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Academic literature on the topic 'Vector error correction model (VEC model)'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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Journal articles on the topic "Vector error correction model (VEC model)"

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Pradhan, Kailash. "The Hedging Effectiveness of Stock Index Futures: Evidence for the S&P CNX Nifty Index Traded in India." South East European Journal of Economics and Business 6, no. 1 (April 1, 2011): 111–23. http://dx.doi.org/10.2478/v10033-011-0010-2.

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The Hedging Effectiveness of Stock Index Futures: Evidence for the S&P CNX Nifty Index Traded in IndiaThis study evaluates optimal hedge ratios and the hedging effectiveness of stock index futures. The optimal hedge ratios are estimated from the ordinary least square (OLS) regression model, the vector autoregression model (VAR), the vector error correction model (VECM) and multivariate generalized autoregressive conditional heteroskedasticity (M-GARCH) models such as VAR-GARCH and VEC-GARCH using the S&P CNX Nifty index and its futures index. Hedging effectiveness is measured in terms of within sample and out of sample risk-return trade-off at various forecasting horizons. The analysis found that the VEC-GARCH time varying hedge ratio provides the greatest portfolio risk reduction and generates the highest portfolio returns.

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Hendayanti, Ni Putu Nanik, and Maulida Nurhidayati. "PEMODELAN JUMLAH UANG BEREDAR DAN INFLASI NASIONAL DENGAN VECTOR ERROR CORRECTION MODEL (VECM)." Jurnal Varian 1, no. 1 (September 28, 2017): 1. http://dx.doi.org/10.30812/varian.v1i1.44.

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AbstrakModel Vector Autoregressive (VAR) merupakan salah satu model deret waktu yang berbentuk simultan. VAR adalah suatu sistem persamaan dimana setiap peubah merupakan fungsi linier dari nilai lag (lampau) peubah itu sendiri serta nilai lag dari peubah lain dalam sistem. Seringkali pada model terdapat beberapa hubungan kointegrasi antar peubah, sehingga model VAR yang terbentuk menjadi tidak representatif. Salah satu metode yang dapat mengatasi masalah adanya hubungan kointegrasi antar peubah adalah model Vector Error Correction (VEC). Perekonomian menjadi salah satu pondasi utama kekuatan suatu negara. Namun, stabilitas ekonomi tidak selalu berjalan dengan mulus karena adanya banyak faktor, baik faktor eksternal maupun faktor internal. Salah satu indikator utama yang digunakan untuk melihat perkembangan perekonomian suatu negara adalah tingkat laju inflasi. Inflasi adalah kecenderungan dari harga-harga untuk meningkat secara umum terhadap kelompok barang kebutuhan masyarakat dan bersifat terus menerus. Ada banyak faktor yang mempengarui terjadinya inflasi salah satunya yaitu jumlah uang beredar. Penelitian ini bertujuan untuk memodelkan jumlah uang beredar dan inflasi nasional dengan model Vector Error Correction (VECM). Hasil penelitian menunjukkan bahwa estimasi VECM untuk fungsi inflasi jangka pendek terdapat nilai koreksi kesalahan dari jangka pendek ke jangka panjang sebesar 0,000235. Pada analisis jangka pendek, perubahan jumlah uang beredar pada bulan sebelumnya memberikan pengaruh yang negatif terhadap perubahan inflasi bulan ini sebesar 0,207. Sedangkan perubahan inflasi bulan sebelumnya memberikan pengaruh yang positif terhada perubahan perubahan jumlah uang beredar pada bulan ini sebesar 0,000570.

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Abusharbeh, Mohammed. "Determinants of Islamic bank financing in the Middle East: Vector Error Correction Model (VECM)." Investment Management and Financial Innovations 17, no. 4 (December 9, 2020): 285–98. http://dx.doi.org/10.21511/imfi.17(4).2020.25.

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As the world has been struck with a global financial crisis, Middle Eastern countries have been affected as well. Thus, Islamic banks have expanded, and the competitive advantage has become intensive with the increased number of conventional banks in the global banking system. This manuscript is aimed to examine the impact of macroeconomic and bank-specific factors on Islamic bank financing in the Middle Eastern countries. Therefore, the Vector Error Correction Model and the Granger causality test were run from 2009 to 2018 to detect the long- and short-run relationship between the explanatory variables and Islamic bank financing. The results suggest that both inflation and profitability negatively impact Islamic bank financing in the long run. The paper also revealed bidirectional causality between the variables GDP and bank size and Islamic bank financing. It shows that GDP and bank size are highly dominant factors of Islamic bank financing in the short run. Thus, this paper provides evidence that any short-run shock in the variables of GDP, inflation, and bank size will cause a long-term relationship with Islamic bank financing. This article’s novelty is to ensure resilience within the Islamic banking system during and after the financial crisis. It provides evidence that Islamic banks can cushion their financial activities from economic volatility during the crisis. The results found can be used to predict the growth of Islamic bank financing in upcoming years in the Middle East and all emerging countries.

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KONG, TUAN-YUEN, YUN-PENG CHU, CHIN-FU HSU, and NORDEN E. HUANG. "AN ANATOMY OF ECONOMIC GROWTH IN TAIWAN." Advances in Adaptive Data Analysis 02, no. 02 (April 2010): 217–31. http://dx.doi.org/10.1142/s179353691000046x.

