The reality of the Relationship Between the Return and the Standard Deviation as a Risk

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[14] A. M. Chisholm, An introduction to capital markets: Products, strategies, participants. John Wiley \& Sons, 2003. APPENDIXES Appendix .1 Table (3-1) analyzes the standard deviation of positive and negative values (profits andlosses) as default share prices. Source: - Preparing by the researcher using (Excel,2013) 1 A B 2 C D E 1 Ri Ri 11 Ri Ri(A,C) Ri(A,B) 2 1.00 -1.00 10 -0.09 1.00 1.00 3 0.50 -0.50 9 -0.10 0.50 0.50 4 0.33 -0.33 8 -0.11 0.33 0.33 5 0.25 -0.25 7 -0.13 0.25 0.25 6 0.20 -0.20 6 -0.14 0.20 0.20 7 0.17 -0.17 5 -0.17 0.17 0.17 8 0.14 -0.14 4 -0.20 0.14 0.14 9 0.13 -0.13 3 -0.25 0.13 0.13 10 0.11 -0.11 2 -0.33 0.11 0.11 11 0.10 -0.10 1 -0.50 0.10 0.10 ---- ---- ----- ----- ---- -0.09 -1.00 -0.10 -0.50 -0.11 -0.33 -0.13 -0.25 -0.14 -0.20 -0.17 -0.17 -0.20 -0.14 -0.25 -0.13 -0.33 -0.11 -0.50 -0.10 Average 0.293 -0.293 -0.20 0.05 0 Ϭ 0.277 0.277 0.13 0.33 0.40 Appendix .2 Table (3-2) Analysis of the return and risk of General Electric Company (GE) for the period (2015-2019) GE Close price log Ri Loss Profit Dec, 2019 11.16 1.047664195 -0.010 -0.010 Oct, 2019 11.27 1.051923916 0.129 0.129 Sep , 2019 9.98 0.999130541 0.116 0.116 Aug , 2019 8.94 0.951337519 0.084 0.084 Jul , 2019 8.25 0.916453949 -0.211 -0.211 Jun , 2019 10.45 1.01911629 -0.005 -0.005 May , 2019 10.5 1.021189299 0.112 0.112 Apr , 2019 9.44 0.974971994 -0.072 -0.072 Mar , 2019 10.17 1.007320953 0.018 0.018 Mar, 2019 9.99 0.999565488 -0.038 -0.038 Feb , 2019 10.39 1.016615548 0.063 0.063 Jan , 2019 9.77 0.989894564 0.342 0.342 Dec, 2018 7.28 0.862131379 0.010 0.010 Oct , 2018 7.21 0.857935265 -0.257 -0.257 Sep , 2018 9.71 0.98721923 -0.106 -0.106 Aug , 2018 10.86 1.035829825 -0.127 -0.127 Jul , 2018 12.44 1.09482038 -0.051 -0.051 Jun , 2018 13.11 1.117602692 0.002 0.002 May , 2018 13.09 1.116939647 -0.033 -0.033 Apr , 2018 13.54 1.131618664 0.001 0.001 Mar , 2018 13.53 1.131297797 0.044 0.044 Mar , 2018 12.96 1.112605002 -0.045 -0.045 Feb , 2018 13.57 1.132579848 -0.127 -0.127 Jan , 2018 15.55 1.191730393 -0.073 -0.073 Dec , 2017 16.78 1.224791956 -0.046 -0.046 Oct , 2017 17.59 1.245265839 -0.092 -0.092 Sep , 2017 19.38 1.287353773 -0.166 -0.166 Aug , 2017 23.25 1.366422957 -0.015 -0.015 Jul , 2017 23.61 1.373095987 -0.041 -0.041 Jun , 2017 24.63 1.391464412 -0.052 -0.052 May, 2017 25.97 1.41447195 -0.014 -0.014 Apr , 2017 26.33 1.420450859 -0.056 -0.056 Mar , 2017 27.88 1.445292769 -0.027 -0.027 Feb , 2017 28.66 1.457276186 0.004 0.004 Jan , 2017 28.56 1.455758203 -0.060 -0.060 Dec , 2016 30.38 1.48258777 0.027 0.027 Oct , 2016 29.58 1.47099817 0.057 0.057 Sep , 2016 27.98 1.44684771 -0.018 -0.018 Aug , 2016 28.48 1.454539985 -0.052 -0.052 Jul , 2016 30.04 1.477699928 0.003 0.003 Jun , 2016 29.94 1.476251796 -0.011 -0.011 May , 2016 30.27 1.481012421 0.041 0.041 Source:- Preparing by the researcher using (Excel, 2013) according to data of http://finance.yahoo.com/quote/GE Apr , 2016 29.07 1.463445032 -0.017 -0.017 Mar , 2016 29.57 