The problem of completeness of the forward rate based bond market model driven by a Lévy process under the physical measure is examined. The incompleteness of market in the case when the Lévy measure has a density function is shown. The required elements of the theory of stochastic integration over the compensated jump…
The completeness of a bond market model with infinite number of sources of randomness on a finite time interval in the Heath-Jarrow-Morton framework is studied. It is proved that the market is not complete. A construction of a bounded contingent claim, which can not be replicated, is provided.
We find multi-factor CIR models can exhibit unspanned stochastic volatility.
problem Unspanned stochastic volatility in fixed income markets.
method Formal review and necessary/sufficient conditions for multi-factor CIR models.
result We construct three-factor CIR models that exhibit unspanned stochastic volatility.
The paper analyzes how wealth affects investment strategies in incomplete markets.
problem Investment strategies in markets with incomplete information.
method Developed a five-component decomposition for optimal portfolio choice, solved explicitly for HARA utility and nonrandom interest rate, and used a stochastic volatility model for US equity data.
result Demonstrated the impacts of wealth-dependent utilities on optimal portfolio allocation, including cycle-dependence and hysteresis effect.
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.
We offer mathematical tractability and new insights for a framework of exponential utility with non-negative consumption, a constraint often omitted in the literature giving rise to economically unviable solutions. Specifically, using the Kuhn-Tucker theorem and the notion of aggregate state price density (Malamud and …
In this paper incomplete-information models are developed for the pricing of securities in a stochastic interest rate setting. In particular we consider credit-risky assets that may include random recovery upon default. The market filtration is generated by a collection of information processes associated with economic…
The classical derivation of the well-known Vasicek model for interest rates is reformulated in terms of the associated pricing kernel. An advantage of the pricing kernel method is that it allows one to generalize the construction to the Lévy-Vasicek case, avoiding issues of market incompleteness. In the Lévy-Vasicek mo…
Unified Bayesian framework for CAT bond pricing.
problem Uncertainty in catastrophe occurrences and interest rates in CAT bond markets.
method Bayesian framework based on uncertainty quantification of catastrophes and interest rates.
result Unified asset pricing approach with informative expected risk premia.
The paper develops a pricing method for insurance contracts under incomplete information.
problem Pricing pure endowment contracts with limited insurer information.
method Modeling with stochastic processes, using BSDEs for indifference pricing under partial information.
result The indifference price of insurance derivatives is characterized via BSDEs.
Basel III introduces new capital charges for CVA. These charges, and the Basel 2.5 default capital charge can be mitigated by CDS. Therefore, to price in the capital relief that CDS contracts provide, we introduce a CDS pricing model with three legs: premium; default protection; and capital relief. If markets are compl…
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.
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.
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 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.
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.
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.
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.
We consider a power utility maximization problem with additive habits in a framework of discrete-time markets and random endowments. For certain classes of incomplete markets, we establish estimates for the optimal consumption stream in terms of the aggregate state price density, investigate the asymptotic behaviour of…
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.
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.
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.
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 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…
Developing a climate-aware pricing framework for XL reinsurance and CAT bonds under non-stationary catastrophe risk.
problem Pricing excess-of-loss (XL) reinsurance and catastrophe (CAT) bonds under climate uncertainty.
method Modeling catastrophe arrivals as a Cox process with a temperature-dependent stochastic intensity and aggregate losses following a compound Cox structure.
result Climate dependence materially changes the loss-generation mechanism and affects the valuation of catastrophe-linked contracts.
Investigates optimal strategies under financial uncertainty, proving convergence as uncertainty increases.
problem Utility maximization in financial markets with model uncertainty.
method Explicit representation of optimal strategy, minimax theorem, convergence analysis.
result Optimal strategy converges to a generalized uniform diversification strategy as uncertainty increases.
The possibility of statistical evaluation of the market completeness and incompleteness is investigated for continuous time diffusion stock market models. It is known that the market completeness is not a robust property: small random deviations of the coefficients convert a complete market model into a incomplete one.…
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.
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.
Numerous kinds of uncertainties may affect an economy, e.g. economic, political, and environmental ones. We model the aggregate impact by the uncertainties on an economy and its associated financial market by randomised mixtures of Lévy processes. We assume that market participants observe the randomised mixtures only …
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.
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.
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.
We investigate the possibility of statistical evaluation of the market completeness for discrete time stock market models. It is known that the market completeness is not a robust property: small random deviations of the coefficients convert a complete market model into a incomplete one. The paper shows that market inc…
The paper uses machine learning to predict missing yield parameters from liquid markets to illiquid corporate bonds.
problem Predicting missing yield parameters from illiquid corporate bonds.
method Applying Denoising Autoencoder (DAE) algorithm to historical data of liquid market instruments.
result DAE algorithm outperforms point-in-time inpainting algorithms in predicting unobserved yield surfaces.
The completeness problem of the bond market model with the random factors determined by a Wiener process and Poisson random measure is studied. Hedging portfolios use bonds with maturities in a countable, dense subset of a finite time interval. It is shown that under natural assumptions the market is not complete unles…