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Journal articles on the topic 'Logarithmic Returns'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Miskolczi, Panna. "Note on simple and logarithmic return." Applied Studies in Agribusiness and Commerce 11, no. 1-2 (2017): 127–36. http://dx.doi.org/10.19041/apstract/2017/1-2/16.

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In this paper we describe and clarify the definitions and the usage of the simple and logarithmic returns for financial assets like stocks or portfolios. It can be proven that the distributions of the simple and logarithmic returns are really close to each other. Because of this fact we investigate the question whether the calculated financial risk depends on the use of simple or log returns. To show the effect of the return-type on the calculations, we consider and compare the riskiness order of stocks and portfolios. For our purposes, in the empirical study we use seven Hungarian daily stock

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2

Peters, Edgar E. "R/S Analysis Using Logarithmic Returns." Financial Analysts Journal 48, no. 6 (1992): 81–82. http://dx.doi.org/10.2469/faj.v48.n6.81.

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Krivolapov, Sergei Ya. "PREDICTING LOGARITHMIC STOCK RETURNS BASED ON A NAIVE BAYESIAN CLASSIFIER." SOFT MEASUREMENTS AND COMPUTING 9, no. 70 (2023): 39–46. http://dx.doi.org/10.36871/2618-9976.2023.09.004.

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The time series of the results of stock quotations of a certain company and the values of logarithmic profitability calculated from them are considered. The forecast of the future value of logarithmic profitability is carried out based on the values of this indicator in previous periods. A Gaussian naive Bayesian classifier is used to calculate the forecast.

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4

Mamcarz, Katarzyna. "The Causal Relationship Between Stocks, Gold, Crude Oil, and Bond Returns in Poland." Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia 58, no. 4 (2024): 127–47. http://dx.doi.org/10.17951/h.2024.58.4.127-147.

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Theoretical background: Capital investments involve taking risks to achieve a favourable rate of return. Investors are offered various options, including stocks, bonds, and commodities. The aforementioned investment opportunities are considered alternatives due to their varying price volatility and risk levels. Bonds and gold demonstrate a low or negative correlation with equities. On the other hand, crude oil and gold are positively correlated. An essential issue in analysing financial markets is to capture the dynamic behaviour of the financial time-series data, i.e. variables such as prices

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5

Raudys, Aistis, and Edvinas Goldstein. "Forecasting Detrended Volatility Risk and Financial Price Series Using LSTM Neural Networks and XGBoost Regressor." Journal of Risk and Financial Management 15, no. 12 (2022): 602. http://dx.doi.org/10.3390/jrfm15120602.

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It is common practice to employ returns, price differences or log returns for financial risk estimation and time series forecasting. In De Prado’s 2018 book, it was argued that by using returns we lose memory of time series. In order to verify this statement, we examined the differences between fractional differencing and logarithmic transformations and their impact on data memory. We employed LSTM (long short-term memory) recurrent neural networks and an XGBoost regressor on the data using those transformations. We forecasted risk (volatility) and price value and compared the results of all m

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Chen, Yongjie. "Application of ARIMA Model in Portfolio Optimization." Advances in Economics, Management and Political Sciences 26, no. 1 (2023): 227–36. http://dx.doi.org/10.54254/2754-1169/26/20230575.

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This paper investigates the portfolio allocation strategy using the ARIMA time series model with eight companies in four industries: Technology, Healthcare, Financial Services, and New Energy. This research aims to identify the best portfolio allocation approach that maximizes the returns for investors in each industry. This paper collected daily stock prices of Apple and Microsoft in the technology industry, Johnson & Johnson and Pfizer in the healthcare industry, JPMorgan Chase and Goldman Sachs in the financial services industry, and Tesla and NextEra Energy in the new energy industry f

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7

Ulu, Yasemin. "Volatility Distribution of the DJSTOXXE50 Index." Applied Economics and Finance 7, no. 6 (2020): 101. http://dx.doi.org/10.11114/aef.v7i6.5065.

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In this paper using data from 1995-2005 on 5-minute intraday returns, we construct a model free estimate of the daily realized volatility for the DJSTOXXE50 index. We compute the unconditional volatility distribution of the DJSTOXXE50 index by a nonparametric kernel estimation method. Our results indicate that the unconditional volatility distribution of the DJSTOXXE50 returns are leptokurtic and highly skewed to the right. The logarithmic standard deviations seem to be approximately Gaussian. Our results are inline with previous research for individual DJIA equity return volatility and for Ja

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8

BASNARKOV, LASKO, VIKTOR STOJKOSKI, ZORAN UTKOVSKI, and LJUPCO KOCAREV. "OPTION PRICING WITH HEAVY-TAILED DISTRIBUTIONS OF LOGARITHMIC RETURNS." International Journal of Theoretical and Applied Finance 22, no. 07 (2019): 1950041. http://dx.doi.org/10.1142/s0219024919500419.