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This paper revises Sedgley's model of innovation-driven endogenous growth and applies it to the case of Taiwan. The methods of empirical mode decomposition (EMD) and constrained vector error correction (VEC model or VECM) are used in the process. The EMD is used to filter out very short term fluctuations in growth, while the VECM is used to detect the various factors that affect economic growth, including human capital, public and private capital, knowledge capital and public institutions (the index of protection of property rights). It is the first attempt to include such a rich set of factors affecting economic growth at least for the studies of Taiwan.

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Onakoya, Adegbemi Babatunde, and Hassan Akolade Alayande. "Macroeconomic Variables, the Oil, and the Agricultural Sectors in Nigeria." Asian Social Science 16, no. 1 (December 31, 2019): 69. http://dx.doi.org/10.5539/ass.v16n1p69.

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The present study examined the impact of the macroeconomic variables and the oil sector on the performance of the agricultural sector between 1981and 2017 in Nigeria. The study adopted a three-stage estimation approach. The initial step in this estimation was the conduct of descriptive statistics and stationarity tests of the variables. Some of the series were stationary at level and some others at the first difference which informed the deployment of the Auto regressive distributed lag (ARDL) technique for model estimation. The third stage was the post-estimation of the model in order ascertain its robustness for predictability and policy formulation. These were the Cumulative Sum Control Chart (CUSUM) stability, Vector Error Correction (VEC) Residual Heteroscedasticity, Breusch-Godfrey Serial Correlation LM, Vector Error Correction Residual Normality, and Vector Error Correction (VEC) Residual Heteroscedasticity tests. The results indicated that contrary to the Dutch disease postulation the oil sector positively impacted the output of the agricultural sector. The influence of exchange rate was also positive. Interest and unemployment rates on the other hand, had negative effects. The rate of inflation and the national output had no impact. The study recommended that the Nigerian government should channel resources towards the agricultural sector to ensure increase in foreign earnings and sufficient domestic production.

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Khera, Aastha, and Neelam Dhanda. "Empirical Relationship between Macroeconomic Variables and Stock Prices of Indian Banking Sector: A Vector Error Correction Model Approach." Review of Finance and Banking 12, no. 2 (December 31, 2020): 189–98. http://dx.doi.org/10.24818/rfb.20.12.02.06.

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This existing study aims to investigate the relationship between Indian Bankingstock market prices and macroeconomic variables. The proxy for the Indian Banking stockmarket is Nifty Bank while Foreign Reserve, Exchange Rate (Indian vs US Dollar), Interestrate, and CPI are proxies of macroeconomic variables. Johansen Cointegration and VectorError Correction Model (VECM) on monthly data from January 2013 to July 2020 have beenapplied. Considering the results of cointegration, it is found that there is a long-run asso-ciation between the Indian Banking stock market and constituent macroeconomic variables.Next, the employment of VECM is done for inspecting long run and short-run causality.The result reveals long-run equilibrium in Indian commercial bankís stock prices comingfrom macroeconomic variables. This study has considerable imputations that investors candiversify their portfolio according to the ináuencing power of constituent selected macro-economic variables in the short run and the long run. Exchange rate and foreign reservesdrive the banking stock market in the short run whereas CPI and Interest rate do not createany signiÖcant impact.

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Xiaoge, Zhao, and Zhong Shihu. "The Influence of Administrative Monopoly on Economic Development——An Empirical Study Based on Vector Error Correction Model." International Journal of Business and Management 12, no. 6 (May 18, 2017): 182. http://dx.doi.org/10.5539/ijbm.v12n6p182.

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As a unique form of China's transition economy, the impact of administrative monopoly on economic development can not be ignored. Analyzing the data from 1990 to 2015, this paper investigates the relationship between administrative monopoly and economic development based on Vector Error Correction Model (VEC)model. The results show that there is a long - term equilibrium relationship between administrative monopoly and economic development. In the long run, the administrative monopoly has obvious obstructive effect on economic development. The hardest part, as well as the emphasis in China's economic reform will be how to separate the government from state-owned enterprises and eliminate administrative monopoly.

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Sung, Joo-han. "A Study on the Apartment Sale Price Decision Model Using Vector Error Correction Model (VECM): Focusing on the Housing Market in Changwon City." Housing Finance Research 5, no. 1 (June 2021): 27–49. http://dx.doi.org/10.52344/hfr.2021.5.1.27.

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Hossain, Md Rasel, Ahsanul Haque, Md Abdullah Amir Hamja, and M. Shohel Rana. "MEASURING CO-MOVEMENT OF REAL INTEREST RATE AND INFLATION RATE: USING VEC APPROACH." International Journal of Engineering Technologies and Management Research 7, no. 6 (June 15, 2020): 66–76. http://dx.doi.org/10.29121/ijetmr.v2020.i7.6.687.

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It is important to know the future movement of economic variables for the planning and development of a country, Vector Error Correction (VEC) Model has been applied to disclose hidden long run as well as short-run patterns of the selected variables. ADF unit root testing procedure was applied to satisfy the conditions of applying the VEC Model. Using Johansen cointegration test long-run cointegration has been justified. But the VEC model reveals that long run significant causal relationship between the variables whereas there is no short-run causal relationship. The parameter was estimated using the OLS estimation technique. The validity of the model was confirmed by applying different quantitative approaches such as normality test, autocorrelation test, Portmanteau test, Unit root test, and various graphical approaches which suggested model selection and estimation were correct. The result of this present study may help Govt. agencies as well as planners to take an idea.

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Hossain, Md Rasel, Ahsanul Haque, Md Abdullah Amir Hamja, and M. Shohel Rana. "MEASURING CO-MOVEMENT OF REAL INTEREST RATE AND INFLATION RATE: USING VEC APPROACH." International Journal of Engineering Technologies and Management Research 7, no. 6 (June 15, 2020): 66–76. http://dx.doi.org/10.29121/ijetmr.v7.i6.2020.687.

