A prognosis oriented microscopic stock market model

We present a new microscopic stochastic model for an ensemble of interacting investors that buy and sell stocks in discrete time steps via limit orders based on individual forecasts about the price of the stock. These orders determine the supply and demand fixing after each round (time step) the new price of the stock according to which the limited buy and sell orders are then executed and new forecasts are made. We show via numerical simulation of this model that the distribution of price differences obeys an exponentially truncated Levy-distribution with a self similarity exponent mu~5.Comment: 14 pages RevTeX, 5 eps-figures include

Towards and Effective Financial Management: Relevance of Dividend Discount Model in Stock Price Valuation

The aim of this paper is to analyze the relevance of dividend discount model, i.e. its specific form in stock price estimation known as Gordon growth model. The expected dividends can be a measure of cash flows returned to the stockholder. In this context, the model is useful for assessment of how risk factors, such as interest rates and changing inflation rates, affect stock returns. This is especially important in case when investors are value oriented, i.e. when expected dividends are their main investing drivers. We compared the estimated with the actual stock price values and tested the statistical significance of price differences in 199 publicly traded European companies for the period 2010-2013. Statistical difference between pairs of price series (actual and estimated) was tested using Wilcoxon and Kruskal-Wallis tests of median and distribution equality. The hypothesis that Gordon growth model cannot be reliable measure of stock price valuation on European equity market over period of 2010-2013 due to influence of the global financial crisis was rejected with 95% confidence. Gordon growth model has proven to be reliable measure of stock price valuation even over period of strong global financial crisis influence

Two Price Regimes in Limit Order Books: Liquidity Cushion and Fragmented Distant Field

The distribution of liquidity within the limit order book is essential for the impact of market orders on the stock price and the emergence of price shocks. Hence it is of great interest to improve the understanding of the time-dependent dynamics of the limit order book. In our analysis we find a broad distribution of limit order lifetimes. Around the quotes we find a densely filled regime with mostly short living limit orders, far away from the quotes we find a sparse filling with mostly long living limit orders. We determine the characteristics of those two regimes and point out the main differences. Based on our research we propose a model for simulating the regime around the quotes

VALUATION OF BANKING STOCKS (BUMN) INCLUDED IN LQ45 IN 2013-2017 USING RELATIVE VALUATION METHODS: PRICE EARNING RATIO AND PRICE- BOOK VALUE

Sitting in the LQ 45 range is an honor for a banking company because it indicates if the capital market participants believe and also have admitted if the level of liquidity and market capitalization of the company is good. For issuers who have entered into the LQ 45 index does not mean to be able to relax, but must still work hard to maintain its position because these shares will continue to be monitored by the Indonesia Stock Exchange (BEI). This research will calculate PER and PBV of the banking sector that stands still in LQ45 within 5 years (2011-2016) and provide a comparison result whether there is a significant difference between the result of calculation of fair share by both methods and comparable stock valuation within banks that persisted in LQ 45 index for 5 years. The data used in the form of secondary data i.e. financial statements and data of dividend distribution company in cash. Data collection gathered are secondary data taken from www.idx.com, www.e-bursa.com, Bloomberg, ICMD, and yahoo finance. Hypothesis testing is done by Kolmogorov Smirnov normality test, and t-test i.e. independent samples t-test used to determine whether two samples unrelated to each other have different mean values. The purpose of t-test in this study is to compare stock price as a dependent variable and price earnings ratio as an independent variable, whether there are significant differences or not on the stock prices, and as price-book value become independent variable then stock price as dependent variable, whether there are significant differences or not on the results. Keywords: LQ 45 Index, Banking Industry, Valuation, PER, PB

Research on the Influence of Institutional Investors' Shareholding and Transaction on Stock Price Synchronicity

Chinese institutional investors have experienced rapid growth in both size and volume over the past decade, but their role in the capital market has been inconclusive. By investigating the institutional investors' shareholdings and trading behaviors from 2007 to 2017, the study found that China's stock market overall stock price synchronicity is high. The share price of stocks with high institutional shareholdings is lower, while the increase in institutional investor transactions has failed to reduce stock price synchronicity. By further examining the impact of different types of institutional investor behavior on stock price synchronicity, it is found that there are differences in the influence of various types of institutional investors, and the shareholding and trading behavior of trusts, pension funds and QFII will reduce stock price synchronicity. Therefore, in order to maintain the stability of the capital market, we should continue to vigorously develop institutional investors while improving the structure of institutional investors and optimizing the company's dividend distribution mechanism

PERBEDAAN ABNORMAL RETURN PADA SAAT SEBELUM DAN SESUDAH PENGUMUMAN PEMECAHAN SAHAM TERHADAP PERUSAHAAN YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI) TAHUN 2004- 2010

