Paper uses PCA to analyze Chinese sovereign bonds and discusses bond immunization.
problem Analyzing factors affecting Chinese sovereign bond yield changes.
method Applied Principal Component Analysis (PCA) on bond yield data.
result Identified principal factors influencing Chinese sovereign bond yield changes.
Model prices sovereign contingent convertible bonds during crises.
problem Pricing Sovereign Contingent Convertible bonds (S-CoCo) during crises.
method Model CDS spread regime switching as a hidden Markov process, coupled with a mean-reverting stochastic process. Use Longstaff-Schwartz American option pricing framework for simulation.
result Computed future state contingent S-CoCo prices for risk management.
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.
New model explains low interest rates and large bond market jumps.
problem Explaining recent observations in sovereign bond market.
method Introduces α-CIR model using α-stable Lévy process and branching property. result Unified and parsimonious model for low interest rates and large jumps.
Investigates modeling emerging market bonds as FtD baskets.
problem Modeling emerging market corporate bonds as FtD baskets.
method Uses structural model to modify FtD basket approach.
result Approach feasible for modeling emerging market bonds.
This paper examines how ESG factors influence sovereign bond yields and credit ratings.
problem The impact of ESG factors on sovereign bond yields and credit ratings is not fully understood.
method The study identifies relevant ESG indicators and compares their importance in bond pricing and credit ratings.
result ESG factors, particularly the G and S pillars, are more important for credit ratings than the E pillar.
Study examines how COVID-19 affects bond yields using network filtering methods.
problem Impact of COVID-19 on sovereign bond yields.
method Network filtering methods applied to a correlation matrix of sovereign bond yields.
result Mean correlation decreases across all filtering methods during the COVID-19 period.
The study examines how climate risk influences sovereign debt default decisions.
problem The relationship between climate risk and sovereign debt default decisions.
method Calibration of a model to analyze the credit spreads of sovereign bonds and the impact of climate vulnerability on bond spreads.
result Climate risk does not significantly influence the decision to default on sovereign debt.
Study Italian sovereign bonds pricing using multi-factor models.
problem Empirical analysis of multi-factor models for Italian sovereign bonds.
method Calibration of Cox-Ingersoll-Ross and Vasicek models using Kalman filter and maximum likelihood estimation.
result Optimization algorithms improve term structure fitting over 12 years, including financial crises.
BondBERT improves sentiment analysis for bond markets.
problem Misleading sentiment models for bond markets due to domain-specific dynamics.
method Fine-tuned transformer model on bond-specific news.
result BondBERT produces positive correlations with bond returns and higher forecasting accuracy.
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…
The study extends a framework to analyze cross-impact in multi-asset markets.
problem Analyzing cross-impact and no-dynamic-arbitrage in multi-asset markets.
method Deriving theoretical limits for cross-impact from the condition of absence of dynamical arbitrage, testing these constraints with data.
result Significant violations of cross-impact symmetry found, but not exploitable due to bid-ask spread.
We use principle component analysis (PCA) of cross correlations in European government bonds and European stocks to investigate the systemic risk contained in the European economy. We tackle the task to visualize the evolution of risk, introducing the conditional average rolling sum (CARS). Using this tool we see that …
Study assesses risks of European Safe Bonds using credit risk models.
problem Risks associated with European Safe Bonds and related securities.
method Affine credit risk model with regime switching.
result ESBies are not truly risk-free, impacting market and policy implications.
Study on systemic risk in European insurance sector, showing insurer connections during stress.
problem Understanding systemic risk connectedness in European insurance sector.
method Common connectedness framework applied to returns, volatility, value-at-risk, and expected shortfall.
result Insurers are a significant component of systemic risk connectedness, especially during stress episodes.
Study finds no significant impact of US sovereign credit rating downgrade on equity market.
problem Impact of US sovereign credit rating downgrade on US equity market.
method Event study methodology using three companies and S&P500 index.
result No significant effects of US sovereign credit rating downgrade on US equity market.
Formula calculates bond prices between payments.
problem No new bond pricing formula available.
method Closed-form formula derivation.
result Formula accurately calculates bond prices.
Tether's dominance in U.S. Treasury bills lowers bond yields by 24 basis points.
problem Impact of Tether's market share on U.S. Treasury bill yields.
method Baseline semi-log time trend model and threshold regression analysis.
result Tether's market share reduces 1-month yields by 24 basis points.
Optimizes financial portfolios to minimize systemic risk.
problem Minimizing systemic risk in financial markets.
method Network optimization to rearrange overlapping portfolios.
result Systemic risk can be reduced by more than a factor of two without harming individual banks.
New clustering method for financial data with known cluster number.
problem Clustering financial data with known number of clusters.
method Introduced a covariance-based dissimilarity measure for multifractional Brownian motions.
result Asymptotically consistent clustering algorithms for multifractional Brownian motions.
A new formula for pricing illiquid corporate bonds.
problem Pricing bonds with limited liquidity in the market.
method Option approach with reduced-form interest and credit risk modeling.
result A simple closed formula for illiquid corporate coupon bond prices.
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.
Repo dealers' market power affects bond prices by up to 2 percentage points.
problem Market power of repo dealers impacts bond prices and liquidity.
method Proprietary data on repo and reverse-repo trades analyzed.
result Market power of repo dealers accounts for 0.5-1.3 percentage points of bond yield deviation.
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.
We propose a model for the credit markets in which the random default times of bonds are assumed to be given as functions of one or more independent "market factors". Market participants are assumed to have partial information about each of the market factors, represented by the values of a set of market factor informa…
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.
