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1. Poisson process Models of extreme volatility of Bitcoin prices | |||
ZHANG Han,ZHANG Aidi,GAO Meng | |||
Mathematics 11 July 2023 | |||
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Abstract:In recent years, digital currencies based on blockchain technology have received widespread attention from global investors and financial regulatory agencies, and the dramatic fluctuations of their price are the major conerns. Previous studies on asset price fluctuations mainly focused on traditional capital markets such as stocks and bonds, while there are less research on price fluctuations in the emerging digital currency market i.e. the Bitcoin. Bitcoin is a currency with intrinsic value that is difficult to quantify, produced entirely by computer computing power, and has no endorsement from any national government or financial institution as a financial asset. Therefore, as a financial asset, the Bitcoin prices often experience violent fluctuations due to numerous complex factors. In this study, two Poission process models, non-homogeneous Poisson process (NHPP) model and the fractional Poisson process (FPP) model, are used to fit the violent Bitcoin price volatility sequence. The NHPP model generalizes the intensity λ of the Poisson process to a function λ(t), reflecting the non-stationarity of violent Bitcoin price fluctuation events. The fractional Poisson process is also a generalization of the homogeneous Poisson process model, where the time interval distribution is extended from the exponential distribution to the Mittag-Leffler distribution. The fractional Poisson process reflects long-term memory effects. In this study, two Poisson point process models are applied to the event sequence of sharp fluctuations in the price of Bitcoin through estimating model parameters and graphical evaluation model fitting, and the ocurruing of the next is aslo predicted and analyzed. | |||
TO cite this article:ZHANG Han,ZHANG Aidi,GAO Meng. Poisson process Models of extreme volatility of Bitcoin prices[OL].[11 July 2023] http://en.paper.edu.cn/en_releasepaper/content/4761142 |
2. Nonnegative LAD-LASSO and Application in index tracking | |||
LIANG Rong-Mei | |||
Mathematics 31 October 2022 | |||
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Abstract:In this paper,we combine LAD-LASSO estimation and nonnegative constraint estimation,to propose a robust estimation which can do parameter estimation and variable selection in non negative problem.Compared with LAD-LASSO, he can better handle some non negative problems in economy. And compared with non negative estimation,it can do variable selection.With easily estimated tuning parameters,the non negative enjoys oracle property.Furthermore,we propose a non negative coordinate descent algorithm and do some data simulation. We also applied the model to stock index tracking and compared with non negative LASSO. | |||
TO cite this article:LIANG Rong-Mei. Nonnegative LAD-LASSO and Application in index tracking[OL].[31 October 2022] http://en.paper.edu.cn/en_releasepaper/content/4758259 |
3. SVM-GBDT Model and Internet Finance Credit Risk | |||
ZHANG Yanna,GONG Yicheng,YU Li | |||
Mathematics 07 November 2018 | |||
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Abstract:To measure the users' credit risk of Internet finance, it is defined as the probability that users cannot repay on time. Considering the type of data may be continuous or discrete, the integrated regression estimation model GBDT is used. To adapt the increasing scale of data, this paper proposes a GBDT coupled with SVM model (SVM-GBDT), where SVM is used to select important training data first, and then a GBDT model is trained on the data corresponding to the support vectors of SVM. To test the model's effect, this paper analyzes the credit risk of an Internet financial loan institution's user data, which are offered by the "East Securities Futures Cup" Chinese University Statistical Model Contest. On the test set, the accuracy (A) and harmonic mean (F1) and running time (t) are respectively 0.9427 and 0.970035 and 4.5726 seconds for SVM-GBDT model. Then the SVM-GBDT model are compared with other pure models such as Logistic, SVM, CART, RF, and GBDT models, and the comparing results shows that the SVM-GBDT model has great performance than other models. It's the accuracy (A) and harmonic mean (F1) are slightly higher and the running efficiency are far faster than other five models. This model can help Internet financial companies make loan decisions under the background of big data, and also provide a new practice reference for data mining. | |||
TO cite this article:ZHANG Yanna,GONG Yicheng,YU Li. SVM-GBDT Model and Internet Finance Credit Risk[OL].[ 7 November 2018] http://en.paper.edu.cn/en_releasepaper/content/4746422 |
4. On a Perturbed Compound Poisson Model under a Periodic Threshold Dividend Strategy | |||
WANG Jingying,ZHANG Zhimin | |||
Mathematics 08 April 2018 | |||
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Abstract:In this paper, we propose a new threshold dividend strategy in a compound Poisson model perturbed by a Brownian motion. At a sequence of random observation times, the insurance company makes decision on dividend payments. As long as the observed surplus level is larger than the maximum of the last observed surplus level (after dividend payments) and a threshold level, a fraction of the excess amount will be paid as dividends. In this model, we derive integral equations for the discounted penalty function, and find solutions under the case when the claim size density has rational Laplace transform. Numerical examples are also illustrated. | |||
TO cite this article:WANG Jingying,ZHANG Zhimin. On a Perturbed Compound Poisson Model under a Periodic Threshold Dividend Strategy[OL].[ 8 April 2018] http://en.paper.edu.cn/en_releasepaper/content/4744383 |
5. Prediction of Stock Price Index with Hidden Markov Model | |||
HE Fengxia,HUANG Jingfeng | |||
