scholarly journals Daily Stock Price Behavior of Commercial Banks in Nepal

2007 ◽  
Vol 3 (1) ◽  
pp. 100-110 ◽  
Author(s):  
Keshar J. Baral ◽  
Surya Kumar Shrestha
Keyword(s):  
Stock Prices ◽  
Commercial Banks ◽  
Stock Price ◽  
Serial Correlation ◽  
Fiscal Year ◽  
Price Behavior ◽  
Data Set ◽  
Business Studies ◽  
Random Walk Hypothesis ◽  
The Past

Using the data set on daily stock prices during the fiscal year 2005/06 (July 16, 2005 through July 16, 2006), this paper attempts to analyze the stock price behavior of commercial banks in Nepalese markets. The results of serial correlation and run tests conclude that the proposition of Random Walk Hypothesis (RWH) in Nepalese stock markets does not hold true. This conclusion corroborates with the conclusions of the past studies carried out in Nepalese context.Journal of Nepalese Business Studies 2006/III/1 pp. 100-110

scholarly journals Stock Price Behavior of Nepalese Commercial Banks: Random Walk Hypothesis

2018 ◽  
Vol 5 ◽  
pp. 42-52
Author(s):  
Nirajan Bam ◽  
Rajesh Kumar Thagurathi ◽  
Bipin Shrestha
Keyword(s):  
Random Walk ◽  
Stock Prices ◽  
Commercial Banks ◽  
Stock Price ◽  
Fiscal Year ◽  
Data Set ◽  
Random Walk Hypothesis ◽  
The Past ◽  
Random Behavior ◽  
Run Test

Using the data set on daily stock prices during the fiscal year 2015/16 (Sept 23, 2015 through Dec 22, 2015), this paper attempts to analyze the random behavior of stock price of Nepalese Commercial Banks by using run test, serial correlation and run tests and martingale random walk hypothesis under heteroscedasticity assumption of standard error. The results conclude that the proposition of Random Walk Hypothesis (RWH) in Nepalese stock markets does not hold true. This conclusion corroborates with the conclusions of the past studies carried out in Nepalese context.

scholarly journals Was There a Bubble in the 1929 Stock Market?

1993 ◽  
Vol 53 (3) ◽  
pp. 549-574 ◽  
Author(s):  
Peter Rappoport ◽  
Eugene N. White
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Price Behavior ◽  
The Past ◽  
Cointegration Tests ◽  
The Future ◽  
Historical Accounts

In contrast to historical accounts of the boom and crash of the 1929 stock market, recent econometric studies have concluded that there were no bubbles in the American stock market over the past one hundred years. Examining the pricing of loans to stock brokers, we find information on the lenders' perceptions of the future course of stock prices in 1929. From this market, we extract an estimate of the bubble in stock prices. This bubble component contributes significantly to explain stock price behavior, even though standard cointegration tests suggest that there was no bubble in the market.

Stock Price Behavior Associated with Post-1974–75 LIFO Adoptions Announced at Alternative Disclosure Times

1996 ◽  
Vol 11 (4) ◽  
pp. 535-564 ◽  
Author(s):  
Morton Pincus ◽  
Charles E. Wasley
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Earnings Announcements ◽  
Market Response ◽  
Price Behavior ◽  
Positive Information ◽  
Earnings Announcement ◽  
Earnings Growth ◽  
Adoption Decision ◽  
Annual Earnings

We examine the behavior of stock prices at the time of post-1974–75 LIFO adoption announcements. We exploit recent theoretical and empirical developments in the LIFO adoption literature in an attempt to resolve some of the mixed findings in Hand (1993). We study LIFO adoptions announced prior to as well as at the time of annual earnings announcements. Previous research has mostly centered on 1974–75 adoptions made at the time of annual earnings announcements. Our study of LIFO adoptions announced prior to annual earnings announcement dates enables us to provide evidence on whether the early announcement of a LIFO adoption is used by firms to signal positive information about earnings growth. Collectively, our results suggest that in explaining the market response to LIFO adoption announcements, extant models of the LIFO adoption decision do not fully capture the richness of differing inflationary environments or of alternative disclosure times.

scholarly journals Prediksi Harga Saham Dalam Berinvestasi Pada Perusahaan Manufaktur

2021 ◽  
Vol 9 (2) ◽  
pp. 101-114
Author(s):  
Fauziyah Fauziyah
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Manufacturing Industry ◽  
Stock Exchange ◽  
Manufacturing Sector ◽  
Prediction Method ◽  
Manufacturing Companies ◽  
Upward Trend ◽  
Stock Trading ◽  
The Past

