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Results for “backwardation” · papers 18 · wiki 4
Academic Papers · 18arXiv q-fin live 18 · desk corpus 0
arXiv · arXiv q-fin · 2019

Latency and Liquidity Risk

Latency (i.e., time delay) in electronic markets affects the efficacy of liquidity taking strategies. During the time liquidity takers process information and send marketable limit orders (MLOs) to the exchange, the limit order book (LOB) might undergo updates, so there is no guarantee that MLOs are filled. We develop a latency-optimal trading strategy that improves the marksmanship of liquidity takers. The interacti

Álvaro Cartea, Sebastian Jaimungal, Leandro Sánchez-Betancourt
arXiv · arXiv q-fin · 2010

Applications of time-delayed backward stochastic differential equations to pricing, hedging and portfolio management

In this paper we investigate novel applications of a new class of equations which we call time-delayed backward stochastic differential equations. Time-delayed BSDEs may arise in finance when we want to find an investment strategy and an investment portfolio which should replicate a liability or meet a target depending on the applied strategy or the past values of the portfolio. In this setting, a managed investment

Lukasz Delong
arXiv · arXiv q-fin · 2026

Reaction-boundary variance and adjoint-consistent local-volatility projection

We derive an operational-time variance kernel for a latent-order-book reaction boundary and use it to separate three objects usually collapsed in calendar-time volatility models: a structural boundary cumulant, a clock projection, and a pricing-measure choice. The reaction boundary is the zero of a bid--ask imbalance field. For a locally linear book, signed order-flow perturbations displace this zero through a damped

Chris Angstmann, Tim Gebbie
arXiv · arXiv q-fin · 2019

An FBSDE approach to market impact games with stochastic parameters

We analyze a market impact game between $n$ risk averse agents who compete for liquidity in a market impact model with permanent price impact and additional slippage. Most market parameters, including volatility and drift, are allowed to vary stochastically. Our first main result characterizes the Nash equilibrium in terms of a fully coupled system of forward-backward stochastic differential equations (FBSDEs). Our s

Samuel Drapeau, Peng Luo, Alexander Schied, Dewen Xiong
arXiv · arXiv q-fin · 2026

optimal credit portfolio and consumption with regime switching and default contagion

We study optimal portfolio and consumption in a regime-switching multi-name credit market with default contagion. Defaults generate portfolio losses and alter the intensities of surviving securities. Under Cobb--Douglas utility, homogeneity reduces the HJB equation to a recursive ODE system indexed by the default states. Solving it backward from the all-default state, we establish existence and uniqueness of positive

Fei Sun, Wenyuan Wang, Kaixin Yan
arXiv · arXiv q-fin · 2026

Visibility graphs can make money in financial markets

Traditional technical analysis indicators, although widely used by market participants, are often not sufficiently effective. We propose the Visibility Graphs Relative Strength Index (VGRSI), based on backward visibility relations in the price of a financial instrument. Rescaled to the 0--100 range, it can generate profitable trading signals. The performance of the indicator was evaluated using an automated trading s

Rafał Rak
arXiv · arXiv q-fin · 2025

Causal PDE-Control Models for Dynamic Portfolio Optimization with Latent Drivers

Classical portfolio models degrade under structural breaks, whereas flexible machine-learning allocation methods often lack arbitrage consistency and interpretability. We propose Causal PDE-Control Models (CPCMs), a framework that integrates structural causal drivers, nonlinear filtering, and forward-backward PDE control to produce robust and transparent allocation rules under partial information. We construct driver

Alejandro Rodriguez Dominguez
arXiv · arXiv q-fin · 2023

Integrating Different Informations for Portfolio Selection

Following the idea of Bayesian learning via Gaussian mixture model, we organically combine the backward-looking information contained in the historical data and the forward-looking information implied by the market portfolio, which is affected by heterogeneous expectations and noisy trading behavior. The proposed combined estimation adaptively harmonizes these two types of information based on the degree of market ef

Yi Huang, Wei Zhu, Duan Li, Shushang Zhu, Shikun Wang
arXiv · arXiv q-fin · 2021

Mean-Variance Portfolio Selection in Contagious Markets

We consider a mean-variance portfolio selection problem in a financial market with contagion risk. The risky assets follow a jump-diffusion model, in which jumps are driven by a multivariate Hawkes process with mutual-excitation effect. The mutual-excitation feature of the Hawkes process captures the contagion risk in the sense that each price jump of an asset increases the likelihood of future jumps not only in the