IKA MERDEKAWATY. The Differences Abnormal Return Before and After Stock Splits Announcement of Companies Listed on The Indonesian Stock Exchange in 2004- 2010. Jakarta, Faculty of Economics, State University of Jakarta, 2010 This research aimed the determine whether there are differences before and after stock splits announcements of campanies listed on the Indonesian Stock Exchange in 2004-2010, so that investors can take advantage of the moment to make a profit Stock splits is a corporae action taken by the company to break a piece of stock to more aimed to the new pirce in order that stock price are within the range appropriate so that small investorswho are interested, the more widespread distribution of shares, as well as signal to the public that the company has a good performance and a good prespect in the future. Stock splits announcement generally gets a reaction from the market in the form of an increase or decrase in the stock price can be measured by using abnormal return. This study uses ex post facto survey and comparative approach. The population of this research is that companies do stock splits during the year 2004-2010 amounted 63 companies and the number of samples taken by 40 companies. Data collection by taking the secondary data available on Capital Market Data Centre (PDPM) IBII during the window period is 11 trading days consisting of 5 days prior to the announcement, 1-day, 5 days after the announcement of the date of execution, stock splits date, the daily closing stock price, and daily Composite Stock Proce Index. For the normality test show that L table before is 0,11270 and L after was 0,0585 and L 0,1400. It means that data has normal dstribution. Test of homogeneity obtained F at 5% significance level is 1.70 and F were obtained from the calculation of 1.53 and smaller than F table, it can be concluded that the sample variance is homogeneous. Once the data proved normal and homogeneous, then to test the hypothesis used paired sample t-test and obtained t count tabel 2.33 and 2.02 t Table . Because t countl > t concluded that there are differences in abnormal returns both before and after the announcement of split

Generalized Multiplicative Error Models: Asymptotic Inference and Empirical Analysis

Title from PDF of title page, viewed on August 7, 2015Dissertation advisor: Yong ZengVitaIncludes bibliographic reference (pages 109-117)Thesis (Ph.D.)--Department of Mathematics and Statistics and Department of Economics. University of Missouri--Kansas City, 2015This dissertation consists of two parts. The first part focuses on extended Multiplicative Error Models (MEM) that include two extreme cases for nonnegative series. These extreme cases are common phenomena in high-frequency financial time series. The Location MEM(p,q) model incorporates a location parameter so that the series are required to have positive lower bounds. The estimator for the location parameter turns out to be the minimum of all the observations and is shown to be consistent. The second case captures the nontrivial fraction of zero outcomes feature in a series and combines a so-called Zero-Augmented general F distribution with linear MEM(p,q). Under certain strict stationary and moment conditions, we establish a consistency and asymptotic normality of the semiparametric estimation for these two new models. The second part of this dissertation examines the differences and similarities between trades in the home market and trades in the foreign market of cross-listed stocks. We exploit the multiplicative framework to model trading duration, volume per trade and price volatility for Canadian shares that are cross-listed in the New York Stock Exchange (NYSE) and the Toronto Stock Exchange (TSX). We explore the clustering effect, interaction between trading variables, and the time needed for price equilibrium after a perturbation for each market. The clustering effect is studied through the use of univariate MEM(1,1) on each variable, while the interactions among duration, volume and price volatility are captured by a multivariate system of MEM(p,q). After estimating these models by a standard QMLE procedure, we exploit the Impulse Response function to compute the calendar time for a perturbation in these variables to be absorbed into price variance, and use common statistical tests to identify the difference between the two markets in each aspect. These differences are of considerable interest to traders, stock exchanges and policy makers.Introduction -- Literature review -- Location multiplicative error model(1,1): asymptotic properties of a modified QMLE -- Asymptotic analysis for location MEM(p,q) -- Asymptotic analysis for zero-augmented generalized F distribution MEM (p,p) -- Cross-listed shares behavior in domestic and foreign markets: an application of vector MEM -- Conclusion -- Appendix A. Proofs for chapter 3 -- Appendix B. Proofs for chapter 4 -- Appendix C. Proofs for chapter

The impact of order size on stock liquidity: a representative study

Liquidity, the ease of trading an asset, strongly varies between different sizes of stock positions. We analyze this aspect using the Xetra Liquidity Measure (XLM), which calculates daily, weighted spread for impatient traders transacting against the limit order book. For this measure, we have data for 160 German stocks over 5.5 years, which allows us a representative analysis of the order-size impact on liquidity cost and its main statistical characteristics. We find that in the sample period average liquidity costs rose to over 100bp in large DAX and to 460bp in large SDAX positions. Over the last 5.5 years, liquidity has equally improved across all order sizes. Liquid position sizes, however, suffered less badly during the recent sub-prime crises, which represents another type of the flight-to-liquidity. As the basis for further theoretical analysis, we find that trends in liquidity levels and inefficiencies in liquidity prices of large positions generate non-normality in the liquidity distribution. We also show that - as a rule of thumb - liquidity of an order size relative to market value and transaction volume is constant across stocks and time. While order size is not the most important liquidity determinant, doubling order size increases liquidity cost by 5-10% on average when accounting for other differences in stocks. --asset liquidity,liquidity cost,price impact,weighted spread,Xetra liquidity measure (XLM)