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

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.

2007 ◽  
Vol 3 (1) ◽  
pp. 100-110 ◽  
Author(s):  
Keshar J. Baral ◽  
Surya Kumar Shrestha

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


Author(s):  
Risa Leigh Kavalerchik

This paper explores the stationarity of price movements, dividend yields, and earnings yields for stock market indices and individual stocks within the broader context of the random walk hypothesis. In general, in order for a stock’s price to follow a random walk, its future price must be unforecastable based on all currently available information in the stock market, including its price history. If a stock price is stationary in a given time period, its statistical process does not change over time, meaning that the series has a deterministic trend, which could even be flat. This investigation tests for stationarity in the time series of prices and dividend yields of the Dow Jones Industrial Average (DJIA), the S&P 500 Index, and their underlying component stocks based on the results of univariate and panel unit root tests. I also test for the stationarity of earnings yields for the components of the DJIA. I find that prices of the DJIA and its underlying components behave in a more stationary manner than do the prices of the S&P 500 and its underlying components. Dividend yields behave in an equally non-stationary fashion for the underlying components of both the DJIA and S&P 500. Interestingly, earnings yields for the DJIA prove to exhibit more stationarity than the dividend yields for the DJIA and S&P 500, suggesting that earnings data have some predictability for stock prices.


GIS Business ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 109-126
Author(s):  
Nitin Tanted ◽  
Prashant Mistry

One of the highly controversial issues in the area of finance is “Efficient Market Hypothesis”. Efficient Market Hypothesis states that, “In an efficient market, all available price information is reflected in the stock prices and it is not possible to generate abnormal returns compared to other investors.” A lot of studies conducted previouslyto test the Efficient Market Hypothesis, confirmed the theory until recent years, when some academicians found it to be non-applicable in financial markets. According to them, it is possible to forecast the stock price movements using Technical Analysis. The results of various studies have been inconclusive and indefinite about the issue. This study attempted to test the efficiency of FMCG Sector stocks in India in its weak form. For the study, closing prices of top 10 stocks from Nifty FMCG index has been taken for the 5-year period ranging from 1st October 2014 to 30th September 2019. Wald-Wolfowitz Run test has been used to test the haphazard movements in the stock price movements. The results indicated that FMCG sector stocks does support the Efficient Market Hypothesis and exhibit efficiency in its weak form. Hence, it is not possible to accurately predict the price movements of these stocks.


2021 ◽  
Vol 9 (2) ◽  
pp. 101-114
Author(s):  
Fauziyah Fauziyah

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


2009 ◽  
Vol 14 (S1) ◽  
pp. 3-41 ◽  
Author(s):  
Kian-Ping Lim ◽  
Robert D. Brooks

This paper employs the rolling bicorrelation test to measure the degree of nonlinear departures from a random walk for aggregate stock price indices of fifty countries over the sample period 1995–2005. We find that stock markets in economies with low per capita GDP in general experience more frequent price deviations than those in the high-income group. This clustering effect is not due to market liquidity or other structural characteristics, but instead can be explained by cross-country variation in the degree of private property rights protection. Our conjecture is that weak protection deters the participation of informed arbitrageurs, leaving those markets dominated by sentiment-prone noise traders whose correlated trading causes stock prices in emerging markets to deviate from the random walk benchmarks for persistent periods of time.


2021 ◽  
Vol 13 (2) ◽  
pp. 79-88
Author(s):  
Janesh Sami

The main goal of this paper is to investigate the random walk hypothesis in Fiji using monthly data from January 2000 to October 2017. Applying augmented Dickey Fuller (ADF 1979, 1981) and Phillips-Perron (1988), Zivot-Andrews (1992), and Narayan and Popp (2010) unit root tests, this study finds that stock prices is best characterized as non-stationary. The estimated multiple structural break dates in the stock prices corresponds with devaluation of Fijian dollar by 20 percent in 2009 and General Elections in September 2014, which Fiji First Party won by majority votes. The empirical results indicate that stock prices are best characterized as a unit root (random walk) process, indicating that the weak-form efficient market hypothesis holds in Fiji’s stock market. Hence, it will be difficult to predict future returns based on historical movement of stock prices in Fiji’s stock market.


Author(s):  
Sławomir Juszczyk

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.


2020 ◽  
pp. 1-19
Author(s):  
Kristian Rydqvist ◽  
Rong Guo

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.


Author(s):  
Denis Spahija ◽  
Seadin Xhaferi

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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