An empirical testing of comparative efficiency of static and dynamic factor models towards stock returns’ predictability in capital market of Pakistan

2020 ◽  
Vol 4 (2) ◽  
pp. 141-162
Author(s):  
Laila Taskeen Qazi ◽  
Atta ur Rahman ◽  
Shahid Ali ◽  
Sohail Alam
Keyword(s):  
Time Series ◽  
Stock Returns ◽  
Time Series Data ◽  
Factor Model ◽  
Efficient Market Hypothesis ◽  
Factor Models ◽  
Series Data ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Returns Predictability

Efficient Market Hypothesis has its supporters and critics as it has invited significant attention of research scholarship in recent years. The taxonomy and existence of this hypothesis is widely debated in terms of making economic decisions in the capital markets. Stock returns predictability has galvanized researchers to use forecasting models. Literature shows that forecasting is possible yet it debates problems associated with the techniques used for forecasting from the time series data. The study relies on stock returns for 67 randomly selected companies listed on the Pakistan Stock Exchange. The static and the dynamic factor models are compared in terms of forecast efficiency. The study also uses eight macroeconomic variables to forecast stock returns by including gold prices, crude oil prices, market capitalization, PSX- 100 index, PSX-100 index turnover, KIBOR 1-month rates, KIBOR 3 years rates and Rupee to Dollar rates. The results of the hit rates and out-of-sample forecasting technique suggest that dynamic factor model is the best multivariate time series forecasting model in the Pakistani context.

scholarly journals The Effect of Firm Profitability on Expected Stock Return in ASEAN Stock Market

2021 ◽  
Vol 25 (3) ◽  
pp. 642-655
Author(s):  
Nathania Clara ◽  
Sung Suk Kim
Keyword(s):  
Time Series ◽  
Stock Returns ◽  
Stock Return ◽  
Time Series Data ◽  
Factor Model ◽  
Total Sample ◽  
Series Data ◽  
Operating Profit ◽  
Firm Profitability ◽  
Expected Stock Returns

This research discusses and analyzes the company's profitability related to the company's stock return performance Profitability of the firm is related to the firm's performance of stock return. This study uses time-series data with a total sample of 1,010 firms from five countries in ASEAN (Indonesia, Thailand, Malaysia, Philippines, and Vietnam) from January 2010 to December 2019. Fama-French 3 factor model based on two different profitability showed that profitability positively affects the stock return in ASEAN markets. Fama-MacBeth's (1973) regression confirms that firm profitability scaled by operating profit-to-equity or operating profit-to-assets positively influences expected stock returns in the ASEAN market.DOI: 10.26905/jkdp.v25i3.5598

scholarly journals Did the new Law for State-owned Firms affect those that are publicly traded?

2020 ◽  
Vol 18 (1) ◽  
pp. 23
Author(s):  
Vitor Kayo De Oliveira ◽  
Marcio Holland ◽  
Joelson O. Sampaio
Keyword(s):  
Time Series ◽  
Corporate Governance ◽  
Stock Returns ◽  
Time Series Data ◽  
Series Data ◽  
High Dimensional ◽  
Publicly Traded

<p>This paper studies the effects of a new law aimed at state-owned enterprises in Brazil. In particular, it analyzes whether this legislation, promoting improved corporate governance, leads to a reduced perception of risks in the management of these companies and, therefore, in the volatility of their stock returns. To do this, the ArCo (Artificial Counterfactual) methodology is applied, using high-dimensional panel time-series data from 2011 to 2018. Our results show that thirteen out of twenty stocks present a reduction in their volatility, six out of twenty stocks have contradictory results and one stock does not present a statistically significant result.</p>

scholarly journals MODELING LONGEVITY RISK WITH GENERALIZED DYNAMIC FACTOR MODELS AND VINE-COPULAE

2015 ◽  
Vol 46 (1) ◽  
pp. 165-190 ◽  
Author(s):  
Helena Chuliá ◽  
Montserrat Guillén ◽  
Jorge M. Uribe
Keyword(s):  
Factor Model ◽  
Risk Measures ◽  
Mortality Rates ◽  
Factor Models ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Mortality Risks ◽  
Static Factor ◽  
Vine Copula ◽  
The Uk

AbstractWe present a methodology to forecast mortality rates and estimate longevity and mortality risks. The methodology uses generalized dynamic factor models fitted to the differences in the log-mortality rates. We compare their prediction performance with that of models previously described in the literature, including the traditional static factor model fitted to log-mortality rates. We also construct risk measures using vine-copula simulations, which take into account the dependence between the idiosyncratic components of the mortality rates. The methodology is applied to forecast mortality rates for a population portfolio for the UK and to estimate longevity and mortality risks.

