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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.

169,181 papers · 148 categories

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481115 · Jun 202019922001200920182026
48 results for bond selling

Optimizes selling bonds with non-negative prices using a Brownian bridge model.

problem Maximizing the expected value of an exponential gain function on a Brownian bridge.
method Develops pathwise properties of the Brownian bridge and uses martingale methods of optimal stopping theory.
result Solves the stopping problem for the exponential of a Brownian bridge.

We study the pricing and the hedging of claim ψ which depends on the default times of two firms A and B. In fact, we assume that, in the market, we can not buy or sell any defaultable bond of the firm B but we can only trade defaultable bond of the firm A. Our aim is then to find the best price and hedging of ψ using o…

2012-09-26abs ↗pdf ↗

Analyzes transaction costs for corporate bonds using a new analytical methodology.

problem Challenges in assessing the quality of corporate bond executions via Transaction Cost Analysis.
method Analyzes TRACE Enhanced dataset to estimate initiator, bid-ask spread, and mid-price dynamics; applies regularized regression models and transient impact models.
result Identifies price impact asymmetry between customer-buy and consumer-sell orders.

Using a bondholder who seeks to determine when to sell his bond as our motivating example, we revisit one of Larry Shepp's classical theorems on optimal stopping. We offer a novel proof of Theorem 1 from from \cite{Shepp}. Our approach is that of guessing the optimal control function and proving its optimality with mar…

2016-05-03abs ↗pdf ↗

This paper uses CausalGANs and RL with LLM to predict bond yields.

problem Challenges in financial bond yield forecasting due to data scarcity and market conditions.
method Proposes a novel framework combining CausalGANs, RL, and LLM for synthetic data generation and trading signals.
result Improves forecasting performance over existing methods with low Mean Absolute Error.

A continuous-time Markowitz's mean-variance portfolio selection problem is studied in a market with one stock, one bond, and proportional transaction costs. This is a singular stochastic control problem,inherently in a finite time horizon. With a series of transformations, the problem is turned into a so-called double …

2009-06-03abs ↗pdf ↗

New method for valuing and hedging credit risk when defaults cannot be hedged.

problem Valuation and hedging of counterparty credit risk when there's no protection available.
method Local risk-minimization approach via BSDE (Backward Stochastic Differential Equation)
result Optimal strategy computed for valuing and hedging credit risk.

Model for equity trading with asynchronous price updates converging to a stationary return distribution.

problem Equity trading dynamics with asynchronous price updates and varying number of participants.
method Modeling agents' adaptive strategies and using numerical simulations to analyze returns.
result The model converges to a stationary return distribution, with mean returns influenced by adaptive mechanisms and agent interactions.

This article presents valuation of Treasury Bonds (T-Bonds) on Macedonian Stock Exchange (MSE) and empirical test of duration, modified duration and convexity of the T-bonds at MSE in order to determine sensitivity of bonds prices on interest rate changes. The main goal of this study is to determine how standard valuat…

2012-06-29abs ↗pdf ↗

Paper uses PCA to analyze Chinese sovereign bonds and discusses bond immunization.

problem Analyzing factors affecting Chinese sovereign bond yield changes.
method Applied Principal Component Analysis (PCA) on bond yield data.
result Identified principal factors influencing Chinese sovereign bond yield changes.

This paper describes a new method of bond portfolio optimization based on stochastic string models of correlation structure in bond returns. The paper shows how to approximate correlation function of bond returns, compute the optimal portfolio allocation using Wiener-Hopf factorization, and check whether a collection o…

2002-08-17abs ↗pdf ↗

Study finds implicit government guarantee improves municipal investment bond ratings.

problem Questioning the objectivity of municipal investment bond ratings due to implicit government guarantee.
method Text mining of policy documents and PMC index model for implicit guarantee strength calculation.
result Implicit government guarantee boosts municipal investment bond ratings, especially in less developed regions.