Yang Shen, Bin Zou
arXiv · arXiv q-fin · 2020

Insider Trading with Temporary Price Impact

We model an informed agent with information about the future value of an asset trying to maximize profits when subjected to a transaction cost as well as a market maker tasked with setting fair transaction prices. In a single auction model, equilibrium is characterized by the unique root of a particular polynomial. Analysis of this polynomial with small levels of risk-aversion and transaction costs reveal a dimension

Weston Barger, Ryan Donnelly
arXiv · arXiv q-fin · 2019

Introduction to Solving Quant Finance Problems with Time-Stepped FBSDE and Deep Learning

In this introductory paper, we discuss how quantitative finance problems under some common risk factor dynamics for some common instruments and approaches can be formulated as time-continuous or time-discrete forward-backward stochastic differential equations (FBSDE) final-value or control problems, how these final value problems can be turned into control problems, how time-continuous problems can be turned into tim

Bernhard Hientzsch
arXiv · arXiv q-fin · 2019

Mean-variance portfolio selection under partial information with drift uncertainty

In this paper, we study the mean-variance portfolio selection problem under partial information with drift uncertainty. First we show that the market model is complete even in this case while the information is not complete and the drift is uncertain. Then, the optimal strategy based on partial information is derived, which reduces to solving a related backward stochastic differential equation (BSDE). Finally, we pro

Jie Xiong, Zuo quan Xu, Jiayu Zheng
arXiv · arXiv q-fin · 2019

An optimal transport problem with backward martingale constraints motivated by insider trading

We study a single-period optimal transport problem on $\mathbb{R}^2$ with a covariance-type cost function $c(x,y) = (x_1-y_1)(x_2-y_2)$ and a backward martingale constraint. We show that a transport plan $γ$ is optimal if and only if there is a maximal monotone set $G$ that supports the $x$-marginal of $γ$ and such that $c(x,y) = \min_{z\in G}c(z,y)$ for every $(x,y)$ in the support of $γ$. We obtain sharp regularity

Dmitry Kramkov, Yan Xu
arXiv · arXiv q-fin · 2018

Pricing Financial Derivatives Subject to Counterparty Risk and Credit Value Adjustment

This article presents a generic model for pricing financial derivatives subject to counterparty credit risk. Both unilateral and bilateral types of credit risks are considered. Our study shows that credit risk should be modeled as American style options in most cases, which require a backward induction valuation. To correct a common mistake in the literature, we emphasize that the market value of a defaultable deriva

David Lee
arXiv · arXiv q-fin · 2018

Mean Field Games with Partial Information for Algorithmic Trading

Financial markets are often driven by latent factors which traders cannot observe. Here, we address an algorithmic trading problem with collections of heterogeneous agents who aim to perform optimal execution or statistical arbitrage, where all agents filter the latent states of the world, and their trading actions have permanent and temporary price impact. This leads to a large stochastic game with heterogeneous age

Philippe Casgrain, Sebastian Jaimungal
arXiv · arXiv q-fin · 2017

Stock Trading Using PE ratio: A Dynamic Bayesian Network Modeling on Behavioral Finance and Fundamental Investment

On a daily investment decision in a security market, the price earnings (PE) ratio is one of the most widely applied methods being used as a firm valuation tool by investment experts. Unfortunately, recent academic developments in financial econometrics and machine learning rarely look at this tool. In practice, fundamental PE ratios are often estimated only by subjective expert opinions. The purpose of this research

Haizhen Wang, Ratthachat Chatpatanasiri, Pairote Sattayatham
arXiv · arXiv q-fin · 2015

Effect of Volatility Clustering on Indifference Pricing of Options by Convex Risk Measures

In this article, we look at the effect of volatility clustering on the risk indifference price of options described by Sircar and Sturm in their paper (Sircar, R., & Sturm, S. (2012). From smile asymptotics to market risk measures. Mathematical Finance. Advance online publication. doi:10.1111/mafi.12015). The indifference price in their article is obtained by using dynamic convex risk measures given by backward stoch

Rohini Kumar
arXiv · arXiv q-fin · 2011

An algorithm for calculating the set of superhedging portfolios in markets with transaction costs

We study the explicit calculation of the set of superhedging portfolios of contingent claims in a discrete-time market model for d assets with proportional transaction costs. The set of superhedging portfolios can be obtained by a recursive construction involving set operations, going backward in the event tree. We reformulate the problem as a sequence of linear vector optimization problems and solve it by adapting k

Andreas Löhne, Birgit Rudloff
Wiki Entities · 4
Option Blackboard · 0
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Encyclopedia · 3
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