Track: High School STEM Project Presentation
Abstract
Various methods are contemplated to trigger a financial investment action. Earning high return and avoiding the variableness risk is a common denominator of investors, but there are all sorts and conditions of investors. Some investors choose risk averse investment in other hand other investors choose risk taking investment. However the ultimate goal of these investors is to form a portfolio that satisfy the minimum needs expected rate of return and minimize the expected risk.
The conflicted connection of expected rate of return and risk was suggested by Markowitz(1952). The efficiency of diversified investment got identified through ‘Portfolio selection theory’ in Markowitz(1952). It decides the investment percentage of reducing the risk and getting highest return. Markowitz portfolio selection theory had been a root and representative of modern investment theory and made a great ripple effect in financial market. Markowitz got credit around the globe by receiving the Nobel Prize for economics.
This research practically analyzed the performance of India stock market by using the investment algorithm based on Markowitz portfolio selection. Indian Bombay stock exchange market was founded in 1875 which holds the longest history in Asia. Research part CEO of Indian financial investment company Aditya Birla predicted that “India SENSEX index will get twice for the next few year.” However it is not sufficient for research which proved Indian markets’ performance by using Markowitz model or harmonizing the theory in Korea.
The investment period holds nine years through 2006 to 2014 to observe the sudden changes in market volatility. 2006-2007 takes up phase before the subprime mortgage crisis, and 2008-2009 takes rapid down phase after 2010-2014 takes Recovery period. Like this, the experiment period takes special fluctuating economic conditions. This research benchmarks SENSEX index which includes 30th market capitalization of India Bombay Stock Exchange(BSE). When we measure the modeled performance, we added exchange stock transaction charge and tax to identical with reality while rebalancing the portfolio. Therefore frequent rebalancing will reflect the market conditions, but too much transaction cost will be required. However possibility of error existed only to beg the rebalancing cycle as eight weeks.
To form an optimal portfolio, Data reference period was fixed in three years and analyzed the portfolio that shows highest performance when the rebalancing cycle were four, eight, and twelve weeks. In addition this paper measure Sharpe ratio which examine the performance of an investment by adjusting for its risk.
After the process portfolio is composed with three setups. Minimum expected rate of return K is divided into 10%, 15%, 20%, 25%, 30% and rebalancing cycle was divided into four weeks, eight weeks and twelve weeks, In addition, three years of data reference period was applied at the latest date from first investment point. Due to the result, four weeks of rebalancing cycle performed higher return rate at every section and K more than SENSEX rate of change. In other hand, SENSEX index showed higher Sharpe ratio than each portfolio at every section. The highest Sharpe ratio shown in portfolio was twelve weeks of rebalancing cycle and 25% of K, the lowest Sharpe ratio shown in portfolio was four weeks of rebalancing cycle and 30% of K. Therefore in terms of risk-adjusted return, the optimal portfolio is twelve weeks of rebalancing and 25% K. The optimal portfolio in terms of return rate is 4 weeks of rebalancing cycle and 30% K.
In conclusion, the investment portfolio has been constructed using past data on investment profit for the study. The study draw the optimal solution for portfolio selection, and the proposed methodology showed productive investment outcome.