Hisse senedi analiz yöntemleri, portföy analizi ve bir uygulama
Stock analysis, portfolio management and a study on several stocks of İstanbul stock exchange market
- Tez No: 14387
- Danışmanlar: DOÇ.DR. NİYAZİ BERK
- Tez Türü: Yüksek Lisans
- Konular: İşletme, Business Administration
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1991
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 99
Özet
ÖZET Hisse senedi analiz yöntemleri, portföy analizi, analizde yararlanılabilecek istatistiksel kavramlar ve kullanılabilecek modellerin incelendiği bu çalışma dört bölümden oluşmaktadır. Birinci bölümde hisse senedi analiz yöntemleri incelenmekte, temel olarak piyasa trendlerini veri olarak kabul eden teknik analiz konusu üzerinde durulmakta ve kullanılan modeller örneklerle açıklanmaktadır. ikinci bölümde hisse senedi analizinde yararlanı labilecek istatistiksel kavramlar açıklanmakta, hisse senedinin riskinin birer göstergesi olarak kabul edilen varyans ve beta katsayısı ile korelasyon katsayısı kav ramları açıklanmakta ve kullanılabilecek formüller ince lenmektedir. üçüncü bölümde portföy analizi ile ilgili modeller incelenmekte, portföy oluşturmak suretiyle hisse senetle rinin risklerinin ne şekilde da ğıta labil diği ve beklenen getirinin. nasıl bir değişim gösterdiği konusunda başvuru labilecek iki temel model olan Markawitz modeli, ve Finan sal Varlık Fiyat landırma Modeli açıklanmış ve karşılaştı rıl m ıştır. Dördüncü bölümde, İstanbul Menkul Kıymetler Borsa sı 'nda işlem görmekte olan 20 adet hisse senedini içeren bir uygulama yapılmıştır. Hisse senetlerinin riskleri he saplanmış, sistematik ve sistematik olmayan risk olarak bölümlendiril miş, böylece riskin hangi oranlarda piyasa dalgalanmaları ve firma içi faktörlere bağlı olduğu incelenmiştir. v
Özet (Çeviri)
SUMMARY STOCK ANALYSIS, PORTFOLIO MANAGEMENT AND A STUDY ON SEVERAL STOCKS OF ISTANBUL STOCK EXCHANGE MARKET STOCK ANALYSIS METHODS The Basic Analysis The aim of the basic analysis is to determine the monetary value of a stock and consider this value with the market value in a period of time which is observed. This analysis gives the investor the opportunity of making decision to select the stocks for investment. The analysis before evaluating the stocks are the analysis of economy, sector and the analysis of companies. The infprmations obtained from these analysis are as the fol lowings: a) Future earnings of company, b) The divident ratio to be paid to shareholders, c) Growth ratio of divident, d) Price / earnings ratio. The increases and decreases in stock prices in the future can be estimated by the graphics which show the price and volume trends by technical analysis method. In technical analysis, the reasons of changes in the prices are not taken into consideration. The only importanat subject is to determine the best time to buy and sell the stock or the best stock to buy. II. SOME STATISTICAL CONCEPTS In portfolio theory, the subject to be interested in is what happens when individual securities are combined into a portfolio. The risk of a portfolio is usually measured in terms of the variability in its returns. As a consequence, one of the major questions to be asked is“ What happens to the variability in the returns to the portfolio as one or more stocks are added to the bundle? ”TiThe three statistics which used to describe the simple probability distribution are the expected value, the variance, and the standart deviation. If the disribution and its associated probabilities can be observed, the population values can be computed for these statistics. Otherwise, it's necessary to infer its shape by taking sample estimates of these statistics. The joint probability distribution depicts the relationship between two stocks or between a single stock and the market portfolio. Three of the statistics that describe the properties of the joint probability distri bution are the covariance, the coefficient of correlation and the coefficient of determination. The covariance is unbounded and provides an information only about the di rection of the relationship. The correlation coefficient can be thought of as a standardized covarience and ranges between +1 and -1. The square of correlation coefficient is equal to the coefficient of determination. It gives information about the percentage of the variability in the returns on one investment that can be explained by variability in the returns on another. The relationship between a stock and the market portfolios described by the stocks characteristic line. The slope of the characteristic line is called the stocks beta factor. It shows the change in stock's return which is in relation with the change in market's return. The residual variancs of a stock indicates the propensity of the returns to deviate from its characteristic