arXiv research

The paper analyzes corporate security prices in incomplete credit risk models.

This paper uses RL to optimize bid-ask spreads for illiquid corporate bonds.

QCML improves bond similarity learning in illiquid markets.

Broker uses multi-task dynamic pricing to learn competitive prices in credit markets.

The paper uses option theory to estimate corporate bond liquidity spreads.

New formulations capture aversion to ambiguity about volatility.

Study finds it hard to establish common factor pricing in corporate bonds.

This paper presents a method to estimate mid-prices of European corporate bonds using real-time dealer information.

This study examines the execution phase of corporate share buy-backs, highlighting inefficiencies and costs.

Analyzes transaction costs for corporate bonds using a new analytical methodology.

New model prices corporate bonds by accounting for non-hedgeable risk.

We study the pricing problem for corporate defaultable bond from the viewpoint of the investors outside the firm that could not exactly know about the information of the firm. We consider the problem for pricing of corporate defaultable bond in the case when the firm value is only declared in some fixed discrete time a…

Traded corporations are required by law to have a majority of outside directors on their board. This requirement allows the existence of directors who sit on the board of two or more corporations at the same time, generating what is commonly known as interlocking directorates. While research has shown that networks of …

Corporate bond factor research is flawed due to measurement errors and ex-post filtering.

According to theoretical models of valuing risky corporate securities, risk of default is primary component in overall yield spread. However, sizable empirical literature considers it otherwise by giving more importance to non-default risk factors. Current study empirically attempts to provide relative solution to this…

Develops a new model to better predict corporate bond yields.

The paper uses daily bond price data to estimate corporate default spreads, improving credit risk assessment.

Model for corporate bond pricing with credit rating migration, solving a double free boundary problem.

A new formula for pricing illiquid corporate bonds.

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

Paper proposes a new method to compute cryptocurrency prices securely.

Study shows Bitcoin security tied to mining rewards and prices.

We describe and document three mechanisms by which corporations can influence or even control stock prices. (i) Parent and holding companies wield control over other publicly traded companies. (ii) Through clever management of treasury stock based on buyback programs and stock issuance, stock price fluctuations can be …

Study upper hedging prices for contingent claims in models with various types of arbitrage.

This study examines how banks and securities markets coevolved in 19th century Belgium.

Paper examines how crypto-assets affect corporate governance of SMEs and public companies.

Study uses neural networks to predict firm earnings, outperforming benchmarks and analysts.

Paper proposes a supervised similarity framework for corporate bonds using RF proximities.

New model values equity-linked securities with guaranteed return.

Simplified proof for asset pricing theory.

A common assumption in financial engineering is that the market price for any derivative coincides with an objectively defined risk-neutral price - a plausible assumption only if traders collectively possess objective knowledge about the price dynamics of the underlying security over short time scales. Here we assume t…

Study examines reasons for Nutek India's share price drop.

Contextual bandit framework improves revenue optimization in securities lending market.

Paper proposes a new trading strategy using corporate event detection from news articles.

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…

We consider a class of generalized capital asset pricing models in continuous time with a finite number of agents and tradable securities. The securities may not be sufficient to span all sources of uncertainty. If the agents have exponential utility functions and the individual endowments are spanned by the securities…

Study on price formation in a market with a major player and minor firms.

Paper tackles market making in corporate bonds using deep reinforcement learning.

In this paper we formulate a corporate bond (CB) pricing model for deriving the term structure of default probabilities (TSDP) and the recovery rate (RR) for each pair of industry factor and credit rating grade, and these derived TSDP and RR are regarded as what investors imply in forming CB prices in the market at eac…

The distribution of share prices follows Zipf's law, similar to financial indicators.

Paper develops security model and pricing for stable digital currency in quantum blockchain network.

The paper explores how mining costs, rewards, and blockchain security are interconnected.

Unified framework for pricing various debt securities.

Formula calculates bond prices between payments.

This paper optimizes a dynamic portfolio using novel dynamic programming.

A one-factor asset pricing model with an Ornstein--Uhlenbeck process as its state variable is studied under partial information: the mean-reverting level and the mean-reverting speed parameters are modeled as hidden/unobservable stochastic variables. No-arbitrage pricing formulas for derivative securities written on a …

New theory predicts security prices through a physical law, not randomness.

This study proposes a new model for predicting financial distress in SMEs using machine learning.