Research on the Pricing of Convertible bonds in China Migration risk based on credit rating

At present,further research and exploration on credit risks are being carried out in the global field,and increasingly profound modem credit risks are exposed to the bond market.This requires that we cannot ignore the impact of credit rating migration risk on bond pricing,so as to adapt to the sustainable and healthy development of the bond market under the new normal of China's economy.The innovation point of this paper is to try to analyze the pricing of Convertible bonds in China from the perspective of credit rating migration risk.Tsiveriotis and Femandes(1998)model is selected,and the credit risk in the model is assumed to be caused by the credit rating migration risk,and the credit spread is used to measure the credit rating migration risk.The research conclusion of this paper is as follows:First,it is valid to consider the risk of credit rating migration in the TF(1998)model.The market price of convertible bonds is on average 1.22% higher 1han the theoretical value of the model.In general,the theoretical value obtained from the model has little deviation from the market price,and has a good fitting degree.Second,from the Angle of credit rating,the selection of 32 samples of convertible bonds only empirical research shows that the credit rating of AA-convertible bonds average deviation rate is negative,suggest that the credit rating of AA-the phenomenon of convertible bonds value is underestimated,and AAA credit rating to AA,AA+,the average deviation rate of convertible bonds is positive,that credit rating AA(containing AA)more convertible bond value is overrated phenomenon,and the higher the credit rating of the average deviation rate of convertible bond,the greater the overvalued levels.It has certain guiding significance for participants in the convertible bond market.

Pricing Catastrophe Options with Credit Risk in a Regime-Switching Model

In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.

Artificial Intelligence-Based Automated Actuarial Pricing and Underwriting Model for the General Insurance Sector

The Automated Actuarial Pricing and Underwriting Model has been enhanced and expanded through the implementation of Artificial Intelligence to automate three distinct actuarial functions: loss reserving, pricing, and underwriting. This model utilizes data analytics based on Artificial Intelligence to merge microfinance and car insurance services. Introducing and applying a no-claims bonus rate system, comprising base rates, variable rates, and final rates, to three key policyholder categories significantly reduces the occurrence and impact of claims while encouraging increased premium payments. We have enhanced frequency-severity models with eight machine learning algorithms and adjusted the Automated Actuarial Pricing and Underwriting Model for inflation, resulting in outstanding performance. Among the machine learning models utilized, the Random Forest (RANGER) achieved the highest Total Aggregate Comprehensive Automated Actuarial Loss Reserve Risk Pricing Balance (ACAALRRPB), establishing itself as the preferred model for developing Automated Actuarial Underwriting models tailored to specific policyholder categories.

PRICING CATASTROPHE OPTIONS WITH COUNTERPARTY CREDIT RISK IN A REDUCED FORM MODEL

In this paper, we study the price of catastrophe Options with counterparty credit risk in a reduced form model. We assume that the loss process is generated by a doubly stochastic Poisson process, the share price process is modeled through a jump-diffusion process which is correlated to the loss process, the interest rate process and the default intensity process are modeled through the Vasicek model： We derive the closed form formulae for pricing catastrophe options in a reduced form model. Furthermore, we make some numerical analysis on the explicit formulae.

Risk Assessment M ode of Sale-Leaseback——Based on Fuzzy Analytic Hierarchy Process

Sale-leaseback is paid special focus on for its great application in China in recent years.By giving a detailed analysis,an analysis of the features of sale-leaseback and a study of the risks of it are given in this paper.Then a quantitative analysis of commercial real estate sale-leaseback is carried out.The scientific theoretical analysis is provided in this paper for risk assessment in commercial real estate sale-leaseback mode in China.An effective approach is put forward for sale-leaseback project evaluation and prevention of risk.A useful means is given to supervise commerciai real estate sale-leaseback mode for relevant departments and a certain contribution is made to a further sound development of commercial real estate sale-leaseback mode.

Option Pricing when the Regime-Switching Risk is Priced

We study the pricing of an option when the price dynamic of the underlying risky asset is governed by a Markov-modulated geometric Brownian motion. We suppose that the drift and volatility of the underlying risky asset are modulated by an observable continuous-time, finite-state Markov chain. We develop a two- stage pricing model which can price both the diffusion risk and the regime-switching risk based on the Esscher transform and the minimization of the maximum entropy between an equivalent martingale measure and the real-world probability measure over different states. Numerical experiments are conducted and their results reveal that the impact of pricing regime-switching risk on the option prices is significant.

