Portfolio Return and Risk Analysis of Two Different Equity Investment Styles - Research Proposal Example

Abstract

Investment management is concerned with the professional management of securities such as shares or bonds and also financial assets such as real estate businesses (Schub, 2013). Clients include both institutions such as schools or investment companies (Swensen, 2000). At a more personal level, the clients may include mutual investment schemes. Portfolio management involves trying to find the balance between risks and potential performance of asset investment, taking into account asset allocation and SWOT analysis that will help in choosing between equity and debt. It's all about trying to maximize return on a given risk. The managers can provide personalized investment solutions to clients (Markowitz, 2009). The investment management industry has gone on to give employment for many people (100,000 as of July 2008 in Asia), generating a lot of revenue ($120 million per year in Europe and Asia as of 2008).

1. INTRODUCTION

Style means a group of assets that are categorized together due to the similar financial characteristics that they share. The two commonly used equity style measures are capitalization and valuation. For analysis, classification and dishing out equity portfolios firms have gone on to use investment style as the principle method. Investment funds have been rated based on this principle. Investors nowadays use this technique to select the appropriate shares for investing into and to also get diversity on their investment. In response to this most mutual equity schemes have started to classify themselves as being of distinct investment styles, and using terms such as "small company value" in their brand names.

Both institutional and individual investors have positively taken to style investing. The reasons for this believed to be the simplification of which stocks and funds have been classified, such that instead of choosing from thousands of securities listed; there are fewer categories involved. The benefit of this is that investors can efficiently make good decisions on where they need to invest in since information is amply simplified (Mullainathan, 2000). Investors can also identify good portfolio managers for their funds as investment styles usually get graded with their respective directors. Managers are ranked using statistical values such as growth value index, and through this, the elite individuals are easy to identify (Sharpe, 1992).

These benefits are specifically taken advantage of by institutional investors such as investment and pension schemes where portfolios have to be systematically allocated through following a set of stipulated rules

The origin of different investment styles usually boils down to fundamental factors in their funds becoming favorable, with time the style develops and matures as investors flock in, adding funds, raising the profile of the said style. With time, the method becomes obsolete as the emerging marketing trends prove unfavorable. This completes its life cycle and later it may reemerge.

Recently, investment style has grown in stature and importance; this clearly means that it has a bigger say on the financial markets and valuing of their various funds. The model of this paper combines two differing investment styles and the portfolio performance each generates, taking into account other fundamentals that play a significant role in deciding whether they prove profitable or not.

1.2 Research Objective

The main goal of this research work was to identify the relationship between portfolio performance and risk related to two different investing styles over three separate time frames in Chinese funds.

2. LITERATURE REVIEW

Investors are categorized into two, passive and active. The passive investors hang onto the funds for a long time with the intention of waiting for a huge appreciation in stock prices, thus a low turnover. On the contrary, the active investors look for a short time fix, buying and selling shares with the aim of quick profit. Research suggests that passive investment usually outperforms active investment (Sachs 2010). This is because active portfolio management a lot of trading fee is incurred resulting to reduced profit on the whole. Over a period, it was discovered active investment incurred a charge of 40.4 bases while the passive one was on a basis of 5 (French 2008).

Investment portfolios are classified as either growth stocks or value stocks. An investment fund will be termed as a value stock if it has a high dividend yield and a low P/E rate showing that the stock is trading at a lower price compared to its fundamentals. On the other hand, a growth stock has a low dividend outing and a high P/E rate showing that the company has a high capital value rather than a high income (Lakonishok et al., 1994)

When an investment client decides to invest in growth stocks, they should consider the company's cash flows positive, revenues through dividends and income. Value stocks provide higher returns in comparison to growth stocks. Stock with a low P/E rate has a higher return than that with a high P/E rate (Bassu 1977).This was done with stocks from the NYSE, over 1300 in number between 1955 and 1970. According to Chan et al. (2002), investments in value stocks proved more profitable than in growth stocks in the Japanese market. In the research, they used cash flow, (C/P) income yields (E/P) and the stature of the company for the findings.

According to another report (Fama and French 1992), value stocks had a higher return due to a lot of risks that they carried underneath. Port et al. (1997) concluded that the reason value stocks had a higher profit margin was due to the lower expectations for returns in comparison to the growth stock.("glamour stocks") This analysis was made after studying stock prices at the NYSE between 1976 and 1993.