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It is important to know the future movement of economic variables for the planning and development of a country, Vector Error Correction (VEC) Model has been applied to disclose hidden long run as well as short-run patterns of the selected variables. ADF unit root testing procedure was applied to satisfy the conditions of applying the VEC Model. Using Johansen cointegration test long-run cointegration has been justified. But the VEC model reveals that long run significant causal relationship between the variables whereas there is no short-run causal relationship. The parameter was estimated using the OLS estimation technique. The validity of the model was confirmed by applying different quantitative approaches such as normality test, autocorrelation test, Portmanteau test, Unit root test, and various graphical approaches which suggested model selection and estimation were correct. The result of this present study may help Govt. agencies as well as planners to take an idea.

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Dissertations / Theses on the topic "Vector error correction model (VEC model)"

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Silber, Frank. "Makroökonometrische Anpassungsanalyse im Vector-Error-Correction-Model (VECM) : Untersuchungen an ausgewählten Arbeitsmärkten /." Frankfurt am Main: Lang, 2003. http://www.gbv.de/dms/zbw/362076561.pdf.

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Mvita, Mpinda Freddy. "The impact of dividend policy on shareholders' wealth : evidence from the Vector Error Correction Model." Diss., University of Pretoria, 2012. http://hdl.handle.net/2263/31010.

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Dividend policy is widely researched in financial management, but determining whether it affects the market price per share is difficult. There has been much published on the subject, which presented theories such as the Modigliani, Miller, Gordon, Lintner, Walter and Richardson propositions and the relevance and irrelevance theories. However, little research has been done on the impact of dividend policy on shareholders’ wealth while considering the short- and long-run effects. The Vector Error Correction Model (VECM) was used to describe the short-run and long-run dynamics or the adjustment of the cointegrated variables towards their equilibrium values in South Africa. This study attempts to explain the effect of dividend policy on the market price per share. A sample of 46 companies listed on the Johannesburg Securities Exchange (JSE) was selected for the period 1995-2010. Three variables were used, namely the market price per share, the dividend per share and the earnings per share. The market price per share was used as a proxy in measuring shareholders’ wealth and the dividend per share was used as a proxy in measuring the dividend policy. Fixed and random effects models were applied to panel data to determine the relation between dividend policy and market price per share. The fixed effects method was used to control the stable characteristics of the companies over a fixed period. The random effects model was applied when the companies’ characteristics differed. Results for both models indicated that dividend yield is positively related to market price per share, while earnings per share do not have a significant impact on the market price per share. To test the strength of the long-run relationship, the VECM was applied. The coefficient for dividend per share in the co-integrating equation was positive, while the coefficient for earnings per share was negative. This confirms previous research findings. The results suggest that there is a long-run relationship between dividend per share and market price per share. The Granger causality test indicates there is bi-directional Granger causality between market price per share and dividend per share in South Africa. Therefore dividend policy does have a significant long-run impact on the share price and therefore provides a signal about the company’s financial success.
Dissertation (MCom)--University of Pretoria, 2012.
Financial Management
Unrestricted

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Meki, Brian. "Examining long-run relationships of the BRICS stock market indices to identify opportunities for implementation of statistical arbitrage strategies." Thesis, University of the Western Cape, 2012. http://hdl.handle.net/11394/4348.

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>Magister Scientiae - MSc
Purpose:This research investigates the existence of long-term equilibrium relationships among the stock market indices of Brazil, Russia, India, China and South Africa (BRICS). It further investigates cointegrated stock pairs for possible implementation of statistical arbitrage trading techniques.Design:We utilize standard multivariate time series analysis procedures to inspect unit roots to assess stationarity of the series. Thereafter, cointegration is tested by the Johansen and Juselius (1990) procedure and the variables are interpreted by a Vector Error Correction Model (VECM). Statistical arbitrage is investigated through the pairs trading technique.Findings:The five stock indices are found to be cointegrated. Analysis shows that the cointegration rank among the variables is significantly influenced by structural breaks. Two pairs of stock variables are also found to be cointegrated. This guaranteed the mean reversion property necessary for the successful execution of the pairs trading technique. Determining the optimal spread threshold also proved to be highly significant with respect to the success of this trading technique.Value:This research seeks to expand on the literature covering long-run co-movements of the volatile emerging market indices. Based on the cointegration relation shared by the BRICS, the research also seeks to encourage risk taking when investing. We achieve this by showing the potential rewards that can be realized through employing appropriate statistical arbitrage trading techniques in these markets.

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Ramanauskaitė, Giedrė. "Stress testing in credit risk analysis." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080620_110415-38466.