A Bond Pricing Model with Credit Migration Risk:Different Upgrade and Downgrade Thresholds

In this paper, a new corporate bond pricing model with credit migration risk is proposed. This model sets different thresholds for the rising or falling of credit ratings, which forms a buffer zone that could reduce the frequency of credit rating changes. Mathematically, this model is a system of partial differential equations with overlapping area. The existence, uniqueness, regularity and asymptotic behavior of the solution are obtained. Furthermore, a numerical scheme and its stability, convergence and accuracy are discussed in detail. Calibration and analysis of the parameters are also suggested.

Carbon emission trading system and stock price crash risk of heavily polluting listed companies in China:based on analyst coverage mechanism

This study reveals the inconsistencies between the negative externalities of carbon emissions and the recognition condition of accounting statements.Hence,the study identifies that heavily polluting enterprises in China have severe off-balance sheet carbon reduction risks before implementing the carbon emission trading system(CETS).Through the staggered difference-in-difference(DID)model and the propen-sity score matching-DID model,the impact of CETS on reducing the risk of stock price crashes is examined using data from China’s A-share heavily polluting listed companies from 2007 to 2019.The results of this study are as follows:(1)CETS can significantly reduce the risk of stock price crashes for heavily polluting companies in the pilot areas.Specifically,CETS reduces the skewness(negative conditional skewness)and down-to-up volatility of the firm-specific weekly returns by 8.7%and 7.6%,respectively.(2)Heterogeneity analysis further shows that the impacts of CETS on the risk of stock price crashes are more significant for heavily polluting enterprises with the bear market condition,short-sighted management,and intensive air pollution.(3)Mechanism tests show that CETS can reduce analysts’coverage of heavy polluters,reducing the risk of stock price crashes.This study reveals the role of CETS from the stock price crash risk perspective and helps to clarify the relationship between climatic risk and corporate financial risk.

Time-varying impact of political risk on copper prices

Using the International Country Risk Guide(ICRG)index to represent countries’political risk,the time-varying effect of political risk on copper prices was examined based on the time-varying parameter structural vector autoregression with stochastic volatility(TVP-SVAR-SV)model.The empirical results show that the impact of political risk on copper prices is time-varying and has tended to increase gradually in recent years.There are significant country-level differences in the impact of political risk on copper prices.Political risk has a stronger and longer-lasting impact on copper prices in exporting countries.In terms of risk sources,external and internal conflicts contribute most to international copper price fluctuations in the sample period.The impact of political risk on copper prices reaches an extreme level during the international financial crisis,the European debt crisis,and the election of Donald Trump.

An Approach to Quantify the Heat Wave Strength and Price a Heat Derivative for Risk Hedging

Mitigating the heat stress via a derivative policy is a vital financial option for agricultural producers and other business sectors to strategically adapt to the climate change scenario. This study has provided an approach to identifying heat stress events and pricing the heat stress weather derivative due to persistent days of high surface air temperature （SAT）. Cooling degree days （CDD） are used as the weather index for trade. In this study, a call-option model was used as an example for calculating the price of the index. Two heat stress indices were developed to describe the severity and physical impact of heat waves. The daily Global Historical Climatology Network （GHCN-D） SAT data from 1901 to 2007 from the southern California, USA, were used. A major California heat wave that occurred 20-25 October 1965 was studied. The derivative price was calculated based on the call-option model for both long-term station data and the interpolated grid point data at a regular 0.1~ x0.1~ latitude-longitude grid. The resulting comparison indicates that （a） the interpolated data can be used as reliable proxy to price the CDD and （b） a normal distribution model cannot always be used to reliably calculate the CDD price. In conclusion, the data, models, and procedures described in this study have potential application in hedging agricultural and other risks.

Continuous-Time Models for Firm Valuation and Their Collateral Effect on Risk-Neutral Probabilities and No-Arbitraging Principle

Extensions of Merton’s model(EMM)considering the firm’s payments and generating new types of firm value distribution are suggested.In the open log-value/time space,these distributions evolve from initially normal to negatively skewed ones,and their means are concave-down functions of time.When payments are set to zero or proportional to the firm value,EMM turns into the Geometric Brownian model(GBM).We show that risk-neutral probabilities(RNPs)and the no-arbitraging principle(NAP)follow from GBM.When firm’s payments are considered,RNPs and NAP hold for the entire market for short times only,but for long-term investments,RNPs and NAP just temporarily hold for individual stocks as far as mean year returns of the firms issuing those stocks remain constant,and fail when the mean year returns decline.The developed method is applied to firm valuation to derive continuous-time equations for the firm present value and project NPV.

