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Full-Text Articles in Business
Historical Perspectives In Volatility Forecasting Methods With Machine Learning, Zhiang Qiu, Clemens Kownatzki, Fabien Scalzo, Eun Sang Cha
Historical Perspectives In Volatility Forecasting Methods With Machine Learning, Zhiang Qiu, Clemens Kownatzki, Fabien Scalzo, Eun Sang Cha
Seaver College Research And Scholarly Achievement Symposium
Volatility forecasting in the financial market plays a pivotal role across a spectrum of disciplines, such as risk management, option pricing, and market making. However, volatility forecasting is challenging because volatility can only be estimated, and different factors influence volatility, ranging from macroeconomic indicators to investor sentiments. While recent works suggest advances in machine learning and artificial intelligence for volatility forecasting, a comprehensive benchmark of current statistical and learning-based methods for such purposes is lacking. Thus, this paper aims to provide a comprehensive survey of the historical evolution of volatility forecasting with a comparative benchmark of key landmark models. We …
Reactions Of Stock Market To Monetary Policy Shocks During The Global Financial Crisis: The Nigerian Case, Aliyu Shehu U.R.
Reactions Of Stock Market To Monetary Policy Shocks During The Global Financial Crisis: The Nigerian Case, Aliyu Shehu U.R.
CBN Journal of Applied Statistics (JAS)
This paper seeks to assess the reactions of Nigeria’s stock market to monetary policy innovations during the period of global financial crisis on the basis of monthly data over the period January, 2007 to August, 2011. In particular, stock market return was regressed against major monetary policy instruments; money stock (M1, and M2) and monetary policy rate (MPR). The theoretical basis for the paper stems from the works of new classical macroeconomics and rational expectation hypothesis (REH). Lucas (1972) postulated that only the unanticipated monetary shock influences real economic activity. Using the GARCH by developed Engle and Bollerslev (1986) and …
Data Driven Value-At-Risk Forecasting Using A Svr-Garch-Kde Hybrid, Marius Lux, Wolfgang Karl Hardle, Stefan Lessmann
Data Driven Value-At-Risk Forecasting Using A Svr-Garch-Kde Hybrid, Marius Lux, Wolfgang Karl Hardle, Stefan Lessmann
Sim Kee Boon Institute for Financial Economics
Appropriate risk management is crucial to ensure the competitiveness of financial institutions and the stability of the economy. One widely used financial risk measure is value-at-risk (VaR). VaR estimates based on linear and parametric models can lead to biased results or even underestimation of risk due to time varying volatility, skewness and leptokurtosis of financial return series. The paper proposes a nonlinear and nonparametric framework to forecast VaR that is motivated by overcoming the disadvantages of parametric models with a purely data driven approach. Mean and volatility are modeled via support vector regression (SVR) where the volatility model is motivated …
Is Google Search Behavior Related To Volatility? Incorporating Google Trends Data Into A Garch Model For Equity Volatility, Timothy De Silva
Is Google Search Behavior Related To Volatility? Incorporating Google Trends Data Into A Garch Model For Equity Volatility, Timothy De Silva
Undergraduate Economic Review
Intuitively, one would expect that internet search volume would contain valuable information about investor sentiment for a company. With the development of new data sources, such as Google Trends, this relationship can be more easily and objectively examined. This paper seeks to examine the relationship between a company’s stock price volatility and its Google search volume. A small cross-section of twenty companies is considered, and the goal of this paper is to demonstrate the power of Google Trends data in hope of initiating further research. Using a conventional GARCH framework for financial market volatility, an economically and statistically significant contemporaneous …
Day-Of-The-Week Anomaly: An Illusion Or A Reality? Evidence From Naira/Dollar Exchange Rates, Osarumwense Osabuohien-Irabor
Day-Of-The-Week Anomaly: An Illusion Or A Reality? Evidence From Naira/Dollar Exchange Rates, Osarumwense Osabuohien-Irabor
CBN Journal of Applied Statistics (JAS)
