Bond Prices Research Articles

Bond Pricing Under Sticky OU Process

Bond Pricing Under Sticky OU Process

Practice of Python in Programming and Optimization of Quantitative Analysis Model of Fixed Income

Python has become an indispensable tool in fixed income trading. This paper introduces the principles and general process of data analysis visualisation by analysing the basic operation and performance of personal investment and finance, combined with data analysis in the era of big data. The library of data analysis tools using Python has become an indispensable tool in fixed income trading. In fixed income trading, it supports fixed income traders to handle tasks such as bond pricing, interest rate modelling, and credit risk analysis Using Python's powerful data processing capabilities, traders can simplify data collection, analysis, and reporting to make better decisions. Based on the Python language, financial data is acquired from different platforms, processed and analysed step-by-step, ensuring that the model remains accurate and stable in different market conditions. Backtesting and ongoing performance evaluations have revealed that Python can be a valuable asset in the dynamic world of fixed income trading by refining trading strategies and effectively managing risk.

How does informed trading affect credit bond spreads: Evidence from China's interbank bond market

China's interbank bond market is an institutional investor market, and transactions are more information-based. Whether and how informed trading can affect credit bond pricing is an urgent problem to be solved in the study of China's bond asset pricing. This paper uses credit bond issuance and trading data and stock high-frequency trading data from May 2014 to December 2020 to construct informed trading probability and bond liquidity indicators. Using regression analysis and adjustment and mediation effect test methods, this paper studies the impact of informed trading on China's interbank credit bond pricing and the channel role of liquidity. The results show that the probability of informed trading has a significant positive impact on credit bond spreads. Informed trading leads to an increase in credit bond spreads by amplifying bond illiquidity. The amplifying effect of informed trading on credit bond spreads is stronger for bonds with high illiquidity. The amplifying effect of informed trading on credit bond spreads will be stronger in private enterprises, enterprises with low information transparency, and high debt ratios. This study reveals the risk nature of informed trading in China's interbank bond market, which helps to deepen the understanding and management of the bond market.

Analysis of Financial Fraud Based on the GONE TheoryA Case Study of Hangzhou Century Co., Ltd.

Convertible bonds allow creditors to convert their claims into company shares under certain conditions. Because of this debt-equity conversion feature, the issuance conditions, pricing and conversion value of convertible bonds are highly susceptible to financial information. Increasing the market value of a company's stock by exaggerating earnings or concealing debt may lead to convertible bond investment decisions based on misinformation, which in turn affects investors and the healthy operation of the market. Based on the GONE theory, this paper analyses the motivation of financial fraud in convertible bond documents and proposes corresponding preventive measures for its characteristics. Through the research and analysis of this type of financial forgery, the preventive governance of financial forgery can be further strengthened, which not only helps to protect the company's reputation and ensure the accuracy and reliability of the financial report, but also helps to attract and maintain the trust of investors, avoid possible legal risks and economic losses, and create a transparent and honest financial environment for the market to promote the efficiency of the market and the fair competition of enterprises.

Pricing Model Construction and Empirical Research on Catastrophe Bond Pricing for Three Major Crops in China

Agricultural disaster risks are significant for the sector's development, and existing risk management tools have limitations.This paper introduces a nationwide catastrophe bond for wheat, maize, and rice , offering broad coverage for China's agriculture. The paper utilizes marginal distribution and Copula function fitting to model the disaster losses of the three major crops from 1990 to 2022. It employs Monte Carlo simulation to generate a 10,000-year event set and rank correlation to align simulated data with real data. The bond price is then calculated using the Wang model, addressing the challenge of data scarcity and providing an innovative approach to catastrophe bond design. The study finds that bond prices increase with the coverage period and risk level, with interest-risk bonds offering higher returns and risks than principal-and-interest risk bonds. Catastrophe bonds present a more stable risk diversification method compared to reinsurance, both in terms of returns and potential losses.To further the development of agricultural catastrophe bonds, the paper recommends optimizing the issuance environment and establishing a robust market infrastructure.