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A growing body of literature suggests that heavy tailed distributions represent an adequate model for the observations of log returns of stocks. Motivated by these findings, here, we develop a discrete time framework for pricing of European options. Probability density functions of log returns for different periods are conveniently taken to be convolutions of the Student’s [Formula: see text]-distribution with three degrees of freedom. The supports of these distributions are truncated in order to obtain finite values for the options. Within this framework, options with different strikes and ma

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9

Dwiana Putra, I. Made Pande, and I. Dewa Nyoman Badera. "Identifikasi Hubungan Linier dan Non-Linier antara Rasio-Rasio Keuangan dan Return Saham." Akuntabilitas 12, no. 1 (2019): 83–92. http://dx.doi.org/10.15408/akt.v12i1.10093.

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Researches on relevance of financial ratios on stock returns mostly adopt linearity assumptions. This research aims to show the relevance of financial ratios on stock return and to compare the accuracy of linear and non linear models. Linear and non linear multivariate regression models are constructed from several financial ratios towards stock return to identify ratios with significant influences and subsequently compared in regard of their determinations. The samples consist of manufacturing companies listed on IDX from 2009 through 2016 totaling 97 companies. Results of bivariate regressio

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10

REMER, RALF, and REINHARD MAHNKE. "STOCHASTIC VOLATILITY MODELS AND THEIR APPLICATION TO GERMAN DAX DATA." Fluctuation and Noise Letters 04, no. 04 (2004): R67—R78. http://dx.doi.org/10.1142/s0219477504002166.

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We focus on the stochastic description of the stock price dynamics. Thereby we concentrate on the Heston model and the Hull–White model. We derive the stationary probability density distribution of the variance of both models in the case of zero correlation coefficient. These distributions are used to calculate solutions for the logarithmic returns of the stock price for short time lags. Furthermore we apply the solutions of both models to the German tick-by-tick Dax data [1]. The data are from May 1996 to December 2001. We use the probability density distributions of the logarithmic returns,

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11

Krivolapov, S. Ya. "REGRESSION MODEL FOR FITTING THE DISTRIBUTION LAW LOGARITHMIC STOCK RETURNS." SOFT MEASUREMENTS AND COMPUTING 4, no. 53 (2022): 16–26. http://dx.doi.org/10.36871/2618-9976.2022.04.002.

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Data on daily stock quotations of 216 Russian companies for the period from 2004 to 2021 are considered. The subject of the study is the law of distribution of the logarithmic profitability of shares. Out of the total number of companies, a part of the companies is left for the subsequent testing of the model. For each of the remaining companies, using the methods of the Python language, a law is selected (out of 40 available candidates), in the "best" way (in the sense of the KulbackLeibler distance), approximating the law of sample distribution. One of the most frequently appearing as the "b

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Krivolapov, Sergei Ya. "CLUSTER ANALYSIS OF DISTRIBUTION LAWS LOGARITHMIC STOCK RETURNS RUSSIAN COMPANIES." SOFT MEASUREMENTS AND COMPUTING 6, no. 67 (2023): 95–111. http://dx.doi.org/10.36871/2618-9976.2023.06.009.

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The problem of systematization of the laws of distribution of the logarithmic profitability of shares according to the data on stock quotes of 216 companies on the Moscow Exchange is considered. For each company, the "distance" (used in Kolmogorov's fit test) is calculated from its sample to 12 symmetrical distribution laws. According to the results of cluster analysis of the obtained data array, 5 relatively homogeneous clusters were identified. Python language tools are used to fit the distribution law and perform cluster analysis.

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KRAWIECKI, A. "MICROSCOPIC SPIN MODEL FOR THE STOCK MARKET WITH ATTRACTOR BUBBLING ON REGULAR AND SMALL-WORLD LATTICES." International Journal of Modern Physics C 19, no. 07 (2008): 1035–45. http://dx.doi.org/10.1142/s0129183108012777.

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A multi-agent spin model for changes of prices in the stock market based on the Ising-like cellular automaton with interactions between traders randomly varying in time is investigated by means of Monte Carlo simulations. The structure of interactions has topology of a small-world network obtained from regular two-dimensional square lattices with various coordination numbers by randomly cutting and rewiring edges. Simulations of the model on regular lattices do not yield time series of logarithmic price returns with statistical properties comparable with the empirical ones. In contrast, in the

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14

Zaimović, Azra. "Testing the CAPM in Bosnia and Herzegovina with Continuously Compounded Returns." South East European Journal of Economics and Business 8, no. 1 (2013): 35–43. http://dx.doi.org/10.2478/jeb-2013-0006.