Abstract Indonesia Stock Exchange (IDX) is a term that is well known in the world of stocks in Indonesia. One of the company sectors listed on the IDX is manufacturing. The contribution of the manufacturing sector to Gross Domestic Product (GDP) was recorded to be the largest compared to other sectors. In this research, the manufacturing companies that will be used as the object of research to predict their stock prices are manufacturing companies listed in LQ45. In stock trading, prices fluctuate up or down. Stock conditions that fluctuate every day make investors who are going to invest in the Manufacturing industry must observe and study the past company data before investing. This data is important for investors to find out what might happen to a company's stock price. Thus, predicting stock prices in the manufacturing industry for the future is needed as a stage in deciding which manufacturing companies are good to investing in. The prediction method in this research uses ARIMA. The results obtained are the stock prices of companies GGRM, HMSP, ICBP, INDF, INTP and UNVR following a downward trend, so that the actions taken by investor in these companies are selling stocks, while for the stock prices of companies ASII, CPIN, INKP, JPFA, SMGR, TKIM, following an upward trend, so that the actions taken by investors in these companies are buying stocks.Keywords: Prediction, ARIMA, Investment  BEI merupakan istilah yang terkenal pada dunia saham di Indonesia. Sektor perusahaan yang terdapat di BEI salah satunya adalah manufaktur. Kontribusi sektor manufaktur dalam Produk Domestik Bruto (PDB) tercatat yang paling besar dibandingkan sektor lainnya. Di dalam penelitian ini, perusahaan manufaktur yang akan dijadikan objek penelitian untuk diramalkan harga sahamnya yaitu perusahaan manufaktur yang terdaftar di LQ45.  Pada perdagangan saham, harga mengalami fluktuasi naik maupun turun.  Keadaan saham yang fluktuasi setiap hari menjadikan investor yang akan berinvestasi di industri Manufaktur harus mengamati dan mempelajari data perusahaan dimasa lalu sebelum melakukan investasi. Data tersebut penting bagi investor untuk mengetahui kemungkinan yang terjadi pada harga saham suatu perusahaan. sehingga, meramal harga saham pada industri manufaktur untuk masa yang akan datang sangat dibutuhkan sebagai tahapan dalam memutuskan perusahaan Manufaktur yang baik dalam melakukan investasi. Metode Prediksi dalam penelitian ini menggunakan ARIMA. Hasil yang didapat yaitu harga saham perusahaan GGRM, HMSP, ICBP, INDF, INTP dan UNVR mengikuti tren turun, sehingga langkah yang diambil untuk investor pada perusahaan tersebut adalah menjualnya sedangkan untuk harga saham perusahaan ASII, CPIN, INKP, JPFA, SMGR, TKIM, mengikuti tren naik, sehingga langkah yang diambil untuk investor pada perusahaan tersebut adalah membeli saham.Kata Kunci: Prediksi, ARIMA, Investasi

scholarly journals Health Check-up of Commercial Banks in the Framework of CAMEL: A Case Study of Joint Venture Banks in Nepal

2007 ◽  
Vol 2 (1) ◽  
pp. 41-55 ◽  
Author(s):  
Keshar J. Baral
Keyword(s):  
Commercial Banks ◽  
Large Scale ◽  
Joint Venture ◽  
Balance Sheet ◽  
Health Check ◽  
Annual Reports ◽  
Financial Health ◽  
Data Set ◽  
Business Studies

Using the data set published by joint venture banks in their annual reports, and NRB in its supervision annual reports, this paper examines the financial health of joint venture banks in the CAMEL framework. The health check up conducted on the basis of publicly available financial data concludes that the health of joint venture banks is better than that of the other commercial banks. In addition, the perusal of indicators of different components of CAMEL indicates that the financial health of joint venture banks is not so strong to manage the possible large scale shocks to their balance sheet and their health is fair. Journal of Nepalese Business Studies Vol.2(1) 2005 pp.41-55

scholarly journals LISTING OF SHARES OF SOME COMMERCIAL BANKS AND FINANCIAL SERVICES COMPANIES IN POLAND

2018 ◽  
pp. 43-51
Author(s):  
Sławomir Juszczyk
Keyword(s):  
Stock Prices ◽  
Financial Services ◽  
Commercial Banks ◽  
Stock Price ◽  
Stock Exchange ◽  
Price Volatility ◽  
Strongly Correlated ◽  
Stock Price Volatility ◽  
Warsaw Stock Exchange

The purpose of the research was to identify the volatilities of daily quotes of banks and financial services companies listed on Warsaw Stock Exchange in the six-year period ie 2011-2016. It was found that the volatility of the stock price of the eCard was the strongest correlated with BPH stock price volatility, while the volatility of KREDYTIN stock prices was strongly correlated with the volatility of BZ WBK shares, ING and PKO BP. The strongest correlation between the stock prices of banks and the surveyed financial services companies was on the day of their listing. Unlike banks, financial services companies are highly diversified.

