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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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20406080 · Jun 202019922001200920172026
48 results for bonding curve

Neural network model improves robustness of mortgage bond yield curve estimation.

problem Overfitting and instability in traditional yield curve estimation methods for small mortgage bond markets.
method Neural network framework with a new loss function for smoothness and stability.
result Empirical results show more robust and stable yield curve estimates compared to existing methods.

The paper explains how to construct a credit spread curve from bond prices.

problem The challenge of constructing a credit spread curve from bond prices.
method Fit parametrised survival curves to construct the curve, avoiding the Z-spread issue.
result A concise treatment of the high-dollar price bonds trading at higher yields is explained.

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.

Optimizes bond portfolios to avoid worst-case losses.

problem Finding the worst-case value of a bond portfolio over a range of yield curves and spreads.
method Solves a convex-concave saddle point optimization problem to find the worst-case value and construct a robust portfolio.
result Constructs a bond portfolio that includes the worst-case value, ensuring robustness against market uncertainties.

Develops a new model to better predict corporate bond yields.

problem Persistent shifts in interest rates undermine single-regime models.
method Regime-switching generalized CIR model with two-state short-rate process and credit factors.
result The model improves joint curve fit and delivers interpretable probabilities.

Deep learning framework for bond and yield curve forecasting with no-arbitrage constraints.

problem Arbitrage-free yield curve and bond price forecasting.
method Combines Kalman, extended Kalman, and particle filters with LSTM/CLSTM, and introduces AER term.
result Arbitrage regularization improves forecast accuracy, especially at short maturities.

Paper proposes embedding models to capture semantic similarities of categorical attributes in financial bonds.

problem Challenges in finding similar bonds due to overshadowing of categorical non-financial attributes.
method Embedding models to capture semantic similarities of categorical attributes.
result Improves risk modeling and curve construction via sparse-issuer augmentation.

We equip a knot KK with a set of colored bonds, that is, colored intervals properly embedded into R3K\mathbb{R}^3 \setminus K. Such a construction can be viewed as a structure that topologically models a closed protein chain including any type of bridges connecting the backbone residues. We introduce an invariant of su…

2019-10-10abs ↗pdf ↗

This paper tackles missing data in Burundian bond market yield curves.

problem Missing data challenges accurate yield curve construction in Burundian sovereign bond market.
method Exploration of data limitations, proposing and testing various imputation methods (LR, Previous value, miss-Forest, Next value).
result Linear Regression method performs best across variables, approximating normal distribution for error values.

There is an observed basis between repo discounting, implied from market repo rates, and bond discounting, stripped from the market prices of the underlying bonds. Here, this basis is explained as a convexity effect arising from the decorrelation between the discount rates for derivatives and bonds. Using a Hull-White …

2019-05-08abs ↗pdf ↗

This paper uses crypto derivatives data to estimate yield curves for cryptocurrencies.

problem Estimating yield curves for cryptocurrencies without bond markets.
method Using mathematical tools and data from cryptocurrency derivatives markets.
result Yield curves can be constructed for cryptocurrencies using derivative data.

We model bond's price curves corresponding to the sovereign uruguayan debt nominated in USD, as an alternative to the official bond prices publication released by the Central Bank of Uruguay (CBU). Four different gaussian models are fitted, based on historical data issued by the CBU, corresponding to some of the more f…

2015-08-01abs ↗pdf ↗

The paper uses daily bond price data to estimate corporate default spreads, improving credit risk assessment.

problem Outdated credit risk information from quarterly accounting items.
method Adapting classic yield curve estimation methods to corporate bonds, using Bayesian estimation.
result High-frequency credit risk proxy via corporate default spreads improves model stability and prediction uncertainty.

Empirical study on long-term discount rates using historical bond prices.

problem Estimating long-term real interest rates and discount rates from historical bond data.
method Using Fourier transforms to derive the discount function and fitting it to historical data.
result Estimated long-term discount rates of 1.7% for UK and 2.2% for US.