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Abstract The capital markets of neighboring transitional Western Balkan countries have attracted a lot of interest from domestic and international investors in the last decade, who view them as an attractive alternative to investing in more developed markets. These markets are characterized by higher returns, and higher volatility of stock returns as compared to those of developed markets. The recent economic and financial crises devastated capital markets worldwide. The new Bosnian capital market faced its hardest times following the withdrawal of international investors. The aim of this pape

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15

Ceballos Bejarano, Ferdinand Eddington, Juan Carlos Hihuana Hallasi, and Judid Carina Viza Huayllaso. "Optimizing Investment Portfolios Using Quadratic Programming: An Approach from the Markowitz Model." Minerva 6, sp (2025): 7–11. https://doi.org/10.47460/minerva.v6isp.200.

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The application of the Markowitz model is analyzed from five financial assets, a matrix of logarithmic returns was constructed to estimate the parameters. Through computational resolution, the optimal portfolio was obtained that complies with an established minimum return, simultaneously minimizing the level of risk. The results were visualized across the efficient frontier, identifying the optimal combinations between risk and return. It is concluded that the Markowitz model continues to be a valid and valuable tool for the rational management of investments, especially when it is complemente

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16

Rubenis, Oskars, and Andrejs Matvejevs. "Increments of Normal Inverse Gaussian Process as Logarithmic Returns of Stock Price." Information Technology and Management Science 21 (December 14, 2018): 93–97. http://dx.doi.org/10.7250/itms-2018-0015.

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Normal inverse Gaussian (NIG) distribution is quite a new distribution introduced in 1997. This is distribution, which describes evolution of NIG process. It appears that in many cases NIG distribution describes log-returns of stock prices with a high accuracy. Unlike normal distribution, it has higher kurtosis, which is necessary to fit many historical returns. This gives the opportunity to construct precise algorithms for hedging risks of options. The aim of the present research is to evaluate how well NIG distribution can reproduce stock price dynamics and to illuminate future fields of app

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17

Hürlimann, Werner. "Financial Data Analysis with Two Symmetric Distributions." ASTIN Bulletin 31, no. 1 (2001): 187–211. http://dx.doi.org/10.2143/ast.31.1.1002.

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AbstractThe normal inverted gamma mixture or generalized Student t and the symmetric double Weibull, as well as their logarithmic counterparts, are proposed for modeling some loss distributions in non-life insurance and daily index return distributions in financial markets. For three specific data sets, the overall goodness-offit from these models, as measured simultaneously by the negative log-likelihood, chi-square and minimum distance statistics, is found to be superior to that of various “good” competitive models including the log-normal, the Burr, and the symmetric α-stable distribution.

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18

Ahmed, Naeem, and Mudassira Sarfraz. "Stock Market Volatility Measure Using Non-Traditional Tool Case of Germany." Economics and Business 32, no. 1 (2018): 126–35. http://dx.doi.org/10.2478/eb-2018-0010.

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Abstract. This study examines the stock market volatility of German bench-mark stock index DAX 30 using logarithmic extreme day return. German stock markets have been analyzed extensively in literature. We look into volatility issue from the standpoint of extreme-day changes. Our analysis indicates the non-normality of German stock market and higher probability of negative trading days. We measure the occurrences of extreme-day returns and their significance in measuring annual volatility. Our time series analysis indicates that the occurrences of extreme-days show a cyclical trend over the sa

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19

Ishigaki, Aya, Tetsuo Yamada, and Surendra M. Gupta. "Design of a Closed-Loop Supply Chain with Stochastic Product Returns." International Journal of Automation Technology 11, no. 4 (2017): 563–71. http://dx.doi.org/10.20965/ijat.2017.p0563.

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This research focuses on the relation between time variation and the behaviors of a closed-loop supply chain with stochastic product returns. In recent years, activities that reduce environmental impact, such as recycling and reusing materials, have been increasing. Designing a closed-loop supply chain for recycling or reuse operations will support social responsibility and competitive advantage. However, in order to establish supply chains for sustainability, it is necessary to consider not only environmental benefits but also economic efficiency. Moreover, both the quantity of demand and ret

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20

Hudson, Robert S., and Andros Gregoriou. "Calculating and comparing security returns is harder than you think: A comparison between logarithmic and simple returns." International Review of Financial Analysis 38 (March 2015): 151–62. http://dx.doi.org/10.1016/j.irfa.2014.10.008.

