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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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8152330 · Jan 202619922001200920172026
48 results for Equity baskets

The study analyzes the differences between physical and risk-neutral correlation estimates for equity baskets.

problem Analyzing the differences between physical and risk-neutral correlation estimates for equity baskets.
method Assumed equicorrelation, reduced dimensionality, approximated ICS from implied volatilities, analyzed dynamics using dynamic semiparametric factor model.
result Proposed profitability improvement schemes based on implied correlation forecasts.

The paper solves the skewness problem in high-dimensional basket options.

problem Inconsistent skewness between individual stock options and basket options on an index.
method Developed an effective local volatility model and calibrated the basket to the index smile using a jump-diffusion model.
result The method resolves the skewness issue, matching the index smile in basket option prices.

This paper examines pricing and hedging strategies for cross-currency equity protection swaps.

problem Dynamic requirements from EPS buyers in cross-currency equity protection swaps.
method Detailed analysis of two hedging paradigms, including separate and aggregated returns, with consideration of different types of returns.
result Proposes various hedging strategies with practical implications for EPS providers and investors.

The article models financial asset returns using Gaussian mixtures and EVT-based copulas to price equity options.

problem Modeling financial asset returns and pricing equity options considering extreme values.
method Modeling marginal distributions with Gaussian mixtures and joint dependence structure with EVT-based copulas.
result The approach accurately prices various equity options on Atos and Dassault Systems actions.

Paper forecasts stock correlations using a hybrid model combining graph neural networks and transformers.

problem Improving stock correlation forecasts for better portfolio management.
method Hybrid model combining Transformer and graph attention networks for forecasting residual deviations from historical data.
result The hybrid model reduces correlation forecasting error compared to rolling-window estimates.

Quantum state preparation framework speeds up basket option pricing.

problem Limited practical benefit of quantum amplitude estimation due to state-preparation depth.
method Structure-aware tensor-train rank-based variational state preparation.
result State-preparation depth scaling replaced with linear scaling, maintaining low basket-pricing errors.

Flat plumbing basket surfaces of links were introduced to study the geometry of the complement of the links. In present article, we study links of the flat plumbing basket numbers 44 or less using a special presentation of the flat plumbing basket surfaces. We find a complete classification theorem of links of the fla…

2014-12-25abs ↗pdf ↗

A flat plumbing basket is a Seifert surface consisting of a disk and bands contained in distinct pages of the disk open book decomposition of the 3-sphere. In this paper, we examine close connections between flat plumbing baskets and the contact structure supported by the open book. As an application we give lower boun…

2017-10-31abs ↗pdf ↗

Method calibrates basket options using rearranged samples from constituent processes.

problem Calibrate basket options with non-linear dependency structure.
method Propose a method to extract dependency structure from market data through systematic sampling rearrangement, then calibrate a local volatility model.
result Efficiently calibrates basket options with near-perfect accuracy.

A flat plumbing basket is a surface consisting a disk and finitely many bands which are contained in distinct pages of the trivial open book decomposition of S3\mathbf{S}^{3}. In this paper, we construct a Legendrian link from a flat plumbing basket, and we describe a relation among the self-linking number, the Thursto…

2017-09-26abs ↗pdf ↗

Develops M2 model for next-basket recommendation considering user preferences, item popularity, and transition patterns.

problem Next-basket recommendation problem considering user preferences, item popularity, and transition patterns.
method Mixed model with preferences, popularities, and transitions (M2) using ed-Trans for transition patterns among items.
result Significantly outperforms state-of-the-art methods on all datasets in all tasks, with up to 22.1% improvement.

Complementary products recommendation is an important problem in e-commerce. Such recommendations increase the average order price and the number of products in baskets. Complementary products are typically inferred from basket data. In this study, we propose the BB2vec model. The BB2vec model learns vector representat…

2018-09-25abs ↗pdf ↗

Generative model prices basket options efficiently.

problem Real-time pricing of basket options with varying market inputs.
method Truncated path signatures and Mixture Density Networks (MDN) for learning the terminal density.
result The model produces small pricing errors and matches Monte Carlo simulations closely.

New formulas for pricing Asian and basket options using stochastic expansion.

problem Pricing Asian and basket options under time-dependent parameters.
method Stochastic Taylor expansion around a log-normal proxy model.
result Highly accurate approximations for Asian options and vanilla options with discrete dividends.