Do regional trusts alleviate bond market risks? Evidence from the Chinese municipal corporate bond pricing

Municipal corporate bonds have attracted significant attention due to their pricing mechanisms and reflect China's distinct financial landscape. Existing research has highlighted the influence of informal institutional factors on bond pricing. This study introduces the social trust index to measure regional trust levels and assesses its correlation with municipal corporate bond issuance pricing. The empirical analysis indicates that higher regional trust levels are significantly associated with reduced issuance credit spreads for municipal corporate bonds. The relationship is moderated by local economic development and the strength of implicit government guarantees. Employing the “Yongmei” event as a case study, this research explores the dynamics of bond pricing mechanisms following a reduction in government implicit guarantees and finds that a weakening of these guarantees intensifies the influence of regional trust on credit spreads. Additionally, default events are observed to have spillover effects, impacting neighboring provinces and the overall market. This research extends the investigation of regional trust's pricing mechanisms to the municipal corporate bond market, thereby enriching the study of informal institutions' impact on financial market pricing. The findings underscore the importance of effectively harnessing market mechanisms by governments to mitigate risks in the municipal corporate bond sector.

Tobias A. Jopp, War, Bond Prices, and Public Opinion. How Did the Amsterdam Bond Market Perceive the Belligerents’ War Effort During World War One. (Economy and History, Vol. 2.) Tübingen, Mohr Siebeck 2021

Tobias A. Jopp, War, Bond Prices, and Public Opinion. How Did the Amsterdam Bond Market Perceive the Belligerents’ War Effort During World War One. (Economy and History, Vol. 2.) Tübingen, Mohr Siebeck 2021

Does the impact of credit rating downgrade on bond returns vary by region: Empirical evidence from China

Utilizing trading data from corporate and enterprise bonds that experienced credit rating downgrades between 2012 and 2022, this study employs event study methodology and regression analysis to examine the regional differences in the impact of credit rating downgrades on bond pricing and the mechanisms behind these effects. The study found that, during the window period when the bond credit rating is downgraded, there is a significant difference in the cumulative abnormal return of bonds between the eastern and non-eastern regions. Heterogeneity analysis indicates that bonds with higher credit ratings and those issued by non-state-owned enterprises are more significantly affected by credit rating downgrades. This study provides empirical evidence of regional disparities in the impact of credit rating downgrades, and proposes a theoretical mechanism whereby differences in the degree of marketization influence these effects through varying expectations of government implicit guarantees. The findings offer a theoretical foundation for optimizing decision-making by participants in the Chinese bond market.

ЗАДАЧА ОПТИМАЛЬНОГО СТОХАСТИЧЕСКОГО УПРАВЛЕНИЯ И ОЦЕНКИ СТОИМОСТИ КОРПОРАТИВНЫХ ОБЛИГАЦИЙ, ЗАВИСЯЩИХ ОТ ВРЕМЕНИ И СЛУЧАЙНЫХ СОСТОЯНИЙ ПАРАМЕТРОВ

In the optimal stochastic control problem, one estimates, using the utility indifference method, the bond price and the premium of a default swap contract (Credit default swap) when the model parameters (market interest rate, drift coef-ficient, and volatility of risky underlying assets) are random functions of time and state. Namely, the interest rate of the risk-free asset depends on time, and the prices of risky assets are described by linear homogeneous stochastic dif-ferential equations (SDEs) with multiplicative noise. To do this, the authors consider a portfolio with a risk-free asset and a risky asset with no default risk. For each such portfolio, the authors determine the amount of risky assets that maximizes the expected utility of its final wealth. This quantity allows one to solve the parabolic partial differential equations arising from the Hamilton-Jacobi-Bellman (HJB) equation by transforming them into ordinary differential equations using the method of variable separation to obtain the instantaneous value function of each portfolio. The authors derive the bond price and the default swap-contract premium (CDS) rate, which are the amounts that provide the same level of the expected utility by investing all of one’s wealth in a portfolio that does not contain these credit instruments, or by investing these amounts in credit instruments and the remainder of one’s wealth in the portfolio.

