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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.

168,657 papers · 148 categories

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77155232309 · Jun 202019922001200920172026
48 results for call prices

Proposes a model for clearing prices in financial markets due to margin calls.

problem Determining prices in financial markets following margin calls and short squeezes.
method Developed an explicit formulation for clearing prices after margin calls and short squeezes.
result Identified a threshold short interest ratio leading to discontinuity in clearing prices.

A statistical decision problem is hidden in the core of option pricing. A simple form for the price C of a European call option is obtained via the minimum Bayes risk, R_B, of a 2-parameter estimation problem, thus justifying calling C Bayes (B-)price. The result provides new insight in option pricing, among others obt…

2013-04-18abs ↗pdf ↗

Model earnings call transcripts for better stock price prediction.

problem Predicting future stock price movements using earnings call transcripts.
method Deep learning framework with an attention mechanism to encode text data into vectors for predicting stock price movements.
result The proposed model outperforms traditional machine learning methods in stock price prediction.

It is well known that in models with time-homogeneous local volatility functions and constant interest and dividend rates, the European Put prices are transformed into European Call prices by the simultaneous exchanges of the interest and dividend rates and of the strike and spot price of the underlying. This paper inv…

2006-12-21abs ↗pdf ↗

The study examines how including additional call option prices affects model-independent price bounds for exotic derivatives.

problem Improving model-independent price bounds for exotic derivatives using additional call option prices.
method Characterization of market settings that guarantee improved price bounds and exclusion of any improvement.
result The inclusion of additional call option prices can significantly impact model-independent price bounds.

An analytic method for pricing American call options is provided; followed by an empirical method for pricing Asian call options. The methodology is the pricing theory presented in "A Modern Theory of Random Variation", by Patrick Muldowney, 2012.

2015-07-11abs ↗pdf ↗

We investigate the position of the Buchen-Kelly density in a family of entropy maximising densities which all match European call option prices for a given maturity observed in the market. Using the Legendre transform which links the entropy function and the cumulant generating function, we show that it is both the uni…

2011-02-01abs ↗pdf ↗

We study the statistical regularities of opening call auction using the ultra-high-frequency data of 22 liquid stocks traded on the Shenzhen Stock Exchange in 2003. The distribution of the relative price, defined as the relative difference between the order price in opening call auction and the closing price of last tr…

2009-05-05abs ↗pdf ↗

We derive the Black-Scholes-Merton dual equation, which has exactly the same form as the Black-Scholes-Merton equation. The novel and general equation works for options with a payoff of homogeneous of degree one, including European, American, Bermudan, Asian, barrier, lookback, etc., and leads to new insights into pric…

2019-12-22abs ↗pdf ↗

There exist several methods how more general options can be priced with call prices. In this article, we extend these results to cover a wider class of options and market models. In particular, we introduce a new pricing formula which can be used to price more general options if prices for call options and digital opti…

2012-07-26abs ↗pdf ↗

The space of call price functions has a natural noncommutative semigroup structure with an involution. A basic example is the Black--Scholes call price surface, from which an interesting inequality for Black--Scholes implied volatility is derived. The binary operation is compatible with the convex order, and therefore …

2017-01-14abs ↗pdf ↗

Asymptotic expansions for call prices and implied volatilities in exponential Lévy models.

problem Developing precise call-price and implied volatility approximations for asset-price models.
method Analyzing the asymptotic behavior of at-the-money call prices and implied volatilities for Lévy-driven asset-price models.
result First-order asymptotic expansions for at-the-money call prices and implied volatilities in exponential Lévy models.

We show that the existence of an equivalent local martingale measure for asset prices does not prevent negative prices for European calls written on positive stock prices. In particular, we illustrate that many standard no-arbitrage arguments implicitly rely on conditions stronger than the No Free Lunch With Vanishing …

2012-04-09abs ↗pdf ↗

Study earnings calls to predict stock price movements, finding them more predictive than traditional data.

problem Improving investment decisions by analyzing earnings calls for stock price predictions.
method Graph Neural Network based approach to process and analyze earnings call transcripts.
result Earnings call transcripts are more predictive of stock price movements than traditional hard data.

The paper uses deep learning to detect asset price bubbles in tech stocks.

problem Detecting financial asset price bubbles using deep learning.
method Deep learning techniques applied to call option prices for financial asset bubbles detection.
result The proposed deep learning algorithm provides a theoretical foundation for positive and continuous stochastic asset price processes.