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The supervising institutions do not give to commercial banks indications what models have to be used for stress testing. This research was done in order to find out which mathematical/statistical models are and can be used in credit risk stress testing. Credit risk is one of the biggest financial risks that every bank faces. Stress testing is a tool of credit risk assessment that helps to estimate the consequences of the events that have really small probability to happen but if they occur, banks can have significant losses. This study determined that the most plausible event is adverse macroeconomic conditions. For this reason, models that include macroeconomic impact were presented. Vector autoregression and vector error correction model were tested using the empirical data received from Swedish central bank, Swedish statistics and Eurostat. For financial stability it is worth using vector autoregression or vector error correction model as they describe the macroeconomic environment in the most suitable way and they are appropriate for shock analysis by showing how the impact of any factor can change the whole system. Structure: introduction, main part (credit risk, methods and empirical analysis), publication, conclusions, references. Thesis consists of: 50 p. text without appendices, 13 pictures, 11 tables, 26 bibliographical entries. Appendices included.
Kredito įstaigų priežiūros institucijos nepateikia komerciniams bankams kokius metodus jie turėtų naudoti testavime nepalankiomis sąlygomis. Tiriamasis darbas buvo atliktas tuo tikslu, kad būtų išsiaiškinta kokie matematiniai ir statistiniai metodai yra ir gali būti naudojami kredito rizikos vertinime testuojant nepalankiomis sąlygomis. Kredito rizika yra viena iš didžiausių finansinių rizikų su kuria bankai susiduria. Testavimas nepalankiomis sąlygomis yra kredito rizikos vertinimo įrankis, padedantis nustatyti įvykių, kurių realizavimosi tikimybės yra mažos, tačiau jiems įvykus, bankai patirtų reikšmingus nuostolius, pasekmes. Šis tyrimas nustatė, jog labiausiai tikėtinas įvykis gali būti ypatingai nepalankios ekonominės sąlygos. Dėl šios priežasties darbe yra pristatyti metodai, kurie įvertina makroekonominių veiksnių įtaką. Vektorinė autoregresija ir vektorinis paklaidų korekcijos modelis buvo patikrinti naudojant Švedijos centrinio banko, Švedijos statistikos departamento ir Eurostat empirinius duomenis. Finansinio stabilumo įvertinimui vertėtų naudoti vektorinį autoregresijos ar vektorinį paklaidų korekcijos modelius, nes šie modeliai geriausiai aprašo ekonominę aplinką bei yra labai tinkami šokų analizei, kadangi įvertina bet kurio veiksnio įtaką visai sistemai. Struktūra: įvadas, pagrindinė dalis (kredito rizika, metodai ir empirinė analizė), publikacija, išvados, literatūros sąrašas. Tiriamasis darbas sudarytas iš: 50 psl. teksto be priedų, 13 paveikslų, 11... [toliau žr. visą tekstą]

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Louw, Riëtte. "Forecasting tourism demand for South Africa / Louw R." Thesis, North-West University, 2011. http://hdl.handle.net/10394/7607.

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Tourism is currently the third largest industry within South Africa. Many African countries, including South Africa, have the potential to achieve increased economic growth and development with the aid of the tourism sector. As tourism is a great earner of foreign exchange and also creates employment opportunities, especially low–skilled employment, it is identified as a sector that can aid developing countries to increase economic growth and development. Accurate forecasting of tourism demand is important due to the perishable nature of tourism products and services. Little research on forecasting tourism demand in South Africa can be found. The aim of this study is to forecast tourism demand (international tourist arrivals) to South Africa by making use of different causal models and to compare the forecasting accuracy of the causal models used. Accurate forecasts of tourism demand may assist policy–makers and business concerns with decisions regarding future investment and employment. An overview of South African tourism trends indicates that although domestic arrivals surpass foreign arrivals in terms of volume, foreign arrivals spend more in South Africa than domestic tourists. It was also established that tourist arrivals from Africa (including the Middle East), form the largest market of international tourist arrivals to South Africa. Africa is, however, not included in the empirical analysis mainly due to data limitations. All the other markets namely Asia, Australasia, Europe, North America, South America and the United Kingdom are included as origin markets for the empirical analysis and this study therefore focuses on intercontinental tourism demand for South Africa. A review of the literature identified several determinants of tourist arrivals, including income, relative prices, transport cost, climate, supply–side factors, health risks, political stability as well as terrorism and crime. Most researchers used tourist arrivals/departures or tourist spending/receipts as dependent variables in empirical tourism demand studies. The first approach used to forecast tourism demand is a single equation approach, more specifically an Autoregressive Distributed Lag Model. This relationship between the explanatory variables and the dependent variable was then used to ex post forecast tourism demand for South Africa from the six markets identified earlier. Secondly, a system of equation approach, more specifically a Vector Autoregressive Model and Vector Error Correction Model were estimated for each of the identified six markets. An impulse response analysis was undertaken to determine the effect of shocks in the explanatory variables on tourism demand using the Vector Error Correction Model. It was established that it takes on average three years for the effect on tourism demand to disappear. A variance decomposition analysis was also done using the Vector Error Correction Model to determine how each variable affects the percentage forecast variance of a certain variable. It was found that income plays an important role in explaining the percentage forecast variance of almost every variable. The Vector Autoregressive Model was used to estimate the short–run relationship between the variables and to ex post forecast tourism demand to South Africa from the six identified markets. The results showed that enhanced marketing can be done in origin markets with a growing GDP in order to attract more arrivals from those areas due to the high elasticity of the real GDP per capita in the long run and its positive impact on tourist arrivals. It is mainly up to the origin countries to increase their income per capita. Focussing on infrastructure development and maintenance could contribute to an increase in future tourist arrivals. It is evident that arrivals from Europe might have a negative relationship with the number of hotel rooms available since tourists from this region might prefer accommodation with a safari atmosphere such as bush lodges. Investment in such accommodation facilities and the marketing of such facilities to Europeans may contribute to an increase in arrivals from Europe. The real exchange rate also plays a role in the price competitiveness of the destination country. Therefore, in order for South Africa to be more price competitive, inflation rate control can be a way to increase price competitiveness rather than to have a fixed exchange rate. Forecasting accuracy was tested by estimating the Mean Absolute Percentage Error, Root Mean Square Error and Theil’s U of each model. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was estimated for each origin market as a benchmark model to determine forecasting accuracy against this univariate time series approach. The results showed that the Seasonal Autoregressive Integrated Moving Average model achieved more accurate predictions whereas the Vector Autoregressive model forecasts were more accurate than the Autoregressive Distributed Lag Model forecasts. Policy–makers can use both the SARIMA and VAR model, which may generate more accurate forecast results in order to provide better policy recommendations.
Thesis (M.Com. (Economics))--North-West University, Potchefstroom Campus, 2011.