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21

Das, Akashdeep, Tinni Chaudhuri, Surupa Sinha Roy, Sanjib Biswas, and Banhi Guha. "Selection of Appropriate Portfolio Optimization Strategy." Theoretical and Applied Computational Intelligence 1, no. 1 (2023): 58–81. http://dx.doi.org/10.31181/taci1120237.

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Portfolio optimization is a critical task in financial management, aiming to maximize expected returns while minimizing risk. This study compares the performance of Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Dynamic Programming (DP), and Differential Evolutionary Algorithm (DEA) in optimizing portfolios in the NIFTY 50 market. Using daily stock data from March 2023 to May 2023, we evaluate the algorithms based on performance metrics including the Sharpe ratio, expected return, volatility and Sortino ratio. Then an integrated multi-criteria decision making (MCDM) framework of Lo

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22

DENG, WEIBING, WEI LI, XU CAI, and QIUPING A. WANG. "ON THE APPLICATION OF THE CROSS-CORRELATIONS IN THE CHINESE FUND MARKET: DESCRIPTIVE PROPERTIES AND SCALING BEHAVIORS." Advances in Complex Systems 14, no. 01 (2011): 97–109. http://dx.doi.org/10.1142/s0219525911002871.

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On the basis of the relative daily logarithmic returns of 88 different funds in the Chinese fund market (CFM) from June 2005 to October 2009, we construct the cross-correlation matrix of the CFM. It is shown that the logarithmic returns follow an exponential distribution, which is commonly shared by some emerging markets. We hereby analyze the statistical properties of the cross-correlation coefficients in different time periods, such as the distribution, the mean value, the standard deviation, the skewness and the kurtosis. By using the method of the scaled factorial moment, we observe the in

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23

Perez, Katarzyna, and Marcin Bartkowiak. "Chasing Returns of Open-End Investment Funds Using Recurrent Neural Networks. A Long-Term Study." Central European Economic Journal 12, no. 59 (2025): 49–65. https://doi.org/10.2478/ceej-2025-0004.

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Abstract The primary motivation of this study is to empower individual investors with a data-driven strategy for finding long-term investment returns by leveraging recurrent neural networks (RNNs) to forecast fund performance and construct dynamic portfolios. Specifically, we use RNN to forecast the returns of open-end investment funds and build a portfolio of top-performing funds based on these forecasts. Using a sample of 71 equity, fixed income, hybrid and money market funds in the Polish market from 2005 to 2022, we train the network over five years to generate annual logarithmic return fo

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24

Ren, Louie, Peter Ren, and Yong Glasure. "On the different forms of returns from moving average buy-sell trading rule in the stock market." Benchmarking: An International Journal 25, no. 1 (2018): 253–58. http://dx.doi.org/10.1108/bij-06-2016-0099.

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Purpose The purpose of this paper is to examine three different forms of returns based on the price difference, percentage change, and difference in logarithm price from moving average buy-sell trading rule. Statistical linear correlation, the means of returns from buy/sell days, and the flexibility of long-term moving periods are examined. Design/methodology/approach Traditional linear correlations, pairwise student t-test, and ϕ coefficient for two binary buy/sell decision variables are studied from the simple block bootstrap (convenience) sampling from S&P, Dow Jones, and NASDAQ price i

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Střelcová, Petra, and Luboš Střelec. "Using of correlation and distribution tests for efficiency testing of the Czech capital market." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 57, no. 6 (2009): 241–52. http://dx.doi.org/10.11118/actaun200957060241.

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This paper deals with efficiency testing of the Czech stock market. In this work there are defined different forms of efficiency, whereas key attention is focused on the weak-form of market efficiency. The goal of this paper is to find the weak-form of efficiency with the help of various tests. We have used some basic methods for our analysis: the autocorrelation coefficient, the Ljung-Box test and selected tests of normality – some classical normality tests (the Shapiro-Wilk test, the Jarque-Bera test, the Lilliefors test) and some robust normality tests (the robust Jarque-Bera test, the dire

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Liu, Jia. "A Bayesian Semiparametric Realized Stochastic Volatility Model." Journal of Risk and Financial Management 14, no. 12 (2021): 617. http://dx.doi.org/10.3390/jrfm14120617.

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This paper proposes a semiparametric realized stochastic volatility model by integrating the parametric stochastic volatility model utilizing realized volatility information and the Bayesian nonparametric framework. The flexible framework offered by Bayesian nonparametric mixtures not only improves the fitting of asymmetric and leptokurtic densities of asset returns and logarithmic realized volatility but also enables flexible adjustments for estimation bias in realized volatility. Applications to equity data show that the proposed model offers superior density forecasts for returns and improv

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FANG, WEN, and JUN WANG. "STATISTICAL PROPERTIES AND MULTIFRACTAL BEHAVIORS OF MARKET RETURNS BY ISING DYNAMIC SYSTEMS." International Journal of Modern Physics C 23, no. 03 (2012): 1250023. http://dx.doi.org/10.1142/s0129183112500234.

