2
## 63 1791.65 2
## 64 1798.61 2
## 65 1803.71 3
## 66 1793.05 2
## 67 1790.53 2
## 68 1838.90 3
## 69 1831.55 3
## 70 1819.01 3
## 71 1826.47 3
## 72 1844.54 3
## 73 1863.49 3
## 74 1863.67 3
## 75 1874.43 3
## 76 1884.18 3
## 77 1886.03 3
## 78 1877.13 3
## 79 1896.89 3
## 80 1913.23 3
## 81 1912.93 3
## 82 1927.94 3
## 83 1921.60 3
## 84 1925.46 3
## 85 1898.37 3
## 86 1901.10 3
## 87 1895.50 3
## 88 1915.37 3
## 89 1909.01 3
## 90 1891.20 3
## 91 1874.85 3
## 92 1854.06 3
## 93 1854.10 3
## 94 1875.84 3
## 95 1853.29 3
## 96 1870.36 3
## 97 1857.30 3
## 98 1833.48 3
## 99 1837.11 3
## 100 1817.17 3
## 101 1819.83 3
## 102 1800.65 3
## 103 1775.65 2
## 104 1758.96 2
## 105 1750.00 2
## 106 1736.68 2
## 107 1756.55 2
## 108 1677.54 1
## 109 1674.99 1
## 110 1684.04 1
## 111 1694.82 1
## 112 1702.93 2
## 113 1674.49 1
## 114 1662.54 1
## 115 1672.80 1
## 116 1644.63 1
## 117 1658.19 1
## 118 1614.77 1
## 119 1591.17 1
## 120 1647.81 1
## 121 1699.13 1
## 122 1713.83 2
## 123 1710.29 2
## 124 1693.21 1
## 125 1696.24 1
## 126 1709.61 2
## 127 1728.34 2
## 128 1676.73 1
## 129 1652.79 1
## 130 1767.84 2
## 131 1808.51 3
## 132 1818.27 3
## 133 1813.14 3
## 134 1846.10 3
## 135 1880.33 3
## 136 1879.64 3
## 137 1860.91 3
## 138 1867.62 3
## 139 1860.14 3
## 140 1824.09 3
## 141 1814.09 3
## 142 1796.85 2
## 143 1754.03 2
## 144 1754.82 2
## 145 1755.49 2
## 146 1782.56 2
## 147 1791.43 2
## 148 1813.40 3
## 149 1806.50 3
## 150 1829.04 3
## 151 1814.98 3
## 152 1802.91 3
## 153 1830.50 3
## 154 1843.72 3
## 155 1870.79 3
## 156 1882.73 3
## 157 1885.44 3
## 158 1893.78 3
## 159 1896.59 3
## 160 1879.13 3
## 161 1864.80 3
## 162 1894.44 3
## 163 1902.93 3
## 164 1877.33 3
## 165 1867.90 3
## 166 1855.56 3
## 167 1861.58 3
## 168 1816.27 3
## 169 1788.40 2
## 170 1784.49 2
## 171 1766.90 2
## 172 1754.84 2
## 173 1729.80 2
## 174 1742.85 2
## 175 1782.82 2
## 176 1772.15 2
## 177 1751.03 2
## 178 1704.31 2
## 179 1676.98 1
## 180 1673.66 1
## 181 1679.18 1
## 182 1646.01 1
## 183 1646.89 1
## 184 1698.90 1
## 185 1718.98 2
## 186 1747.17 2
## 187 1753.74 2
## 188 1741.32 2
## 189 1737.24 2
## 190 1731.77 2
## 191 1717.06 2
## 192 1701.67 2
## 193 1690.99 1
## 194 1684.32 1
## 195 1680.36 1
## 196 1660.36 1
## 197 1667.98 1
## 198 1654.93 1
## 199 1655.99 1
## 200 1649.00 1
## 201 1659.92 1
## 202 1654.42 1
## 203 1635.46 1
## 204 1631.44 1
## 205 1631.86 1
## 206 1593.61 1
## 207 1580.54 1
## 208 1599.10 1
## 209 1642.64 1
## 210 1654.89 1
## 211 1651.98 1
## 212 1617.00 1
## 213 1639.65 1
## 214 1669.57 1
## 215 1685.83 1
## 216 1680.50 1
## 217 1652.54 1
## 218 1683.18 1
## 219 1687.06 1
## 220 1678.50 1
## 221 1663.43 1
## 222 1636.43 1
## 223 1731.19 2
## 224 1766.85 2
## 225 1757.95 2
## 226 1761.06 2
## 227 1765.12 2
## 228 1747.55 2
## 229 1716.47 2
## 230 1697.83 1
## 231 1685.30 1
## 232 1695.50 1
## 233 1645.82 1
## 234 1652.71 1
VNIM=VNIMH
VNIM=replace(VNIM,VNIMH==1,"<=1700")
VNIM=replace(VNIM,VNIMH==2,">1700&<=1800")
VNIM=replace(VNIM,VNIMH==3,">1800")
VNIMM=data.frame(VNIMH,VNIM)
VNIMM
## VNIMH VNIM
## 1 2 >1700&<=1800
## 2 3 >1800
## 3 3 >1800
## 4 3 >1800
## 5 3 >1800
## 6 3 >1800
## 7 3 >1800
## 8 3 >1800
## 9 3 >1800
## 10 3 >1800
## 11 2 >1700&<=1800
## 12 2 >1700&<=1800
## 13 2 >1700&<=1800
## 14 2 >1700&<=1800
## 15 2 >1700&<=1800
## 16 2 >1700&<=1800
## 17 2 >1700&<=1800
## 18 2 >1700&<=1800
## 19 2 >1700&<=1800
## 20 2 >1700&<=1800
## 21 2 >1700&<=1800
## 22 2 >1700&<=1800
## 23 2 >1700&<=1800
## 24 2 >1700&<=1800
## 25 2 >1700&<=1800
## 26 2 >1700&<=1800
## 27 2 >1700&<=1800
## 28 2 >1700&<=1800
## 29 2 >1700&<=1800
## 30 2 >1700&<=1800
## 31 1 <=1700
## 32 1 <=1700
## 33 1 <=1700
## 34 1 <=1700
## 35 1 <=1700
## 36 2 >1700&<=1800
## 37 2 >1700&<=1800
## 38 2 >1700&<=1800
## 39 3 >1800
## 40 2 >1700&<=1800
## 41 3 >1800
## 42 3 >1800
## 43 3 >1800
## 44 3 >1800
## 45 3 >1800
## 46 3 >1800
## 47 3 >1800
## 48 3 >1800
## 49 3 >1800
## 50 3 >1800
## 51 3 >1800
## 52 3 >1800
## 53 3 >1800
## 54 3 >1800
## 55 3 >1800
## 56 3 >1800
## 57 3 >1800
## 58 3 >1800
## 59 3 >1800
## 60 3 >1800
## 61 3 >1800
## 62 2 >1700&<=1800
## 63 2 >1700&<=1800
## 64 2 >1700&<=1800
## 65 3 >1800
