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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.

168,742 papers · 148 categories

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295886115 · Jan 202619922001200920172026
48 results for Treasury bond market

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.

Study uses VIX for zero-coupon Treasury rates, proving long-term stability and returns.

problem Modeling zero-coupon Treasury rates with VIX for volatility.
method Multivariate autoregressive stochastic volatility model, proving stability and Law of Large Numbers.
result VIX accurately models zero-coupon Treasury rates and returns.

We present cross and time series analysis of price fluctuations in the U.S. Treasury fixed income market. By means of techniques borrowed from statistical physics we show that the correlation among bonds depends strongly on the maturity and bonds' price increments do not fulfill the random walk hyphoteses.

2000-03-02abs ↗pdf ↗

We derive a closed-form formula for computing bond prices between coupon payments. Our results cover both the `Treasury' and the `Street' pricing methods used by sovereign and corporate issuers. We apply our formulas to two UK gilts, the 8% Treasury Gilt 2015, and the 0.5% Treasury Gilt 2022, and show that we can obtai…

2018-01-18abs ↗pdf ↗

We study the tick dynamical behavior of the bond futures in Korean Futures Exchange(KOFEX) market. Since the survival probability in the continuous-time random walk theory is applied to the bond futures transaction, the form of the decay function in our bond futures model is discussed from two kinds of Korean Treasury …

2002-12-17abs ↗pdf ↗

This paper proposes a Monte Carlo technique for pricing the forward yield to maturity, when the volatility of the zero-coupon bond is known. We make the assumption of deterministic default intensity (Hazard Rate Function). We make no assumption on the volatility of the yield. We actually calculate the initial value of …

2012-04-20abs ↗pdf ↗

We introduce the minority game theory for two kinds of the Korean treasury bond (KTB) in Korean futures exchange markets. Since we discuss numerically the standard deviation and the global efficiency for an arbitrary strategy, our case is found to be approximate to the majority game. Our result presented will be compar…

2005-03-01abs ↗pdf ↗

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 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.

The Heath-Jarrow-Morton (HJM) formulation of treasury bonds in terms of forward rates is recast as a problem in path integration. The HJM-model is generalized to the case where all the forward rates are allowed to fluctuate independently. The resulting theory is shown to be a two-dimensional Gaussian quantum field theo…

1998-09-14abs ↗pdf ↗

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.

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

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 study the evolution of probability distribution functions of returns, from the tick data of the Korean treasury bond (KTB) futures and the S$&$P 500 stock index, which can be described by means of the Fokker-Planck equation. We show that the Fokker-Planck equation and the Langevin equation from the estimated Kramers…

2005-12-22abs ↗pdf ↗

We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correl…

2013-12-05abs ↗pdf ↗

In general, homeowners refinance in response to a decrease in interest rates, as their borrowing costs are lowered. However, it is worth investigating the effects of refinancing after taking the underlying costs into consideration. Here we develop a synthetic mortgage calculator that sufficiently accounts for such cost…

2016-03-05abs ↗pdf ↗

The study proposes a new interest rate model that captures long-term periodicity in U.S. Treasury yields.

problem The conventional Hull-White model fails to adequately capture long-term economic cycles in interest rates.
method The study introduces a sinusoidal Hull-White model with a time-varying mean reversion speed.
result The proposed model improves bond pricing and interest rate derivative valuation, especially for longer maturities.

The herd behavior of returns is investigated in Korean futures exchange market. It is obtained that the probability distribution of returns for three types of herding parameter scales as a power law RβR^{-β} with the exponents β=3.6 β=3.6(KTB203) and 2.9(KTB209) in two kinds of Korean treasury bond. For our case since the…

2003-04-07abs ↗pdf ↗

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 ↗

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.

Survival strategy for crypto firms in bear markets using BTC-to-sats payments rail.

problem Downside risk in crypto reserves during bear markets.
method Conservative treasury policy, operating line monetizing holdings, BTC-to-sats payments rail.
result Sustained mNAV premium through cycles with disclosed KPIs.

A study finds that only a few factors explain corporate bond risk, rendering extensive bond factor literature redundant.

problem The redundancy of extensive bond factor literature in explaining corporate bond risk premia.
method Bayesian Model Averaging Stochastic Discount Factor analysis of 18 quadrillion models.
result A Bayesian Model Averaging SDF explains risk premia better than low-dimensional models, with an out-of-sample Sharpe ratio of 1.5 to 1.8.

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.

Study uses ML to predict currency and bond returns from news sentiment.

problem Predicting financial returns from news sentiment.
method Pretrained FinBERT model on finance-specific language, XGBoost classifier, SHAP for interpretability.
result XGBoost strategy outperforms benchmarks with Sharpe ratios > 5.

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.

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.

This paper analyzes tokenized U.S. Treasuries, revealing patterns and roles in blockchain transactions.

problem Limited empirical analysis of transaction-level behaviors in tokenized U.S. Treasuries.
method Quantitative dissection of U.S. Treasury-backed RWA tokens across multiple chains, introducing a curvature-aware representation learning model for address-level economic role inference.
result Decoded transaction-level patterns reveal the degree of retail participation and distinguish roles in Web3 finance.

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.

Tokenized RWAs face liquidity issues despite promising markets.

problem Low trading volumes and limited investor participation in tokenized assets.
method Empirical analysis of tokenized real estate, private credit, and treasury funds.
result Most tokenized assets exhibit low transfer activity and limited secondary trading.