scholarly journals Fitting dynamic factor models to non-stationary time series

2011 ◽  
Vol 163 (1) ◽  
pp. 51-70 ◽  
Author(s):  
Michael Eichler ◽  
Giovanni Motta ◽  
Rainer von Sachs
Keyword(s):  
Time Series ◽  
Factor Models ◽  
Stationary Time Series ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Stationary Time

scholarly journals Permanent-Transitory decomposition of cointegrated time series via Dynamic Factor Models, with an application to commodity prices

2021 ◽  
Author(s):  
Chiara Casoli ◽  
Riccardo (Jack) Lucchetti
Keyword(s):  
Factor Model ◽  
Commodity Prices ◽  
Standard Technique ◽  
Factor Models ◽  
Monte Carlo Experiment ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Common Component ◽  
Stable Pattern

Abstract We propose a cointegration-based Permanent-Transitory decomposition for non-stationary Dynamic Factor Models. Our methodology exploits the cointegration relations among the observable variables and assumes they are driven by a common and an idiosyncratic component. The common component is further split into a long-term non-stationary and a short-term stationary part. A Monte Carlo experiment shows that incorporating the cointegration structure into the DFM leads to a better reconstruction of the space spanned by the factors, compared to the most standard technique of applying a factor model in differenced systems. We apply our procedure to a set of commodity prices to analyse the comovement among different markets and find that commodity prices move together mostly due to long-term common forces; while the trend for the prices of most primary goods is declining, metals and energy exhibit an upward or at least stable pattern since the 2000s.

scholarly journals Identifikasi Model I-Garch (Integrated Generalized Autoregressive Conditionally Heterocedastic) Untuk Peramalan Value At Risk

2020 ◽  
Vol 3 (1) ◽  
pp. 25-38
Author(s):  
Nendra Mursetya Somasih Dwipa
Keyword(s):  
Time Series ◽  
Stock Returns ◽  
Confidence Level ◽  
Value At Risk ◽  
Time Series Data ◽  
Composite Index ◽  
Information Criteria ◽  
Stock Index ◽  
Series Data ◽  
Residual Variance

A stock returns data are one of type time series data who has a high volatility and different variance in every point of time. Such data are volatile, seting up a pattern of asymmetrical, having a nonstationary model, and that does not have a constant residual variance (heteroscedasticity). A time series ARCH and GARCH model can explain the heterocedasticity of data, but they are not always able to fully capture the asymmetric property of high frequency. Integrated Generalized Autoregresive Heteroskedascticity (IGARCH) model overcome GARCH weaknesses in capturing unit root. Furthermore IGARCH models were used to estimate the value of VaR as the maximum loss that will be obtained during a certain period at a certain confidence level. The aim of this study was to determine the best forecasting model of Jakarta Composite Index (JSI). The model had used in this study are ARCH, GARCH, and IGARCH. From the case studies were carried out, the result of forecasting volatility of stock index by using IGARCH(1,1) obtained log likelihood values that 3857,979 to the information criteria AIC = -6,3180; BIC = -6,3013; SIC = -6,3180; dan HQIC = -6,3117. Value of VaR movement of the JCI if it becomes greater the investment is Rp.500,000,000.00 with a confidence level of 95% on the date of July 2, 2015 using a model IGARCH (1,1) is Rp7.166.315,00.

scholarly journals The relationship between βeta and stock returns in the JSE securities exchange in South Africa

2011 ◽  
Vol 9 (1) ◽  
pp. 558-566
Author(s):  
Raphael Tabani Mpofu
Keyword(s):  
South Africa ◽  
Time Series ◽  
Regression Analysis ◽  
Financial Markets ◽  
Stock Returns ◽  
South African ◽  
Time Series Data ◽  
Series Data ◽  
The South ◽  
The Relationship

The purpose of this study was is to examine the relationship between stock βeta and returns in the JSE Securities Exchange. If the model is applicable in its entirety or can explain the beta-stock returns relationship, it raises an important academic question, mainly, how should the South African financial market be viewed by investors and portfolio managers, given the political-social-economical classifications that South Africa finds itself in, sometimes referred to as developing, emerging or underdeveloped? The time-series data used was from Sharenet as well as from the South African Reserve Bank macro-economic time series data. The sample period consisted of 10 years of monthly time series data between January 2001 and December 2010. Regression analysis was applied using the conditional approach. When using the conditional capital asset pricing model (CAPM) and cross-sectional regression analysis, the findings strongly supported the significant relationship between stock excess returns and βeta. However, the results do not provide strong evidence of a CAPM relation between risks and realized return trade-off in the South African financial markets. These results demonstrate that the South African financial markets are complex and financial tools, such as the CAPM can be used to explain complex financial phenomenon as in other developed markets, although complete reliance on the CAPM should be relied upon.

Sign in / Sign up

Export Citation Format

Share Document