## 66 2 >1700&<=1800
## 67 2 >1700&<=1800
## 68 3 >1800
## 69 3 >1800
## 70 3 >1800
## 71 3 >1800
## 72 3 >1800
## 73 3 >1800
## 74 3 >1800
## 75 3 >1800
## 76 3 >1800
## 77 3 >1800
## 78 3 >1800
## 79 3 >1800
## 80 3 >1800
## 81 3 >1800
## 82 3 >1800
## 83 3 >1800
## 84 3 >1800
## 85 3 >1800
## 86 3 >1800
## 87 3 >1800
## 88 3 >1800
## 89 3 >1800
## 90 3 >1800
## 91 3 >1800
## 92 3 >1800
## 93 3 >1800
## 94 3 >1800
## 95 3 >1800
## 96 3 >1800
## 97 3 >1800
## 98 3 >1800
## 99 3 >1800
## 100 3 >1800
## 101 3 >1800
## 102 3 >1800
## 103 2 >1700&<=1800
## 104 2 >1700&<=1800
## 105 2 >1700&<=1800
## 106 2 >1700&<=1800
## 107 2 >1700&<=1800
## 108 1 <=1700
## 109 1 <=1700
## 110 1 <=1700
## 111 1 <=1700
## 112 2 >1700&<=1800
## 113 1 <=1700
## 114 1 <=1700
## 115 1 <=1700
## 116 1 <=1700
## 117 1 <=1700
## 118 1 <=1700
## 119 1 <=1700
## 120 1 <=1700
## 121 1 <=1700
## 122 2 >1700&<=1800
## 123 2 >1700&<=1800
## 124 1 <=1700
## 125 1 <=1700
## 126 2 >1700&<=1800
## 127 2 >1700&<=1800
## 128 1 <=1700
## 129 1 <=1700
## 130 2 >1700&<=1800
## 131 3 >1800
## 132 3 >1800
## 133 3 >1800
## 134 3 >1800
## 135 3 >1800
## 136 3 >1800
## 137 3 >1800
## 138 3 >1800
## 139 3 >1800
## 140 3 >1800
## 141 3 >1800
## 142 2 >1700&<=1800
## 143 2 >1700&<=1800
## 144 2 >1700&<=1800
## 145 2 >1700&<=1800
## 146 2 >1700&<=1800
## 147 2 >1700&<=1800
## 148 3 >1800
## 149 3 >1800
## 150 3 >1800
## 151 3 >1800
## 152 3 >1800
## 153 3 >1800
## 154 3 >1800
## 155 3 >1800
## 156 3 >1800
## 157 3 >1800
## 158 3 >1800
## 159 3 >1800
## 160 3 >1800
## 161 3 >1800
## 162 3 >1800
## 163 3 >1800
## 164 3 >1800
## 165 3 >1800
## 166 3 >1800
## 167 3 >1800
## 168 3 >1800
## 169 2 >1700&<=1800
## 170 2 >1700&<=1800
## 171 2 >1700&<=1800
## 172 2 >1700&<=1800
## 173 2 >1700&<=1800
## 174 2 >1700&<=1800
## 175 2 >1700&<=1800
## 176 2 >1700&<=1800
## 177 2 >1700&<=1800
## 178 2 >1700&<=1800
## 179 1 <=1700
## 180 1 <=1700
## 181 1 <=1700
## 182 1 <=1700
## 183 1 <=1700
## 184 1 <=1700
## 185 2 >1700&<=1800
## 186 2 >1700&<=1800
## 187 2 >1700&<=1800
## 188 2 >1700&<=1800
## 189 2 >1700&<=1800
## 190 2 >1700&<=1800
## 191 2 >1700&<=1800
## 192 2 >1700&<=1800
## 193 1 <=1700
## 194 1 <=1700
## 195 1 <=1700
## 196 1 <=1700
## 197 1 <=1700
## 198 1 <=1700
## 199 1 <=1700
## 200 1 <=1700
## 201 1 <=1700
## 202 1 <=1700
## 203 1 <=1700
## 204 1 <=1700
## 205 1 <=1700
## 206 1 <=1700
## 207 1 <=1700
## 208 1 <=1700
## 209 1 <=1700
## 210 1 <=1700
## 211 1 <=1700
## 212 1 <=1700
## 213 1 <=1700
## 214 1 <=1700
## 215 1 <=1700
## 216 1 <=1700
## 217 1 <=1700
## 218 1 <=1700
## 219 1 <=1700
## 220 1 <=1700
## 221 1 <=1700
## 222 1 <=1700
## 223 2 >1700&<=1800
## 224 2 >1700&<=1800
## 225 2 >1700&<=1800
## 226 2 >1700&<=1800
## 227 2 >1700&<=1800
## 228 2 >1700&<=1800
## 229 2 >1700&<=1800
## 230 1 <=1700
## 231 1 <=1700
## 232 1 <=1700
## 233 1 <=1700
## 234 1 <=1700
# MA HOA VN30
VN30MH=dulieu$VN30
VN30MH=replace(VN30MH,dulieu$VN30<=1900,1)
VN30MH=replace(VN30MH,dulieu$VN30>1900&dulieu$VN30<=2000,2)
VN30MH=replace(VN30MH,dulieu$VN30>2000,3)
VN30=data.frame(dulieu$VN30,VN30MH)
VN30
## dulieu.VN30 VN30MH
## 1 1936.69 2
## 2 1976.82 2
## 3 1967.64 2
## 4 1968.52 2
## 5 1963.01 2
## 6 1984.89 2
## 7 1961.57 2
## 8 1982.96 2
## 9 1979.23 2
## 10 1970.01 2
## 11 1936.15 2
## 12 1942.00 2
## 13 1927.79 2
## 14 1887.06 1
## 15 1875.73 1
## 16 1876.14 1
## 17 1877.68 1
## 18 1876.81 1
## 19 1909.23 2
## 20 1936.46 2
## 21 1922.53 2
## 22 1925.18 2
## 23 1911.09 2
## 24 1902.79 2
## 25 1916.88 2
## 26 1927.35 2
## 27 1917.69 2
## 28 1872.07 1
## 29 1886.27 1
## 30 1849.12 1
## 31 1824.35 1
## 32 1806.50 1
## 33 1829.36 1
## 34 1845.32 1
## 35 1826.90 1
## 36 1881.32 1
## 37 1887.32 1
## 38 1931.65 2
## 39 1941.65 2
## 40 1916.05 2
## 41 1946.06 2
## 42 1939.84 2
## 43 1970.82 2
## 44 1987.11 2
## 45 1998.44 2
## 46 1995.91 2
## 47 1991.11 2
## 48 2002.56 3
## 49 2009.04 3
## 50 2013.35 3
## 51 1995.71 2
## 52 2004.29 3
## 53 2008.57 3
## 54 2004.62 3
## 55 2010.15 3
## 56 1995.12 2
## 57 1980.13 2
## 58 1963.57 2
## 59 1967.22 2
## 60 1957.17 2
## 61 1960.19 2
## 62 1962.48 2
## 63 1944.36 2
## 64 1947.28 2
## 65 1960.97 2
## 66 1951.92 2
## 67 1936.81 