Performance and development of a thin stock market: the Stockholm Stock Exchange 1912–2017

2020 ◽  
pp. 1-19
Author(s):  
Kristian Rydqvist ◽  
Rong Guo
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Selection ◽  
Data Set ◽  
Transaction Prices ◽  
Limit Orders ◽  
A Value

We estimate historical stock returns for Swedish listed companies in a newly constructed data set of daily stock prices that spans more than 100 years. Stock returns exhibit all the familiar characteristics. The growth of the public sector depressed the stock market, and the process of globalization revitalized it. Banks played an important role in the early development of the stock market. There was little trading in the past, and we examine the effects on return measurement from missing data. Stock selection and the replacement of missing transaction prices through search back procedures or limit orders make little difference to a value-weighted stock price index, while ignoring the price effects of capital operations makes a big difference.

scholarly journals Does Macroeconomic Indicators Influence Stock Price Behavior? Evidence from Nigerian Stock Market

2019 ◽  
Vol 6 (2) ◽  
pp. 26
Author(s):  
Peter Ego Ayunku
Keyword(s):  
Stock Market ◽  
Significant Influence ◽  
Stock Prices ◽  
Stock Price ◽  
Time Series Data ◽  
Unit Root Test ◽  
Series Data ◽  
Price Behavior ◽  
Market Growth ◽  
Integration Test

This paper investigate whether macroeconomics indicators influences stock price behavior in Nigerian stock market, using an annual time series data spanning from 1985-2015. The study employed some econometric tools such as Augmented Dicker Fuller (ADF) Unit Root test, Johansen’s co integration test, Vector Error Correction Model (VECM) to analyze the variables of interest. The study found out that Money Supply (MS) has an inverse but statistically significant  influence on stock prices in Nigerian stock market also Treasury Bill Rate (TBR) has an inverse and statistically insignificant influence on stock market prices. While on the other hand, Market Capitalization (MCAP) has a positive and statistically significant influence on stock prices while Exchange Rate (EXR) has positive but statistically insignificant relationship with stock prices in the Nigerian Stock Market. In view of the above, the study recommends amongst others that monetary authorities should try as much as possible to implement sound macroeconomic policies that would enhance stock market growth and development in Nigeria. 

Stock Price Modeling: Separation of Trend and Fluctuations, and Implications

2015 ◽  
Vol 18 (04) ◽  
pp. 1550027 ◽  
Author(s):  
B. D. Craven ◽  
Sardar M. N. Islam
Keyword(s):  
Behavioral Finance ◽  
Positive Feedback ◽  
Stock Prices ◽  
Stock Price ◽  
Additive Model ◽  
Logarithmic Scale ◽  
Price Behavior ◽  
Interaction Terms ◽  
Wide Range ◽  
Short Time

A series of stock prices typically shows a large trend and smaller fluctuations. These two parts are often studied together, as if parts of a single process; but they appear to be separately caused. In this paper, the two parts are analyzed separately, so that one does not distort the other, and some spurious interaction terms are avoided. This contributes a model, in which a wide range of features of stock price behavior are identified. With logarithms of stock prices, the two parts become of more comparable size. This is found to lead to a simpler additive model. On a logarithmic scale, the stock prices show the trend as a straight line (which can be extrapolated), with added fluctuations filling a narrow band. The trend and fluctuations are thus separated. The trend appears to be largely generated by a positive feedback process, describing investor behavior. The width of the fluctuation band does not grow with time, so positive feedback is not its cause. The movement of stock prices can be understood by analyzing the trend and fluctuations as separate processes; the latter considered as a stationary stochastic process with a scale factor. This analysis is applied to a historical dataset [Formula: see text] index of daily prices from February 1928). Here, the fluctuations are autocorrelated over short time intervals; there is little structure, except for market crash periods, when variability increases. The slope of the trend showed some jumps, not predictable from price history. This approach to modeling describes many aspects of stock price behavior, which are usually discussed in behavioral finance.

scholarly journals FUNDAMENTAL AND TECHNICAL ANALYSIS OF THE STOCK PRICE

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Denis Spahija ◽  
Seadin Xhaferi
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Exchanges ◽  
Full Time ◽  
Equal Opportunities ◽  
Factors Affecting ◽  
The Past ◽  
Real Value

Trading with stocks in developed market conditions for some is fun, for others it is a way to preserve the real value of the asset, while for the most is a challenge to gain bigger profits quickly and easily. Dreams on stock market alchemy rely on the development and upgrading of special systems whose ultimate goal is to uncover stock price secrets and their changes. What are the chances of this happening? Chances are minimal, according to experiences from the world’s leading stock exchanges in the past. The stock market complexity, the number and unpredictability of factors affecting stock prices and unexpected changes or stability do not give much hope to those who know what’s going to happen in the future. In such endeavors there are equal opportunities for both stock exchange experts and full-time amateurs. For all this, if the stock market cannot be defeated or deceived, then it is better to join it. So this means: to create a diversified portfolio of securities that provides a safe income, slightly higher than annual inflation, minimizing the risk.

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