line. If a stock is perfectly correlated with the market, its re sidual variance is equal to zero. The beta factor is defined as the systematic risk and includes, a) The risk of interest rate, b) Purchasing risk and c) Market risk. III. PORTFOLIO MANAGEMENT When a portfolio is constructed by investing some of money in one stock and the rest in one other, there becomes a question to be asked“What will the probability distribution of returns to the portfolio look like ?”If the standart deviation is accepted as a reason able of the risk of a portfolio, it will be find out how viito predict the risk and expected rate of return of a portfolio based on the characteristic of the stocks put into it. The expected portfolio return is simply a weighted average of the expected rate of return of the stocks in it. The weights are the fractions of the investment com- mited to each security in the portfolio. If a security is bought, the weight for it is positive; if it is sold short, the weight is negative. The portfolio variance is determined on the basis of a covariance matrix for the individual stocks in the portfolio. For each covariance element in the matrix, the covariance is multiplied by the two portfolio weights for the associated stocks. Then sum of all the products is equal to the variance of the portfolio. A combination line shows what happens to the expected return and standard deviation of a two security portfolio as the portfolio weigths changed in two securi ties. Combination lines are linear for the cases of per - feet pasitive or perfect negative correlation between the returns on the two securities. Between these limits of correlation; combination lines are curved. If one of the investment is risk - free; the combination line is a straight line. It extends out from the risk-free rate and passing through the position of the other risky invest- men t. The Markawitz Model and The Single Index Model The Markowitz model and the single-index model are used as portfolio models in constructing the minimum variance set. The difference between the two models is the formulas used in each to determine the variance of a portfolio. The formula used by Markawitz is perfectly accurate; the formula used by the single-index model is an approximation that is as accurate as its assumption that the residuals for differnt stocks are perfectly uncorrelated with each other. The Markwitz model dosen ' t make any assumption regarding the source of the variances between stocks in the covariance matrix. However, the single-index model assumes that the residuals, or deviations from the characteristic line will be uncorrelated with each other. The variance of portfolio in Markawitz model is computed by the following formulas viiim 2 cr* (rp ) = S Xj xk Cav ( r., rR ) J, K X If the population is large, a large number of covariances will be estimated and a large amount of computational time is required to compute the variance of any given portfolio. This is the problem with the Markawitz model. An alternative formula is needed to calculate the portfolio variance that is capable of dealing with large population of stocks. If the single -index model is used to find the minimum variance set, the following formula can be used; m m aMr.) = [ S x.p- ]2 (T2 (r ) + £ x2 CT2(e.) P., J J m. j j j=l j=i This formula shows that less amount of time is required to compute the variance of a portfolio by using single- index model. The Capital Asset Pricing Model This model can be viewed as a theory of the way stocks would be priced if rational investors in the market took positions on the officient set. The CAPM implies a linear, positively sloped relationship between expected return of stock and beta. There are two conditions to be accepted; The first is, the probability distributions for portfolio return are normal. In this case, the probabilitiy distributions are fully described by their expected returns and standard deviations. The second is that the relationship between investor utility and portfolio wealth are quadratic in form. In this case, the investor is concerned with the expected return and the standard ixdeviation. In the Capital Asset Pricing Model, the risk of a portfolio is measured in terms of its standard deviation or variance. The security market line is drawn in expected return-beta space. It is linear and positively sloped. All individual securities and portfolios are positioned on the security market line. In the last section, twenty stocks of Istanbul Stock Exchange are analysed to find the systematic and unsystematic risk of these stocks. At the result it is found that the average of systematic risk is nearly 59“/. and the average of unsystematic risk is nearly 41 ”/. of the average risk of these 20 stocks.
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