2
## 68 1986.28 2
## 69 1982.29 2
## 70 1974.60 2
## 71 1972.99 2
## 72 1989.71 2
## 73 1997.06 2
## 74 1999.82 2
## 75 2022.46 3
## 76 2027.90 3
## 77 2021.72 3
## 78 2010.93 3
## 79 2027.51 3
## 80 2028.94 3
## 81 2027.45 3
## 82 2046.37 3
## 83 2050.58 3
## 84 2068.62 3
## 85 2043.51 3
## 86 2053.97 3
## 87 2040.51 3
## 88 2074.06 3
## 89 2079.10 3
## 90 2053.41 3
## 91 2032.30 3
## 92 2014.62 3
## 93 2022.75 3
## 94 2041.40 3
## 95 2011.42 3
## 96 2024.74 3
## 97 2025.41 3
## 98 2007.08 3
## 99 2009.04 3
## 100 1988.11 2
## 101 1979.19 2
## 102 1961.60 2
## 103 1946.55 2
## 104 1925.66 2
## 105 1928.23 2
## 106 1915.01 2
## 107 1931.01 2
## 108 1840.96 1
## 109 1836.25 1
## 110 1837.43 1
## 111 1852.99 1
## 112 1861.84 1
## 113 1829.59 1
## 114 1811.92 1
## 115 1821.53 1
## 116 1791.25 1
## 117 1814.73 1
## 118 1770.16 1
## 119 1741.05 1
## 120 1797.99 1
## 121 1854.19 1
## 122 1868.84 1
## 123 1873.65 1
## 124 1852.99 1
## 125 1853.60 1
## 126 1859.80 1
## 127 1889.94 1
## 128 1836.96 1
## 129 1780.71 1
## 130 1904.19 2
## 131 1942.76 2
## 132 1956.53 2
## 133 1959.35 2
## 134 2010.75 3
## 135 2061.75 3
## 136 2069.82 3
## 137 2049.64 3
## 138 2050.85 3
## 139 2039.80 3
## 140 2018.64 3
## 141 2016.47 3
## 142 2000.90 3
## 143 1951.58 2
## 144 1947.75 2
## 145 1943.60 2
## 146 1969.27 2
## 147 1988.19 2
## 148 1997.69 2
## 149 2004.31 3
## 150 2029.81 3
## 151 2018.98 3
## 152 1997.13 2
## 153 2019.88 3
## 154 2032.28 3
## 155 2077.76 3
## 156 2082.35 3
## 157 2080.38 3
## 158 2085.61 3
## 159 2094.24 3
## 160 2080.35 3
## 161 2047.48 3
## 162 2067.10 3
## 163 2089.21 3
## 164 2080.24 3
## 165 2066.21 3
## 166 2074.03 3
## 167 2096.76 3
## 168 2055.96 3
## 169 2028.68 3
## 170 2030.63 3
## 171 2009.70 3
## 172 1990.66 2
## 173 1965.97 2
## 174 1976.21 2
## 175 2023.13 3
## 176 2012.87 3
## 177 1985.28 2
## 178 1933.28 2
## 179 1903.47 2
## 180 1897.95 1
## 181 1909.87 2
## 182 1869.84 1
## 183 1867.03 1
## 184 1924.29 2
## 185 1946.98 2
## 186 1973.02 2
## 187 1983.82 2
## 188 1975.50 2
## 189 1979.53 2
## 190 1971.99 2
## 191 1950.12 2
## 192 1933.56 2
## 193 1923.92 2
## 194 1921.18 2
## 195 1923.55 2
## 196 1909.60 2
## 197 1916.36 2
## 198 1899.89 1
## 199 1897.46 1
## 200 1886.20 1
## 201 1898.07 1
## 202 1893.54 1
## 203 1871.54 1
## 204 1864.23 1
## 205 1872.27 1
## 206 1821.60 1
## 207 1804.18 1
## 208 1824.71 1
## 209 1869.60 1
## 210 1886.47 1
## 211 1897.71 1
## 212 1857.64 1
## 213 1885.36 1
## 214 1925.18 2
## 215 1949.76 2
## 216 1949.28 2
## 217 1900.76 2
## 218 1944.60 2
## 219 1945.78 2
## 220 1930.88 2
## 221 1915.90 2
## 222 1870.86 1
## 223 1977.14 2
## 224 2022.27 3
## 225 2009.64 3
## 226 2013.69 3
## 227 2012.28 3
## 228 1980.57 2
## 229 1940.89 2
## 230 1922.95 2
## 231 1909.65 2
## 232 1918.97 2
## 233 1859.51 1
## 234 1859.80 1
VN30M=VN30MH
VN30M=replace(VN30M,VN30MH==1,"<=1900")
VN30M=replace(VN30M,VN30MH==2,">1900&<=2000")
VN30M=replace(VN30M,VN30MH==3,">2000")
VN30MM=data.frame(VN30MH,VN30M)
VN30MM
## VN30MH VN30M
## 1 2 >1900&<=2000
## 2 2 >1900&<=2000
## 3 2 >1900&<=2000
## 4 2 >1900&<=2000
## 5 2 >1900&<=2000
## 6 2 >1900&<=2000
## 7 2 >1900&<=2000
## 8 2 >1900&<=2000
## 9 2 >1900&<=2000
## 10 2 >1900&<=2000
## 11 2 >1900&<=2000
## 12 2 >1900&<=2000
## 13 2 >1900&<=2000
## 14 1 <=1900
## 15 1 <=1900
## 16 1 <=1900
## 17 1 <=1900
## 18 1 <=1900
## 19 2 >1900&<=2000
## 20 2 >1900&<=2000
## 21 2 >1900&<=2000
## 22 2 >1900&<=2000
## 23 2 >1900&<=2000
## 24 2 >1900&<=2000
## 25 2 >1900&<=2000
## 26 2 >1900&<=2000
## 27 2 >1900&<=2000
## 28 1 <=1900
## 29 1 <=1900
## 30 1 <=1900
## 31 1 <=1900
## 32 1 <=1900
## 33 1 <=1900
## 34 1 <=1900
## 35 1 <=1900
## 36 1 <=1900
## 37 1 <=1900
## 38 2 >1900&<=2000
## 39 2 >1900&<=2000
## 40 2 >1900&<=2000
## 41 2 >1900&<=2000
## 42 2 >1900&<=2000
## 43 2 >1900&<=2000
## 44 2 >1900&<=2000
## 45 2 >1900&<=2000
## 46 2 >1900&<=2000
## 47 2 >1900&<=2000
## 48 3 >2000
## 49 3 >2000
## 50 3 >2000
## 51 2 >1900&<=2000
## 52 3 >2000
## 53 3 >2000
## 54 3 >2000
## 55 3 >2000
## 56 2 >1900&<=2000
## 57 2 >1900&<=2000
## 58 2 >1900&<=2000
## 59 2 >1900&<=2000
## 60 2 >1900&<=2000
## 61 2 >1900&<=2000
## 62 2 >1900&<=2000
## 63 2 >1900&<=2000
## 64 2 >1900&<=2000
## 65 2 >1900&<=2000
## 66 2 >1900&<=2000
## 67 2 >1900&<=2000
## 68 2 >1900&<=2000
## 69 2 >1900&<=2000
## 70 2 >1900&<=2000
## 71 2 >1900&<=2000
## 72 2 >1900&<=2000
## 73 2 >1900&<=2000
## 74 2 >1900&<=2000
## 75 3 >2000
## 76 3 >2000
## 77 3 >2000
## 78 3 >2000
## 79 3 >2000
## 80 3 >2000
## 81 3 >2000
## 82 3 >2000
## 83 3 >2000
## 84 3 >2000
## 85 3 >2000
## 86 3 >2000
## 87 3 >2000
## 88 3 >2000
## 89 3 >2000
## 90 3 >2000
## 91 3 >2000
## 92 3 >2000
## 93 3 >2000
## 94 3 >2000
## 95 3 >2000
## 96 3 >2000
## 97 3 >2000
## 98 3 >2000
## 99 3 >2000
## 100 2 >1900&<=2000
## 101 2 >1900&<=2000
## 102 2 >1900&<=2000
## 103 2 >1900&<=2000
## 104 2 >1900&<=2000
## 105 2 >1900&<=2000
## 106 2 >1900&<=2000
## 107 2 >1900&<=2000
## 108 1 <=1900
## 109 1 <=1900
## 110 1 <=1900
## 111 1 <=1900
## 112 1 <=1900
## 113 1 <=1900
## 114 1 <=1900
## 115 1 <=1900
## 116 1 <=1900
## 117 1 <=1900
## 118 1 <=1900
## 119 1 <=1900
## 120 1 <=1900
## 121 1 <=1900
## 122 1 <=1900
## 123 1 <=1900
## 124 1 <=1900
## 125 1 <=1900
## 126 1 <=1900
## 127 1 <=1900
## 128 1 <=1900
## 129 1 <=1900
## 130 2 >1900&<=2000
## 131 2 >1900&<=2000
## 132 2 >1900&<=2000
## 133 2 >1900&<=2000
## 134 3 >2000
## 135 3 >2000
## 136 3 >2000
## 137 3 >2000
## 138 3 >2000
## 139 3 >2000
## 140 3 >2000
## 141 3 >2000
## 142 3 >2000
## 143 2 >1900&<=2000
## 144 2 >1900&<=2000
## 145 2 >1900&<=2000
## 146 2 >1900&<=2000
## 147 2 >1900&<=2000
## 148 2 >1900&<=2000
## 149 3 >2000
## 150 3 >2000
## 151 3 >2000
## 152 2 >1900&<=2000
## 153 3 >2000
## 154 3 >2000
## 155 3 >2000
## 156 3 >2000
## 157 3 >2000
## 158 3 >2000
## 159 3 >2000
## 160 3 >2000
## 161 3 >2000
## 162 3 >2000
## 163 3 >2000
## 164 3 >2000
## 165 3 >2000
## 166 3 >2000
## 167 3 >2000
## 168 3 >2000
## 169 3 >2000
## 170 3 >2000
## 171 3 >2000
## 172 2 >1900&<=2000
## 173 2 >1900&<=2000
## 174 2 >1900&<=2000
## 175 3 >2000
## 176 3 >2000
## 177 2 >1900&<=2000
## 178 2 >1900&<=2000
## 179 2 >1900&<=2000
## 180 1 <=1900
## 181 2 >1900&<=2000
## 182 1 <=1900
## 183 1 <=1900
## 184 2 >1900&<=2000
## 185 2 >1900&<=2000
## 186 2 >1900&<=2000
## 187 2 >1900&<=2000
## 188 2 >1900&<=2000
## 189 2 >1900&<=2000
## 190 2 >1900&<=2000
## 191 2 >1900&<=2000
## 192 2 >1900&<=2000
## 193 2 >1900&<=2000
## 194 2 >1900&<=2000
## 195 2 >1900&<=2000
## 196 2 >1900&<=2000
## 197 2 >1900&<=2000
## 198 1 <=1900
## 199 1 <=1900
## 200 1 <=1900
## 201 1 <=1900
## 202 1 <=1900
## 203 1 <=1900
## 204 1 <=1900
## 205 1 <=1900
## 206 1 <=1900
## 207 1 <=1900
## 208 1 <=1900
## 209 1 <=1900
## 210 1 <=1900
## 211 1 <=1900
## 212 1 <=1900
## 213 1 <=1900
## 214 2 >1900&<=2000
## 215 2 >1900&<=2000
## 216 2 >1900&<=2000
## 217 2 >1900&<=2000
## 218 2 >1900&<=2000
## 219 2 >1900&<=2000
## 220 2 >1900&<=2000
## 221 2 >1900&<=2000
## 222 1 <=1900
## 223 2 >1900&<=2000
## 224 3 >2000
## 225 3 >2000
## 226 3 >2000
## 227 3 >2000
## 228 2 >1900&<=2000
## 229 2 >1900&<=2000
## 230 2 >1900&<=2000
## 231 2 >1900&<=2000
## 232 2 >1900&<=2000
## 233 1 <=1900
## 234 1 <=1900
# MA HOA S&P 500
SP500MH=dulieu$SP500
SP500MH=replace(SP500MH,dulieu$SP500<=6700,1)
SP500MH=replace(SP500MH,dulieu$SP500>6700&dulieu$VN30<=7000,2)
SP500MH=replace(SP500MH,dulieu$SP500>7000,3)
SP500=data.frame(dulieu$SP500,SP500MH)
SP500
## dulieu.SP500 SP500MH
## 1 7656.98 3
## 2 7591.70 3
## 3 7636.36 3
## 4 7673.52 3
## 5 7718.60 3
## 6 7747.71 3
## 7 7666.60 3
## 8 7631.47 3
## 9 7686.14 3
## 10 7711.76 3
## 11 7730.99 3
## 12 7675.70 3
## 13 7677.28 3
## 14 7652.86 3
## 15 7674.37 3
## 16 7641.16 3
## 17 7707.98 3
## 18 7691.76 3
## 19 7745.06 3
## 20 7785.76 3
## 21 7798.99 3
## 22 7748.50 3
## 23 7728.20 3
## 24 7753.11 3
## 25 7757.64 3
## 26 7709.96 3
## 27 7723.55 3
## 28 7736.52 3
## 29 7600.50 3
## 30 7489.72 3
## 31 7437.63 3
## 32 7316.15 3
## 33 7428.78 3
## 34 7413.18 3
## 35 7411.98 3
## 36 7408.30 3
## 37 7498.96 3
## 38 7509.20 3
## 39 7443.28 3
## 40 7457.69 3
## 41 7533.77 3
## 42 7572.40 3
## 43 7543.59 3
## 44 7515.34 3
## 45 7575.39 3
## 46 7543.64 3
## 47 7482.71 3
## 48 7503.85 3
## 49 7537.43 3
## 50 7483.24 3
## 51 7483.23 3
## 52 7499.36 3
## 53 7440.43 3
## 54 7354.02 3
## 55 7357.49 