Mathematics 08 April 2016 | |||
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Abstract:The change law of the stock price which is affected by lots of stochastic interference factors is filled with complex nonlinearity and randomicity. Therefore, predicting the stock price accurately is of great research significance. This paper concerns the closing price of S&P 500 index as the research object and the status quo and characteristics of the S&P 500 index is analyzed. A new prediction method on the basis of continuous hidden Markov model with the combination of K-Means clustering algorithm is established. The proposed prediction method for the stock price index has more certain validity and feasibility compared with the Autoregressive Integrated Moving Average Model(ARIMA) in the time series. | |||
TO cite this article:HE Fengxia,HUANG Jingfeng. Prediction of Stock Price Index with Hidden Markov Model[OL].[ 8 April 2016] http://en.paper.edu.cn/en_releasepaper/content/4683378 |
6. The compound Poisson risk model with random gains and periodic dividend strategy | |||
WANG Qian-qian,LIU Chao-Lin,ZHANG Zhi-Min | |||
Mathematics 04 April 2016 | |||
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Abstract:In this paper, we consider a compound Poisson risk model with random gains and periodic dividend strategy. At a sequence of dividend decision times, the insurer observes the surplus level to decide dividend payments. We study the expected discounted dividend payments until ruin. Integro-differential equations are derived and solved. At last, we present some numerical results when the claim sizes follow exponential distribution. | |||
TO cite this article:WANG Qian-qian,LIU Chao-Lin,ZHANG Zhi-Min. The compound Poisson risk model with random gains and periodic dividend strategy[OL].[ 4 April 2016] http://en.paper.edu.cn/en_releasepaper/content/4682999 |
7. Zero-inflated Negative Binomial Model and its Application in Car Insurance | |||
Jiang Tingting,Huang Wei | |||
Mathematics 13 April 2015 | |||
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Abstract:Under many circumstances, most car insurance data appears to be zero-inflated and their risks are nonhomogeneous. These lead to general traditional claim frequency models lost their prediction effect, so they are unsuitable to fit this kind of data. This paper is using the car insurance data for GINB model, ZINB model and C-ZINB model to do empirical research, the results demonstrate that the C-ZINB model can overcome the risk of homogeneity and zero inflation very well. In addition, C-ZINB model has good simulation prediction effect. | |||
TO cite this article:Jiang Tingting,Huang Wei. Zero-inflated Negative Binomial Model and its Application in Car Insurance[OL].[13 April 2015] http://en.paper.edu.cn/en_releasepaper/content/4638882 |
8. Selection of Covariates for estimating causal effects in a Given Diagram | |||
ZHANG San-Feng, LI Si | |||
Mathematics 26 December 2014 | |||
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Abstract:Graphical models with the corresponding linear structural equation model can be used to describe a causal-effect relationship. A common problem is argued about which covariates in the diagram should be used to estimate the causal effect of a control plan. The covariates selection in this paper is back-door criterion. Unfortunately the result of selection of covariates is not unique as we shown in the following part. In this paper, we evaluated the asymptotic variance of the estimated causal effect with different plans and give a comparison between them. | |||
TO cite this article:ZHANG San-Feng, LI Si. Selection of Covariates for estimating causal effects in a Given Diagram[OL].[26 December 2014] http://en.paper.edu.cn/en_releasepaper/content/4625554 |
9. Optimal dividend, capital injection and reinsurance strategies with transaction costs | |||
WANG Rong-Ming, YAO Ding-Jun, XU Lin | |||
Mathematics 20 October 2014 | |||
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Abstract:This paper investigates an optimal dividend and capital injection problemwith non-cheap excess-of-loss reinsurance policy. The insurancecompany can control its surplus by paying dividends and injecting capitals, which incur proportional and fixed transaction costs. Moreover, both insurer and reinsurer rely on theexpectation premium principle to calculate their premiums but withdifferent safety loadings. The goal of insurance company is todetermine optimal dividend, capital injection and reinsurance strategiesfor maximizing the difference between the expected discounteddividends minus the expected discounted capital injections untilthe time of bankruptcy. By solving the corresponding impulse control problem, closed-form expressions for the value functionand optimal strategy are derived. | |||
TO cite this article:WANG Rong-Ming, YAO Ding-Jun, XU Lin. Optimal dividend, capital injection and reinsurance strategies with transaction costs[OL].[20 October 2014] http://en.paper.edu.cn/en_releasepaper/content/4614350 |
10. Empirical Likelihood Diagnosis of Varying Coefficient Errors-in-Variables Models with Longitudinal Data | |||
Wang Shuling,Zheng Lin,Dai Jiangtao | |||
Mathematics 27 May 2014 | |||
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Abstract:In this paper,we investigate the empirical likelihood diagnosis of varying coefficient errors-in-variables models with longitudinal data.The empirical log-likelihood ratios fro the time-varying coefficient function based on the global variance structures are introduced.First,the estimation equation based on empirical likelihood method are estabilished.Then,some diagnostic statistics are proposed.At last,Monte Carlo simulation is given to illustrate our results | |||
TO cite this article:Wang Shuling,Zheng Lin,Dai Jiangtao. Empirical Likelihood Diagnosis of Varying Coefficient Errors-in-Variables Models with Longitudinal Data[OL].[27 May 2014] http://en.paper.edu.cn/en_releasepaper/content/4598788 |
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