Applied Mathematical Finance最新文献_第5页

Structural Clustering of Volatility Regimes for Dynamic Trading Strategies 动态交易策略中波动机制的结构聚类

Applied Mathematical Finance Pub Date : 2020-04-21 DOI: 10.1080/1350486X.2021.2007146

A. Prakash, Nick James, Max Menzies, Gilad Francis

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引用次数: 19

Sequential Hypothesis Testing in Machine Learning, and Crude Oil Price Jump Size Detection 机器学习中的序贯假设检验与原油价格跳跃大小检测

Applied Mathematical Finance Pub Date : 2020-04-19 DOI: 10.1080/1350486X.2020.1859943

Michael Roberts, I. Sengupta

引用次数: 12

Exact Simulation of Variance Gamma-Related OU Processes: Application to the Pricing of Energy Derivatives 方差相关OU过程的精确模拟:在能源衍生品定价中的应用

Applied Mathematical Finance Pub Date : 2020-04-14 DOI: 10.1080/1350486X.2020.1813040

P. Sabino

引用次数: 12

Is the Variance Swap Rate Affine in the Spot Variance? Evidence from S&P500 Data 在即期方差中，方差互换率是仿射的吗?标准普尔500指数数据的证据

Applied Mathematical Finance Pub Date : 2020-04-05 DOI: 10.2139/ssrn.3571429

M. Mancino, Simone Scotti, Giacomo Toscano

引用次数: 3

Spoofing and Price Manipulation in Order-Driven Markets 订单驱动市场中的欺骗和价格操纵

Applied Mathematical Finance Pub Date : 2020-03-03 DOI: 10.1080/1350486X.2020.1726783

Á. Cartea, S. Jaimungal, Yixuan Wang

{"title":"Spoofing and Price Manipulation in Order-Driven Markets","authors":"Á. Cartea, S. Jaimungal, Yixuan Wang","doi":"10.1080/1350486X.2020.1726783","DOIUrl":"https://doi.org/10.1080/1350486X.2020.1726783","url":null,"abstract":"ABSTRACT We model the trading strategy of an investor who spoofs the limit order book (LOB) to increase the revenue obtained from selling a position in a security. The strategy employs, in addition to sell limit orders (LOs) and sell market orders (MOs), a large number of spoof buy LOs to manipulate the volume imbalance of the LOB. Spoofing is illegal, so the strategy trades off the gains that originate from spoofing against the expected financial losses due to a fine imposed by the financial authorities. As the fine increases, the investor relies less on spoofing, and if the fine is large, the investor does not spoof the LOB. The arrival rate of buy MOs increases because other traders interpret the spoofed buy-heavy LOB as an upward pressure on prices. When the fine is low, spoofing considerably increases the revenues from liquidating a position. Spoofing increases the PnL because (i) the investor employs fewer MOs to draw the inventory to zero and benefits from roundtrip trades, which stem from spoof buy LOs that are ‘inadvertently’ filled and subsequently unwound with sell LOs; and (ii) the midprice trends upward when the book is buy-heavy; therefore the spoofer sells the asset at better prices.","PeriodicalId":35818,"journal":{"name":"Applied Mathematical Finance","volume":"42 1","pages":"67 - 98"},"PeriodicalIF":0.0,"publicationDate":"2020-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81641005","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: 8

Numerical Ross Recovery for Diffusion Processes Using a PDE Approach 采用PDE方法的扩散过程数值Ross恢复

Applied Mathematical Finance Pub Date : 2020-03-03 DOI: 10.1080/1350486X.2020.1730202

L. von Sydow, J. Waldén

引用次数: 1

Additive Processes with Bilateral Gamma Marginals 双侧伽马边际的加性过程

Applied Mathematical Finance Pub Date : 2020-01-30 DOI: 10.2139/ssrn.3528510

D. Madan, King Wang

引用次数: 10

Portfolio Optimization for Credit-Risky Assets under Marshall–Olkin Dependence 马歇尔-奥尔金依赖下的信用风险资产组合优化

Applied Mathematical Finance Pub Date : 2019-11-02 DOI: 10.1080/1350486X.2020.1727755

Jan-Frederik Mai

引用次数: 0

Numerical Method for Model-free Pricing of Exotic Derivatives in Discrete Time Using Rough Path Signatures 基于粗糙路径特征的离散时间奇异导数无模型定价的数值方法

Applied Mathematical Finance Pub Date : 2019-11-02 DOI: 10.1080/1350486X.2020.1726784

Terry Lyons, Sina Nejad, Imanol Perez Arribas

引用次数: 8

Deep Reinforcement Learning for Market Making in Corporate Bonds: Beating the Curse of Dimensionality 公司债券做市的深度强化学习:战胜维度的诅咒

Applied Mathematical Finance Pub Date : 2019-09-03 DOI: 10.1080/1350486X.2020.1714455

Olivier Gu'eant, Iuliia Manziuk

{"title":"Deep Reinforcement Learning for Market Making in Corporate Bonds: Beating the Curse of Dimensionality","authors":"Olivier Gu'eant, Iuliia Manziuk","doi":"10.1080/1350486X.2020.1714455","DOIUrl":"https://doi.org/10.1080/1350486X.2020.1714455","url":null,"abstract":"ABSTRACT In corporate bond markets, which are mainly OTC markets, market makers play a central role by providing bid and ask prices for bonds to asset managers. Determining the optimal bid and ask quotes that a market maker should set for a given universe of bonds is a complex task. The existing models, mostly inspired by the Avellaneda-Stoikov model, describe the complex optimization problem faced by market makers: proposing bid and ask prices for making money out of the difference between them while mitigating the market risk associated with holding inventory. While most of the models only tackle one-asset market making, they can often be generalized to a multi-asset framework. However, the problem of solving the equations characterizing the optimal bid and ask quotes numerically is seldom tackled in the literature, especially in high dimension. In this paper, we propose a numerical method for approximating the optimal bid and ask quotes over a large universe of bonds in a model à la Avellaneda–Stoikov. As classical finite difference methods cannot be used in high dimension, we present a discrete-time method inspired by reinforcement learning techniques, namely, a model-based deep actor-critic algorithm.","PeriodicalId":35818,"journal":{"name":"Applied Mathematical Finance","volume":"2 1","pages":"387 - 452"},"PeriodicalIF":0.0,"publicationDate":"2019-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87500219","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: 48