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An interacting-agent model of speculative activity explaining price formation in financial markets is considered in the present paper, which based on the stochastic Ising model and the mean field theory. The model describes the interaction strength among the agents as well as an external field, and the corresponding random logarithmic price return process is investigated. According to the empirical research of the model, the time series formed by this Ising model exhibits the bursting typical of volatility clustering, the fat-tail phenomenon, the power-law distribution tails and the long-time

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Siu, Tak Kuen. "Bayesian Lower and Upper Estimates for Ether Option Prices with Conditional Heteroscedasticity and Model Uncertainty." Journal of Risk and Financial Management 17, no. 10 (2024): 436. http://dx.doi.org/10.3390/jrfm17100436.

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This paper aims to leverage Bayesian nonlinear expectations to construct Bayesian lower and upper estimates for prices of Ether options, that is, options written on Ethereum, with conditional heteroscedasticity and model uncertainty. Specifically, a discrete-time generalized conditional autoregressive heteroscedastic (GARCH) model is used to incorporate conditional heteroscedasticity in the logarithmic returns of Ethereum, and Bayesian nonlinear expectations are adopted to introduce model uncertainty, or ambiguity, about the conditional mean and volatility of the logarithmic returns of Ethereu

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SASS, JÖRN, DOROTHEE WESTPHAL, and RALF WUNDERLICH. "EXPERT OPINIONS AND LOGARITHMIC UTILITY MAXIMIZATION FOR MULTIVARIATE STOCK RETURNS WITH GAUSSIAN DRIFT." International Journal of Theoretical and Applied Finance 20, no. 04 (2017): 1750022. http://dx.doi.org/10.1142/s0219024917500224.

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This paper investigates optimal trading strategies in a financial market with multidimensional stock returns, where the drift is an unobservable multivariate Ornstein–Uhlenbeck process. Information about the drift is obtained by observing stock returns and expert opinions which provide unbiased estimates on the current state of the drift. The optimal trading strategy of investors maximizing expected logarithmic utility of terminal wealth depends on the filter which is the conditional expectation of the drift given the available information. We state filtering equations to describe its dynamics

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Santander, Alejandra Guzmán, Eduardo Javier Peña Bautista, Edgar Rayo Visuel, Emma Natalia Mejía Cárdenas, Daniela Valentina Velasco Flores, and Mario Santiago Orozco Escolá. "The art of fitting financial time series for some stock market indexes of some of the main emerging countries and for Mexico with stable Lévy Distributions." Brazilian Journal of Development 9, no. 6 (2023): 18815–29. http://dx.doi.org/10.34117/bjdv9n6-007.

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This paper presents a statistical analysis of the logarithmic fluctuations of the returns of some of the main stock market indices. Samples were analyzed considering daily data covering a period from 01/03/2000 to 09/30/2022, and adjusted to different distributions. Goodness-of-fit tests were performed to quantitatively assess the quality of the estimate. Particular attention was paid to the impact of sample size on the estimated decay of the tail of the distributions. In this study, a forceful rejection of normality was obtained. On the other hand, the null hypothesis that the logarithmic flu

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Malkina, Marina, and Dmitry Rogachev. "Financial contagion of the Russian stock market from the Chinese stock market during the Covid-19 pandemic." BRICS Journal of Economics 5, no. 4 (2024): 73–92. https://doi.org/10.3897/brics-econ.5.e139618.

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The paper explores the financial contagion of the Russian stock market from the Chinese stock market during the global COVID-19 pandemic. Its objectives are to confirm or refute the contagion of these markets during the acute phase of the pandemic and establish the direction, intensity and types of contagion. The study employed average daily values of the RTSI (Moscow exchange) and HSI (Hong Kong stock exchange) indices. To distinguish between the period of exposure of the two countries’ assets to an external shock and the period of relatively calm markets, we calculated the moving normalized

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Orlando, Giuseppe, and Michele Bufalo. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions." Risks 9, no. 5 (2021): 88. http://dx.doi.org/10.3390/risks9050088.