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Hadad, Junior Eli. "Um estudo econométrico do consumo e da renda agregados no Brasil." Universidade Presbiteriana Mackenzie, 2011. http://tede.mackenzie.br/jspui/handle/tede/534.

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Made available in DSpace on 2016-03-15T19:25:37Z (GMT). No. of bitstreams: 1 Eli Hadad Junior.pdf: 290403 bytes, checksum: 413b010b2b66c535b71df800b9626c61 (MD5) Previous issue date: 2011-08-10
The dissertation analyzes data of the Brazilian household consumption and income between the years 1947 and 2009. The study aims to evaluate to what extent the aggregate consumption of Brazilian household may approximate be a random walk. The dissertation uses Johansen's cointegration techniques (1988, 1991) and super exogeneity tests as proposed by Engle and Hendry et al. (1983). The dissertation attempts to evaluate whether interventions that affect consumption will impact the dynamics of aggregate income. These interventions can occur through credit policies and tax changes, among other macroeconomic shocks. Finally, a decomposition is made following the methodology proposed by Gonzalo-Granger (1995) and evaluating the importance of shocks in permanent and temporary changes in consumption.
A dissertação analisa os dados de consumo e renda das famílias brasileiras entre os anos de 1947 e 2009. O trabalho visa avaliar em que medida o consumo agregado das famílias brasileiras pode ser bem aproximando a partir de um passeio aleatório puro. O trabalho utiliza técnicas de cointegração de Johansen (1988, 1991) e testes de super exogeneidade na forma proposta por Hendry, Engle et al. (1983). A dissertação procura avaliar se intervenções que afetam o consumo das famílias geram impacto na dinâmica da renda agregada das mesmas. Tais intervenções podem ser por políticas de crédito, alterações tributárias, choque macroeconômicos entre outras. Por fim uma decomposição entre fatores permanentes e transitórios será feita pela metodologia proposta por Gonzalo-Granger (1995) com o objetivo de avaliar-se a importância dos choques permanentes e transitórios para as variações do consumo.

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Bohlandt, Florian Martin. "Single manager hedge funds - aspects of classification and diversification." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85859.

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Thesis (PhD)--Stellenbosch University, 2013.
A persistent problem for hedge fund researchers presents itself in the form of inconsistent and diverse style classifications within and across database providers. For this paper, single-manager hedge funds from the Hedge Fund Research (HFR) and Hedgefund.Net (HFN) databases were classified on the basis of a common factor, extracted using the factor axis methodology. It was assumed that the returns of all sample hedge funds are attributable to a common factor that is shared across hedge funds within one classification, and a specific factor that is unique to a particular hedge fund. In contrast to earlier research and the application of principal component analysis, factor axis has sought to determine how much of the covariance in the dataset is due to common factors (communality). Factor axis largely ignores the diagonal elements of the covariance matrix and orthogonal factor rotation maximises the covariance between hedge fund return series. In an iterative framework, common factors were extracted until all return series were described by one common and one specific factor. Prior to factor extraction, the series was tested for autoregressive moving-average processes and the residuals of such models were used in further analysis to improve upon squared correlations as initial factor estimates. The methodology was applied to 120 ten-year rolling estimation windows in the July 1990 to June 2010 timeframe. The results indicate that the number of distinct style classifications is reduced in comparison to the arbitrary self-selected classifications of the databases. Single manager hedge funds were grouped in portfolios on the basis of the common factor they share. In contrast to other classification methodologies, these common factor portfolios (CFPs) assume that some unspecified individual component of the hedge fund constituents’ returns is diversified away and that single manager hedge funds should be classified according to their common return components. From the CFPs of single manager hedge funds, pure style indices were created to be entered in a multivariate autoregressive framework. For each style index, a Vector Error Correction model (VECM) was estimated to determine the short-term as well as co-integrating relationship of the hedge fund series with the index level series of a stock, bond and commodity proxy. It was postulated that a) in a well-diversified portfolio, the current level of the hedge fund index is independent of the lagged observations from the other asset indices; and b) if the assumptions of the Efficient Market Hypothesis (EMH) hold, it is expected that the predictive power of the model will be low. The analysis was conducted for the July 2000 - June 2010 period. Impulse response tests and variance decomposition revealed that changes in hedge fund index levels are partially induced by changes in the stock, bond and currency markets. Investors are therefore cautioned not to overemphasise the diversification benefits of hedge fund investments. Commodity trading advisors (CTAs) / managed futures, on the other hand, deliver diversification benefits when integrated with an existing portfolio. The results indicated that single manager hedge funds can be reliably classified using the principal factor axis methodology. Continuously re-balanced pure style index representations of these classifications could be used in further analysis. Extensive multivariate analysis revealed that CTAs and macro hedge funds offer superior diversification benefits in the context of existing portfolios. The empirical results are of interest not only to academic researchers, but also practitioners seeking to replicate the methodologies presented.

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Tao, Juan. "A re-examination of the relationship between FTSE100 index and futures prices." Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/8071.