The paper uses option theory to estimate corporate bond liquidity spreads.
problem Estimating liquidity spreads for corporate bonds.
method Option-theoretic approach considering risk-free rate volatility and credit risk.
result The model provides a robust tool for pricing illiquid bonds.
Investor optimizes consumption and investment in a bond market described by HJM model.
problem Maximizing consumption utility in a bond market with varying maturity bonds.
method Solves consumption-investment problem using HJM factor model and HJB equation.
result Proves the regularity of the solution and applicability of the verification theorem.
Study analyzes bond traders' views on equity market dynamics.
problem Understanding temporal shifts in equity market parameters.
method Utilizes Black-Derman-Toy model and zero-coupon bond pricing.
result Discovers correlations between risk-neutral probability and market variables.
The study models and values CAT bonds across multiple regions.
problem Valuation of CAT bonds with dependencies across different regions.
method Developed models for independent, proportional, and arbitrary two-dimensional distribution cases of catastrophe losses in different areas. Applied normal approximation and Wang's transform for pricing.
result Illustrated differences in scenarios and performance of the approximation on real data.
Open AI models affect bond yields differently than closed ones.
problem Understanding how market reactions to AI releases impact bond yields.
method Analyzed US bond yields before and after the release of open and closed AI models.
result Open AI models shift bond yields in the opposite direction of closed models.
Green bond leaks impact equity markets, altering investor reactions.
problem Green bond leaks affect equity market reactions.
method Identified 259 instances of pre-announcement leaks in 2,036 green bond headlines.
result News leaks significantly alter equity trading dynamics and investor reactions.
Paper tackles market making in corporate bonds using deep reinforcement learning.
problem Optimizing bid and ask quotes for a large universe of bonds in OTC markets.
method Discrete-time actor-critic algorithm with deep neural networks.
result Approximates optimal bid and ask quotes over a large universe of bonds.
This paper analyzes the causal relationships among China's bond market interest rates.
problem Identifying the key interest rates with broad influence on China's bond market.
method Developed multi-variable Granger causality test to construct a directed network of interest rates.
result Short-term interest rates have larger influences on key interest rates, while repo rates are the benchmark.
Paper proposes a framework for precise daily default risk prediction of Chinese credit bonds.
problem Inadequate and inaccurate bond information disclosure creates risk of default for investors.
method Framework includes summarizing factors impacting defaults, constructing a risk index system, and using ConvLSTM neural network for prediction.
result The model provides more responsive and accurate daily default risk predictions than authoritative ratings.
Repo rates are explained as a convexity effect from bond and derivative discount rates.
problem Explaining the observed basis between repo rates and bond prices.
method Using a Hull-White model, derived expressions for repo rates and extrapolation.
result Interpolated and extrapolated repo curves for bond-collateralised derivatives.
This paper presents a method to estimate mid-prices of European corporate bonds using real-time dealer information.
problem Estimating mid-prices in illiquid markets where direct market prices are not available.
method Bayesian approach using particle filtering and sequential Monte Carlo.
result A new method for real-time mid-price estimation of corporate bonds.
Study solves BSDEs for bond market hedging, proving convergence of strategies.
problem Approximate hedging in bond markets using BSDEs.
method Existence and uniqueness of solutions for infinite-dimensional BSDEs driven by cylindrical martingales.
result Sequence of locally risk-minimizing strategies converges to generalized hedging strategy.
Study reveals stylized facts in German bond futures markets.
problem Understanding market dynamics in German bond futures.
method Analyzed tick-by-tick data of four German bond futures contracts.
result Uncovered commonalities and unique characteristics across different futures.
We introduce a theory of stochastic integration with respect to a family of semimartingales depending on a continuous parameter, as a mathematical background to the theory of bond markets. We apply our results to the problem of super-replication and utility maximization from terminal wealth in a bond market. Finally, w…
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…
New game theory approach to bond market liquidity and participant behavior.
problem Uncertainty in market maker types and regulatory structure.
method Liquidity Game theory applied to UK bond market interactions.
result Strategies and structures for market makers and regulators.
Machine learning models predict housing prices using macroeconomic factors.
problem Predicting housing prices using macroeconomic data.
method Used machine learning (kNN and tree-bagging) on a dataset of macroeconomic factors.
result Machine learning models can predict housing prices with uncertainties better than existing index uncertainties.
Study bond market making with hit-ratio target using optimal control and HJB equations.
problem Optimizing bond market making with hit-ratio target in OTC markets.
method Stochastic optimal control approach, dualizing hit-ratio target, HJB equation, Riccati equation, linearization.
result Explicit quote decompositions into riskless spread, inventory-risk correction, and hit-ratio correction.
Deep learning speeds CAT bond valuation.
problem Valuation of Catastrophe bonds.
method Deep neural networks trained to price CAT bonds.
result Trained model provides fast and accurate pricing.
QCML improves bond similarity learning in illiquid markets.
problem Improving similarity learning for illiquid corporate bonds.
method Quantum Cognition Machine Learning (QCML) for supervised distance metric learning.
result QCML outperforms classical tree-based models in high-yield markets.
We investigate default-free bond markets where the standard relationship between a possibly existing bank account process and the term structure of bond prices is broken, i.e. the bank account process is not a valid numéraire. We argue that this feature is not the exception but rather the rule in bond markets when star…
CATNet predicts CAT bond spreads using graph-based deep learning.
problem Complex, relational data in CAT bonds not well captured by traditional models.
method CATNet applies R-GCN to CAT bond primary market as a graph.
result CATNet outperforms Random Forest and XGBoost benchmarks.