This study examines the impact of fundamental factors on stock price of Nepalese commercial banks. Return on assets, return on equity, net profit margin, earning per share and dividend per share are the independent variables. And market price per share and change in market price per share are the dependent variables. Data are collected from the Banking and Financial Statistics and Bank Supervision Report published by Nepal Rastra Bank and annual reports of the selected commercial banks. The study is based on 13 commercial banks of Nepal from 2007 to 2014, leading to a total of 104 observations. The regression models are estimated to test the significance and impact of fundamental factors in stock price of Nepalese commercial banks. The result shows that dividend per share (DPS), return on assets (ROA) and earning per share (EPS) are positively related to the stock price (market price per share and change in market price per share). This indicates that higher the DPS, ROA and EPS, higher would be the stock price. However, net profit margin is negatively related to stock price. The regression result shows that the beta coefficients for DPS and EPS are positively significant with market price per share at 5 percent level of significance.
{"title":"Impact of Fundamental Factors on Stock Price: A Case of Nepalese Commercial Banks","authors":"Prof. Dr. Radhe Shyam Pradhan, L. Paudel","doi":"10.2139/ssrn.3044108","DOIUrl":"https://doi.org/10.2139/ssrn.3044108","url":null,"abstract":"This study examines the impact of fundamental factors on stock price of Nepalese commercial banks. Return on assets, return on equity, net profit margin, earning per share and dividend per share are the independent variables. And market price per share and change in market price per share are the dependent variables. Data are collected from the Banking and Financial Statistics and Bank Supervision Report published by Nepal Rastra Bank and annual reports of the selected commercial banks. \u0000The study is based on 13 commercial banks of Nepal from 2007 to 2014, leading to a total of 104 observations. The regression models are estimated to test the significance and impact of fundamental factors in stock price of Nepalese commercial banks. The result shows that dividend per share (DPS), return on assets (ROA) and earning per share (EPS) are positively related to the stock price (market price per share and change in market price per share). This indicates that higher the DPS, ROA and EPS, higher would be the stock price. However, net profit margin is negatively related to stock price. The regression result shows that the beta coefficients for DPS and EPS are positively significant with market price per share at 5 percent level of significance.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115179053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tjeerd M. Boonman, J. Jacobs, G. Kuper, Alberto Romero
This paper investigates the performance of early warning systems in real-time, using forecasts of indicators that were available at the moment predictions are to be made. The study analyzes currency crises in eight Latin American and Central and Eastern European countries, distinguishing an estimation period 1990-2009 and a prediction period 2010-2014. We apply two varieties of early warning systems: the signal approach and the logit models. For both methods we find that using forecasts of the indicators worsens the predictive ability of early warning systems compared to using the most recently available information (ex post).
{"title":"Early Warning Systems with Real-Time Data","authors":"Tjeerd M. Boonman, J. Jacobs, G. Kuper, Alberto Romero","doi":"10.2139/ssrn.3067757","DOIUrl":"https://doi.org/10.2139/ssrn.3067757","url":null,"abstract":"This paper investigates the performance of early warning systems in real-time, using forecasts of indicators that were available at the moment predictions are to be made. The study analyzes currency crises in eight Latin American and Central and Eastern European countries, distinguishing an estimation period 1990-2009 and a prediction period 2010-2014. We apply two varieties of early warning systems: the signal approach and the logit models. For both methods we find that using forecasts of the indicators worsens the predictive ability of early warning systems compared to using the most recently available information (ex post).","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127332529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-22DOI: 10.16980/JITC.13.4.201708.139
Rongyuan Qin, Ji-hun Heo
This empirical study examines the short-run lead-lag relationship between the VKOSPI index futures and its underlying spot index and KOSPI index using daily data from September 17, 2014 to May 2017. We used the unit root test, Johansen-Juselius cointegration test, Granger causality analysis, impulse response function analysis, and variance decomposition analysis to test the hypothesis that the futures market with no market frictions leads the spot market in this analysis. The results of these analyses using level variables show that there is a bi-directional lead-lag relationship between the VKOSPI futures and VKOSPI index, but in the analysis using first-difference variables, there is only a unidirectional lead-lag relationship form VKOSPI index to VKOSPI futures. This means that the VKOSPI spot market is more efficient than the futures market. Also, there are no lead-lag relationship from VKOSPI futures or VKOSPI index to KOSPI index. It is inconsistent with the main expected hypothesis in our study and the conclusions of previous studies which argue that the VIX futures lead the VIX index and S&P 500 index. This results are related to a lack of liquidity of VKOSPI futures contracts in the Korean derivatives market. Because generally, the Korean institutional investors prefer option trading, to hedge market risk rather than VKOSPI futures. Change in the price of the option will result in the change in the VKOSPI index and subsequently the mechanism that alters the VKOSPI futures or the KOSPI index.
