An increase in the novelty of news predicts negative stock market returns and negative macroeconomic outcomes over the next year. We quantify news novelty - changes in the distribution of news text - through an entropy measure, calculated using a recurrent neural network applied to a large news corpus. Entropy is a better out-of-sample predictor of market returns than a collection of standard measures. Cross-sectional entropy exposure carries a negative risk premium, suggesting that assets that positively covary with entropy hedge the aggregate risk associated with shifting news language. Entropy risk cannot be explained by existing long-short factors.
{"title":"New News is Bad News","authors":"Paul Glasserman, Harry Mamaysky, Jimmy Qin","doi":"arxiv-2309.05560","DOIUrl":"https://doi.org/arxiv-2309.05560","url":null,"abstract":"An increase in the novelty of news predicts negative stock market returns and\u0000negative macroeconomic outcomes over the next year. We quantify news novelty -\u0000changes in the distribution of news text - through an entropy measure,\u0000calculated using a recurrent neural network applied to a large news corpus.\u0000Entropy is a better out-of-sample predictor of market returns than a collection\u0000of standard measures. Cross-sectional entropy exposure carries a negative risk\u0000premium, suggesting that assets that positively covary with entropy hedge the\u0000aggregate risk associated with shifting news language. Entropy risk cannot be\u0000explained by existing long-short factors.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522562","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}
David R. Baños, Salvador Ortiz-Latorre, Oriol Zamora Font
The main purpose of the paper is to derive Thiele's differential equation for unit-linked policies in the Heston-Hawkes stochastic volatility model presented in arXiv:2210.15343. This model is an extension of the well-known Heston model that incorporates the volatility clustering feature by adding a compound Hawkes process in the volatility. Since the model is arbitrage-free, pricing unit-linked policies via the equivalence principle under $mathbb{Q}$ is possible. Some integrability conditions are checked and a suitable family of risk neutral probability measures is found to obtain Thiele's differential equation. The established and practical method to compute reserves in life insurance is by solving Thiele's equation, which is crucial to guarantee the solvency of the insurance company.
{"title":"Thiele's PIDE for unit-linked policies in the Heston-Hawkes stochastic volatility model","authors":"David R. Baños, Salvador Ortiz-Latorre, Oriol Zamora Font","doi":"arxiv-2309.03541","DOIUrl":"https://doi.org/arxiv-2309.03541","url":null,"abstract":"The main purpose of the paper is to derive Thiele's differential equation for\u0000unit-linked policies in the Heston-Hawkes stochastic volatility model presented\u0000in arXiv:2210.15343. This model is an extension of the well-known Heston model\u0000that incorporates the volatility clustering feature by adding a compound Hawkes\u0000process in the volatility. Since the model is arbitrage-free, pricing\u0000unit-linked policies via the equivalence principle under $mathbb{Q}$ is\u0000possible. Some integrability conditions are checked and a suitable family of\u0000risk neutral probability measures is found to obtain Thiele's differential\u0000equation. The established and practical method to compute reserves in life\u0000insurance is by solving Thiele's equation, which is crucial to guarantee the\u0000solvency of the insurance company.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522556","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}
In this research work, we propose a high-order time adapted scheme for pricing a coupled system of fixed-free boundary constant elasticity of variance (CEV) model on both equidistant and locally refined space-grid. The performance of our method is substantially enhanced to improve irregularities in the model which are both inherent and induced. Furthermore, the system of coupled PDEs is strongly nonlinear and involves several time-dependent coefficients that include the first-order derivative of the early exercise boundary. These coefficients are approximated from a fourth-order analytical approximation which is derived using a regularized square-root function. The semi-discrete equation for the option value and delta sensitivity is obtained from a non-uniform fourth-order compact finite difference scheme. Fifth-order 5(4) Dormand-Prince time integration method is used to solve the coupled system of discrete equations. Enhancing the performance of our proposed method with local mesh refinement and adaptive strategies enables us to obtain highly accurate solution with very coarse space grids, hence reducing computational runtime substantially. We further verify the performance of our methodology as compared with some of the well-known and better-performing existing methods.