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The aim of this work was to test how returns are distributed across multiple asset classes, markets and sampling frequency. We examine returns of swaps, equity and bond indices as well as the rescaling by their volatilities over different horizons (since inception to Q2-2020). Contrarily to some literature, we find that the realized distributions of logarithmic returns, scaled or not by the standard deviations, are skewed and that they may be better fitted by t-skew distributions. Our finding holds true across asset classes, maturity and developed and developing markets. This may explain why m

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KRAWIECKI, A. "MICROSCOPIC SPIN MODEL FOR THE STOCK MARKET WITH ATTRACTOR BUBBLING AND HETEROGENEOUS AGENTS." International Journal of Modern Physics C 16, no. 04 (2005): 549–59. http://dx.doi.org/10.1142/s0129183105007285.

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A multi-agent spin model for changes of prices in the stock market is considered, based on the Ising-like cellular automaton with global, randomly varying in time interactions between traders. The presence of "fundamentalists" is taken into account by introducing additional term in the local field acting on each agent, dependent on the ratio between the actual stock price and its fundamental value. Numerical multi-agent as well as mean-field simulations show that for properly chosen parameters, the time series of logarithmic price returns exhibit bursting typical of volatility clustering, due

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Huang, Chun-Sung, Chun-Kai Huang, and Knowledge Chinhamu. "Assessing The Relative Performance Of Heavy-Tailed Distributions: Empirical Evidence From The Johannesburg Stock Exchange." Journal of Applied Business Research (JABR) 30, no. 4 (2014): 1263. http://dx.doi.org/10.19030/jabr.v30i4.8675.

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<p>It has been well documented that the empirical distribution of daily logarithmic returns from financial market variables is characterized by excess kurtosis and skewness. In order to capture such properties in financial data, heavy-tailed and asymmetric distributions are required to overcome shortfalls of the widely exhausted classical normality assumption. In the context of financial forecasting and risk management, the accuracy in modeling the underlying returns distribution plays a vital role. For example, risk management tools such as value-at-risk (VaR) are highly dependent on th

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Belovas, Igoris. "Modeling Baltic market benchmark index: a comparison of models." Lietuvos matematikos rinkinys 60 (December 5, 2019): 6–10. http://dx.doi.org/10.15388/lmr.b.2019.15207.

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In this paper we perform a statistical analysis of the returns of OMX Baltic Benchmark index. We construct symmetric α-stable, non-standardized Student’s t and normal-inverse Gaussian models of daily logarithmic returns of the index, using maximum likelihood method for the estimation of the parameters of the models. The adequacy of the modeling is evaluated with the Kolmogorov-Smirnov tests for composite hypothesis. The results of the study indicate that the normal-inverse Gaussian model outperforms alternative heavy-tailed models for long periods of time, while the non-standardized Student’s

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Sultonov, Mirzosaid. "The Impact of International Sanctions on Russian Financial Markets." Economies 8, no. 4 (2020): 107. http://dx.doi.org/10.3390/economies8040107.

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Russia’s international comportment and geostrategic moves, particularly the invasion of Ukraine and the annexation of Crimea in 2014, caused a substantial change in its international economic and political relations. In response to Russia’s invasion, the United States of America, the European Union, and their allies imposed a series of sanctions. In this study, by applying an exponential generalized autoregressive conditional heteroscedasticity model to daily logarithmic returns of the ruble exchange rate and the closing price index of the Russian Trading System, we analyze how the returns and

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Tan, Jiawei. "Research on the Volatility of the S&P 500 Stock Index Based on GARCH Family Models." Advances in Economics, Management and Political Sciences 51, no. 1 (2023): 178–84. http://dx.doi.org/10.54254/2754-1169/51/20230627.

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Volatility is an important issue in financial research. In this paper, in order to study the volatility of the S&P 500 index, which is representative of the American stock market, is used as research object, and the daily closing prices from July 2018 to July 2022 are selected. It has since become widely accepted in the academic community that stock return volatility is slow moving. Therefore, the series cannot accurately capture the characteristics of volatility. Developing the GARCH model gives us an effective way of describing return volatility. The statistical software EViews is initia

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SOUMARÉ, ISSOUF. "EQUILIBRIUM WITH EXCESSIVE HOLDINGS CONSTRAINT: AN APPLICATION TO DC PENSION PLANS." International Journal of Theoretical and Applied Finance 10, no. 07 (2007): 1159–90. http://dx.doi.org/10.1142/s0219024907004597.

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In this paper, I study the equilibrium implications when some investors in the economy overweight a subset of stocks within their portfolio. I find that the excess returns for the overweighted stocks are lower, all else being equal. This has strong testable implications for stock returns. In the special case of logarithmic preferences, the riskfree rate increases and the market price of risk for the overweighted stock decreases, which create extra incentive for unconstrained agents to exit the stock market and hold bonds, hence clearing the market. The changes of stocks' volatilities are ambig

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Saad, Salma Mansour, and Ali Khazaal Jabbar. "Analysis of the effect of e-currencies on financial performance based on information technology." Eastern-European Journal of Enterprise Technologies 2, no. 13 (116) (2022): 31–37. http://dx.doi.org/10.15587/1729-4061.2022.254839.