{"title":"The Lead-Lag Relationship between Volatility Index Futures and Spot in the Korean Stock Market","authors":"Rongyuan Qin, Ji-hun Heo","doi":"10.16980/JITC.13.4.201708.139","DOIUrl":"https://doi.org/10.16980/JITC.13.4.201708.139","url":null,"abstract":"This empirical study examines the short-run lead-lag relationship between the VKOSPI index futures and its underlying spot index and KOSPI index using daily data from September 17, 2014 to May 2017. We used the unit root test, Johansen-Juselius cointegration test, Granger causality analysis, impulse response function analysis, and variance decomposition analysis to test the hypothesis that the futures market with no market frictions leads the spot market in this analysis. The results of these analyses using level variables show that there is a bi-directional lead-lag relationship between the VKOSPI futures and VKOSPI index, but in the analysis using first-difference variables, there is only a unidirectional lead-lag relationship form VKOSPI index to VKOSPI futures. This means that the VKOSPI spot market is more efficient than the futures market. Also, there are no lead-lag relationship from VKOSPI futures or VKOSPI index to KOSPI index. It is inconsistent with the main expected hypothesis in our study and the conclusions of previous studies which argue that the VIX futures lead the VIX index and S&P 500 index. This results are related to a lack of liquidity of VKOSPI futures contracts in the Korean derivatives market. Because generally, the Korean institutional investors prefer option trading, to hedge market risk rather than VKOSPI futures. Change in the price of the option will result in the change in the VKOSPI index and subsequently the mechanism that alters the VKOSPI futures or the KOSPI index.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128561073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This paper aims to answer how effective the loan-to-value (LTV) regulation has been since 2011 for conventional and Islamic (participation) banks in Turkey in terms of curbing mortgage loan growth and delinquency[1]. Design/methodology/approach The authors first use unit root tests and tests of difference in loan and property price data in pre-LTV and post-LTV period. Second, the authors follow Chow test and ordinary least squares regression analyses to test for a structural break when sensitivity of mortgage loan and delinquency growth changes to property price changes considered. Findings The authors find that two periods are statistically different, while the significance level is lower for Islamic banks. Moreover, loan growth has become less responsive to property price increases; delinquency sensitivity to property price changes has significantly increased in the post-LTV period for conventional banks, while this is not the case for Islamic (participation) banks. Originality/value This paper not only increases empirical evidence regarding the effectiveness of LTV ratio policy but also fills the gap in the literature by providing a comparison between conventional banks and Islamic (participation) banks.