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This thesis examines the validity of the cost of carry model for pricing FTSE100 futures contracts and the relationship between FTSE100 spot and futures markets during two sub-periods characterised by different market trading systems employed by the LSE and LIFFE. The empirical work is carried out using three approaches to econometric modeling: a basic VECM for spot and futures prices, a VECM extended with a DCCTGARCH framework to account for the conditional variance-covariance structure for spot and futures prices and a threshold VECM to capture regime-dependent spot-futures price dynamics. Overall, both the basic VECM and the DCC-TGARCH analysis suggest that there are deviations from the cost of carry relationship in the first sub-sample when transactions costs in both markets are relatively high but that the cost of carry relationship tends to be valid in the second sub-sample when transactions costs are lower. This is further confirmed by the evidence of higher conditional correlations between the two markets in the second sub-sample as compared with the first, using the DCC-TGARCH analysis. This implies that the no-arbitrage cost of carry relationship between spot and futures markets is more effectively maintained by index arbitrageurs in the second period when market conditions are closer to perfect market assumptions, and hence the cost of carry model could be more reasonably used as a benchmark for pricing stock index futures. The threshold VECM analysis depicts regime-dependent price dynamics between FTSE100 spot and futures markets and leads to some interesting and important findings: arbitrage may not be practicable under some market conditions, either because it is difficult to find counterparties for the arbitrage transactions, or because there is significant risk associated with arbitrage; as a result, the cost of carry model may not always be suitable for pricing stock index futures. Furthermore, the threshold values yielded from estimating the threshold VECM reflect the average transaction costs for most arbitrageurs that are more reliable and fair than subjective estimations.

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Molin, Simon. "House Price Dynamics in Sweden : Vector error-correction model." Thesis, Umeå universitet, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172367.

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Movements in house prices can have effects on individuals, financial markets, and the whole economy. After the rapid increase in house prices worldwide since the mid-1990s and after the financial crisis in 2008, many studies have investigated house price dynamics. Furthermore, real house prices in Sweden have increased by more than 200 % since the mid-1990s up until today. This study takes a closer look at the fundamental determinants of house prices to investigate both the long- and short-run dynamics of Swedish house prices. The method of use includes a vector error-correction model, which exposes both long- and short-run dynamics of house prices. The long-run results show that Swedish house prices are currently not overvalued. Furthermore, in the short-run, the results suggest that house prices adjust to their equilibrium level with 7,9 % in each quarter.

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Dahlberg, Magnus, and Gombrii Anders. "Vart är kronan på väg? : Utmaningen med växelkursprognoser - en jämförelse av prognosmodeller." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-439138.

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Riksbanken har under senaste åren blivit kritiserade för deras bristande prognoser av svenska valutakurser. I denna uppsats undersöks det om slumpvandring (RW) är den mest framgångsrika prognosmodellen eller om alternativa ekonometriska prognosmodeller (AR, VAR och VECM) kan estimera framtida växelkurser mer korrekt på kort sikt, ett kvartal fram, och medellång sikt, fyra kvartal fram. I dessa prognosmodeller behandlas fem Svenska makroekonomiska variabler som endogena; KPI, BNP, arbetslöshet, 3 månaders statsobligationer (T-bonds), samt en exogen variabel, Amerikansk-BNP. Den data som används är kvartalsdata från första kvartalet 1993 till andra kvartalet 2020 för respektive variabel. Resultaten från studie visar på att RW är mer ackurat än de multivariata modellerna (VAR och VECM) på både kort sikt och medellång sikt. Residualerna utvärderas genom att kolla på rotmedelkvadratfel (RMSE) från respektive prognos.
In recent years, the Riksbank has been criticized for their underperforming forecasts of Swedish exchange rates. This thesis examines whether the random walk (RW) is the most successful forecasting model when forecasting the exchange rate (SEK / USD) or whether alternative economic forecasting models (AR, VAR and VECM) can estimate future exchange rates more accurately. Both in the short and medium term, one respectively four quarters ahead. In these forecast models, five Swedish macroeconomic variables are treated as endogenous; CPI, GDP, unemployment, three-month Treasury-bonds (T-Bonds), and an exogenous variable, US GDP. The data used is quarterly data from the first quarter of 1993 to the second quarter of 2020 for each variable. Results from the study show that RW is more accurate than the multivariate models (VAR and VECM) in both the short and medium term. The residuals are evaluated by looking at root mean square error (RMSE) from the respective forecast.

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Books on the topic "Vector error correction model (VEC model)"

1

Makroökonometrische Anpassungsanalyse im Vector-Error-Correction-Model (VECM): Untersuchungen an ausgewählten Arbeitsmarkten. Frankfurt am Main: P. Lang, 2003.

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Lloyd, Tim. Testing a capital pricing model of land values: Cointegration and error correction in a vector auto-regression. Nottingham: Department of Economics, University of Nottingham, 1992.

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S, Madheswaran, and Institute for Social and Economic Change, eds. Casuality between energy consumption and output growth in Indian cement industry: An application of panel vector error correction model. Bangalore: Institute for Social and Economic Change, 2010.

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Kurniyati, Yuli. Alokasi dan distribusi anggaran pemerintah daerah Tingkat II untuk sektor pendidikan serta pengaruhnya terhadap pertumbuhan ekonomi regional: Aplikasi Vector Error Correction Model pada kabupaten dan kota di Propinsi Daerah Istimewa Yogyakarta, 1990-2006 : laporan penelitian dosen muda. Yogyakarta: Fakultas Ekonomi, Universitas Proklamasi 45, 2008.

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Pevehouse, Jon, and Jason D. Brozek. Time‐Series Analysis. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0019.

