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Quoreshi, Shahiduzzaman
Publications (9 of 9) Show all publications
Quoreshi, S., Mamode Khan, N. & Uddin, R. (2019). A Review of INMA Integer-valued Model Class, Application and Further Development. FILOMAT
Open this publication in new window or tab >>A Review of INMA Integer-valued Model Class, Application and Further Development
2019 (English)In: FILOMATArticle in journal (Refereed) Accepted
Abstract [en]

In this paper, we review INMA time series of integer-valued model class, and discuss its further development. These models have been developed for analyzing high frequency financial count data. A vivid description of high frequency data in the context of market micro structure is given. The most distinguishing feature that makes the INMA model class different from its continuous variable MA counterpart is that multiplication of variables with real valued parameters no longer remains a viable operation when the result is to be integer-valued. In the estimation of these models, no underlying distributions are assumed. Hence, the discussion of estimations are limited to CL, FGLS and GMM. A further development of estimation procedures for these models have also been reviewed. We suggest that the models could be estimated with Quasi Maximum Likelihood and propose in addition a Generalized Method of Moment of Quasi Maximum Likelihood. We have also discussed how INMA model class can be extended with different underlying distributions for innovations.

Place, publisher, year, edition, pages
Nis: , 2019
National Category
Probability Theory and Statistics Economics
Identifiers
urn:nbn:se:bth-17902 (URN)
Available from: 2019-05-16 Created: 2019-05-16 Last updated: 2019-05-21Bibliographically approved
Stone, T.-A. & Quoreshi, S. (2019). Do Global Value Chains Make Firms More Vulnerable To Trade Shocks?: Evidence from Manufacturing Firms in Sweden. journal of Risk and Financial Management, 12(3), Article ID 151.
Open this publication in new window or tab >>Do Global Value Chains Make Firms More Vulnerable To Trade Shocks?: Evidence from Manufacturing Firms in Sweden
2019 (English)In: journal of Risk and Financial Management, ISSN 1911-8066, Vol. 12, no 3, article id 151Article in journal (Refereed) Published
Abstract [en]

This paper examines the effect of the Global Financial Crisis on manufacturing firms in Sweden by analyzing the effect of trade exposure on firm performance. This study examines the decline in international trade during the global financial crisis by focusing on the relationship between global production linkages and firm performance. The trade exposure at the firm and industry levels were measured to assess the direct and indirect effects of the crisis on firm performance. Robust evidence was found of a negative relationship between trade exposure and the firms' sales and value-added growth during the crisis. In addition, it was found that higher export dependence was associated with lower sales growth during the crisis. Our results also show that the effect of the decline in the external demand on firm performance depends on the international input-output linkages. In particular, industries that are upstream in the value chain experienced a less severe decline in performance during the crisis.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
financial crisis; firm performance; exports; global value chains
National Category
Economics and Business
Identifiers
urn:nbn:se:bth-13280 (URN)10.3390/jrfm12030151 (DOI)000487963000031 ()
Note

open access

Available from: 2016-10-28 Created: 2016-10-28 Last updated: 2019-10-21Bibliographically approved
Quoreshi, A. S., Uddin, R. & Jienwatcharamongkhol, V. (2019). Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model. Journal of Risk and Financial Management, 12(2), Article ID 94.
Open this publication in new window or tab >>Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model
2019 (English)In: Journal of Risk and Financial Management, ISSN 1911-8074, Vol. 12, no 2, article id 94Article in journal (Refereed) Published
Abstract [en]

The current paper studies equity markets for the contagion of squared index returns as a proxy for stock market volatility, which has not been studied earlier. The study examines squared stock index returns of equity in 35 markets, including the US, UK, Euro Zone and BRICS (Brazil, Russia, India, China and South Africa) countries, as a proxy for the measurement of volatility. Results from the conditional heteroskedasticity long memory model show the evidence of long memory in the squared stock returns of all 35 stock indices studied. Empirical findings show the evidence of contagion during the global financial crisis (GFC) and Euro Zone crisis (EZC). The intensity of contagion varies depending on its sources. This implies that the effects of shocks are not symmetric and may have led to some structural changes. The effect of contagion is also studied by decomposing the level series into explained and unexplained behaviors.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
contagion; financial markets; global financial crisis; Euro zone crisis; long memory
National Category
Economics
Identifiers
urn:nbn:se:bth-18534 (URN)10.3390/jrfm12020094 (DOI)000475294000045 ()
Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-09-10Bibliographically approved
Quoreshi, S., Uddin, R. & Mamode Khan, N. (2019). Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework. Journal of Risk and Financial Management, 12(2), Article ID 74.
Open this publication in new window or tab >>Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework
2019 (English)In: Journal of Risk and Financial Management, Vol. 12, no 2, article id 74Article in journal (Refereed) Published
Abstract [en]