3
## 56 7358.22 3
## 57 7365.46 3
## 58 7472.79 3
## 59 7500.58 3
## 60 7420.10 3
## 61 7511.35 3
## 62 7554.29 3
## 63 7431.46 3
## 64 7394.30 3
## 65 7266.99 3
## 66 7386.65 3
## 67 7405.73 3
## 68 7383.74 3
## 69 7584.31 3
## 70 7553.68 3
## 71 7609.78 3
## 72 7599.96 3
## 73 7580.06 3
## 74 7563.63 3
## 75 7520.36 3
## 76 7519.12 3
## 77 7473.47 3
## 78 7445.72 3
## 79 7432.97 3
## 80 7353.61 3
## 81 7403.05 3
## 82 7408.50 3
## 83 7501.24 3
## 84 7444.25 3
## 85 7400.96 3
## 86 7412.84 3
## 87 7398.93 3
## 88 7337.11 3
## 89 7365.12 3
## 90 7259.22 3
## 91 7200.75 3
## 92 7230.12 3
## 93 7209.01 3
## 94 7135.95 3
## 95 7138.80 3
## 96 7173.91 3
## 97 7165.08 3
## 98 7108.40 3
## 99 7137.90 3
## 100 7064.01 3
## 101 7109.14 3
## 102 7126.06 3
## 103 7041.28 3
## 104 7022.95 3
## 105 6967.38 2
## 106 6886.24 2
## 107 6816.89 2
## 108 6824.66 2
## 109 6782.81 2
## 110 6616.85 1
## 111 6611.83 1
## 112 6582.69 1
## 113 6575.32 1
## 114 6528.52 1
## 115 6343.72 1
## 116 6368.85 1
## 117 6477.16 1
## 118 6591.90 1
## 119 6556.37 1
## 120 6581.00 1
## 121 6506.48 1
## 122 6606.49 1
## 123 6624.70 1
## 124 6716.09 2
## 125 6699.38 1
## 126 6632.19 1
## 127 6672.62 1
## 128 6775.80 2
## 129 6781.48 2
## 130 6795.99 2
## 131 6740.02 2
## 132 6830.71 2
## 133 6869.50 2
## 134 6816.63 2
## 135 6881.62 2
## 136 6878.88 2
## 137 6908.86 2
## 138 6946.13 2
## 139 6890.07 2
## 140 6837.75 2
## 141 6909.51 2
## 142 6861.89 2
## 143 6881.31 2
## 144 6843.22 2
## 145 6836.17 2
## 146 6832.76 2
## 147 6941.47 2
## 148 6941.81 2
## 149 6964.82 2
## 150 6932.30 2
## 151 6798.40 2
## 152 6882.72 2
## 153 6917.81 2
## 154 6976.44 2
## 155 6939.03 2
## 156 6969.01 2
## 157 6978.03 2
## 158 6978.60 2
## 159 6950.23 2
## 160 6915.61 2
## 161 6913.35 2
## 162 6875.62 2
## 163 6796.86 2
## 164 6940.01 2
## 165 6944.47 2
## 166 6926.60 2
## 167 6963.74 2
## 168 6977.27 2
## 169 6966.28 2
## 170 6921.46 2
## 171 6920.93 2
## 172 6944.82 2
## 173 6902.05 2
## 174 6858.47 2
## 175 6845.50 2
## 176 6896.24 2
## 177 6905.74 2
## 178 6929.94 2
## 179 6932.05 2
## 180 6909.79 2
## 181 6878.49 2
## 182 6834.50 2
## 183 6774.76 2
## 184 6721.43 2
## 185 6800.26 2
## 186 6816.51 2
## 187 6827.41 2
## 188 6901.00 2
## 189 6886.68 2
## 190 6840.51 2
## 191 6846.51 2
## 192 6870.40 2
## 193 6857.12 2
## 194 6849.72 2
## 195 6829.37 2
## 196 6812.63 2
## 197 6849.09 2
## 198 6812.61 2
## 199 6765.88 2
## 200 6705.12 2
## 201 6602.99 1
## 202 6538.76 1
## 203 6642.16 1
## 204 6617.32 1
## 205 6672.41 1
## 206 6734.11 2
## 207 6737.49 2
## 208 6850.92 2
## 209 6846.61 2
## 210 6832.43 2
## 211 6728.80 2
## 212 6720.32 2
## 213 6796.29 2
## 214 6771.55 2
## 215 6851.97 2
## 216 6840.20 2
## 217 6822.34 2
## 218 6890.59 2
## 219 6890.89 2
## 220 6875.16 2
## 221 6791.69 2
## 222 6738.44 2
## 223 6699.40 1
## 224 6735.35 2
## 225 6735.13 2
## 226 6664.01 1
## 227 6629.07 1
## 228 6671.06 1
## 229 6644.31 1
## 230 6654.72 1
## 231 6552.51 1
## 232 6735.11 2
## 233 6753.72 2
## 234 6714.59 2
SP500M=SP500MH
SP500M=replace(SP500M,SP500MH==1,"<=6700")
SP500M=replace(SP500M,SP500MH==2,">6700&<=7000")
SP500M=replace(SP500M,SP500MH==3,">7000")
SP500MM=data.frame(SP500MH,SP500M)
SP500MM
## SP500MH SP500M
## 1 3 >7000
## 2 3 >7000
## 3 3 >7000
## 4 3 >7000
## 5 3 >7000
## 6 3 >7000
## 7 3 >7000
## 8 3 >7000
## 9 3 >7000
## 10 3 >7000
## 11 3 >7000
## 12 3 >7000
## 13 3 >7000
## 14 3 >7000
## 15 3 >7000
## 16 3 >7000
## 17 3 >7000
## 18 3 >7000
## 19 3 >7000
## 20 3 >7000
## 21 3 >7000
## 22 3 >7000
## 23 3 >7000
## 24 3 >7000
## 25 3 >7000
## 26 3 >7000
## 27 3 >7000
## 28 3 >7000
## 29 3 >7000
## 30 3 >7000
## 31 3 >7000
## 32 3 >7000
## 33 3 >7000
## 34 3 >7000
## 35 3 >7000
## 36 3 >7000
## 37 3 >7000
## 38 3 >7000
## 39 3 >7000
## 40 3 >7000
## 41 3 >7000
## 42 3 >7000
## 43 3 >7000
## 44 3 >7000
## 45 3 >7000
## 46 3 >7000
## 47 3 >7000
## 48 3 >7000
## 49 3 >7000
## 50 3 >7000
## 51 3 >7000
## 52 3 >7000
## 53 3 >7000
## 54 3 >7000
## 55 3 >7000
## 56 3 >7000
## 57 3 >7000
## 58 3 >7000
## 59 3 >7000
## 60 3 >7000
## 61 3 >7000
## 62 3 >7000
## 63 3 >7000
## 64 3 >7000
## 65 3 >7000
## 66 3 >7000
## 67 3 >7000
## 68 3 >7000
## 69 3 >7000
## 70 3 >7000
## 71 3 >7000
## 72 3 >7000
## 73 3 >7000
## 74 3 >7000
## 75 3 >7000
## 76 3 >7000
## 77 3 >7000
## 78 3 >7000
## 79 3 >7000
## 80 3 >7000
## 81 3 >7000
## 82 3 >7000
## 83 3 >7000
## 84 3 >7000
## 85 3 >7000
## 86 3 >7000
## 87 3 >7000
## 88 3 >7000
## 89 3 >7000
## 90 3 >7000
## 91 3 >7000
## 92 3 >7000
## 93 3 >7000
## 94 3 >7000
## 95 3 >7000
## 96 3 >7000
## 97 3 >7000
## 98 3 >7000
## 99 3 >7000
## 100 3 >7000
## 101 3 >7000
## 102 3 >7000
## 103 3 >7000
## 104 3 >7000
## 105 2 >6700&<=7000
## 106 2 >6700&<=7000
## 107 2 >6700&<=7000
## 108 2 >6700&<=7000
## 109 2 >6700&<=7000
## 110 1 <=6700
## 111 1 <=6700
## 112 1 <=6700
## 113 1 <=6700
## 114 1 <=6700
## 115 1 <=6700
## 116 1 <=6700
## 117 1 <=6700
## 118 1 <=6700
## 119 1 <=6700
## 120 1 <=6700
## 121 1 <=6700
## 122 1 <=6700
## 123 1 <=6700
## 124 2 >6700&<=7000
## 125 1 <=6700
## 126 1 <=6700
## 127 1 <=6700
## 128 2 >6700&<=7000
## 129 2 >6700&<=7000
## 130 2 >6700&<=7000
## 131 2 >6700&<=7000
## 132 2 >6700&<=7000
## 133 2 >6700&<=7000
## 134 2 >6700&<=7000
## 135 2 >6700&<=7000
## 136 2 >6700&<=7000
## 137 2 >6700&<=7000
## 138 2 >6700&<=7000
## 139 2 >6700&<=7000
## 140 2 >6700&<=7000
## 141 2 >6700&<=7000
## 142 2 >6700&<=7000
## 143 2 >6700&<=7000
## 144 2 >6700&<=7000
## 145 2 >6700&<=7000
## 146 2 >6700&<=7000
## 147 2 >6700&<=7000
## 148 2 >6700&<=7000
## 149 2 >6700&<=7000
## 150 2 >6700&<=7000
## 151 2 >6700&<=7000
## 152 2 >6700&<=7000
## 153 2 >6700&<=7000
## 154 2 >6700&<=7000
## 155 2 >6700&<=7000
## 156 2 >6700&<=7000
## 157 2 >6700&<=7000
## 158 2 >6700&<=7000
## 159 2 >6700&<=7000
## 160 2 >6700&<=7000
## 161 2 >6700&<=7000
## 162 2 >6700&<=7000
## 163 2 >6700&<=7000
## 164 2 >6700&<=7000
## 165 2 >6700&<=7000
## 166 2 >6700&<=7000
## 167 2 >6700&<=7000
## 168 2 >6700&<=7000
## 169 2 >6700&<=7000
## 170 2 >6700&<=7000
## 171 2 >6700&<=7000
## 172 2 >6700&<=7000
## 173 2 >6700&<=7000
## 174 2 >6700&<=7000
## 175 2 >6700&<=7000
## 176 2 >6700&<=7000
## 177 2 >6700&<=7000
## 178 2 >6700&<=7000
## 179 2 >6700&<=7000
## 180 2 >6700&<=7000
## 181 2 >6700&<=7000
## 182 2 >6700&<=7000
## 183 2 >6700&<=7000
## 184 2 >6700&<=7000
## 185 2 >6700&<=7000
## 186 2 >6700&<=7000
## 187 2 >6700&<=7000
## 188 2 >6700&<=7000
## 189 2 >6700&<=7000
## 190 2 >6700&<=7000
## 191 2 >6700&<=7000
## 192 2 >6700&<=7000
## 193 2 >6700&<=7000
## 194 2 >6700&<=7000
## 195 2 >6700&<=7000
## 196 2 >6700&<=7000
## 197 2 >6700&<=7000
## 198 2 >6700&<=7000
## 199 2 >6700&<=7000
## 200 2 >6700&<=7000
## 201 1 <=6700
## 202 1 <=6700
## 203 1 <=6700
## 204 1 <=6700
## 205 1 <=6700
## 206 2 >6700&<=7000
## 207 2 >6700&<=7000
## 208 2 >6700&<=7000
## 209 2 >6700&<=7000
## 210 2 >6700&<=7000
## 211 2 >6700&<=7000
## 212 2 >6700&<=7000
## 213 2 >6700&<=7000
## 214 2 >6700&<=7000
## 215 2 >6700&<=7000
## 216 2 >6700&<=7000
## 217 2 >6700&<=7000
## 218 2 >6700&<=7000
## 219 2 >6700&<=7000
## 220 2 >6700&<=7000
## 221 2 >6700&<=7000
## 222 2 >6700&<=7000
## 223 1 <=6700
## 224 2 >6700&<=7000
## 225 2 >6700&<=7000
## 226 1 <=6700
## 227 1 <=6700
## 228 1 <=6700
## 229 1 <=6700
## 230 1 <=6700
## 231 1 <=6700
## 232 2 >6700&<=7000
## 233 2 >6700&<=7000
## 234 2 >6700&<=7000
###CAU C.1
# THONG KE DANG RATIO SCALE :
library(psych)
abctb=data.frame(VNIMH,VN30MH,SP500MH)
describe(abctb)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## VNIMH 1 234 2.15 0.82 2 2.19 1.48 1 3 2 -0.29 -1.46 0.05
## VN30MH 2 234 2.04 0.74 2 2.05 1.48 1 3 2 -0.07 -1.18 0.05
## SP500MH 3 234 2.32 0.68 2 2.40 1.48 1 3 2 -0.50 -0.82 0.04
#NHAN XET:
# Ca 3 chi so deu co 234 quan sat khong khuyet thieu
# Chi so SP500MH co gia tri trung binh cao nhat(2.321) va trung vi (2,5), voi phan lon quan sat tap trung o nhom 3 (104 quan sat, chiem 44,4%)
#Chi so VNIMH co trung binh 2.154,nghieng nhieu ve nhom 3 (99 quan sat, chiem 42,3%)
#Chi so VN30MH co trung binh thap nhat (2.043),phan lon tap trung o nhom 2 (106 quan sat, chiem 45,3%)
# Tinh mode va phuong sai VNI
library(DescTools)
##
## Attaching package: 'DescTools'
## The following objects are masked from 'package:psych':
##
## AUC, ICC, SD
Mode(VNIMH)
## [1] 3
## attr(,"freq")
## [1] 99
table(VNIMH)
