This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models:sGARCH,girGARCH,eGARCH,iGARCH,aGARCH,TGARCH,NGARCH,NAGARCH,and AVGARCH along with value at risk e...This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models:sGARCH,girGARCH,eGARCH,iGARCH,aGARCH,TGARCH,NGARCH,NAGARCH,and AVGARCH along with value at risk estimation and backtesting.We use daily data for Total Nigeria Plc returns for the period January 2,2001 to May 8,2017,and conclude that eGARCH and sGARCH perform better for normal innovations while NGARCH performs better for student t innovations.This investigation of the volatility,VaR,and backtesting of the daily stock price of Total Nigeria Plc is important as most previous studies covering the Nigerian stock market have not paid much attention to the application of backtesting as a primary approach.We found from the results of the estimations that the persistence of the GARCH models are stable except for few cases for which iGARCH and eGARCH were unstable.Additionally,for student t innovation,the sGARCH and girGARCH models failed to converge;the mean reverting number of days for returns differed from model to model.From the analysis of VaR and its backtesting,this study recommends shareholders and investors continue their business with Total Nigeria Plc because possible losses may be overcome in the future by improvements in stock prices.Furthermore,risk was reflected by significant up and down movement in the stock price at a 99%confidence level,suggesting that high risk brings a high return.展开更多
This work presents the complexity that emerges in a Bertrand duopoly between two companies in the Greek oil market, one of which is semi-public and the other is private. The game uses linear demand functions for diffe...This work presents the complexity that emerges in a Bertrand duopoly between two companies in the Greek oil market, one of which is semi-public and the other is private. The game uses linear demand functions for differentiated products from the existing literature and asymmetric cost functions that arose after approaches using the published financial reports of the two oil companies (Hellenic Petroleum and Motor Oil). The game is based on the assumption of homogeneous players who are characterized by bounded rationality and follow an adjustment mechanism. The players’ decisions for each time period are expressed by two difference equations. A dynamical analysis of the game’s discrete dynamical system is made by finding the equilibrium positions and studying their stability. Numerical simulations include bifurcation diagrams and strange attractors. Lyapunov numbers’ graphs and sensitivity analysis in initial conditions prove the algebraic results and reveal the complexity and chaotic behavior of the system focusing on the two parameters k<sub>1</sub> and k<sub>2</sub> (speed of adjustment for each player). The d-Backtest method is applied through which an attempt is made to control the chaos that appears outside the stability space in order to return to the locally asymptotically stable Nash equilibrium for the system.展开更多
This research investigates token dormancy as a fundamental metric for evaluating cryptocurrency assets and presents a methodology for its measurement.The valuation method involves 4 distinct parameters and utilizes a ...This research investigates token dormancy as a fundamental metric for evaluating cryptocurrency assets and presents a methodology for its measurement.The valuation method involves 4 distinct parameters and utilizes a 3.5-year daily dataset for the“Chainlink”token.The results are used in optimized ARIMA-GARCH models to analyze the first differences between the variables;the out-of-sample forecasts were assessed with performance metrics.Furthermore,this study introduces a novel fundamental value derived from these approaches,the basis for generating selling signals in a backtested trading strategy.The trading strategy results are compared to a benchmark buy-and-hold strategy and a non-selling dollar-cost-averaging strategy for evaluation.Employing the dollar-cost averaging approach for purchase frequency and utilizing the“isolation forest”technique for identifying selling signals within the trading strategy yielded positive results.展开更多
VaR(Value at Risk)是商业银行市场风险管理的重要方法。本文提出了一种基于组合权重伪似然函数的VaR半参数估计方法,选取股票市场数据进行实证分析,并依据新资本协议对市场风险内部模型法的要求及其它VaR检验准则检验了模型结果。结果...VaR(Value at Risk)是商业银行市场风险管理的重要方法。本文提出了一种基于组合权重伪似然函数的VaR半参数估计方法,选取股票市场数据进行实证分析,并依据新资本协议对市场风险内部模型法的要求及其它VaR检验准则检验了模型结果。结果表明,相对常用VaR模型及改进之前的模型,此方法在多种检验标准下都具有明显优势。展开更多
文摘This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models:sGARCH,girGARCH,eGARCH,iGARCH,aGARCH,TGARCH,NGARCH,NAGARCH,and AVGARCH along with value at risk estimation and backtesting.We use daily data for Total Nigeria Plc returns for the period January 2,2001 to May 8,2017,and conclude that eGARCH and sGARCH perform better for normal innovations while NGARCH performs better for student t innovations.This investigation of the volatility,VaR,and backtesting of the daily stock price of Total Nigeria Plc is important as most previous studies covering the Nigerian stock market have not paid much attention to the application of backtesting as a primary approach.We found from the results of the estimations that the persistence of the GARCH models are stable except for few cases for which iGARCH and eGARCH were unstable.Additionally,for student t innovation,the sGARCH and girGARCH models failed to converge;the mean reverting number of days for returns differed from model to model.From the analysis of VaR and its backtesting,this study recommends shareholders and investors continue their business with Total Nigeria Plc because possible losses may be overcome in the future by improvements in stock prices.Furthermore,risk was reflected by significant up and down movement in the stock price at a 99%confidence level,suggesting that high risk brings a high return.