Classifies uncolored bonded knots with up to 7 singularity points.

problem Classifying uncolored bonded knots with up to 7 singularity points.
method Generation of planar graphs, conversion into bonded knot diagrams, use of Yamada polynomial, and brute-force Reidemeister moves.
result Systematic classification of uncolored bonded knots with singularity number at most seven.

Paper proposes a framework for precise daily default risk prediction of Chinese credit bonds.

problem Inadequate and inaccurate bond information disclosure creates risk of default for investors.
method Framework includes summarizing factors impacting defaults, constructing a risk index system, and using ConvLSTM neural network for prediction.
result The model provides more responsive and accurate daily default risk predictions than authoritative ratings.

Paper analyzes pricing model for bonds with early redemption.

problem Analyzing pricing of bonds with early redemption features.
method Structural approach for mathematical modeling of bond prices.
result Existence and uniqueness of default and early redemption boundaries proved.

We derive simple return models for several classes of bond portfolios. With only one or two risk factors our models are able to explain most of the return variations in portfolios of fixed rate government bonds, inflation linked government bonds and investment grade corporate bonds. The underlying risk factors have nat…

2010-11-14abs ↗pdf ↗

A machine learning model improves relative valuation of municipal bonds.

problem Challenges in determining the value or relative value of municipal bonds.
method Proposes a supervised similarity framework using CatBoost algorithm to identify similar bonds based on risk profiles.
result The similarity-based method outperforms rule-based and heuristic-based methods in back-testing.

Study proposes framework for cyber bonds to compensate cyber attack losses.

problem Cyber risk treatment in finance industry.
method Developed a framework, used publicly available data to determine loss distribution parameters, numerically simulated bond price and characteristics, considered two coupon calculation approaches.
result Numerical simulations of cyber bond price, yield, and characteristics.

Paper uses machine learning to uncover nonlinear dynamics in CAT bond pricing.

problem Traditional linear models miss nonlinear relationships in CAT bond pricing.
method Advanced machine learning techniques applied to CAT bond transaction records.
result Machine learning enhances CAT bond pricing accuracy and reveals complex risk interactions.

In this paper, we are concerned with the valuation of Catastrophic Mortality Bonds and, in particular, we examine the case of the Swiss Re Mortality Bond 2003 as a primary example of this class of assets. This bond was the first Catastrophic Mortality Bond to be launched in the market and encapsulates the behaviour of …

2016-07-24abs ↗pdf ↗

Paper proposes an analytical pricing model for puttable bonds with credit risk.

problem Analytical pricing of puttable bonds with credit risk.
method Developed a 2-factor structural PDE model and derived analytical pricing formula under specific conditions.
result Derived analytical pricing formula for puttable bonds with credit risk.

Study predicts bond yields using machine learning and ultimate forward rates.

problem Forecasting bond yields using ultimate forward rates.
method Applied de Kort-Vellekooptype methodology for UFR estimation, used linear and nonlinear machine learning techniques.
result Nonlinear machine learning models outperform linear models in bond yield forecasting.

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.

The paper optimizes investment strategies with constraints for life-cycle models.

problem Maximizing consumption, death benefit, and wealth under trading constraints.
method Deep pricing kernel approach to solve constrained portfolio optimization.
result Individuals reduce consumption, insurance demand, and wealth due to constraints.

Investors choose between bonds and savings accounts based on utility maximization.

problem Determining the optimal investment strategy in a stochastic interest rate environment.
method Analyzes utility maximization under two investment scenarios using affine term structure models.
result Bond indifference prices are found to be the roots of integral expressions.

To construct a no-arbitrage defaultable bond market, we work on the state price density framework. Using the heat kernel approach (HKA for short) with the killing of a Markov process, we construct a single defaultable bond market that enables an explicit expression of a defaultable bond and credit spread under quadrati…

2011-03-23abs ↗pdf ↗

A pricing formula for discount bonds, based on the consideration of the market perception of future liquidity risk, is established. An information-based model for liquidity is then introduced, which is used to obtain an expression for the bond price. Analysis of the bond price dynamics shows that the bond volatility is…

2009-05-01abs ↗pdf ↗