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This article discusses time-series methods such as simple time-series regressions, ARIMA models, vector autoregression (VAR) models, and unit root and error correction models (ECM). It specifically presents a brief history of time-series analysis before moving to a review of the basic time-series model. It then describes the stationary models in univariate and multivariate analyses. The nonstationary models of each type are addressed. In addition, various issues regarding the analysis of time series including data aggregation and temporal stability are considered. Before concluding, the article briefly reports the time-series techniques in the context of panel data. In general, time-series analysis can help improve the understanding of the political world.

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Book chapters on the topic "Vector error correction model (VEC model)"

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Labuschagne, Coenraad C. A., Niel Oberholzer, and Pierre J. Venter. "A Vector Error Correction Model (VECM) of FTSE/JSE SA Listed Property Index and FTSE/JSE SA Capped Property Index." In Advances in Panel Data Analysis in Applied Economic Research, 95–111. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-70055-7_8.

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Thasnimol, C. M., and R. Rajathy. "Vector Error Correction Model for Distribution Dynamic State Estimation." In Control Applications in Modern Power System, 15–27. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8815-0_2.

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Chen, Jun, Xiaoqi Peng, and Xiuming Tang. "Error Correction of Support Vector Regression Model for Copper-Matte Converting Process." In Proceedings of the 2015 Chinese Intelligent Automation Conference, 117–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46466-3_13.

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Thongkairat, Sukrit, Woraphon Yamaka, and Songsak Sriboonchitta. "A Regime Switching Vector Error Correction Model of Analysis of Cointegration in Oil, Gold, Stock Markets." In Structural Changes and their Econometric Modeling, 514–24. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04263-9_40.

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Yamaka, Woraphon, Pathairat Pastpipatkul, and Songsak Sriboonchitta. "Business Cycle of International Tourism Demand in Thailand: A Markov-Switching Bayesian Vector Error Correction Model." In Lecture Notes in Computer Science, 415–27. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25135-6_38.

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Kuiper, Erno W., and Matthew T. G. Meulenberg. "A Structural Vector Error-Correction Model of Price Time Series to Detect Bottleneck Stages within a Marketing Channel." In Contributions to Economics, 129–41. Heidelberg: Physica-Verlag HD, 1999. http://dx.doi.org/10.1007/978-3-642-48765-1_8.

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Ao, Zou. "Dynamic Impacts of Social Expectation and Macroeconomic Factor on Shanghai Stock Market: An Application of Vector Error Correction Model." In Springer Proceedings in Mathematics & Statistics, 489–96. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08377-3_47.

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Dghais, Amel Abdoullah, and Mohd Tahir Ismail. "Modeling Relationship Between Stock Market of UK and MENA Countries: A Wavelet Transform and Markov Switching Vector Error Correction Model Approach." In Proceedings of the International Conference on Computing, Mathematics and Statistics (iCMS 2015), 165–73. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2772-7_17.

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Ozer, Mustafa, and A. Erinç Yeldan. "The Relationship between Current Account Deficits and Unemployment in Turkey." In Handbook of Research on Comparative Economic Development Perspectives on Europe and the MENA Region, 492–510. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9548-1.ch020.

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In this chapter, we test the nature of the variety of empirical relationships between current account deficits and unemployment in Turkey over 2000Q1–2012Q1. Our working hypothesis in this paper is that the meager job creation in Turkey over 2000s is the direct symptom of a speculative-led growth environment (Grabel, 1995) together with an excessively open and unregulated capital account in the age of relatively cheap and abundant global finance. Based on the vector error correction model (VECM), we found that there is a unidirectional causality running from current account deficits to unemployment. Both Impulse Response and Variance Decomposition analyses are quite consistent with results of VECM. We interpret these findings as evidence of the structural characteristics of unemployment, reflected in output elasticities, being embedded under the deepening external fragility of the Turkish economy over the 2000s.

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Naser, Hanan. "The Economic and Environmental Impact of Large Financial Developments in an Oil-Dependent Economy." In Handbook of Research on Creating Sustainable Value in the Global Economy, 221–40. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1196-1.ch013.

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This study examines the economic and environmental impact of large financial developments in Bahrain from year 2006 to 2016. To do so, the relationship between energy consumption, oil prices, market shares, dividend yields, and economic growth has been investigated using Vector Error Correction Model (VECM). The key findings are summarized as follow: (1) Long run relationship exists between the suggested variables. (2) Both energy and financial markets are significant in the long run relationship, and positively affect the economic growth of Bahrain. (3) According to the estimated ECM term, the model is stable in the short run. (4) Decline in oil price has negative significant drawback on the economic growth of Bahrain. Accordingly, it is recommended that policy makers in Bahrain focuses on implement strong strategies that aim at encouraging investments in non-oil sectors without impeding energy sector or economic growth in order to move towards sustainability.

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Conference papers on the topic "Vector error correction model (VEC model)"

1

Xiong Jiping and Wu Ping. "An Analysis of Forecasting Model of Crude Oil Demand Based on Cointegration and Vector Error Correction Model (VEC)." In 2008 International Seminar on Business and Information Management (ISBIM 2008). IEEE, 2008. http://dx.doi.org/10.1109/isbim.2008.97.

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Lestari, Reni. "Analysis of Stock Market Integration Among ASEAN Countries by Using Vector Error Correction Model (VECM) Approach." In Japan International Business and Management Research Conference. RSF Press & RESEARCH SYNERGY FOUNDATION, 2020. http://dx.doi.org/10.31098/jibm.v1i1.220.