文摘This work presents the complexity that emerges in a Bertrand duopoly between two companies in the Greek oil market, one of which is semi-public and the other is private. The game uses linear demand functions for differentiated products from the existing literature and asymmetric cost functions that arose after approaches using the published financial reports of the two oil companies (Hellenic Petroleum and Motor Oil). The game is based on the assumption of homogeneous players who are characterized by bounded rationality and follow an adjustment mechanism. The players’ decisions for each time period are expressed by two difference equations. A dynamical analysis of the game’s discrete dynamical system is made by finding the equilibrium positions and studying their stability. Numerical simulations include bifurcation diagrams and strange attractors. Lyapunov numbers’ graphs and sensitivity analysis in initial conditions prove the algebraic results and reveal the complexity and chaotic behavior of the system focusing on the two parameters k<sub>1</sub> and k<sub>2</sub> (speed of adjustment for each player). The d-Backtest method is applied through which an attempt is made to control the chaos that appears outside the stability space in order to return to the locally asymptotically stable Nash equilibrium for the system.
文摘以上海期货交易所的3种代表性金属期货价格指数为例,首先对其价格变化的动力学特征及波动模式进行了全面深入的考察,然后运用严谨系统的后验分析(Backtesting analysis)方法,分别在多头和空头两种头寸状况以及5种不同分位数水平下,实证对比了8种风险测度模型对VaR(Value at Risk)和ES(Excepted shortfall)两种不同风险指标估计的精度差异。研究结果表明:在综合考虑了模型对金属期货价格变化动力学的刻画效果以及对不同风险指标的测度精度等因素后,基于有偏学生t分布的APGARCH模型是一个相对合理的风险测度模型选择。
文摘This research investigates token dormancy as a fundamental metric for evaluating cryptocurrency assets and presents a methodology for its measurement.The valuation method involves 4 distinct parameters and utilizes a 3.5-year daily dataset for the“Chainlink”token.The results are used in optimized ARIMA-GARCH models to analyze the first differences between the variables;the out-of-sample forecasts were assessed with performance metrics.Furthermore,this study introduces a novel fundamental value derived from these approaches,the basis for generating selling signals in a backtested trading strategy.The trading strategy results are compared to a benchmark buy-and-hold strategy and a non-selling dollar-cost-averaging strategy for evaluation.Employing the dollar-cost averaging approach for purchase frequency and utilizing the“isolation forest”technique for identifying selling signals within the trading strategy yielded positive results.
文摘VaR(Value at Risk)是商业银行市场风险管理的重要方法。本文提出了一种基于组合权重伪似然函数的VaR半参数估计方法,选取股票市场数据进行实证分析,并依据新资本协议对市场风险内部模型法的要求及其它VaR检验准则检验了模型结果。结果表明,相对常用VaR模型及改进之前的模型,此方法在多种检验标准下都具有明显优势。
文摘以沪深300股指期货指数的30分钟交易数据为例,首先对其价格变化的动力学特征及波动模式进行了全面深入的考察,然后运用严谨系统的后验分析(Backtesting analysis)方法,分别在多头和空头两种头寸状况以及5种不同分位数水平下,实证对比了8种风险测度模型对VaR(Value at Risk)和ES(Excepted shortfall)两种不同风险指标估计的精度差异。研究结果表明:我国股指期货市场的价格波动具有较为明显的有偏和尖峰厚尾分布、聚集特征和长记忆性;采用有偏学生t分布和长记忆模型有助于提高对沪深300股指期货的风险测度精度,而在波动模型中包含杠杆效应项对提高风险估计精度并无太多帮助;在综合考虑了模型对沪深300股指期货价格变化动力学的刻画效果以及对不同风险指标的测度精度等因素后,基于有偏学生t分布的GARCH模型是一个相对合理的风险测度模型选择。