New approximations for Asian basket spread options using stochastic Taylor expansions.

problem Pricing Asian basket spread options under the Black-Scholes model.
method Stochastic Taylor expansion applied to a log-normal proxy model.
result Highly accurate approximations for Asian and spread options, without numerical integration.

In this paper we give definitions of matrix rates of return which do not depend on the choice of basis describing baskets. We give their economic interpretation. The matrix rate of return describes baskets of arbitrary type and extends portfolio analysis to the complex variable domain. This allows us for simultaneous a…

2006-07-19abs ↗pdf ↗

Study efficient numerical methods for American basket options.

problem Valuation of American basket options.
method Partial differential complementarity problems (PDCPs) and efficient discretization.
result Approximations of American basket options are close and converge favourably.

We empirically test predictability on asset price by using stock selection rules based on maximum drawdown and its consecutive recovery. In various equity markets, monthly momentum- and weekly contrarian-style portfolios constructed from these alternative selection criteria are superior not only in forecasting directio…

2014-03-31abs ↗pdf ↗

The possibility that the collective dynamics of a set of stocks could lead to a specific basket violating the efficient market hypothesis is investigated. Precisely, we show that it is systematically possible to form a basket with a non-trivial autocorrelation structure when the examined time scales are at the order of…

2010-06-27abs ↗pdf ↗

The flat plumbing basket presentation of a link is introduced by Furihata, Hirasawa and Kobayashi. In this paper, we show that the pass-equivalence and an equivalence introduced by using the flat plumbing basket presentation are the same relation. Furthermore, we obtain an evaluation of the minimal number of bands used…

2013-11-14abs ↗pdf ↗

OMBA learns product and user representations for better online market basket analysis.

problem Limited ability to uncover rarely occurring and temporal associations in MBA.
method Jointly learns product and user representations, captures temporal dynamics, scalable online method.
result OMBA outperforms state-of-the-art methods by 21% on real-world datasets.

This paper sets out to provide a general framework for the pricing of average-type options via lower and upper bounds. This class of options includes Asian, basket and options on the volume-weighted average price. We demonstrate that in cases under discussion lower bounds allow for the dimensionality of the problem to …

2016-12-27abs ↗pdf ↗

Theoretical models applied to option pricing should take into account the empirical characteristics of the underlying financial time series. In this paper, we show how to price basket options when assets follow a shifted log-normal process with jumps capable of accommodating negative skewness. Our technique is based on…

2013-12-16abs ↗pdf ↗

We consider the problem of computing upper and lower bounds on the price of a European basket call option, given prices on other similar baskets. Although this problem is very hard to solve exactly in the general case, we show that in some instances the upper and lower bounds can be computed via simple closed-form expr…

2003-02-19abs ↗pdf ↗

Platform uses queries to elicit investor preferences for portfolio trades, improving allocation efficiency.

problem Hidden-information problem in institutional crossing markets where investors value trades as portfolios but liquidity discovery is organized by individual securities.
method Modeling portfolio crossing as preference elicitation, using price-directed demand queries and value queries to verify selected packages.
result Hybrid procedure using demand and value queries recovers 88-95% of full-information welfare with a limited query budget.

The problem of quantile hedging for basket derivatives in the Black-Scholes model with correlation is considered. Explicit formulas for the probability maximizing function and the cost reduction function are derived. Applicability of the results for the widely traded derivatives as digital, quantos, outperformance and …

2010-10-27abs ↗pdf ↗

The paper calculates XVA for complex basket derivatives using machine learning.

problem Computing XVA for American basket derivatives with multiple underlying assets.
method The approach combines machine learning (Gaussian Process Regression) with numerical techniques (control variates) to handle high-dimensional control problems.
result The proposed machine learning methods effectively compute XVA for basket derivatives.

Emerging market hard-currency bonds are an asset class of growing importance, and contain exposure to an EM sovereign and the underlying industry. The authors investigate how to model this as a modification of the well-known first-to-default (FtD) basket, using the structural model, and find the approach feasible.

2018-04-24abs ↗pdf ↗

This paper uses basket option formulas to price vanilla options with discrete dividends.

problem Pricing vanilla options on stocks with discrete cash dividends.
method Uses existing basket option formulas for European options on a single asset with cash dividends in the piecewise lognormal model.
result Explains the use of basket option formulas for a specific problem in the piecewise lognormal model.