Type of paper:Â | Report |
Categories:Â | Equity Risk management Financial management |
Pages: | 4 |
Wordcount: | 1013 words |
Presentation of the changes in the portfolio to the client based on the differences between the years
The investment kinds used in the U.S. annual returns and benchmarking results are on the financials, consumer, industrial, health care, and information. The utilizes and the S& P U.S. trends, and the S& P 500 index also present results based on the years. In the ending year of 2013, the consumer demand for products were high, with 3.06% with utilities having the lowest investments of 1.13%. The clients at this year had to invest more in S& P 500 index having 2.39%, which was the highest in the all period between 2013 and 2019. The negative trends on the S&P of -0.16% show there were poor sales, and thus, there should be no investment to be taken into consideration. In 2014, the investment on utilizes was registered to be higher with 2.21%, and therefore it was the best time for investing in the sector. In 2015, investing in information was most profound since there was a high percentage of 1.00%. The financial industry in 2015 had the most negative value of -0.05% which makes the clients not invest in it rather information sector being more preferred (Bai, X., Scheinberg, K. and Tutuncu, R., 2016 p. 21). In the preceding year of 2016, the financial sector portfolio was at 1.88% is the highest while the healthcare sector was lower, with -0.16% which has a higher risk of being invested in by the different customers. In 2017, the information sector had a high value of 2.81%, thus boosting the investment value for more clients. The utilities in 2017 were 0.18%, thus causing the investors to invest in the information sector according to the portfolio information (Fabozzi, F.J. and Markowitz, H.M. eds., 2011 p. 33). In 2018, most sectors were performing at negatively, but the most exciting industry for the clients was healthcare, with a value of 0.65%. The financial industry was performing at its lowest since it had -1.05%. In 2019, the information sector was the most profound with 3.56%, thus attracting more clients based on having lower risk. The healthcare on the other side had a lower value of 1.64%, thus making it highly risky, and therefore, clients had to be discouraged from investing.
Comparison of assets allocation
The total annual return depicts that in 2019 the most provident portfolio to be invested in was of 2.37%. The benchmarking performance gives a good illustration of more precision for pooling in more investments for the clients to have an annual rate of 2.055. In 2014, investment in the U.S. trend was also favorable for doing business, and this presents the clients to be more introduced to the market of portfolios (Roncalli, T. and Weisang, G., 2016 p. 36). The two methods used in the comparison of the portfolios of assets to be invested in include risk parity and the trend following. In the computation of the risk parity method, there is the use of the total weights for identifying the risk levels.
Asset class vol1/volWeight
Asset class1 0.51% 5 16.67
Asset class 2 0.09% 4 33.33
Asset class 3 0.18% 2 50
Total 11 100
(Galane, L.C., 2014 p. 102)
The risk parity approach is based on the alternatives of the asset classes that have a high value. The risk parity depicted shows a reduction of the weight of equities, and there is an increase in the bonds for the creation of a good portfolio. There is an illustration of equal allocation of risk on the asset classes of 108 and 2019. The risk parities of the portfolios are treated to come from the equities during the computation of the volume and the weighted total of the bonds allocated.
The second approach is on the trend followed by (Faber, M.2007 p. 67), it deals with an illustration of quantitative values that are tactical for asset allocation. There is an illustration of sharing risky asset classes with a total of 20%. The asset classes are divided into bonds, international stocks, property, commodities, and the U. S trends. The assessment of each stock is based on the price rise and the average trend of the positive trend. In 2013 there were 0 annual returns on the portfolio while its benchmark portfolio was 0.00%, thus showing low prices sold. In 2019 it depicted the highest asset class of annual returns of 2.05% with its rice in benchmarking, resulting in giving a suitable value. The positive results on the annual returns make the clients more investments in the asset class of 2019. The negative asset class of -0.28% shows a reduction in the annual returns of 2018 to 0.090%. The clients, therefore, for the best market for the allocation of equity bonds are in the asset class of 2019 with a positive percentage (Forsyth, P.A., and Vetzal, K.R., 2017 p. 87). The beginning of allocation of the asset starts with a zero, but it rises to a positive value with time, thus making more clients but their investments in the market.
Notably, the most preferred approach to be used by the clients to assess the equity allocation of bonds into their portfolio stocks of U.S trends is the risk parity technique. The risk parity shows the volumes, asset classes, and the weighted total for the clients to weigh on the most market to be issued with equity at the end of the year. The asset allocation strategies that are most good for investments of the equity remain to be the risk parity method, and this depicts the positive values and the share of 60/40 equity allocation on the portfolio of the risks that arise out of the equities which were in 2019.
References
Bai, X., Scheinberg, K., and Tutuncu, R., 2016. Least-squares approach to risk parity in portfolio selection. Quantitative Finance, 16(3), pp.357-376.
Faber, M. T. (2007). A quantitative approach to tactical asset allocation. The Journal of Wealth Management, 9(4), 69-79.
Fabozzi, F.J. and Markowitz, H.M. eds., 2011. The theory and practice of investment management: Asset allocation, valuation, portfolio construction, and strategies (Vol. 198). John Wiley & Sons.
Forsyth, P.A., and Vetzal, K.R., 2017. Dynamic mean-variance asset allocation: Tests for robustness. International Journal of Financial Engineering, 4(02n03), p.1750021.
Galane, L.C., 2014. The risk parity approach to asset allocation (Doctoral dissertation, Stellenbosch: Stellenbosch University).
Roncalli, T., and Weisang, G., 2016. Risk parity portfolios with risk factors. Quantitative Finance, 16(3), pp.377-388.
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