Yield curve modeling is an essential problem in finance. In this work, we explore the use of Bayesian statistical methods in conjunction with Nelson-Siegel model. We present the hierarchical Bayesian model for the parameters of the Nelson-Siegel yield function. We implement the MAP estimates via BFGS algorithm in rstan…

2018-09-17abs ↗pdf ↗

Interest-rate risk is a key factor for property-casualty insurer capital. P&C companies tend to be highly leveraged, with bond holdings much greater than capital. For GAAP capital, bonds are marked to market but liabilities are not, so shifts in the yield curve can have a significant impact on capital. Yield-curve scen…

2019-12-22abs ↗pdf ↗

Machine learning models outperform traditional econometric methods for forecasting term structure of government bonds

problem Forecasting the term structure of government bonds
method Combining traditional econometric models with neural network architectures
result Neural network models consistently outperform traditional models in both forecasting accuracy and portfolio performance

The utility-based pricing of defaultable bonds in the case of stochastic intensity models of default risk is discussed. The Hamilton-Jacobi- Bellman (HJB) equations for the value functions is derived. A finite difference method is used to solve this problem. The yield-spreads for both buyer and seller are extracted. Th…

2010-03-22abs ↗pdf ↗

In this paper we present a rigorously motivated pricing equation for derivatives, including general cash collateralization schemes, which is consistent with quoted market bond prices. Traditionally, there have been differences in how instruments with similar cash flow structures have been priced if their definition fal…

2014-06-22abs ↗pdf ↗

This study models Burundi's bond market yield curve using Nelson-Siegel and Svensson models.

problem Modeling the yield curve of Burundian bond market for financial analytics.
method Collected treasury securities auction reports, computed zero-coupon rates, and applied Nelson-Siegel and Svensson models.
result Nelson-Siegel model is optimal for Burundian yield curve modeling.

We derive an equation of motion for interest-rate yield curves by applying a minimum Fisher information variational approach to the implied probability density. By construction, solutions to the equation of motion recover observed bond prices. More significantly, the form of the resulting equation explains the success …

2005-07-13abs ↗pdf ↗

We introduce a Vasicek-type short rate model which has two additional parameters representing memory effect. This model presents better results in yield curve fitting than the classical Vasicek model. We derive closed-form expressions for the prices of bonds and bond options. Though the model is non-Markov, there exist…

2015-04-07abs ↗pdf ↗

Proposes a bond portfolio solution for managing interest rate risk.

problem Managing long-term assets and liabilities under interest rate risk.
method Proposes a bond portfolio solution based on ambiguity-averse preferences, accommodating various constraints and interest rate perturbations.
result Optimal portfolio can be computed as a simple generalized least squares problem, enhancing out-of-sample performance.

Adaptive market maker curves minimize arbitrage losses in DeFi.

problem Asset trading prices in AMMs trail behind centralized exchanges, causing LP losses.
method Adapts market maker bonding curves to trader behavior using a differential equation derived from the Glosten-Milgrom model.
result Optimal adaptive curves minimize arbitrage losses while remaining competitive.

A new model explains relative spreads between economies using dynamic Nelson-Siegel and functional regression.

problem Analyzing and predicting relative spreads between economies in fixed income markets.
method State-space functional regression model incorporating dynamic Nelson-Siegel model and kernel PCA.
result The new model outperforms the dynamic Nelson-Siegel model in explaining relative spreads.

Group Shapley evaluates feature groups in business data, improving explainability in AI.

problem Evaluating the importance of feature groups in business and economic data.
method Developed Group Shapley and a significance testing procedure based on chi-square approximation.
result Market-related variables are identified as the most influential feature group.

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 ↗

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 ↗

We discuss a simple extension of the Ho and Lee model with generic time-dependent drift in which: 1) we compute bond prices analytically; 2) the yield curve is sensible and the asymptotic yield is positive; and 3) our analytical solution provides a clean and simple way of separating volatility from the drift in the sho…

2015-02-21abs ↗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.