arXiv - QuantFin - Mathematical Finance最新文献

COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning COMEX 铜期货波动率预测：计量经济学模型和深度学习

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-09-12 DOI: arxiv-2409.08356

Zian Wang, Xinyi Lu

{"title":"COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning","authors":"Zian Wang, Xinyi Lu","doi":"arxiv-2409.08356","DOIUrl":"https://doi.org/arxiv-2409.08356","url":null,"abstract":"This paper investigates the forecasting performance of COMEX copper futures\u0000realized volatility across various high-frequency intervals using both\u0000econometric volatility models and deep learning recurrent neural network\u0000models. The econometric models considered are GARCH and HAR, while the deep\u0000learning models include RNN (Recurrent Neural Network), LSTM (Long Short-Term\u0000Memory), and GRU (Gated Recurrent Unit). In forecasting daily realized\u0000volatility for COMEX copper futures with a rolling window approach, the\u0000econometric models, particularly HAR, outperform recurrent neural networks\u0000overall, with HAR achieving the lowest QLIKE loss function value. However, when\u0000the data is replaced with hourly high-frequency realized volatility, the deep\u0000learning models outperform the GARCH model, and HAR attains a comparable QLIKE\u0000loss function value. Despite the black-box nature of machine learning models,\u0000the deep learning models demonstrate superior forecasting performance,\u0000surpassing the fixed QLIKE value of HAR in the experiment. Moreover, as the\u0000forecast horizon extends for daily realized volatility, deep learning models\u0000gradually close the performance gap with the GARCH model in certain loss\u0000function metrics. Nonetheless, HAR remains the most effective model overall for\u0000daily realized volatility forecasting in copper futures.","PeriodicalId":501084,"journal":{"name":"arXiv - QuantFin - Mathematical Finance","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249777","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}

引用次数: 0

A market resilient data-driven approach to option pricing 市场弹性数据驱动的期权定价方法

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-09-12 DOI: arxiv-2409.08205

Anindya Goswami, Nimit Rana

引用次数: 0

Ergodicity and Law-of-large numbers for the Volterra Cox-Ingersoll-Ross process Volterra Cox-Ingersoll-Ross 过程的遍历性和大数定律

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-09-06 DOI: arxiv-2409.04496

Mohamed Ben Alaya, Martin Friesen, Jonas Kremer

引用次数: 0

Irreversible investment under weighted discounting: effects of decreasing impatience 加权贴现下的不可逆投资：不耐烦程度递减的影响

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-09-02 DOI: arxiv-2409.01478

Pengyu Wei, Wei Wei

引用次数: 0

Long-term decomposition of robust pricing kernels under G-expectation G-预期下稳健定价内核的长期分解

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-08-31 DOI: arxiv-2409.00535

Jaehyun Kim, Hyungbin Park

引用次数: 0

Brief Synopsis of the Scientific Career of T. R. Hurd 赫德科学生涯简介

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-08-29 DOI: arxiv-2408.16891

Matheus R. Grasselli, Lane P. Hughston

引用次数: 0

Option Pricing with Stochastic Volatility, Equity Premium, and Interest Rates 随机波动、股票溢价和利率的期权定价

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-08-27 DOI: arxiv-2408.15416

Nicole Hao, Echo Li, Diep Luong-Le

引用次数: 0

Asset pricing under model uncertainty with finite time and states 有限时间和状态下模型不确定性的资产定价

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-08-23 DOI: arxiv-2408.13048

Shuzhen Yang, Wenqing Zhang

引用次数: 0

A case study on different one-factor Cheyette models for short maturity caplet calibration 针对短期限胶囊校准的不同单因子切耶特模型案例研究

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-08-21 DOI: arxiv-2408.11257

Arun Kumar Polala, Bernhard Hientzsch

{"title":"A case study on different one-factor Cheyette models for short maturity caplet calibration","authors":"Arun Kumar Polala, Bernhard Hientzsch","doi":"arxiv-2408.11257","DOIUrl":"https://doi.org/arxiv-2408.11257","url":null,"abstract":"In [1], we calibrated a one-factor Cheyette SLV model with a local volatility\u0000that is linear in the benchmark forward rate and an uncorrelated CIR stochastic\u0000variance to 3M caplets of various maturities. While caplet smiles for many\u0000maturities could be reasonably well calibrated across the range of strikes, for\u0000instance the 1Y maturity could not be calibrated well across that entire range\u0000of strikes. Here, we study whether models with alternative local volatility\u0000terms and/or alternative stochastic volatility or variance models can calibrate\u0000the 1Y caplet smile better across the strike range better than the model\u0000studied in [1]. This is made possible and feasible by the generic simulation,\u0000pricing, and calibration frameworks introduced in [1] and some new frameworks\u0000presented in this paper. We find that some model settings calibrate well to the\u00001Y smile across the strike range under study. In particular, a model setting\u0000with a local volatility that is piece-wise linear in the benchmark forward rate\u0000together with an uncorrelated CIR stochastic variance and one with a local\u0000volatility that is linear in the benchmark rate together with a correlated\u0000lognormal stochastic volatility with quadratic drift (QDLNSV) as in [2]\u0000calibrate well. We discuss why the later might be a preferable model. [1] Arun Kumar Polala and Bernhard Hientzsch. Parametric differential machine\u0000learning for pricing and calibration. arXiv preprint arXiv:2302.06682 , 2023. [2] Artur Sepp and Parviz Rakhmonov. A Robust Stochastic Volatility Model for\u0000Interest Rate Dynamics. Risk Magazine, 2023","PeriodicalId":501084,"journal":{"name":"arXiv - QuantFin - Mathematical Finance","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216343","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}

引用次数: 0

Optimal stopping and divestment timing under scenario ambiguity and learning 情景模糊和学习条件下的最佳停止和撤资时机

arXiv - QuantFin - Mathematical Finance Pub Date : 2024-08-18 DOI: arxiv-2408.09349

Andrea Mazzon, Peter Tankov

引用次数: 0