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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.

168,657 papers · 148 categories

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8162432 · Nov 201919922001200920172026
48 results for treasury securities

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.

The study calculates securities lending haircuts and indemnification costs.

problem Managing borrower default risk in securities markets.
method Repo haircut model applied to securities lending transactions; quantifies haircuts and indemnification costs.
result Computed borrower-dependent haircuts and indemnification costs for US Treasuries and equities.

In this manuscript we analyse the leading statistical properties of fluctuations of (log) 3-month US Treasury bill quotation in the secondary market, namely: probability density function, autocorrelation, absolute values autocorrelation, and absolute values persistency. We verify that this financial instrument, in spit…

2007-06-08abs ↗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.

In fixed income sector, the yield curve is probably the most observed indicator by the market for trading and fifinancing purposes. A yield curve plots interest rates across different contract maturities from short end to as long as 30 years. For each currency, the corresponding curve shows the relation between the lev…

2018-08-10abs ↗pdf ↗

We reconsider the multivariate Kyle model in a risk-neutral setting with a single, perfectly informed rational insider and a rational competitive market maker, setting the price of n correlated securities. We prove the unicity of a symmetric, positive definite solution for the impact matrix and provide insights on its …

2018-06-20abs ↗pdf ↗

We introduce simple cost and risk proxy metrics that can be attached to Treasury issuance strategy to complement analysis of the resulting portfolio weighted-average maturity (WAM). These metrics are based on mapping issuance fractions to their long-term, asymptotic portfolio implications for cost and risk under mechan…

2018-02-09abs ↗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.

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 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 ↗

A robust machine learning approach forecasts U.S. Treasury yields, reducing risk for investors.

problem Noisy and uncertain U.S. Treasury yields pose risk to forecast users.
method Formulates yield curve forecasting as a distributionally robust problem, combining factor models and machine learning.
result Robust forecast combinations improve out-of-sample performance across different maturity periods.

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.

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 ↗

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 ↗

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 ↗

Funding is a cost to trading desks that they see as an input. Current FVA-related literature reflects this by also taking funding costs as an input, usually constant, and always risk-neutral. However, this funding curve is the output from a Treasury point of view. Treasury must consider Regulatory-required liquidity bu…

2013-10-12abs ↗pdf ↗

Machine learning models predict US economic recessions using Treasury term spreads.

problem Predicting US economic recessions using Treasury term spreads.
method Gradient Boosting and Random Forest methods trained with SHapley Additive exPlanations (SHAP) framework.
result 3 month to 6 month Treasury term spread is the most relevant for predicting US economic recession.

The paper extends MS models with TVTP to U.S. Treasury yields, finding reliable regime dynamics but challenging TVTP identification.

problem Identifying time-varying transition probabilities in Markov-switching models for U.S. Treasury yields.
method Developed a comprehensive MS model with TVTP, including simulations and an R package for estimation.
result Regime means, variances, and transition probabilities are reliably identified, but TVTP coefficients are harder to estimate.

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.

Study finds significant BTC co-movements with equity markets, highlighting dynamic risk management needs.

problem Understanding the impact of corporate Bitcoin holdings on equity markets.
method Dataset of 39 firms, daily returns analysis, Pearson correlations, single factor model regressions, transfer entropy.
result BTC has a significant positive beta with equity markets, with BTC as the dominant information driver.

This study examines whether tokenized assets improve liquidity and finds significant differences across categories.

problem Improving liquidity for real-world assets through tokenization.
method Examined tokenized real-world assets using Ethereum-based data, measuring liquidity through turnover, active addresses, and active-month indicator.
result Gold-backed tokens show more persistent on-chain activity than Treasury and private-credit-related products, but asset value alone does not reliably predict liquidity.

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 ↗

Study improves prediction of commodity futures using multi-factor model.

problem Improving accuracy in predicting commodity futures prices.
method State-space functional regression model incorporating yield curve dynamics.
result Functional regression model outperforms Schwartz-Smith model in estimating short-end of futures curve.

Optimizes a portfolio for an investor preferring accepted securities over a reference security.

problem Investor preference for a set of securities over a reference security with constraints.
method Mean-variance optimization with Sharpe Ratio performance measurement.
result Derives an optimal portfolio that maximizes returns while minimizing risk.

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 ↗

We say that a pair of points x and y is secure if there exist a finite set of blocking points such that any geodesic between x and y passes through one of the blocking points. The main point of this paper is to exhibit new examples of blocking phenomena both in the manifold and the billiard table setting. As an approac…

2007-07-03abs ↗pdf ↗

Sparse oblique decision tree improves security rules for renewable power systems.

problem Identifying secure operating conditions in power systems with high renewable energy.
method Sparse weighted oblique decision tree to learn and embed linear security rules.
result The method significantly increases secure states and reduces solution time.

A riemannian manifold is secure if the geodesics between any pair of points in the manifold can be blocked by a finite number of point obstacles. Compact, flat manifolds are secure. A standing conjecture says that these are the only secure, compact riemannian manifolds. The conjecture claims, in particular, that a riem…

2008-06-22abs ↗pdf ↗

Securely trains regression models with secret sharing for data collaboration.

problem Balancing data collaboration for technological improvements with security concerns.
method Secret sharing scheme for scalable and efficient secure multiparty training.
result Scalable and efficient protocols for training linear and logistic regression 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.