{"title":"Loan-to-Value Policy: Evidence from Turkish Dual Banking System","authors":"Burak Pirgaip, Ali Hepşen","doi":"10.2139/ssrn.3022886","DOIUrl":"https://doi.org/10.2139/ssrn.3022886","url":null,"abstract":"\u0000Purpose\u0000This paper aims to answer how effective the loan-to-value (LTV) regulation has been since 2011 for conventional and Islamic (participation) banks in Turkey in terms of curbing mortgage loan growth and delinquency[1].\u0000\u0000\u0000Design/methodology/approach\u0000The authors first use unit root tests and tests of difference in loan and property price data in pre-LTV and post-LTV period. Second, the authors follow Chow test and ordinary least squares regression analyses to test for a structural break when sensitivity of mortgage loan and delinquency growth changes to property price changes considered.\u0000\u0000\u0000Findings\u0000The authors find that two periods are statistically different, while the significance level is lower for Islamic banks. Moreover, loan growth has become less responsive to property price increases; delinquency sensitivity to property price changes has significantly increased in the post-LTV period for conventional banks, while this is not the case for Islamic (participation) banks.\u0000\u0000\u0000Originality/value\u0000This paper not only increases empirical evidence regarding the effectiveness of LTV ratio policy but also fills the gap in the literature by providing a comparison between conventional banks and Islamic (participation) banks.\u0000","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124727463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Chinese stock market is unique in which it is moved more by individual retail investors than institutional investors. Therefore, for economic and political stability it is more important to efficiently manage the risk of the Chinese stock market. We investigate its volatility dynamics through the GARCH model with three types of heavy-tailed distributions, the Student’s t, the NIG and the NRIG distributions. Our results show that estimated parameters for all the three types of distributions are statistical significant and the NIG distribution has the best empirical performance in fitting the Chinese stock market index returns.
{"title":"GARCH Model, Heavy Tails and the Chinese Stock Market Returns","authors":"Michael Day, Mark Diamond","doi":"10.2139/ssrn.3018940","DOIUrl":"https://doi.org/10.2139/ssrn.3018940","url":null,"abstract":"The Chinese stock market is unique in which it is moved more by individual retail investors than institutional investors. Therefore, for economic and political stability it is more important to efficiently manage the risk of the Chinese stock market. We investigate its volatility dynamics through the GARCH model with three types of heavy-tailed distributions, the Student’s t, the NIG and the NRIG distributions. Our results show that estimated parameters for all the three types of distributions are statistical significant and the NIG distribution has the best empirical performance in fitting the Chinese stock market index returns.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"324 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116299908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As other developed economies over the world, the stock market plays a crucial role in facilitating the economic growth. In this paper, we compare two different types of heavy-tailed distribution, the Student’s t distribution and the normal reciprocal inverse Gaussian distribution, within the generalized autoregressive conditional heteroskedasticity (GARCH) framework for the daily stock market returns of South Korea (KOSPI). Our results show two important findings: i) the daily KOSPI returns exhibit conditional heavy tails even after volatility clustering effect has been accounted for; and ii) the NRIG distribution has a better in-sample performance than the Student’s t distribution.
{"title":"Heavy-Tailed Distributions, GARCH Model and the Stock Market Returns in South Korea","authors":"Yoon Hong, Ji-chul Lee, Guoping Ding","doi":"10.2139/ssrn.3014472","DOIUrl":"https://doi.org/10.2139/ssrn.3014472","url":null,"abstract":"As other developed economies over the world, the stock market plays a crucial role in facilitating the economic growth. In this paper, we compare two different types of heavy-tailed distribution, the Student’s t distribution and the normal reciprocal inverse Gaussian distribution, within the generalized autoregressive conditional heteroskedasticity (GARCH) framework for the daily stock market returns of South Korea (KOSPI). Our results show two important findings: i) the daily KOSPI returns exhibit conditional heavy tails even after volatility clustering effect has been accounted for; and ii) the NRIG distribution has a better in-sample performance than the Student’s t distribution.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122276616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study we model the monthly and the daily US, Euro Zone, UK and Australian exchange rates in India using the symmetric (sGARCH) and the asymmetric (GJR-GARCH and EGARCH) volatility models with the normal, the student t and the skewed student t error distributions. We also investigate the effect of the net US dollars (USD) purchase/ sale by the central bank, the net foreign institutional investor (FII) inflows and the one month forward spot differential on the monthly US exchange rate. Furthermore, we also test the presence of the calendar effect such as the monthly effect and the day-of-week effect on these exchange rates. We find that the models with the normal error distribution tend to fit the monthly log returns of the exchange rates better than those with the non-normal error distribution and the converse is true for the daily log returns. The calendar effects in the mean model are pronounced and Fridays on an average witness an appreciation of the Indian rupee against all the currencies we tested. Month of August has significant impact on the US exchange rate and June on the other three exchange rates. The leverage effect is not pronounced in all the exchange rates. The EGARCH models with the calendar effect dummies in the volatility model are not parsimonious. The net purchase/ sale of USD in a given month by the central bank and the one month forward spot differential do not have any significant impact on the monthly US exchange rate. But the net inflow of USD from foreign institutional investors leads to an appreciation of Indian rupee against USD. Thus the concern that capital inflows, especially the easily repatriable ones, could appreciate the Indian rupee seems to be correct but the net purchase/ sale of USD by the RBI does not seem to be abating the impact.