## VNIMH
## 1 2 3
## 63 72 99
var(VNIMH)
## [1] 0.6715087
#NHAN XET:Mode cua bien VNIMH la 3 voi 99 quan sat
#Phuong sai cua bien VNIMH = 0.6715087
# Tinh mode va phuong sai VN30
library(DescTools)
Mode(VN30MH)
## [1] 2
## attr(,"freq")
## [1] 106
table(VN30MH)
## VN30MH
## 1 2 3
## 59 106 69
var(VN30MH)
## [1] 0.5475221
#NHAN XET:Mode cua bien VN30MH la 2 voi 106 quan sat
#Phuong sai cua bien VN30MH = 0.5475221
# Tinh mode va phuong sai SP500
library(DescTools)
Mode(SP500MH)
## [1] 3
## attr(,"freq")
## [1] 104
table(SP500MH)
## SP500MH
## 1 2 3
## 29 101 104
var(SP500MH)
## [1] 0.4676461
#NHAN XET:Mode cua bien SP500MH la 3 voi 104 quan sat
#Phuong sai cua bien SP500MH = 0.4676461
###C.2: RATIO SCALE
library(psych)
abctb=data.frame(dulieu$VNI,dulieu$VN30,dulieu$SP500)
describe(abctb)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## dulieu.VNI 1 234 1771.87 84.44 1777.00 1773.32 112.95 1580.54 1927.94 347.40 -0.16 -1.07 5.52
## dulieu.VN30 2 234 1952.45 74.25 1958.26 1954.45 79.45 1741.05 2096.76 355.71 -0.26 -0.54 4.85
## dulieu.SP500 3 234 7100.40 376.37 6943.14 7089.89 401.23 6343.72 7798.99 1455.27 0.28 -1.28 24.60
#NHAN XET: Bien co gia tri trung binh cao nhat la dulieu$SP500 = 7100
#Bien co do phan tan lon nhat la dulieu$SP500 voi Gmd = 426.5
#dulieu$VNI co trung vi = 1773 , dulieu$VN30 co trung vi = 1954 ,dulieu$SP500 co trung vi = 7117
#dulieu$VNI, dulieu$VN30,dulieu$SP500 co gia tri nho nhat lan luot la 1580.54,1741.05,6343.72
#dulieu$VNI, dulieu$VN30,dulieu$SP500 co gia tri lon nhat lan luot la 1927.94,2096.76,7798.99
# Phuong sai
var(dulieu$VNI)
## [1] 7129.79
var(dulieu$VN30)
## [1] 5513.643
var(dulieu$SP500)
## [1] 141653.9
#NHAN XET: Phuong sai cua 3 bien dulieu$VNI,dulieu$VN30,dulieu$SP500 lan luot la 7129.79, 5513.643 , 141653.9
###CAU D.Ve do thi
#D.1 DO THI TRON
pie(table(VNIM),col=c("darkseagreen","forestgreen","lightgreen"),main="DO THI CHI SO VN INDEX")
pie(table(VN30M),col=c("wheat","lightyellow","yellow"),main="DO THI CHI SO VN30")
pie(table(SP500M),col=c("azure","lightblue","royalblue"),main="DO THI CHI SO SP500")
#NHAN XET: Do thi tron chi so VN INDEX chiem ty trong lon nhat la >1800 diem va chiem ty trong nho nhat la <=1700
#Do thi tron chi so VN30 chiem ty trong lon nhat la >1900&<=2000 diem va chiem ty trong nho nhat la <=1900
#Do thi tron chi so SP500 chiem ty trong lon nhat la >7000 va chiem ty trong nho nhat la <=6700
#D.2 DO THI COT
VNIM.freq<-table(VNIM)
VNIM.freq
## VNIM
## <=1700 >1700&<=1800 >1800
## 63 72 99
barplot(VNIM.freq,xlab="Diem",ylab="So ngay",main="Bieu do cot cua chi so VN INDEX",col=c("magenta","hotpink","lightpink"))
#NHAN XET: Cot >1800 diem co so ngay lon nhat = 99 ngay , cot <=1700 diem co so ngay nho nhat = 63 ngay
VN30M.freq<-table(VN30M)
VN30M.freq
## VN30M
## <=1900 >1900&<=2000 >2000
## 59 106 69
barplot(VN30M.freq,xlab="Diem",ylab="So ngay",main="Bieu do cot cua chi so VN 30",col=c("blue","lightblue","azure"))
#NHAN XET: Cot >1900&<=2000 diem co so ngay lon nhat = 106 ngay , cot <=1900 diem co so ngay nho nhat = 59 ngay
SP500M.freq<-table(SP500M)
SP500M.freq
## SP500M
## <=6700 >6700&<=7000 >7000
## 29 101 104
barplot(SP500M.freq,xlab="Diem",ylab="So ngay",main="Bieu do cot cua chi so SP500",col=c("forestgreen","darkseagreen","lightgreen"))
#NHAN XET: Cot >7000 diem co so ngay lon nhat = 104 ngay , cot <=6700 diem co so ngay nho nhat = 29 ngay
#D.3 DO THI DUONG
plot(dulieu$STT,dulieu$VNI,type="o",xlab="ngay thu",ylab="diem VNI",pch=19,main="Diem cua VNI tu ngay 1 den ngay 234",col="darkgreen")
plot(dulieu$STT,dulieu$VN30,type="o",xlab="ngay thu",ylab="diem VN30",pch=19,main="Diem cua VN30 tu ngay 1 den ngay 234",col="red")
plot(dulieu$STT,dulieu$SP500,type="o",xlab="ngay thu",ylab="diem SP500",pch=19,main="Diem cua SP500 tu ngay 1 den ngay 234",col="hotpink")
#NHAN XET:
#Trong 234 ngay,ca 3 chi so VNI,VN30 va SP500 deu co su bien dong giam manh tai giai doan ngay 100-120
#Chi so VNI va VN30 co xu huong bien dong rat tuong dong nhau,dat 2 dinh lon tai khoang ngay 60-70 va ngay 130-140
#Chi so SP500 duy tri o muc cao dau chu ky, giam manh tai giai doan ngay 100-120,sau do phuc hoi va di ngang tich luy quanh muc 6800-7000 diem o giai doan sau.