This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and FGLS in terms of eliminating serial correlations, but the estimator can be sensitive to start value. Hence, two-stage QML has been suggested. In empirical estimation on two stock transaction data for Ericsson and AstraZeneca, the 2SQML turns out relatively more efficient than CLS and FGLS. The empirical results suggest that both of the series have long memory properties that imply that the impact of macroeconomic news or rumors in one point of time has a persistence impact on future transactions.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
count data; estimation; finance; high frequency; intraday; time series
National Category
Probability Theory and Statistics Economics
Identifiers
urn:nbn:se:bth-17901 (URN)10.3390/jrfm12020074 (DOI)000475294000025 ()
Note

open access

Available from: 2019-05-16 Created: 2019-05-16 Last updated: 2019-09-10Bibliographically approved
Quoreshi, S. & Mollah, S. (2018). Conditional Heteroskedasticity in Long Memory Model ‘FIMACH’ for Return Volatilities in Equity Markets. In: : . Paper presented at International Conference on Time Series and Forecasting, ITISE 2018,Granada (pp. 825-840). , 2, Article ID 177.
Open this publication in new window or tab >>Conditional Heteroskedasticity in Long Memory Model ‘FIMACH’ for Return Volatilities in Equity Markets
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper incorporates conditional heteroscedasticity properties in the long memory model and applies the model on squared returns of BRICS (Brazil, Russia, India, China, and South Africa), UK and USA equity markets to capture the volatility of stock return. The conditional first- and second-order moments are provided. The CLS, FGLS and QML are discussed and 2SQML estimator is proposed. The simulation study suggests that the proposed 2SQML estimator performs better than the other three estimators. Both in simulation and empirical studies, we find that the proposed model FIMACH outperforms FIGARCH in terms of eliminating serial correlations.

Keywords
Long Memory Conditional Heteroskedastic Model, Return Volatility.
National Category
Economics
Identifiers
urn:nbn:se:bth-17211 (URN)9788417293574 (ISBN)
Conference
International Conference on Time Series and Forecasting, ITISE 2018,Granada
Available from: 2018-11-01 Created: 2018-11-01 Last updated: 2018-11-02Bibliographically approved
Quoreshi, S. (2017). A bivariate integer-valued long-memory model for high-frequency financial count data. Communications in Statistics - Theory and Methods, 46(3), 1080-1089
Open this publication in new window or tab >>A bivariate integer-valued long-memory model for high-frequency financial count data
2017 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 46, no 3, p. 1080-1089Article in journal (Refereed) Published
Abstract [en]

We propose a bivariate integer-valued fractional integrated (BINFIMA) model to account for the long-memory property and apply the model to high-frequency stock transaction data. The BINFIMA model allows for both positive and negative correlations between the counts. The unconditional and conditional first- and second-order moments are given. The model is capable of capturing the covariance between and within intra-day time series of high-frequency transaction data due to macroeconomic news and news related to a specific stock. Empirically, it is found that Ericsson B has mean recursive process while AstraZeneca has long-memory property.

Place, publisher, year, edition, pages
Taylor & Francis, 2017
Keywords
Count data, Estimation, Finance, Intra-day, Reaction time, Time series, Human reaction time, Count datum, High frequency HF, Long-memory property, Negative correlation, Recursive process, Second order moment, Stock transaction, Bins
National Category
Business Administration
Identifiers
urn:nbn:se:bth-13482 (URN)10.1080/03610926.2014.997361 (DOI)000387274200004 ()2-s2.0-84994034965 (Scopus ID)
Available from: 2016-11-24 Created: 2016-11-23 Last updated: 2017-11-29Bibliographically approved
Mollah, S., Quoreshi, S. & Zafirov, G. (2016). Equity market contagion during global financial and Eurozone crises: Evidence from a dynamic correlation analysis. Journal of international financial markets, institutions, and money, 41, 151-167
Open this publication in new window or tab >>Equity market contagion during global financial and Eurozone crises: Evidence from a dynamic correlation analysis
2016 (English)In: Journal of international financial markets, institutions, and money, ISSN 1042-4431, E-ISSN 1873-0612, Vol. 41, p. 151-167Article in journal (Refereed) Published
Abstract [en]

The devastation resulting from the recent global financial and Eurozone crises is immense. Most researchers commonly believe that the global financial crisis originated in the United States, and spread immediately to global financial hubs where it eventually became the Eurozone crisis. Several studies have been conducted on financial market contagion during both global and Eurozone crises; however, the issue of whether equity market contagion spreads from the United States to the world equity markets during these crises has not been addressed yet. Through using US dollar-denominated MSCI daily indices from fifty-five equity markets for the period 2003-2013, we have found evidence of contagion in developed and emerging markets during the global and Eurozone crises. We show that contagion spread from the United States to the world markets during both crises. Our regression results identify that the bank risk transfer between the United States and other countries is the key transmission channel for cross-country correlations. This study has an important policy implication for portfolio diversification between the United States and other countries during these crises. © 2015 Elsevier B.V.

Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
Contagion; Eurozone crisis; Financial markets; Global financial crisis
National Category
Business Administration
Identifiers
urn:nbn:se:bth-11788 (URN)10.1016/j.intfin.2015.12.010 (DOI)000373611400010 ()2-s2.0-84960494590 (Scopus ID)
Available from: 2016-04-01 Created: 2016-04-01 Last updated: 2017-11-30Bibliographically approved
Månsson, J. & Quoreshi, S. (2015). Evaluating regional cuts in the payroll tax from a firm perspective. The annals of regional science, 54(2), 323-347
Open this publication in new window or tab >>Evaluating regional cuts in the payroll tax from a firm perspective
2015 (English)In: The annals of regional science, ISSN 0570-1864, E-ISSN 1432-0592, Vol. 54, no 2, p. 323-347Article in journal (Refereed) Published
Abstract [en]

With few exceptions reduced payroll taxes are analysed with regards to employment and wage effects. Our study extends the impacts to cover several possible firm outcomes using a multilevel modelling approach. Between 20-55 percent in the variation in the outcomes can be explained by municipality differences. On firm level the result follows a clear business logic. In the short run, profits and turnover increased wish later on transforms into increased wages. After seven years we find indication of impacts on investments. Thus, the support has some short-term impacts that are reduced with time and the long-term effects are questionable.

Place, publisher, year, edition, pages
Springer, 2015
Keywords
Payroll tax cuts, impacts, firm perspectives, regional heterogeneity, multilevel analysis
National Category
Economics
Identifiers
urn:nbn:se:bth-6328 (URN)10.1007/s00168-015-0656-2 (DOI)000353356800001 ()oai:bth.se:forskinfo90CC079C8019E0B8C1257DCC007C0DF9 (Local ID)oai:bth.se:forskinfo90CC079C8019E0B8C1257DCC007C0DF9 (Archive number)oai:bth.se:forskinfo90CC079C8019E0B8C1257DCC007C0DF9 (OAI)
Note

The final publication is available at Springer via http://dx.doi.org/[10.1007/s00168-015-0656-2]".

Available from: 2015-05-26 Created: 2015-01-13 Last updated: 2017-12-04Bibliographically approved
Quoreshi, S. (2014). A long-memory integer-valued time series model, INARFIMA, for financial application. Quantitative Finance, 14(12), 2225-2235
Open this publication in new window or tab >>A long-memory integer-valued time series model, INARFIMA, for financial application
2014 (English)In: Quantitative Finance, ISSN 1469-7688, Vol. 14, no 12, p. 2225-2235Article in journal (Refereed) Published
Abstract [en]

A model to account for the long-memory property in a count data framework is proposed and applied to high-frequency stock transactions data. By combining features of the INARMA and ARFIMA models, an Integer-valued Auto Regressive Fractionally Integrated Moving Average (INARFIMA) model is proposed. The unconditional and conditional first- and second-order moments are given. The CLS, FGLS and GMM estimators are discussed. In its empirical application to two stock series for AstraZeneca and Ericsson B, we find that both series have a fractional integration property.

Abstract [sv]

INARFIMA modell föreslås. CLS är FGLS och GMM estimatorer diskuteras. I sin empiriska tillämpning på två aktieserier för AstraZeneca och Ericsson B finner vi att båda serierna har långminne. Intra-dag, hög frekvens, Estimation, Fractional integration, Reaktionstid

Place, publisher, year, edition, pages
Routledge, 2014
Keywords
Intra-day, High-frequency, Estimation, Fractional integration, Reaction time
National Category
Economics Probability Theory and Statistics
Identifiers
urn:nbn:se:bth-6431 (URN)10.1080/14697688.2012.711911 (DOI)oai:bth.se:forskinfo3C918ECD41431757C1257DCC007700C3 (Local ID)oai:bth.se:forskinfo3C918ECD41431757C1257DCC007700C3 (Archive number)oai:bth.se:forskinfo3C918ECD41431757C1257DCC007700C3 (OAI)
External cooperation:
Note

http://www.tandfonline.com/doi/full/10.1080/14697688.2012.711911#.VLWQdivF9oc

Available from: 2015-01-19 Created: 2015-01-13 Last updated: 2016-09-01Bibliographically approved
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