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Globalization has driven the economy of countries to relate to each other. It brings relationships in the capital among countries in the world, especially in ASEAN region countries. This study aimed to analyze the integration of the stock market among countries in the ASEAN region. The stock market was analyzed are the Indonesia Stock Exchange, Malaysia Stock Exchange, Singapore Stock Exchange, Thailand Stock Exchange, Vietnam Stock Exchange, and Philippine Stock Exchange. This study using the Vector Error Correction Model (VECM) as the method. The result of this study shows that, in the long term Singapore Stock Index (STI), Malaysia Stock Index (KLSE), Philippines (PSEi), and Indonesia Stock Index (JKSE) are positively correlated. This means the change of stock index price in one country will affect other related countries in the long term. In the short term of VECM estimation, found the Vietnam Stock Index (VNI), Singapore Stock Exchange (STI), Philippine (PSEi) are positively correlated and negatively correlated with Thailand Stock Exchange (SET). For the managerial implication, the result of this study is expected as a reference or basis of consideration of investment decisions. This because long-term stock market movements are important because they impact international portfolio management and risk diversification.

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Suharsono, Agus, Auliya Aziza, and Wara Pramesti. "Comparison of vector autoregressive (VAR) and vector error correction models (VECM) for index of ASEAN stock price." In INTERNATIONAL CONFERENCE AND WORKSHOP ON MATHEMATICAL ANALYSIS AND ITS APPLICATIONS (ICWOMAA 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.5016666.

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Zhao, Ziping, and Daniel P. Palomar. "Robust maximum likelihood estimation of sparse vector error correction model." In 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2017. http://dx.doi.org/10.1109/globalsip.2017.8309093.

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Arce, Paola, Jonathan Antognini, Werner Kristjanpoller, and Luis Salinas. "An Online Vector Error Correction Model for Exchange Rates Forecasting." In International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005205901930200.

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Karn, Arodh Lal, and Rakshha Kumari Karna. "Supply line engineering on importation and exportation: bimstec perspective." In Contemporary Issues in Business, Management and Economics Engineering. Vilnius Gediminas Technical University, 2019. http://dx.doi.org/10.3846/cibmee.2019.016.

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Purpose – the purpose of this paper is to investigate whether supply line engineering strategies of goods and service exports, exports transport services and export time have a significant impact on GDP growth of BIMSTEC countries or not. Research methodology – the study employed a panel vector error correction model (VECM) instead of loose VAR to examine the short and long-run relationship among the selected indicators and GDP growth. Findings – in the long-run, the time of export negatively and suggestively associate with GDP. Conversely, VECM based Granger causality test signposted that in short-run only unidirectional causality running from goods and service exports (GSE), trade duration like exports time (ET) toward GDP and for the rest of the variables no causality found. Research limitations – this study is contextualized only on Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand. Practical implications – to investigate the current position of the link between supply line logistics strategies and economic growth by using annual data for the period of 1980 to 2014 and possible weaknesses and logistics presence. Originality/Value – this paper is an attempt, first of its kind, to fill up this shortfall, to estimate the relationship of exports transport services, exports time, and goods and services exports with GDP growth of BIMSTEC countries.

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Algan, Neşe, Başak Gül Aktakas, and İpek Tekin. "The Relationship between Corruption and Economic Growth as a Social Issue: A Case Study on Turkey." In International Conference on Eurasian Economies. Eurasian Economists Association, 2014. http://dx.doi.org/10.36880/c05.00996.

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The present study aims to investigate the relationship between corruption and economic growth by taking the driving force of education into account. A significant contribution of the education level to the reduction process of corruption is expected to occur. For this reason, the number of those who are convicted of corruption offenses depending on their educational status for Turkey are to be taken into account, whereas the effect of education being a separate variable on growth and corruption will not be considered. In this regard, Vector Error Correction (VECM) model will be used as a method for the years between 1980-2011 and the relationship between corruption and economic growth will be analyzed. The contribution of the study to the literature is to reveal the impact of those who cause corruption depending on their education level on growth by undertaking the education levels separately. According to the empirical findings, considering corruption convicts who are literate but not graduated from a school and those having graduated from primary and secondary education, it was observed that corruption affects growth in a negative way. In contrast, given the corruption crimes which were committed by the graduates of both high school and vocational school at high school level and higher education, it was determined that there is a positive relationship between corruption and economic growth.

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Kong, Feng, and Xiaojuan Wu. "Time Series Forecasting Model with Error Correction by Structure Adaptive Support Vector Machine." In 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.88.

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Baniya, Jeevan. "Linkages between Real Sector and Financial Sector in Nepal: A Vector Error Correction Model." In 5th International Conference on New Ideas in Management, Economics and Accounting. Acavent, 2018. http://dx.doi.org/10.33422/5imea.2018.02.57.

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Chengli Zheng and Ting He. "Investor sentiment and stock index: A test of causality based on vector error correction model." In 2010 2nd International Conference on Information Science and Engineering (ICISE). IEEE, 2010. http://dx.doi.org/10.1109/icise.2010.5690893.

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Reports on the topic "Vector error correction model (VEC model)"

1

Hoffman, Dennis, and Robert H. Rasche. STLS/US-VECM 6.1: A Vector Error-Correction Forecasting Model of the US Economy. Federal Reserve Bank of St. Louis, 1997. http://dx.doi.org/10.20955/wp.1997.008.

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Anderson, Richard G., Dennis Hoffman, and Robert H. Rasche. A Vector Error-Correction Forecasting Model of the U.S. Economy. Federal Reserve Bank of St. Louis, 1998. http://dx.doi.org/10.20955/wp.1998.008.

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