{"title":"Asymmetric and Symmetric Volatility Models for Exchange Rates in India – The Impact of the Net Purchase of US Dollars by the Central Bank and Net Inflows by Foreign Institutional Investors","authors":"Anand Shah, Anupam Bahri","doi":"10.2139/ssrn.2918848","DOIUrl":"https://doi.org/10.2139/ssrn.2918848","url":null,"abstract":"In this study we model the monthly and the daily US, Euro Zone, UK and Australian exchange rates in India using the symmetric (sGARCH) and the asymmetric (GJR-GARCH and EGARCH) volatility models with the normal, the student t and the skewed student t error distributions. We also investigate the effect of the net US dollars (USD) purchase/ sale by the central bank, the net foreign institutional investor (FII) inflows and the one month forward spot differential on the monthly US exchange rate. Furthermore, we also test the presence of the calendar effect such as the monthly effect and the day-of-week effect on these exchange rates. We find that the models with the normal error distribution tend to fit the monthly log returns of the exchange rates better than those with the non-normal error distribution and the converse is true for the daily log returns. The calendar effects in the mean model are pronounced and Fridays on an average witness an appreciation of the Indian rupee against all the currencies we tested. Month of August has significant impact on the US exchange rate and June on the other three exchange rates. The leverage effect is not pronounced in all the exchange rates. The EGARCH models with the calendar effect dummies in the volatility model are not parsimonious. The net purchase/ sale of USD in a given month by the central bank and the one month forward spot differential do not have any significant impact on the monthly US exchange rate. But the net inflow of USD from foreign institutional investors leads to an appreciation of Indian rupee against USD. Thus the concern that capital inflows, especially the easily repatriable ones, could appreciate the Indian rupee seems to be correct but the net purchase/ sale of USD by the RBI does not seem to be abating the impact.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124715324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper sought to test An interest rate commission agent banking model’s viability and reliability. An interest rate commission agent banking system (AIRCABS) increased the investor loan funding agent bank’s profitability and sustainability by shifting credit risk and liquidity crunch to investors and entrepreneurs. The bank increases stable deposit by applying discrete market deposit interest rate incentive into depositors’ accounts and by letting depositors latter to shift to investor position having the bank as an agent to collect proportionate credit price instead of deposit interest rate on the portion of the fund the bank has already invested. Therefore, an interest rate commission agent bank found viable and reliable.