{"title":"Enhancing accuracy for solving American CEV model with high-order compact scheme and adaptive time stepping","authors":"Chinonso Nwankwo, Weizhong Dai, Tony Ware","doi":"arxiv-2309.03984","DOIUrl":"https://doi.org/arxiv-2309.03984","url":null,"abstract":"In this research work, we propose a high-order time adapted scheme for\u0000pricing a coupled system of fixed-free boundary constant elasticity of variance\u0000(CEV) model on both equidistant and locally refined space-grid. The performance\u0000of our method is substantially enhanced to improve irregularities in the model\u0000which are both inherent and induced. Furthermore, the system of coupled PDEs is\u0000strongly nonlinear and involves several time-dependent coefficients that\u0000include the first-order derivative of the early exercise boundary. These\u0000coefficients are approximated from a fourth-order analytical approximation\u0000which is derived using a regularized square-root function. The semi-discrete\u0000equation for the option value and delta sensitivity is obtained from a\u0000non-uniform fourth-order compact finite difference scheme. Fifth-order 5(4)\u0000Dormand-Prince time integration method is used to solve the coupled system of\u0000discrete equations. Enhancing the performance of our proposed method with local\u0000mesh refinement and adaptive strategies enables us to obtain highly accurate\u0000solution with very coarse space grids, hence reducing computational runtime\u0000substantially. We further verify the performance of our methodology as compared\u0000with some of the well-known and better-performing existing methods.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522565","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}
This paper presents a convenient framework for modeling default process and pricing derivative securities involving credit risk. The framework provides an integrated view of credit valuation adjustment by linking distance-to-default, default probability, survival probability, and default correlation together. We show that risky valuation is Martingale in our model. The framework reduces the technical issues of performing risky valuation to the same issues faced when performing the ordinary valuation. The numerical results show that the model prediction is consistent with the historical observations.
{"title":"Default Process Modeling and Credit Valuation Adjustment","authors":"David Xiao","doi":"arxiv-2309.03311","DOIUrl":"https://doi.org/arxiv-2309.03311","url":null,"abstract":"This paper presents a convenient framework for modeling default process and\u0000pricing derivative securities involving credit risk. The framework provides an\u0000integrated view of credit valuation adjustment by linking distance-to-default,\u0000default probability, survival probability, and default correlation together. We\u0000show that risky valuation is Martingale in our model. The framework reduces the\u0000technical issues of performing risky valuation to the same issues faced when\u0000performing the ordinary valuation. The numerical results show that the model\u0000prediction is consistent with the historical observations.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522485","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}
We present a study of the short maturity asymptotics for Asian options in a jump-diffusion model with a local volatility component, where the jumps are modeled as a compound Poisson process which are later extended to L'evy jumps, that includes the exponential L'{e}vy model as a special case. Both fixed and floating strike Asian options are considered. Explicit results are obtained for the first-order asymptotics of the Asian options prices for a few popular models in the literature: the Merton jump-diffusion model, the double-exponential jump model, and the Variance Gamma model. We propose an analytical approximation for Asian option prices which satisfies the constraints from the short-maturity asymptotics, and test it against Monte Carlo simulations. The asymptotic results are in good agreement with numerical simulations for sufficiently small maturity.