1.470851325 -0.033 -0.033 Mar , 2016 30.57 1.485295439 0.091 0.091 Feb , 2016 28.02 1.447468131 0.001 0.001 Jan , 2016 27.98 1.44684771 -0.066 -0.066 Dec , 2015 29.95 1.476396827 0.040 0.040 Oct , 2015 28.79 1.459241665 0.035 0.035 Sep , 2015 27.81 1.444200989 0.147 0.147 Aug , 2015 24.25 1.384711743 -0.030 -0.030 Jul, 2015 25.01 1.398113692 -0.004 -0.004 Jun , 2015 25.1 1.399673721 -0.018 -0.018 May , 2015 25.55 1.407390904 -0.026 -0.026 Apr , 2015 26.22 1.418632687 0.007 0.007 Mar , 2015 26.04 1.41564098 0.091 0.091 Mar , 2015 23.86 1.377670439 -0.045 -0.045 Feb , 2015 24.99 1.397766256 0.088 0.088 Jan , 2015 22.97 1.361160995 -0.055 -0.055 Dec,2014 24.3 1.385606274 Average 20.21 1.26 -0.01 -0.06 0.06 Ϭ 8.17 0.204 0.089 0.058 0.074 Appendix .3 Table (3-3) Analysis of the return and risk of General Electric Company (Appl) for the period (2015-2019) Apple Close price log Ri Loss Profit Dec, 2019 293.65 2.468 0.09878391 0.09878391 Oct , 2019 267.25 2.427 0.07432867 0.07432867 Sep, 2019 248.76 2.396 0.110684467 0.110684467 Aug , 2019 223.97 2.350 0.072961579 0.072961579 Jul , 2019 208.74 2.320 -0.020184 -0.020184 Jun , 2019 213.04 2.328 0.076394503 0.076394503 May, 2019 197.92 2.296 0.130519221 0.130519221 Apr, 2019 175.07 2.243 -0.12757263 -0.12757263 Mar, 2019 200.67 2.302 0.158937338 0.158937338 Feb , 2019 173.15 2.238 0.040314828 0.040314828 Jan, 2019 166.44 2.221 0.055154051 0.055154051 Dec, 2018 157.74 2.198 -0.1166984 -0.1166984 Oct, 2018 178.58 2.252 -0.18404459 -0.18404459 Sep , 2018 218.86 2.340 -0.03047754 -0.03047754 Aug , 2018 225.74 2.354 -0.00830295 -0.00830295 Jul , 2018 227.63 2.357 0.196226812 0.196226812 Jun , 2018 190.29 2.279 0.027983361 0.027983361 May, 2018 185.11 2.267 -0.00941831 -0.00941831 Apr, 2018 186.87 2.272 0.130763645 0.130763645 Mar, 2018 165.26 2.218 -0.07219852 -0.07219852 Feb , 2018 178.12 2.251 0.063847578 0.063847578 Jan, 2018 167.43 2.224 -0.01063641 -0.01063641 Dec , 2017 169.23 2.228 -0.01524585 -0.01524585 Oct , 2017 171.85 2.235 0.016623284 0.016623284 Sep , 2017 169.04 2.228 0.096807682 0.096807682 Aug , 2017 154.12 2.188 -0.0602439 -0.0602439 Jul , 2017 164 2.215 0.102669266 0.102669266 Jun , 2017 148.73 2.172 0.032703791 0.032703791 May , 2017 144.02 2.158 -0.05721393 -0.05721393 Apr , 2017 152.76 2.184 0.06341803 0.06341803 Mar , 2017 143.65 2.157 0.048616687 0.048616687 Feb, 2017 136.99 2.137 0.128883395 0.128883395 Jan, 2017 121.35 2.084 0.047746503 0.047746503 Dec , 2016 115.82 2.064 0.047955121 0.047955121 Oct, 2016 110.52 2.043 -0.02659856 -0.02659856 Sep , 2016 113.54 2.055 0.004334365 0.004334365 Aug, 2016 113.05 2.053 0.065504241 0.065504241 Jul , 2016 106.1 2.026 0.018136455 0.018136455 Jun , 2016 104.21 2.018 0.090062762 0.090062762 May, 2016 95.6 1.980 -0.04265972 -0.04265972 Apr , 2016 99.86 1.999 0.065286964 0.065286964 Mar , 2016 93.74 1.972 -0.03050988 -0.03050988 Feb , 2016 96.69 1.985 -0.00667762 -0.00667762 Jan , 2016 97.34 1.988 -0.07524226 -0.07524226 Source:- Preparing by the researcher using (Excel, 2013) according to data http://finance.yahoo.com/quote/Appl Dec , 2015 105.26 2.022 -0.11022823 -0.11022823 Oct , 2015 118.3 2.073 -0.01004184 -0.01004184 Sep , 2015 119.5 2.077 0.083408885 0.083408885 Aug , 2015 110.3 2.043 -0.02320227 -0.02320227 Jul , 2015 112.92 2.053 -0.06908491 -0.06908491 Jun, 2015 121.3 2.084 -0.03292673 -0.03292673 May , 2015 125.43 2.098 -0.03722751 -0.03722751 Apr , 2015 130.28 2.115 0.040990811 0.040990811 Mar , 2015 125.15 2.097 0.068197337 0.068197337 Jan , 2015 117.16 2.069 0.061424171 0.061424171 Dec , 2014 110.38 2.043 Average 155.79 2.17 0.02 -0.05 0.07 Ϭ 47.64 0.128 0.077 0.046 0.043

@article{1703946,
      author = {Abbas Fadhil Resen },
      title = {The reality of the Relationship Between the Return and the Standard Deviation as a Risk},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {6},
      pages = {170-181},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703946.pdf},
      abstract = {Financial management uses the standard deviation as a basic indicator to measure and evaluate the risk of the share or portfolio targeted for investment as one of the statistical dispersion measures adopted in this field. Standard deviation is also widely used in other financial indicators to assess the level of portfolio investment risk and performance. With all of these indicators, this type of investment is still subject to violent shocks, which result in financial crises and shocks that have negative effects on the performance of local, regional, and global financial markets. Here, the research seeks to check the validity of adopting the standard deviation index as a risk and the accuracy of the results that this statistical indicator gives to the investor in light of its wide use. The most important findings of the researcher have confirmed that there is a technique that can be followed to fix the fault that results from squaring the values. These values exist under the root which leads to the alteration of all return values into positive values and distorts the evaluation, we can do the process by separating positive returns from negative returns and then calculating the standard deviation of the return positive values as a safety indicator with a direct correlation. The rise of this indicator specifies a high percentage of profits that exceed its arithmetic average (average return). While another standard deviation depends on the negative return values (such as risk) because they show the level of losses that exceed its arithmetic mean. The higher the ratio is, the higher the risk will be, then compare them according to the client's level of risk and his level of profit-seeking. As for the most important recommendations acclaimed by the researcher are to adopt the standard deviation of negative observations only from the returns approved in the evaluation to calculate the risk among other indicators that adopt this indicator (the standard deviation) to reach wider indicators in use such as the ratio of Sharp and the calculation of systemic risk (beta) Add to the market deviation and variance.},
      keywords = {Risk and Return, Stocks, Financial markets, Capital return.},
      month = {December},
  }