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.
Research aims to predict fallen angel bonds' bankruptcy using machine learning.
Satellite imagery improves house price prediction models.
Proves existence of minimal surfaces of arbitrary genus with two ends.
Ethereum upgrades increased TPS and lowered fees, with L2s surpassing Solana in 2029.
Accurate real time crime prediction is a fundamental issue for public safety, but remains a challenging problem for the scientific community. Crime occurrences depend on many complex factors. Compared to many predictable events, crime is sparse. At different spatio-temporal scales, crime distributions display dramatica…
Study of bonded knots and braids with new algebraic models.
Developed algebraic theory of bonded braids, proving Markov theorem.
Study finds it hard to establish common factor pricing in corporate bonds.
In the present paper we show that the Binomial-tree approach for pricing, hedging, and risk assessment of Convertible bonds in the framework of the Tsiveriotis-Fernandes model has serious drawbacks. Key words: Convertible bonds, Binomial tree, Tsiveriotis-Fernandes model, Convertible bond pricing, Convertible bond Gree…
Model shows government incentives boost green bond investment.
Model proteins with bonds using Kauffman bracket skein module.
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…
Bayesian method for imputing actigraph data from mobile devices.
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…
Study finds implicit government guarantee improves municipal investment bond ratings.
Classifies uncolored bonded knots with up to 7 singularity points.
Paper proposes a framework for precise daily default risk prediction of Chinese credit bonds.
In this paper, we study hyperkahler metric and practice GMN's construction of hyperkahler metric on focus-focus fibrations. We explicitly compute the action-angel coordinates on the local model of focus-focus fibration, and show its semi-global invariant should be harmonic to admit a compatible holomorphic 2-form. Then…
We show that the martingale component in the long-term factorization of the stochastic discount factor due to Alvarez and Jermann (2005) and Hansen and Scheinkman (2009) is highly volatile, produces a downward-sloping term structure of bond Sharpe ratios, and implies that the long bond is far from growth optimality. In…
Paper analyzes pricing model for bonds with early redemption.
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…
A machine learning model improves relative valuation of municipal bonds.
We propose an option approach for pricing bond illiquidity that is reminiscent of the celebrated work of Longstaff (1995) on the non-marketability of some non-dividend-paying shares in IPOs. This approach describes a quite common situation in the fixed income market: it is rather usual to find issuers that, besides liq…
Paper uses machine learning to uncover nonlinear dynamics in CAT bond pricing.
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 …
Deep learning speeds CAT bond valuation.
Paper proposes an analytical pricing model for puttable bonds with credit risk.
BondBERT improves sentiment analysis for bond markets.
Study predicts bond yields using machine learning and ultimate forward rates.
The paper uses option theory to estimate corporate bond liquidity spreads.
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 …
Investor optimizes consumption and investment in a bond market described by HJM model.
We present an avatar of the Euler obstruction to foliated structures on certain non-metric surfaces. This adumbrates (at least for the simplest 2D-configurations) that the standard mechanism---to the effect that the devil of algebra sometimes barricades the existence of angelic geometric structures (obstruction theory …
Study analyzes bond traders' views on equity market dynamics.
The article studies random infinite ideal hyperbolic polyhedra and their dual graphs, establishing new boundary theories.
Risk-only investment strategies have been growing in popularity as traditional in- vestment strategies have fallen short of return targets over the last decade. However, risk-based investors should be aware of four things. First, theoretical considerations and empirical studies show that apparently dictinct risk-based …
Deep learning models price convertible bonds with complex reset and call features.
In this three-part series of papers, we argue that the conventional spread measures are not well defined for credit-risky bonds and introduce a set of credit term structures which correct for the biases associated with the strippable cash flow valuation assumption. We demonstrate that the resulting estimates are signif…
Investors choose between bonds and savings accounts based on utility maximization.
Matrix factorization was used to generate investment recommendations for investors. An iterative conjugate gradient method was used to optimize the regularized squared-error loss function. The number of latent factors, number of iterations, and regularization values were explored. Overfitting can be addressed by either…
Method estimates travel times on urban roads using Uber data.
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…
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…
Random forest predicts catastrophe bond spreads with 93% accuracy.
Corporate bond factor research is flawed due to measurement errors and ex-post filtering.
Approximates bond option volatilities using affine short-rate models.
Unified framework for pricing various debt securities.
Motivated by the developments in cyber risk treatment in the finance industry, we propose a general framework of cyber bond, whose main purpose is to insure (compensate) losses of a cyber attack. Based on a database of publicly available cyber events, we determine cyber loss distribution parameters and use them to nume…