Equity Market Pricing and Central Bank Interventions: A Panel Data Approach

This paper analyzes the effects of central bank interventions via large-scale purchases of government debt securities on the pricing of stock market indices. This study examines the effects of changes in the size of the Federal Reserve’s balance sheet in three intervention scenarios: during the 2008–2013 period, the 2020–2022 period, and in the years between by using the instrumental variables three-stage least squares (3SLS) method for a time series approach, and calculates the effects of these interventions on each index in a fund of funds setup using the panel data strategy. This study confirms that large-scale purchases of government debt securities in response to the Great Recession and COVID-19 crises influenced the pricing of equity markets via their effect on the pricing of treasury bonds, with different degrees of sensitivity of each index to the effects on yields. Although the findings apply to the U.S. market, the results indicate that the pricing of small capitalization indices such as the Russell 2000 are less sensitive to changes in treasury yields caused by central bank interventions than large capitalization indices such as the DJIA. This research contributes to the understanding of financial asset pricing, particularly by identifying price distortions within equity market portfolios.

Capital flow freezes

AbstractThe period following the 2008 financial crisis focused attention on “twin-crises,” where banking crises precipitate sovereign crises due to increased bank support. We show that when private sector debt is renegotiated centrally, and bargaining power is low, it results in suboptimally low levels of debt and default rates (haircuts). If, instead, the bargaining power is sufficiently high, the supply of debt exceeds its demand and capital inflows “freeze”. These inefficiencies arise because the decentralized borrowers fail to consider how their bond supply impacts debt renegotiation outcomes, affecting both bond prices and the asset span. These issues can be addressed through macroprudential policies in the form of taxing capital inflows.

Pricing of sustainability-linked bonds

We examine the pricing of sustainability-linked bonds (SLBs), where the cash flows depend on the bond issuer achieving one or more Environmental, Social and Governance (ESG) goals. Investors are willing to accept a 1–2bps lower yield due to the bond’s ESG label, providing evidence of investors caring about environmental impact. Furthermore, we find the average probability of missing the target is 14%–39% so firms set ESG targets that are easy to reach. We find that the SLB market is efficient: the prices of SLBs depend strongly on the size of the potential penalty and there is no evidence of mispricing. Finally, our results suggest that SLBs serve as financial hedges against ESG risk.

Impact of correlation between interest rates and mortality rates on the valuation of various life insurance products

Abstract In this paper, we question the traditional independence assumption between mortality risk and financial risk and model the correlation between these two risks, estimating its impact on the price of different life insurance products. The interest rate and the mortality intensity are modelled as two correlated Hull and White models in an affine set-up. We introduce two building blocks, namely the zero-coupon survival bond and the mortality density, calculate them in closed form and perform an investigation about their dependence on the correlation between mortality and financial risk, both with theoretical results and numerical analysis. We study the impact of correlation also for more structured insurance products, such as pure endowment, annuity, term insurance, whole life insurance and mixed endowment. We show that in some cases, the inclusion of correlation can lead to a severe underestimation or overestimation of the best estimate. Finally, we illustrate that the results obtained using a traditional affine diffusive set-up can be generalised to affine jump diffusion by computing the price of the zero-coupon survival bond in the presence of jumps.

Convertible Bond Pricing in Chinese Transportation Industry : A Comparison Methods Between Binomial Tree model and Black-Scholes Model

Convertible Bond Pricing in Chinese Transportation Industry : A Comparison Methods Between Binomial Tree model and Black-Scholes Model

Does accrual information impact municipal bond prices? Evidence from Japan using AI

IMPACT This article explains some aspects of the role of accrual-based information disclosed by local governments, which has been a subject of debate for some time. Using eXplainable AI (XAI), the authors demonstrate that accrual-based information is reflected in local government bond prices in Japan. The article has important findings for practitioners. The first is the pricing process for municipal bonds. This is useful for practices in municipal bond issuance and investment for financial instruments. The second is the applicability of machine learning in bond markets. The findings will also be useful to data scientists and public officers in local governments looking to create value through the use of machine learning (particularly XAI).