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E-currency is a form of digital currency that employs encryption to safeguard transactions, limit the manufacture of new units, and verify asset transfers. Bitcoin exchange rates and returns are the primary subjects of this study. In order to measure volatility, the standard deviation of logarithmic returns is determined. This study used a special test to determine whether or not the data were normal. Findings of high volatility were also made using a plot, a statistical process control chart, and other methods. Normality test (casual test) has been investigated accordingly to approve and vali

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Salma, Mansour Saad, and Khazaal Jabbar Ali. "Analysis of the effect of e-currencies on financial performance based on information technology." Eastern-European Journal of Enterprise Technologies 2, no. 13 (116) (2022): 31–37. https://doi.org/10.15587/1729-4061.2022.254839.

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E-currency is a form of digital currency that employs encryption to safeguard transactions, limit the manufacture of new units, and verify asset transfers. Bitcoin exchange rates and returns are the primary subjects of this study. In order to measure volatility, the standard deviation of logarithmic returns is determined. This study used a special test to determine whether or not the data were normal. Findings of high volatility were also made using a plot, a statistical process control chart, and other methods. Normality test (casual test) has been investigated accordingly to approve and vali

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Emmanuel, Sabastine, Saratha Sathasivam, Muraly Velavan, and Vediyappan Govinda. "Adaptive Portfolio Strategies: Comparing Pre-, during and Post-COVID-19 Dynamics using Mean-Variance Optimization." Semarak International Journal in Modern Accounting and Finance 4, no. 1 (2025): 1–17. https://doi.org/10.37934/sijmaf.4.1.117.

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This study examines the influence of the COVID-19 epidemic on the global stock market using mean-variance optimization (MVO) based on Markowitz's portfolio theory. The analysis examines the performance of portfolios tailored to different sectors both before, during and the post-pandemic. It provides insights into the changes in risk-return characteristics across diverse businesses. The dataset consists of the mean closing prices of a variety of stocks, divided into two/three separate periods: before the outbreak of COVID-19, during the COVID-19 and post-pandemic. The study utilizes covariance

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Zheng, Nan, Cuiyang Huang, and Jean-Claude Dufour. "LSTM Networks and ARIMA Models for Financial Time Series Prediction." Applied and Computational Engineering 134, no. 1 (2025): 56–63. https://doi.org/10.54254/2755-2721/2025.22270.

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In this study, we evaluate the forecasting effectiveness of the classical ARIMA model and the deep learning-based LSTM model in the financial domain. An investment portfolio comprising equal shares of gold, the S&P 500, and 2-year U.S, is constructed to predict future trends, thereby accounting for market factors and risk-free interest rates. Various historical data are used to train the model and forecast the value of protfolio respectively. For the ARIMAmodel,predictions are made by segmenting the model into three groups based on the time span of the training data. The LSTM model utilize

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Othman, Anwar Hasan Abdullah, Syed Musa Alhabshi, and Razali Haron. "The effect of symmetric and asymmetric information on volatility structure of crypto-currency markets." Journal of Financial Economic Policy 11, no. 3 (2019): 432–50. http://dx.doi.org/10.1108/jfep-10-2018-0147.

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Purpose This paper aims to examine whether the crypto-currencies’ market returns are symmetric or asymmetric informative, through analysing the daily logarithmic returns of bitcoin currency over the period of 2011-2017. Design/methodology/approach In doing so, the symmetric informative analysis is estimated by applying the generalised auto-regressive conditional heteroscedasticity (GARCH) (1,1) model, whereas asymmetric informative or leverage effects analysis is estimated by exponential GARCH (1,1), asymmetric power ARCH (1,1) and threshold GARCH (1,1) models. In addition, the generalized aut

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Yuan, Jiacong. "Research on properties of Bitcoin Based on GARCH model." Highlights in Science, Engineering and Technology 44 (April 13, 2023): 169–76. http://dx.doi.org/10.54097/hset.v44i.7314.

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Cryptocurrencies have become a world-class phenomenon, with governments, companies and investors facing huge challenges and opportunities. Bitcoin is the one of most widely known cryptocurrencies. People prefer to use Bitcoin as an asset to invest for profit and hedge risk than for its payment function. This is the reason for the study of bitcoin market is so important. Many scholars had used daily data on bitcoin to construct different GARCH models to analyse the volatility of its returns. This research builds a GARCH model for the logarithmic return series of the bitcoin price to understand

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Seetharam, Yudhvir, and James Britten. "Non-linear modelling of market cycles in South Africa." International Journal of Emerging Markets 10, no. 4 (2015): 670–83. http://dx.doi.org/10.1108/ijoem-05-2013-0079.