{"title":"Asymptotics for Short Maturity Asian Options in a Jump-Diffusion model with Local Volatility","authors":"Dan Pirjol, Lingjiong Zhu","doi":"arxiv-2308.15672","DOIUrl":"https://doi.org/arxiv-2308.15672","url":null,"abstract":"We present a study of the short maturity asymptotics for Asian options in a\u0000jump-diffusion model with a local volatility component, where the jumps are\u0000modeled as a compound Poisson process which are later extended to L'evy jumps,\u0000that includes the exponential L'{e}vy model as a special case. Both fixed and\u0000floating strike Asian options are considered. Explicit results are obtained for\u0000the first-order asymptotics of the Asian options prices for a few popular\u0000models in the literature: the Merton jump-diffusion model, the\u0000double-exponential jump model, and the Variance Gamma model. We propose an\u0000analytical approximation for Asian option prices which satisfies the\u0000constraints from the short-maturity asymptotics, and test it against Monte\u0000Carlo simulations. The asymptotic results are in good agreement with numerical\u0000simulations for sufficiently small maturity.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522564","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}
Haochen Li, Yi Cao, Maria Polukarov, Carmine Ventre
In this study, we introduce a physical model inspired by statistical physics for predicting price volatility and expected returns by leveraging Level 3 order book data. By drawing parallels between orders in the limit order book and particles in a physical system, we establish unique measures for the system's kinetic energy and momentum as a way to comprehend and evaluate the state of limit order book. Our model goes beyond examining merely the top layers of the order book by introducing the concept of 'active depth', a computationally-efficient approach for identifying order book levels that have impact on price dynamics. We empirically demonstrate that our model outperforms the benchmarks of traditional approaches and machine learning algorithm. Our model provides a nuanced comprehension of market microstructure and produces more accurate forecasts on volatility and expected returns. By incorporating principles of statistical physics, this research offers valuable insights on understanding the behaviours of market participants and order book dynamics.
{"title":"An Empirical Analysis on Financial Market: Insights from the Application of Statistical Physics","authors":"Haochen Li, Yi Cao, Maria Polukarov, Carmine Ventre","doi":"arxiv-2308.14235","DOIUrl":"https://doi.org/arxiv-2308.14235","url":null,"abstract":"In this study, we introduce a physical model inspired by statistical physics\u0000for predicting price volatility and expected returns by leveraging Level 3\u0000order book data. By drawing parallels between orders in the limit order book\u0000and particles in a physical system, we establish unique measures for the\u0000system's kinetic energy and momentum as a way to comprehend and evaluate the\u0000state of limit order book. Our model goes beyond examining merely the top\u0000layers of the order book by introducing the concept of 'active depth', a\u0000computationally-efficient approach for identifying order book levels that have\u0000impact on price dynamics. We empirically demonstrate that our model outperforms\u0000the benchmarks of traditional approaches and machine learning algorithm. Our\u0000model provides a nuanced comprehension of market microstructure and produces\u0000more accurate forecasts on volatility and expected returns. By incorporating\u0000principles of statistical physics, this research offers valuable insights on\u0000understanding the behaviours of market participants and order book dynamics.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522490","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}
In a market of stocks represented by strictly positive continuous semimartingales, a contingent claim function is a positive C^{2, 1} function of the stock prices and time with a given terminal value. If a contingent claim function satisfies a certain parabolic differential equation, it will generate a portfolio with value process that replicates the contingent claim function. This parabolic differential equation is a general form of the Black-Scholes equation.
