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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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275380106 · May 202619922001200920172026
48 results for bond trading

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 ↗

The paper explains the fair basis in bond-CDS trading during financial crises.

problem Large basis trading losses during financial crises are not explained by reduced form models.
method Dynamic spread model with bond repo financing, economic capital approach.
result Unhedged and unhedgeable residual jump to default risk exists, affecting fair basis level.

The study shows how trade uncertainty affects stock-bond correlations over time.

problem Impact of trade policy uncertainty on stock-bond correlations.
method Daily data analysis using GARCH-based models (CCC, STCC, DCC) with TPU and political dummy variables.
result Time-varying correlation models better capture the dynamics of stock-bond correlations than constant models.

Bond prices are a reflection of extremely complex market interactions and policies, making prediction of future prices difficult. This task becomes even more challenging due to the dearth of relevant information, and accuracy is not the only consideration--in trading situations, time is of the essence. Thus, machine le…

2017-03-31abs ↗pdf ↗

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 ↗

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.

ABM simulates OTC government bond market dynamics, enhancing liquidity and stability.

problem Understanding and ensuring market stability and liquidity in OTC government bond markets.
method Developed a bespoke ABM to simulate market-maker interactions and test hypotheses.
result Greater agent diversity enhances market liquidity and reducing market-making costs improves stability.

Investigates how 'green' labels affect bond market dynamics.

problem Understanding the impact of 'green' labels on bond market trading activity.
method Used Hawkes processes and a moving average model to analyze high-frequency bond price dynamics.
result Differences in bond market dynamics emerge during periods with interest rate announcements, especially for energy market issuers.

The electronic platform has been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Transaction Cost Analysis (TCA). One of the challenges in TCA is to build a realistic benchmark for the expected transaction cost and to chara…

2019-03-21abs ↗pdf ↗

Quantum computing improves fill probability estimation in bond trading.

problem Estimating fill probabilities in complex financial markets with uncertainties.
method Quantum learning algorithms applied to real bond trading data.
result Quantum-enhanced models achieve up to 34% better performance in fill prediction.

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.

TRIBE model uses LLMs to simulate human trading behavior in bond markets.

problem Complexities in decentralized bond market transactions.
method Agent-based model augmented with LLMs to simulate human-like decision-making.
result Slight trade aversion in LLMs can lead to complete market collapse.

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.

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.

I explain the root of persistent failure of efforts to remove tax-induced distortions of economic incentives. It lies in FUNDAMENTAL IMPOSSIBILITY of objectively evaluating tax base. Distortions can be entirely avoided in the sector of publicly traded corporations. Evaluation can be bypassed by taxing it in shares (to …

2000-12-18abs ↗pdf ↗

The paper assesses how equity tail risk impacts US Treasury bond returns.

problem The effects of equity tail risk on the US government bond market.
method Estimating equity tail risk using option-implied stock market volatility and assessing its predictive power in reduced-form regressions and a term structure model.
result Equity tail risk significantly predicts one-month excess returns on Treasuries.

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 ↗

This paper improves bond market making by adjusting hit-ratios for client flow quality.

problem Economic misleading of raw hit-ratios in corporate bond market making.
method Stochastic-control framework with residual-quality-adjusted hit-ratio.
result Optimal quotes decompose into various components, improving service/economics frontier.

We apply the Continuous Time Random Walk (CTRW) framework, introduced in finance by Scalas et al., to the analysis of the probability distribution of time intervals between two consecutive trades in the case of BTP futures prices traded at LIFFE in 1997. Results corroborate the validity of the CTRW approach for the des…

2000-12-28abs ↗pdf ↗

Shorting IG ETFs can hedge bond portfolios during market drawdowns effectively.

problem Managing downside risk in bond portfolios during market crises.
method Constructing three signals (Momentum, Liquidity, Credit) to dynamically hedge short IG positions.
result Dynamic hedge removes when predicted hedged return mean reverts, achieving higher returns and Sortino ratios.

We consider an optimal consumption/investment problem to maximize expected utility from consumption. In this market model, the investor is allowed to choose a portfolio which consists of one bond, one liquid risky asset (no transaction costs) and one illiquid risky asset (proportional transaction costs). We fully chara…

2016-02-23abs ↗pdf ↗

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.

The study identifies features making cross-impact relevant in explaining price variance of US assets.

problem Understanding the relevance of cross-impact in explaining price variance of US assets.
method Using tick-by-tick data spanning 5 years for 500 US assets, the study investigates the features making cross-impact relevant.
result Price formation is endogenous within highly liquid assets, influencing less liquid correlated products with a constrained impact velocity.

Paper proposes a supervised similarity framework for corporate bonds using RF proximities.

problem Challenges in measuring similarity for corporate bonds due to noisy data and lack of ground truth.
method Proposes a supervised similarity framework using Random Forest for corporate bonds, introducing a novel metric to evaluate similarities.
result Random Forest outperforms other methods in evaluating similarities for corporate bonds.

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

Financial markets provide a natural quantitative lab for understanding some of the most advanced human behaviours. Among them is the use of mathematical tools known as financial instruments. Besides money, the two most fundamental financial instruments are bonds and equities. More than 30 years ago Mehra and Prescott f…

2015-07-26abs ↗pdf ↗

TraderTalk uses LLMs to simulate human trading interactions in financial markets.

problem Simulating realistic human trading interactions in financial markets.
method Hybrid ABM with LLM-generated behaviors for detailed conversations.
result Successfully replicates trade-to-order volume ratios in financial markets.

We propose a model for equity trading in a population of agents where each agent acts to achieve his or her target stock-to-bond ratio, and, as a feedback mechanism, follows a market adaptive strategy. In this model only a fraction of agents participates in buying and selling stock during a trading period, while the re…

2018-09-25abs ↗pdf ↗

Study forecasts U.S. bond index using deep learning, finding persistence is key.

problem Forecasting U.S. aggregate bond index with deep learning methods.
method Constructed a stationary but maximally persistent representation of the bond index, evaluated using MLPs and CNNs.
result Deep learning models outperform traditional methods in short-horizon forecasting of bond indices.

TradeMech nets trades without changing counterparty relationships.

problem Netting trades without altering counterparty exposure in complex financial networks.
method Transforms contracts into chains and cycles, nets designated object multilaterally, and replaces contracts with new multiparty agreements.
result Maximal multilateral netting of a designated object while preserving each agent's profit and counterparty risk.

We discuss risk measures representing the minimum amount of capital a financial institution needs to raise and invest in a pre-specified eligible asset to ensure it is adequately capitalized. Most of the literature has focused on cash-additive risk measures, for which the eligible asset is a risk-free bond, on the grou…

2012-06-03abs ↗pdf ↗