Dynamic Asset Pricing in a Unified Bachelier–Black–Scholes–Merton Model

We present a unified, market-complete model that integrates both Bachelier and Black–Scholes–Merton frameworks for asset pricing. The model allows for the study, within a unified framework, of asset pricing in a natural world that experiences the possibility of negative security prices or riskless rates. Unlike the classical Black–Scholes–Merton, we show that option pricing in the unified model differs depending on whether the replicating, self-financing portfolio uses riskless bonds or a single riskless bank account. We derive option price formulas and extend our analysis to the term structure of interest rates by deriving the pricing of zero-coupon bonds, forward contracts, and futures contracts. We identify a necessary condition for the unified model to support a perpetual derivative. Discrete binomial pricing under the unified model is also developed. In every scenario analyzed, we show that the unified model simplifies to the standard Black–Scholes–Merton pricing under specific limits and provides pricing in the Bachelier model limit. We note that the Bachelier limit within the unified model allows for positive riskless rates. The unified model prompts us to speculate on the possibility of a mixed multiplicative and additive deflator model for risk-neutral option pricing.

Tone or term: Machine-learning text analysis, featured vocabulary extraction, and evidence from bond pricing in China

We apply the machine-learning technique proposed by Zhou et al. (2024) to analyze credit rating reports in China’s bond markets, identifying featured vocabulary and generating text analysis scores. Compared with the traditional bag-of-words text analysis, evidence suggests three advantages of machine-learning scoring. Firstly, it covers featured vocabulary that compensates for missing information; secondly, it reduces misclassification of words’ sentiments; moreover, it mitigates the problem of equal weighting inherent in the bag-of-words method. Our findings indicate that the featured vocabulary neglected in the bag-of-words method plays a crucial role in text analysis and significantly contributes to bond pricing. Additionally, we find that machine-learning text analysis can address AAA rating inflation within China’s bond markets to some extent. In contrast, the bag-of-words method exhibits limited efficacy in mitigating this issue.

The effect of ASC 842 leases on bond yields

This study examines how the formal recognition of lease liabilities required by ASC 842 affects corporate bonds pricing. We document significant bond yield increases with the unexpected off-balance sheet liability revealed by the company. The yield reaction displays an asymmetric pattern, with an increase in yields for previously underestimated operating lease liabilities, but no correction for overestimations. Credit ratings are more likely to be downgraded at firms with severely underestimated operating leases. Collectively, our results suggest that ASC 842 has implications for corporate bond pricing.

Pricing of insurance-linked securities: a multi-peril approach

In this paper we build a methodology for pricing of insurance-linked securities which are tied to multiple natural catastrophe perils. As a representative example, we construct a multi-peril catastrophe (CAT) bond which can be linked to the industry loss indices or actual losses incurred by an insurer. We provide pricing formulas for such CAT bonds. We illustrate the introduced methodology on the US natural catastrophe data obtained from Property Claim Services (PCS). Within this dataset, we specifically examine two types of risks: losses associated with wind and thunderstorm events, and those linked to winter storm events. Then, we fit and validate the underlying compound non-homogeneous Poisson processes taking into account the fact that the data are left-truncated. The best fitted loss distributions appear to be Burr and Generalised Extreme Value and for the first peril and log-normal for the second. Finally, we visualise the zero-coupon CAT bond prices for the selected best-fitted models.

The investment of renewable energy: Is green bond a safe-haven to hedge U.S. monetary policy uncertainty?

This paper uses the bootstrap rolling-window Granger causality test to investigate the relationship between U.S. monetary policy uncertainty and green bond. The method addresses the limitations of ignoring the instability of coefficients and the time-varying relationship between the variables in previous literature. The results find both insignificant and significant relationship in the full period. One explanation of the insignificant relationship is that the changes of investor sentiment influence their judgment regarding to the monetary policy uncertainty and green bond, and thus the significance of the relationship between the variables. Besides, this paper finds the significant inter-relationship is time-varying. Specifically, in the sub-period when the market sentiment is low, the rising monetary policy uncertainty influences green bond price negatively. Meanwhile, the unexpected changes of green bond may also have both positive and negative effects on monetary policy uncertainty in different sub-periods. Thus, this paper proposes that the impact mechanism between the variables is effective when the investors are irrational. Furthermore, the findings may provide valuable implications for investors and governments, including adjusting investment strategy when the monetary policy is unclear, increasing monetary policy transparency, and monitoring speculative activity in green bond market. In addition, it is necessary to emphasize that the validity of the findings is limited to the U.S. and the period when investors’ sentiment experience large fluctuations. Finally, future research may consider expand the analysis to the green stock, as it is another important channel for renewable energy investment.