###CAU E PHAN TICH TUONG QUAN
VNI=dulieu$VNI
VN30=dulieu$VN30
SP500=dulieu$SP500
library(psych)
vars=cbind(VNI,VN30,SP500)
pairs.panels(vars)
library(Hmisc)
##
## Attaching package: 'Hmisc'
## The following objects are masked from 'package:DescTools':
##
## %nin%, Label, Mean, Quantile
## The following object is masked from 'package:psych':
##
## describe
## The following objects are masked from 'package:base':
##
## format.pval, units
result=rcorr(as.matrix(vars),type="pearson")
result$r
## VNI VN30 SP500
## VNI 1.0000000 0.8724787 0.5218174
## VN30 0.8724787 1.0000000 0.2350912
## SP500 0.5218174 0.2350912 1.0000000
result$P
## VNI VN30 SP500
## VNI NA 0.0000000000 0.0000000000
## VN30 0 NA 0.0002857094
## SP500 0 0.0002857094 NA
#NHAN XET:
#Cac bien VNI,VN30,SP500 deu co moi quan he tuong quan duong voi nhau vi he so tuong quan Pearson cua cac moi quan he nay > 0
#Moi tuong quan giua cac bien VNI,VN30,SP500 co y nghia thong ke vi gia tri Sig.(p-value) cua cac moi quan he nay deu nho hon 5%(p<0.005)
# DO THI TUONG QUAN DA BIEN
library(psych)
vars=cbind(VNI,VN30,SP500)
pairs.panels(vars)
#NHAN XET:
#VNI va VN30 co moi tuong quan duong rat manh voi he so r = 0.87, cac diem phan tan tap trung di theo duong cheo tang.
#VNI va SP500 co moi tuong quan duong o muc trung binh voi he so r = 0.52, du lieu co xu huong tang nhung phan tan rong hon.
#VN30 va SP500 co moi tuong quan duong yeu voi he so r = 0.24, cac diem phan tan rai rac.
#Duong cheo chinh cho thay VNI va VN30 co phan bo tuong doi doi xung, trong khi SP500 co dang phan bo 2 dinh.
###CAU F MO HINH HOI QUY TUYEN TINH DA BIEN
mreg=lm(VNI~VN30+SP500)
summary(mreg)
##
## Call:
## lm(formula = VNI ~ VN30 + SP500)
##
## Residuals:
## Min 1Q Median 3Q Max
## -68.935 -24.353 1.831 16.333 76.002
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -524.28020 59.42185 -8.823 2.79e-16 ***
## VN30 0.90252 0.02803 32.197 < 2e-16 ***
## SP500 0.07521 0.00553 13.599 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 30.88 on 231 degrees of freedom
## Multiple R-squared: 0.8674, Adjusted R-squared: 0.8662
## F-statistic: 755.5 on 2 and 231 DF, p-value: < 2.2e-16
###nhan xet cau f:
#phuong trinh hoi quy: VNI = -524.28020 + 0.90252*VN30 + 0.07521*SP500 + ei
#ket qua hoi quy cho thay mo hinh co y nghia thong ke tong the
#voi gia tri F-statistic bang 755.5 va muc y nghia (p < 0,001)
#he so R2 = 0.8674; cho thay cac bien VN30 va SP500 giai thich khoang 86,74% su bien thien cua VNI
#trong khi R2 hieu chinh dat 0.8662
#xet rieng tung bien, VN30 co tac dong cung chieu den VNI voi he so hoi quy 0.90252
#dieu nay co nghia khi VN30 tang 1 don vi thi VNI tang 0.90252 don vi (voi đieu kien SP500 khong doi)
#va moi quan he nay co y nghia thong ke o muc 1% (p < 0,001)
#SP500 cung co tac dong cung chieu voi he so hoi quy 0.07521 va co y nghia thong ke o muc 1% (p < 0,001)
#cho thay khi SP500 tang 1 don vi thi VNI tang 0.07521 don vi
#nhin chung, ca hai bien VN30 va SP500 deu co moi quan he cung chieu
#va co y nghia thong ke voi VNI trong mo hinh nghien cuu.
###CAU G:
mreg=lm(VNI~VN30+SP500)
summary(mreg)
##
## Call:
## lm(formula = VNI ~ VN30 + SP500)
##
## Residuals:
## Min 1Q Median 3Q Max
## -68.935 -24.353 1.831 16.333 76.002
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -524.28020 59.42185 -8.823 2.79e-16 ***
## VN30 0.90252 0.02803 32.197 < 2e-16 ***
## SP500 0.07521 0.00553 13.599 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 30.88 on 231 degrees of freedom
## Multiple R-squared: 0.8674, Adjusted R-squared: 0.8662
## F-statistic: 755.5 on 2 and 231 DF, p-value: < 2.2e-16
library(car)
## Loading required package: carData
##
## Attaching package: 'car'
## The following object is masked from 'package:DescTools':
##
## Recode
## The following object is masked from 'package:psych':
##
## logit
vif(mreg)
## VN30 SP500
## 1.058501 1.058501
require(lmtest)
## Loading required package: lmtest
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
dwtest(mreg)
##
## Durbin-Watson test
##
## data: mreg
## DW = 0.07651, p-value < 2.2e-16
## alternative hypothesis: true autocorrelation is greater than 0
op=par(mfrow=c(2,2))
plot(mreg)
###nhan xet cau g:
#Kiem dinh da cong tuyen cho thay VIF cua VN30 va SP500 deu bang 1.058501, nho hon 2 => Mo hinh khong co da cong tuyen dang ke.
#Kiem dinh Durbin-Watson cho thay DW = 0.07651, p-value < 2.2e-16 => Mo hinh co hien tuong tu tuong quan duong bac nhat rat manh.
#Do thi Residuals vs Fitted: Duong xu huong mau do uon cong => Co dau hieu dang ham tuyen tinh chua phu hop hoan toan.
#Do thi Q-Q Residuals: Phan lon cac diem nam gan duong cheo => Phan du co xu huong gan phan phoi chuan.
#Do thi Scale-Location: Duong xu huong mau do giam => Co dau hieu phuong sai sai so khong dong nhat.
#Do thi Residuals vs Leverage: Mot so quan sat co do don bay cao hon cac diem con lai => Can kiem tra them khoang cach Cook de danh gia muc do anh huong.
#=> Mo hinh khong co da cong tuyen dang ke, nhung co tu tuong quan duong manh va dau hieu phuong sai sai so khong dong nhat. Can xem xet cac khuyet tat truoc khi ket luan ve do tin cay cua mo hinh.