The call auction is a widely used trading mechanism, especially during the opening and closing periods of financial markets. In this paper, we study a standard call auction problem where orders are submitted according to Poisson processes, with random prices distributed according to a general distribution, and may be c…

2014-07-16abs ↗pdf ↗

Deep learning models price convertible bonds with complex reset and call features.

problem Pricing convertible bonds with path-dependent reset and call provisions.
method Formulated as a PPDE, deep learning approximates conditional expectations.
result Deep learning produces stable and accurate prices across various model specifications.

This paper analyzes a time-dependent CFMM called RMM-01, focusing on its pricing and stability.

problem Analyzing the pricing and stability of a time-dependent CFMM called RMM-01.
method Introducing the general framework for CFMMs, analyzing pricing properties, and examining time-varying price stability.
result Determining parameter bounds for RMM-01 to achieve a more stable price than Uniswap.

Robust, or model-independent properties of the variance swap are well-known, and date back to Dupire and Neuberger, who showed that, given the price of co-terminal call options, the price of a variance swap was exactly specified under the assumption that the price process is continuous. In Cox and Wang we showed that a…

2013-08-20abs ↗pdf ↗

In this paper, a standard PDE for the pricing of arithmetic average strike Asian call option is presented. A Crank-Nicolson Implicit Method and a Higher Order Compact finite difference scheme for this pricing problem is derived. Both these schemes were implemented for various values of risk free rate and volatility. Th…

2011-06-10abs ↗pdf ↗

Study asset price bubbles in markets with short sales prohibitions and model uncertainty.

problem Investigating asset price bubbles in markets with short sales prohibitions and model uncertainty.
method Introducing a novel definition of the fundamental price and analyzing the types and characterization of bubbles using a new fundamental theorem of asset pricing and superhedging duality.
result Two distinct types of bubbles arise depending on the maturity structure of the asset, and conditions for their existence are provided.

In this work, we expand the idea of Samuelson[3] and Shepp[2,5,6] for stock optimization using the Bachelier model [4] as our models for the stock price at the money (X[stock price]= K[strike price]) for the American call and put options [1]. At the money (X= K) for American options, the expected payoff of both the cal…

2009-02-26abs ↗pdf ↗

Quantum algorithm for pricing European call options.

problem Accurate valuation of financial derivatives, especially for complex models and options.
method Transforms classical FFT into quantum QFT for pricing European call options.
result Quantum algorithm outperforms classical Monte Carlo simulation in NISQ era.

Study large deviations in fractional volatility models with non-Gaussian volatility.

problem Large deviations in fractional volatility models with non-Gaussian volatility.
method Established a small-noise large deviation principle for log-price.
result Logarithmic call price asymptotics for large strikes in a special case.

Quantum effects improve stock option pricing model.

problem Persistent discrepancies between classical Black-Scholes model and actual stock prices.
method Introduced an additional pseudo-Wiener process to represent non-classical information.
result The norm of a complex quantity compensates for price discrepancies, providing market evidence for non-classical processes.

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 ↗

Alternative closed-form formula for spread call option prices under log-normal models.

problem Valuation of spread call options under log-normal models.
method Developed an alternative closed-form formula for spread call option prices.
result Our formula performs better for certain range of model parameters than existing closed-form formula.

We derive the implied volatility estimation formula in European power call options pricing, where the payoff functions are in the form of V=(STαK)+V=(S^α_T-K)^{+} and V=(STαKα)+V=(S^α_T-K^α)^{+} (α>0α>0)respectively. Using quadratic Taylor approximations, We develop the computing formula of implied volatility in European power call op…

2012-03-03abs ↗pdf ↗

In this paper, we price American-style Parisian down-and-in call options under the Black-Scholes framework. Usually, pricing an American-style option is much more difficult than pricing its European-style counterpart because of the appearance of the optimal exercise boundary in the former. Fortunately, the optimal exer…

2015-11-05abs ↗pdf ↗

We propose a neural network approach to price EU call options that significantly outperforms some existing pricing models and comes with guarantees that its predictions are economically reasonable. To achieve this, we introduce a class of gated neural networks that automatically learn to divide-and-conquer the problem …

2016-09-14abs ↗pdf ↗