{"title":"Portfolios Generated by Contingent Claim Functions, with Applications to Option Pricing","authors":"Ricardo T. Fernholz, Robert Fernholz","doi":"arxiv-2308.13717","DOIUrl":"https://doi.org/arxiv-2308.13717","url":null,"abstract":"In a market of stocks represented by strictly positive continuous\u0000semimartingales, a contingent claim function is a positive C^{2, 1} function of\u0000the stock prices and time with a given terminal value. If a contingent claim\u0000function satisfies a certain parabolic differential equation, it will generate\u0000a portfolio with value process that replicates the contingent claim function.\u0000This parabolic differential equation is a general form of the Black-Scholes\u0000equation.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522563","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}
The accuracy of predictions of price and return probabilities substantially determines the reliability of asset pricing and portfolio theories. We develop successive approximations that link up predictions of the market-based probabilities of price and return for the whole stock market with predictions of price and return probabilities for stocks of a particular company and show that economic complexity limits the accuracy of any forecasts. The economic origin of the restrictions lies in the fact that the predictions of the m-th statistical moments of price and return require descriptions of the economic variables composed by sums of the m-th powers of economic or market transactions during an averaging time interval. The attempts to predict the n-th statistical moments of price and return of stocks that are under the action of a single risk result in estimates of the n-dimensional risk rating vectors for economic agents. In turn, the risk rating vectors play the role of coordinates for the description of the evolution of economic variables. The lack of a model description of the economic variables composed by sums of the 2-d and higher powers of market transactions causes that, in the coming years, the accuracy of the forecasts will be limited at best by the first two statistical moments of price and return, which determine Gaussian distributions. One can ignore existing barriers and limits but cannot overcome or resolve them. That significantly reduces the reliability and veracity of modern asset pricing and portfolio theories. Our results could be essential and fruitful for the largest investors and banks, economic and financial authorities, and market participants.
{"title":"Economic Complexity Limits Accuracy of Price Probability Predictions by Gaussian Distributions","authors":"Victor Olkhov","doi":"arxiv-2309.02447","DOIUrl":"https://doi.org/arxiv-2309.02447","url":null,"abstract":"The accuracy of predictions of price and return probabilities substantially\u0000determines the reliability of asset pricing and portfolio theories. We develop\u0000successive approximations that link up predictions of the market-based\u0000probabilities of price and return for the whole stock market with predictions\u0000of price and return probabilities for stocks of a particular company and show\u0000that economic complexity limits the accuracy of any forecasts. The economic\u0000origin of the restrictions lies in the fact that the predictions of the m-th\u0000statistical moments of price and return require descriptions of the economic\u0000variables composed by sums of the m-th powers of economic or market\u0000transactions during an averaging time interval. The attempts to predict the\u0000n-th statistical moments of price and return of stocks that are under the\u0000action of a single risk result in estimates of the n-dimensional risk rating\u0000vectors for economic agents. In turn, the risk rating vectors play the role of\u0000coordinates for the description of the evolution of economic variables. The\u0000lack of a model description of the economic variables composed by sums of the\u00002-d and higher powers of market transactions causes that, in the coming years,\u0000the accuracy of the forecasts will be limited at best by the first two\u0000statistical moments of price and return, which determine Gaussian\u0000distributions. One can ignore existing barriers and limits but cannot overcome\u0000or resolve them. That significantly reduces the reliability and veracity of\u0000modern asset pricing and portfolio theories. Our results could be essential and\u0000fruitful for the largest investors and banks, economic and financial\u0000authorities, and market participants.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522557","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}
Natasha Latif, Shafqat Ali Shad, Muhammad Usman, Chandan Kumar, Bahman B Motii, MD Mahfuzer Rahman, Khuram Shafi, Zahra Idrees
In this paper, we price European Call three different option pricing models, where the volatility is dynamically changing i.e. non constant. In stochastic volatility (SV) models for option pricing a closed form approximation technique is used, indicating that these models are computationally efficient and have the same level of performance as existing ones. We show that the calibration of SV models, such as Heston model and the High Order Moment based Stochastic Volatility (MSV) is often faster and easier. On 15 different datasets of index options, we show that models which incorporates stochastic volatility achieves accuracy comparable with the existing models. Further, we compare the In Sample and Out Sample pricing errors of each model on each date. Lastly, the pricing of models is compared among three different market to check model performance in different markets. Keywords: Option Pricing Model, Simulations, Index Options, Stochastic Volatility Models, Loss Function http://www.sci-int.com/pdf/638279543859822650.pdf
