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A New Approach for Solving Boundary Value Problem in Partial Differential Equation Arising in financial market

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Applied Mathematics 2016年第9期7卷 840-851页

作者： Fadugba Sunday Emmanuel Emeka Helen Oluyemisi Department of Mathematical Sciences Ekiti State University Ado Ekiti Nigeria Department of Mathematical and Physical Sciences Afe Babalola University Ado Ekiti Nigeria

In this paper, we present a new approach for solving boundary value problem in partial differential equation arising in financial market by means of the Laplace transform. The result shows that the Laplace transform f... 详细信息

关键词： Black-Scholes-Merton Model Boundary Value Problem European Call Option financial market Laplace Transform

Improvement in Hurst exponent estimation and its application to financial markets

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financial Innovation 2022年第1期8卷 2317-2337页

作者： A.Gómez-Águila J.E.Trinidad-Segovia M.A.Sánchez-Granero Department of Mathematics(AGA and MASG)and Department of Economics and Business(JETS) University of Almería04120 AlmeríaSpain

This research aims to improve the efficiency in estimating the Hurst exponent in financial time series.A new procedure is developed based on equality in distribution and is applicable to the estimation methods of the Hurst exponent.We show how to use this new procedure with three of the most popular algorithms(generalized Hurst exponet,total triangles area,and fractal dimension)in the literature.Findings show that this new approach improves the accuracy of the original methods,mainly for longer series.The second contribution of this study is that we show how to use this methodology to test whether the series is self-similar,constructing a confidence interval for the Hurst exponent for which the series satisfies this property.Finally,we present an empirical application of this new procedure to stocks of the S&P500 index.Similar to previous contributions,we consider this to be relevant to financial literature,as it helps to avoid inappropriate interpretations of market efficiency that can lead to erroneous decisions not only by market participants but also by policymakers.

关键词： Hurst exponent Long memory financial market TA algorithm GHE algorithm FD algortihms

Credit granting sorting model for financial organizations

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financial Innovation 2022年第1期8卷 307-330页

作者： Paulo Cesar Schotten Leydiana de Sousa Pereira Danielle Costa Morais CDSID-Center for Decision Systems and Information Development Universidade Federal de PernambucoAv.Acadêmico Hélio Ramoss/n–Cidade UniversitáriaRecifePE CEP 50.740-530Brazil

Considering the environment of risks and influences inherent in the decision-making process for credit-granting operations,it has become a matter of survival for financial organizations to seek to improve how they engage in effective decision-making to ensure that their returns on invested capital will meet the expectations established at the beginning of the process.A credit-granting sorting model for financial organizations is proposed.The model aggregates the perspectives of different decision-makers to support an organization in the process of credit analysis and,consequently,to improve its operationality.The decision-making model is based on the ELECTRE TRI-B multicriteria method.It sorts credit-granting proposals into three classes,namely credit approved,technical analysis,and credit rejected.The group decision emerges from the decision rules of the organization’s executive board.This new proposed approach to dealing with credit-granting results in the systematization of credit analysis,reduction of doubt among decision-makers,avoidance of the emergence of informal groups,reduction of conflicts within a financial organization,and external interferences.

关键词： Credit granting ELECTRE TRI-B financial market Group decision-making Multicriteria methods

Empirical Study on the Volatility of the Hang-Seng Index

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Chinese Physics Letters 2006年第3期23卷 754-757页

作者：蔡世民周佩玲杨会杰杨春霞汪秉宏周涛 Department of Electronic Science and Technology University of Science and Technology of China Hefei 230026 Department of Modern Physics and Nonlinear Science Center University of Science and Technology of China Hefei 230026

We study the statistical properties of volatility of price fluctuation for the Hang-Seng index in the Hong Kong stock market, they are measured by locally averaging over a time window T, the absolute value of price change over a short time interval Δt. The data include minute-by-minute records of the Hang-Seng index from 3 January 1994 to 28 May 1997. We find that the cumulative distribution of the volatility is consistent with the asymptotic power-law behaviour, characterized by the power exponent μ= 2.12 ± 0.04, different from that found in the previous studies as μ≈3. The volatility distribution remains the same asymptotic power-law behaviour for the time scales from T = 10 rain to T - 80 rain. Furthermore, we investigate the volatility correlations by using the power spectrum analysis and detrended fluctuation analysis. Both the methods show a long-range power-law decay with the exponent α=0.636±0.002.

关键词： STOCK-market financial market TIME-SERIES MODEL FLUCTUATIONS BEHAVIOR PERCOLATION PATTERNS

Profit Guided or Statistical Error Guided? A Study of Stock Index Forecasting Using Support Vector Regression

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Journal of Systems Science & Complexity 2017年第6期30卷 1425-1442页

作者： HU Zhongyi BAO Yukun CHIONG Raymond XIONG Tao School of Information Management Wuhan University School of Management Huazhong University of Science and Technology School of Electrical Engineering and Computing The University of Newcastle College of Economics and Management Huazhong Agricultural University

Stock index forecasting has been one of the most widely investigated topics in the field of financial forecasting. Related studies typically advocate for tuning the parameters of forecasting models by minimizing learning errors measured using statistical metrics such as the mean squared error or mean absolute percentage error. The authors argue that statistical metrics used to guide parameter tuning of forecasting models may not be meaningful, given the fact that the ultimate goal of forecasting is to facilitate investment decisions with expected profits in the future. The authors therefore introduce the Sharpe ratio into the process of model building and take it as the profit metric to guide parameter tuning rather than using the commonly adopted statistical metrics. The authors consider three widely used trading strategies, which include a na¨?ve strategy, a filter strategy and a dual moving average strategy, as investment scenarios. To verify the effectiveness of the proposed profit guided approach, the authors carry out simulation experiments using three global mainstream stock market indices. The results show that profit guided forecasting models are competitive, and in many cases produce significantly better performances than statistical error guided models. This implies thatprofit guided stock index forecasting is a worthwhile alternative over traditional stock index forecasting practices.