{"title":"An Improvement on an Interest Rate Commission Agent Banking System Model (AIRCABS)","authors":"Ameha Tefera Tessema, J. Kruger","doi":"10.2139/ssrn.3007592","DOIUrl":"https://doi.org/10.2139/ssrn.3007592","url":null,"abstract":"This paper sought to test An interest rate commission agent banking model’s viability and reliability. An interest rate commission agent banking system (AIRCABS) increased the investor loan funding agent bank’s profitability and sustainability by shifting credit risk and liquidity crunch to investors and entrepreneurs. The bank increases stable deposit by applying discrete market deposit interest rate incentive into depositors’ accounts and by letting depositors latter to shift to investor position having the bank as an agent to collect proportionate credit price instead of deposit interest rate on the portion of the fund the bank has already invested. Therefore, an interest rate commission agent bank found viable and reliable.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"6 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126331954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, earnings management has become one of the most widely used and influential phenomena and issues in the financial accounting circles. Several scholars, extensive research and diversity in this regard and have achieved an important result. Considering the importance of taking into account discretionary accruals and earnings management, we actually try to have a stake in this section of the paper. The research to explain about earnings management and capital costs and the relationship of these two firms listed in the Tehran Stock Exchange (Case study: the pharmaceutical industry, petrochemical and cement). Specifically, we aim to identify the characteristics of firms that knowingly manipulated to act in profit, profit management. The sample included 95 companies listed on the Tehran Stock Exchange (Consisting of 46 companies in pharmaceuticals, petrochemicals and cement), for a period of 5 years from 1389 to 1393. The findings showed regardless of the selected sample of target industries and all companies (95 companies) and direct correlation between earnings management and capital cost there. On the other hand complementary studies showing significant difference was observed between different industries.
{"title":"Comparative Evaluation of Earnings Management and the Cost of Capital in Tehran Stock Exchange (Case Study: The Pharmaceutical Industry, Petrochemical and Cement)","authors":"I. Noravesh, amin panahandeh","doi":"10.2139/ssrn.3004626","DOIUrl":"https://doi.org/10.2139/ssrn.3004626","url":null,"abstract":"Nowadays, earnings management has become one of the most widely used and influential phenomena and issues in the financial accounting circles. Several scholars, extensive research and diversity in this regard and have achieved an important result. Considering the importance of taking into account discretionary accruals and earnings management, we actually try to have a stake in this section of the paper. The research to explain about earnings management and capital costs and the relationship of these two firms listed in the Tehran Stock Exchange (Case study: the pharmaceutical industry, petrochemical and cement). Specifically, we aim to identify the characteristics of firms that knowingly manipulated to act in profit, profit management. The sample included 95 companies listed on the Tehran Stock Exchange (Consisting of 46 companies in pharmaceuticals, petrochemicals and cement), for a period of 5 years from 1389 to 1393. The findings showed regardless of the selected sample of target industries and all companies (95 companies) and direct correlation between earnings management and capital cost there. On the other hand complementary studies showing significant difference was observed between different industries.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130376421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Philippine stock market is now the most expensive stock market in the Southeast Asia region. As of July 10, 2017, the total market capitalization is about 101 percent of the gross domestic product (GDP). Normally, the ratio between 75 percent and 90 percent is considered fairly valued. Thus, a risk management tool, which can quantitatively estimate the potential odds of a financial crisis, would be particularly useful for market participants. In this paper, we showed the Skewed t distribution could provide best goodness-of-fit for the Philippine stock market returns compared with several other widely used statistical distributions. The scenarios generated by the Skewed t distribution would be valuable for further risk analysis of the stock market.
{"title":"A Quantitative Risk Management Tool for the Equity Market in Philippines","authors":"R. Alba, Yi-Tai Chiu, Ruiyue Lin","doi":"10.2139/ssrn.3013838","DOIUrl":"https://doi.org/10.2139/ssrn.3013838","url":null,"abstract":"The Philippine stock market is now the most expensive stock market in the Southeast Asia region. As of July 10, 2017, the total market capitalization is about 101 percent of the gross domestic product (GDP). Normally, the ratio between 75 percent and 90 percent is considered fairly valued. Thus, a risk management tool, which can quantitatively estimate the potential odds of a financial crisis, would be particularly useful for market participants. In this paper, we showed the Skewed t distribution could provide best goodness-of-fit for the Philippine stock market returns compared with several other widely used statistical distributions. The scenarios generated by the Skewed t distribution would be valuable for further risk analysis of the stock market.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134336568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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