{"title":"Pragmatic Comparison Analysis of Alternative Option Pricing Models","authors":"Natasha Latif, Shafqat Ali Shad, Muhammad Usman, Chandan Kumar, Bahman B Motii, MD Mahfuzer Rahman, Khuram Shafi, Zahra Idrees","doi":"arxiv-2309.09890","DOIUrl":"https://doi.org/arxiv-2309.09890","url":null,"abstract":"In this paper, we price European Call three different option pricing models,\u0000where the volatility is dynamically changing i.e. non constant. In stochastic\u0000volatility (SV) models for option pricing a closed form approximation technique\u0000is used, indicating that these models are computationally efficient and have\u0000the same level of performance as existing ones. We show that the calibration of\u0000SV models, such as Heston model and the High Order Moment based Stochastic\u0000Volatility (MSV) is often faster and easier. On 15 different datasets of index\u0000options, we show that models which incorporates stochastic volatility achieves\u0000accuracy comparable with the existing models. Further, we compare the In Sample\u0000and Out Sample pricing errors of each model on each date. Lastly, the pricing\u0000of models is compared among three different market to check model performance\u0000in different markets. Keywords: Option Pricing Model, Simulations, Index\u0000Options, Stochastic Volatility Models, Loss Function\u0000http://www.sci-int.com/pdf/638279543859822650.pdf","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522554","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}
We study the problem of valuing a vulnerable derivative with bilateral cash flows between two counterparties in the presence of funding, credit and wrong-way risks, and derive a closed-form valuation formula for an at-the-money (ATM) forward contract as well as a second order approximation for the general case. We posit a model with heterogeneous interest rates and default occurrence and infer a Cauchy problem for the pre-default valuation function of the contract, which includes ab initio any counterparty risk - as opposed to calculating valuation adjustments collectively known as XVA. Under a specific funding policy which linearises the Cauchy problem, we obtain a generic probabilistic representation for the pre-default valuation (Theorem 1). We apply this general framework to the valuation of an equity forward and establish the contract can be expressed as a continuous portfolio of European options with suitably chosen strikes and expiries under a particular probability measure (Theorem 2). Our valuation formula admits a closed-form expression when the forward contract is ATM (Corollary 2) and we derive a second order approximation in moneyness when the contract is close to ATM (Theorem 3). Numerical results of our model show that the forward is more sensitive to funding factors than credit ones, while higher stock funding costs increase sensitivity to credit spreads and wrong-way risk.
{"title":"Analytical valuation of vulnerable derivative contracts with bilateral cash flows under credit, funding and wrong-way risks","authors":"Juan Jose Francisco Miguelez, Cristin Buescu","doi":"arxiv-2308.10568","DOIUrl":"https://doi.org/arxiv-2308.10568","url":null,"abstract":"We study the problem of valuing a vulnerable derivative with bilateral cash\u0000flows between two counterparties in the presence of funding, credit and\u0000wrong-way risks, and derive a closed-form valuation formula for an at-the-money\u0000(ATM) forward contract as well as a second order approximation for the general\u0000case. We posit a model with heterogeneous interest rates and default occurrence\u0000and infer a Cauchy problem for the pre-default valuation function of the\u0000contract, which includes ab initio any counterparty risk - as opposed to\u0000calculating valuation adjustments collectively known as XVA. Under a specific\u0000funding policy which linearises the Cauchy problem, we obtain a generic\u0000probabilistic representation for the pre-default valuation (Theorem 1). We\u0000apply this general framework to the valuation of an equity forward and\u0000establish the contract can be expressed as a continuous portfolio of European\u0000options with suitably chosen strikes and expiries under a particular\u0000probability measure (Theorem 2). Our valuation formula admits a closed-form\u0000expression when the forward contract is ATM (Corollary 2) and we derive a\u0000second order approximation in moneyness when the contract is close to ATM\u0000(Theorem 3). Numerical results of our model show that the forward is more\u0000sensitive to funding factors than credit ones, while higher stock funding costs\u0000increase sensitivity to credit spreads and wrong-way risk.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522569","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}
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