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Purpose – The purpose of this paper is to expand on the sparse literature on non-linear modelling in South Africa and test for non-linearity of the market cycle on the Johannesburg Stock Exchange, with specific focus on a particular non-linear model – a Smooth Transition Auto-Regressive (STAR) model. Design/methodology/approach – Non-linear estimation methods are used to describe the market cycle, as defined by equity prices, for the period 1998-2010. Findings – In applying the STAR model to daily, weekly and monthly returns data, it was found that the fit of this family of models differs heav

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BAUDER, DAVID, TARAS BODNAR, STEPAN MAZUR, and YAREMA OKHRIN. "BAYESIAN INFERENCE FOR THE TANGENT PORTFOLIO." International Journal of Theoretical and Applied Finance 21, no. 08 (2018): 1850054. http://dx.doi.org/10.1142/s0219024918500541.

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In this paper, we consider the estimation of the weights of tangent portfolios from the Bayesian point of view assuming normal conditional distributions of the logarithmic returns. For diffuse and conjugate priors for the mean vector and the covariance matrix, we derive stochastic representations for the posterior distributions of the weights of tangent portfolio and their linear combinations. Separately, we provide the mean and variance of the posterior distributions, which are of key importance for portfolio selection. The analytic results are evaluated within a simulation study, where the p

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Luo, Jinyang. "Utilizing the GARCH Model for Analysis and Prediction of Stock Market Trends." Advances in Economics, Management and Political Sciences 96, no. 1 (2024): 1–11. http://dx.doi.org/10.54254/2754-1169/96/2024mur0102.

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This study utilizes the Generalized Auto-regressive Conditional Heteroskedasticity (GARCH) model to analyze the Shanghai Stock Exchange Composite Index and the Shenzhen Composite Index. It computes the returns and logarithmic returns, fits the GARCH model with a student-t distribution, and calculates the standardized residuals of the stock. Tests for normality and heteroskedasticity of residuals are conducted, follows by the creation of auto-correlation and partial auto-correlation plots to aid in volatility forecasting. The findings indicate that both returns of stock distributions exhibit mu

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Han, Jun S., Nino Kordzakhia, Pavel V. Shevchenko, and Stefan Trück. "On correlated measurement errors in the Schwartz–Smith two-factor model." Dependence Modeling 10, no. 1 (2022): 108–22. http://dx.doi.org/10.1515/demo-2022-0106.

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Abstract The Schwartz–Smith two-factor model is commonly used for pricing of derivatives in commodity markets. For estimating and forecasting the term structures of futures prices, the logarithm of commodity spot price is represented as the sum of short- and long-term factors being the unobservable state variables. The futures prices derived as functions of the spot price lead to the simultaneous set of measurement equations, which is used for joint estimation of unobservable state variables and the model parameters through a filtering procedure. We propose a modified model where the error ter

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Perez, Gerardo “Gerry” Alfonso. "Do Small Indonesian Companies Have a Better Performance in the Stock Market than Larger Ones?" International Journal of Financial Research 8, no. 4 (2017): 1. http://dx.doi.org/10.5430/ijfr.v8n4p1.

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Company specific characteristics, such as size, might have an impact on stock performance. In fact, there is an extensive literature supporting the existence of a small capitalization effect stock in many markets, such as the U.S. (Fama, 1992), UK (Andrikopoulus, 2008)) and Thailand (Alfonso, 2016). In this article the Indonesian case is presented. Indonesia has a growing economy and financial markets and is one of the ASEAN countries. The performance of small and large capitalization stock from 2010 to 2016 was analyzed in this article. The results, at a 5% confidence level, indicate that the

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Daniluk, Katarzyna. "Effectiveness of Investing in the Stocks of Renewable Energy Companies in Poland." Economic and Regional Studies / Studia Ekonomiczne i Regionalne 15, no. 1 (2022): 47–55. http://dx.doi.org/10.2478/ers-2022-0004.

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Abstract Subject and purpose of work: This study investigates the effectiveness of equity investment in renewable energy companies. The aim of the research is to compare the effectiveness of investing in the stocks of companies from the conventional and renewable energy sector on the Warsaw Stock Exchange. Materials and methods: The research material consisted of the stock prices of selected energy companies listed on the Warsaw Stock Exchange’s Main Market and NewConnect. Representative investment portfolios were created and their average monthly logarithmic rates of return, standard deviatio

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