3. RESEARCH DATA AND METHODOLOGY

3.1 Data

Data for this study was spread into three separate time windows, before, during and after the crisis. A period that spans between 2004 and 2013 in years. The data is compiled from Data stream, the national market is gotten from the China-A share market index, and it entails most of the companies listed on the Chinese stock exchange; Shenzen. Data in the form of A-share indices was also retrieved from Data stream. The five companies for each style were chosen based on the P/E were the first 1/3 are large-cap, the 2/3 is mid-cap and the last 3/3 are small cap. Also, all the companies chosen had experienced an unexpected stability throughout the three-time frames, thus allowing for easy, consistent value calculations.

Chinese risk factors are derived from the Morning Star Inc. The values for the bonded fault risk premiums are calculated by the mathematical difference between huge corporate securities and the securities of the government. Measurements for the bond risk horizons are acquired through the numerical difference between the country's Treasury bill and government securities involved. Inflation rates, on the other hand, are gotten from the Chinese consumer price index.

3.2 Data Analysis and Methodology

The companies whose stock listings from Large-cap growth were used are; Shenzhen Kondarl (food producer), Xinjiang ( mining), Steyr Motors (automobiles and parts) China NAT.Accord MDC (Pharmaceuticals biotechnology) and Jinvheng Paper (forestry & paper) and for large-cap Value; Foshan Elect.(Household goods & home construction), Shijiazhuahng Dongfang (electricity), Yanatai Moon ( Industrial engineering) Cofco Bioch ( food producers) and Shane Industry (real estate investment & services).

To obtain the portfolio performance, the formula for the monthly price return in decimal number is:

. Which can be used to measure the return on monthly basis.

The analysis has been used based on investing all the money in all of the stocks where 20% of the money will be invested in each based on 5 different stocks.

The minimum variance portfolios (Optimization) have been done through the Solver using Microsoft Excel. These are shown in the appendix section as table 1 for EWP and table 2 for minimum variance portfolio (MVP)

4.0 Findings and discussion

4.1 Comparison of equal weighted portfolio with minimum variance portfolio.

The equal weight portfolio indexes across the three tome periods tend to have higher returns compared to the minimum variance portfolio both for the large cap growth and value models.

The equal weighted portfolio gives all company a level ground for comparison since it uses the company capitalization as the basis.

On comparing the equal weight portfolio indexes of the two models the large value seeming to be doing better than the large growth in the first two periods but the same changes in the last period.

The minimum variance portfolio operates on the assumption that the higher the variance the higher the risks. Considering the main aim of investing is returns the investors are advised to use that model that offers the minimum risk variance against the maximum return variance.

Using the assumption across the time plans the time span of 2009-2013 provides the maximum return with minimum risk for large growth model while the same period is the most favorable for large value stock model. However a comparison of the two models investors would prefer the large growth model of stock management.

4.2 Basic statistics (mean, median, SD, Variance, Kutorsis, Skewness, Minimum, and maximum)

The statistics have been calculated using excel spread sheets and will be used to analyze the performance of the selected company. The analysis table for the basic statistics are shown in table 3 in the appendix section.

For the performance of the companies’ improved progressive to the second time period with an increase in the mean standard deviations increasing during the second time

frame indicated an increase risks and the fall of the same in the third time period implying reduced relative risks and higher returns with only Cofco Botch displaying rather different characteristics

The variance increases across the models and down the time spans implying that investors are exposed to considerable more risks as the expected returns increase and therefore the selection of the best performing company and the mode of analysis considers the across the time spans.

The maximum increase progressively though the three time spans for Foshan and Shijiazhuang while the other companies increased during the second period and decrease in the third period while the minima uniformly for the companies increased during the second period and decreased through to the third spans.

Kurtosis and skewness assumption is that the portfolio positions are constant through time. In practice they are not, and regardless of the distribution of the financial asset returns, the portfolio returns might exhibit more extreme values than the financial assets themselves purely because the positions are changing. In this article, we examine the skew and kurtosis of portfolio residue.

The kurtosis graph of this companies would be more fat tailed, since the kurtosis gets as large as 5 and as low as -0.5. This implies that asset returns forecasting ability of the companies increase with increase in return on the assets across the three time flames. On the basis therefore companies’ performance were higher in the first time span and decreased in the second spans. With the improved returns in the last span indicate the probability to increase in returns using the large growth stock model.

Conclusions

The large growth stock model is the popular portfolio management and that it has gained popularity among diverse portfolio managers. In practice a management model gains popularity depending on the economic times but is actually faced out as the time progresses and may later emerge in the future. The popularity of the model depends on the capital market variables and its ability to manipulate the same to produce a reflection of the real market risks and the expected returns. The models assume that the large the standard deviation the higher the risks. Therefore, the need to closely study the expected returns with respect to standard deviation to determ9ine the highest possible tern with the minimum/ lowest possible level of risks.