This study examines the day-of-the-week effect in the Nigerian foreign exchange market (Naira against the US dollars), its volatility as well as the asymmetric effects, for the period of 12th May 2009 to 12th June, 2015. The empirical results of GARCH-t(1,1), EGARCH-t(1,1), GJR-GARCH-t(1,1), IGARCH and the OLS methodology shows that the detection of the day-of-the-week effect is influenced by the choice of the volatility model applied. Similarly, the highest or lowest volatility market day goes with the influence of these models. Thus this study clearly support the argument of Charles (2010), that, the days of the week anomalies lies on …
Testing Volatility In Nigeria Stock Market Using Garch Models, Ngozi V. Atoi
Testing Volatility In Nigeria Stock Market Using Garch Models, Ngozi V. Atoi
CBN Journal of Applied Statistics (JAS)
The contributions of error distributions have been ignored while modeling stock market volatility in Nigeria and studies have shown that the application of appropriate error distribution in volatility model enhances efficiency of the model. Using Nigeria All Share Index from January 2, 2008 to February 11, 2013, this study estimates first order symmetric and asymmetric volatility models each in Normal, Student’s-t and generalized error distributions with the view to selecting the best forecasting volatility model with the most appropriate error distribution. The results suggest the presence of leverage effect meaning that volatility responds more to bad news than it does …
A Closer Look At The Impact Of Quantitative Easing On The Capital Markets: Garch Analysis Of The Exchange Traded Funds Market, Nicholas R. Duafala
A Closer Look At The Impact Of Quantitative Easing On The Capital Markets: Garch Analysis Of The Exchange Traded Funds Market, Nicholas R. Duafala
Undergraduate Economic Review
This paper analyzes the effects of quantitative easing (QE) on the capital markets by modeling exchange traded funds (ETFs) returns using a generalized autoregressive conditional heteroskedasticity (GARCH) methodology. The results show that the 10-Year Treasury yields are significant in the returns of some sectors of the economy more so than others, and the Federal Funds Futures trading volume is significant in all ETFs return volatility. The implications of these results not only provide information about the reaction of the ETF market and QE, but also provide insight for developing investment strategies.
Exchange–Rates Volatility In Nigeria: Application Of Garch Models With Exogenous Break, Bala A. Dahiru, Joseph O. Asemota
Exchange–Rates Volatility In Nigeria: Application Of Garch Models With Exogenous Break, Bala A. Dahiru, Joseph O. Asemota
CBN Journal of Applied Statistics (JAS)
This paper examines exchange–rate volatility with GARCH models using monthly exchange–rate return series from 1985:1 to 2011:7 for Naira/US dollar return and from 2004:1 to 2011:7 for Naira/British Pounds and Naira/Euro returns. The study compare estimates of variants of GARCH models with break in respect of the US dollar rates with exogenously determined break points. Our results reveal presence of volatility in the three currencies and equally indicate that most of the asymmetric models rejected the existence of a leverage effect except for models with volatility break. Evaluating the models through standard information criteria, volatility persistence and the log likelihood …
Realized Daily Variance Of S&P 500 Cash Index: A Revaluation Of Stylized Facts, Shirley Huang, Qianqiu Liu, Jun Yu
Realized Daily Variance Of S&P 500 Cash Index: A Revaluation Of Stylized Facts, Shirley Huang, Qianqiu Liu, Jun Yu
Research Collection School Of Economics
In this paper the realized daily variance is obtained from intraday transaction prices of the S&P 500 cash index over the period from January 1993 to December 2004. When constructing realized daily variance, market microstructure noise is taken into account using a technique proposed by Zhang, Mykland and Ait-Sahalia (2005). The time series properties of realized daily variance are compared with those of variance estimates obtained from parametric GARCH and stochastic volatility models. Unconditional and dynamic properties concerning the realized daily variance are examined, the relationship between realized variance and returns is investigated, and the stylized facts concerning realized daily …