关键词： financial market investment trading strategy parameter optimization stock index forecasting support vector regression

Analysis on the Mutation and Time-Varying Characteristics of Coal Price System Evolution from the Perspective of Finance

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Journal of Systems Science & Complexity 2021年第4期34卷 1501-1521页

作者： CHAI Jian LEI Junchan SHI Huiting ZHANG Xuejun LANG Meiling School of Economics and Management Xidian UniversityXi'an 710126China

Coal is essential to ensure China’s energy security.The sudden or gradual change of coal price reflects the degree of disequilibrium or expected disequilibrium of coal supply and demand,which will not be conducive to energy security.Therefore,it is important to analyze the change points of coal price and explore the reason of the price fluctuation.This paper analyses the coal price from January2008 to June 2019 as the perspective of the financial market.Firstly,the PPM-DBSCAN model is used to identify the mutation point of coal price fluctuation.Secondly,path analysis is used to extract the core driving factors that affect coal price.Thirdly,the authors construct a time-varying and time-lag effect analysis model for structural changes of coal price based on the TVP-VAR model.The results show that there are 11 mutation points of coal price fluctuation.financial market factors,coal supply and demand and alternative factors are the reasons of coal price mutation.The authors find that the imbalance of coal supply and demand in traditional view cannot fully explain the fluctuation of coal price.The impact of the financial market and non-thermal power generation have more influence on the coal price.

关键词： Coal price financial market mutation

Asymmetric and symmetric meta-correlations in financial markets

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Chinese Physics B 2016年第10期25卷 579-586页

作者：李晓辉沈翔瀛黄吉平 Department of Physics and State Key Laboratory of Surface Physics Fudan University

In financial markets, the relation between fluctuations of stock prices and trading behaviors is complex. It is intriguing to quantify this kind of meta-correlation between market fluctuations and the synchronous behaviors. We refine the theoretical index leverage model proposed by Reigneron et al., to exactly quantify the meta-correlation under various levels of price fluctuations [Reigneron P A, Allez R and Bouchaud J P 2011 Physica A 390 3026]. The characteristics of meta-correlations in times of market losses, are found to be significantly different in Chinese and American financial markets. In addition,unlike the asymmetric results at the daily scale, the correlation behaviors are found to be symmetric at the high-frequency scale.

关键词： financial market collective behavior complex system asymmetry and symmetry

The Effects of FED’s and ECB’s QE Announcements on Exchange Rates of Bitcoin,Euro,and Dollar in the Period of COVID-19:An Event Study Approach

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Journal of Modern Accounting and Auditing 2022年第5期18卷 212-224页

作者： Sofia Karagiannopoulou Paris Patsis Nikolaos Sariannidis University of Western Macedonia KozaniGreece University of Western Macedonia GrevenaGreece

Corresponding to the pandemic COVID-19,both FED and ECB were committed to using their full range of tools,such as the helicopter money policy and a new quantitative easing programme to support the economy in this challenging time.The goal of this study is to explore the impact of ECB’s and FED’s COVID-19 Quantitative Easing(QE)announcements on exchange rates.Using an event study with daily data from 01/10/2019 to 02/05/2020,it investigates the impact of these“Odyssean shocks”on EUR/USD,BTC/EUR,and BTC/USD.The empirical results show an unexpected behavior of exchange rates in response to monetary policy actions.More specifically,the ECB’s announcement led to appreciation of the Euro against the Dollar.On the other hand,the FED’s announcement leads to depreciation of the Euro.The virtual exchange rates of Bitcoin do not seem to be affected by the announcements of the ECB and the FED,confirming the role of Bitcoin as a decentralised currency and independent of Central Banks and governments.The conclusions of the study are useful for investors and policy makers,as the unforeseen COVID-19 crisis has disturbed and modified investor behavior.

关键词： monetary policy Central Bank financial market

Exploring Apple’s Stock Price Volatility Using Five GARCH Models

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Proceedings of Business and Economic Studies 2022年第5期5卷 137-145页

作者： Sihan Fu Kexin He Jialin Li Zheng Tao College of Science and Technology Wenzhou-Kean UniversityWenzhou 325005Zhejiang ProvinceChina College of Business&Public Management Wenzhou-Kean UniversityWenzhou 325005Zhejiang ProvinceChina Department of Statistics and Data Science National University of Singapore10 Kent Ridge Crescent 119077Singapore

The financial market is the core of national economic development,and stocks play an important role in the financial market.Analyzing stock prices has become the focus of investors,analysts,and people in related fields.This paper evaluates the volatility of Apple Inc.(AAPL)returns using five generalized autoregressive conditional heteroskedasticity(GARCH)models:sGARCH with constant mean,GARCH with sstd,GJR-GARCH,AR(1)GJR-GARCH,and GJR-GARCH in mean.The distribution of AAPL’s closing price and earnings data was analyzed,and skewed student t-distribution(sstd)and normal distribution(norm)were used to further compare the data distribution of the five models and capture the shape,skewness,and loglikelihood in Model 4-AR(1)GJR-GARCH.Through further analysis,the results showed that Model 4,AR(1)GJR-GARCH,is the optimal model to describe the volatility of the return series of AAPL.The analysis of the research process is both,a process of exploration and reflection.By analyzing the stock price of AAPL,we reflect on the shortcomings of previous analysis methods,clarify the purpose of the experiment,and identify the optimal analysis model.

关键词： financial market Stock price Volatility GARCH model