Contingent convertible lease modeling and credit risk management

The main objective of this study is to determine a lease agreement to finance an investment project and a solution for managing credit risk.This study investigates three types of contingent leases to reduce the costs associated with bankruptcy and compensate for the lessor’s position.A leasing defaultable contract allows the lessor to obtain the rent that will be recovered if the lessee defaults.A leasing convertible contract can be automatically converted into shares when certain default conditions related to the cash flows generated by the firm are met.These conditions are triggered by the ratio of the firm’s value and leasing payments.A Defaultable-Convertible-Leasing contract with a payback option grants the lessor the right but not the obligation to convert the remaining lease payments into stocks or to break up the contract and pick up the rented equipment when the firm reaches the default threshold.These contracts are motivated by contributing to the range of risk-management strategies by adding more flexibility to standard leasing contracts and contingent rents.Closed-form securities pricing solutions are set forward in a dynamic model for firms with existing assets and a growth option financed by shares and a contingent lease.Risk-neutral pricing theory and the backward induction method are used to determine the pricing of corporate securities.Numerical analysis shows that leasing convertible contracts and defaultable-convertible contracts with payback options impact the service value of the leased asset,maturity,and inefficiencies resulting from insolvency and asset substitution.An optimal conversion rate reduces inefficiencies,thus making the leasing convertible contract and defaultable-convertible-leasing contract with payback option a reliable solution to ensure business continuity and loss coverage of the leasers upon default.

Investor Attention,Analyst Optimism,and Stock Price Crash Risk

This paper used the A-shares listed companies in China as samples,constructed a comprehensive indicator of investor attention,and conducted an empirical analysis on the correlations among investor attention,analyst optimism,and stock price crash risk.The results indicated that investor attention aggravates the stock price crash risk and has a positive effect on analyst optimism.Meanwhile,the analyst optimism plays a mediating role in the positive correlation between investor attention and stock price crash risk.In addition to that,institutional investor attention also has direct and indirect effects on the crash risk.

Research on Agricultural Product Price Risk and Risk Management

There are a variety of reasons for agricultural product price risk,and drastic volatility in agricultural product price can give a tremendous negative impact on agriculture and even whole society. The paper argues that the agricultural product price risks include( i) price risk caused by decrease in yield and quality of agricultural products due to natural disasters;( ii) price risk caused by actual change of the market supply and demand;( iii) price fluctuation risk caused by the change of the price of the related products;( iv) sharp price volatility risk caused by market speculation;( v) risk caused by periodic property of agricultural products and lack of elasticity of agricultural demand;( vi)risk caused by lack of government management. Agricultural product price risk poses great harm to farmers,small and medium-sized agricultural operators and general consumers. This paper brings forward the specific recommendations for solving agricultural product price risk.

Corporate pledgeable asset ownership and stock price crash risk

We investigate how a firm’s corporate pledgeable asset ownership(CPAO)affects the risk of future stock price crashes.Using pledgeable asset ownership and crash risk data for a large sample of U.S.firms,we provide novel empirical evidence that a firm’s risk of a future stock price crash decreases with an increase in its pledgeable assets.Our main findings are valid after conducting various robustness tests.Further channel tests reveal that firms with pledgeable assets increase their collateral value,thereby enhancing corporate transparency and limiting bad news hoarding,resulting in lower stock price crash risk.Overall,the results show that having more pledgeable assets enables easier access to external financing,making it less likely that managers will hoard bad news.

Production response to price risk and market liberalization of Nigerian major agricultural crops

This study models supply response for major agricultural crops in Nigeria which include the standard arguments and price risk. The data comes from Central Bank of Nigeria annual reports and statement of account, National Bureau of Statistics＇ abstract of statistics and annual Agricultural survey manual. The data are analyzed using autoregressive distributed lag and cointegration and error correction models. The results indicate that producers are responsive not only to price but also to price risk and exchange rate.

Coal price fluctuations and the impact on financial risk Evidence from China＇s coal listed companies

With the rise of coal price, the proportion of loss-making enterprises shows an upward trend in China＇s coal industry. This paper uses Altman Z-Score model to measure financial risk of 19 listed companies in the coal industry in A-share market from 1995 to 2007. Empirical results show that Year-Based price index of coal price has a negative correlation with the financial risk but has no significance, and coal chain price has a significant negative correlation with the financial risk. Further research indicates that enterprises increase bad investment, and a lot of debts caused by short-term rise in coal prices. The results also show that the financial risk in the coal industry declines with the rise of GDP growth rate and increases with the rise of inflation rate.

Liquidity risk integration in portfolio choice： The bid efficient frontier

In this paper, a tractable solution is proposed to integrate, to a certain extent, market liquidity risk in the portfolio selection process. It is shown how an investor may take advantage of this additional risk source within the standard mean-variance optimization framework, by in certain circumstances overcoming the pitfalls of illiquidity and in others seizing a liquidity premium. Bid prices appear effective to capture liquidity risk. The efficient frontier conceived with bid prices consists of mean-variance optimal allocations that cover more liquid stocks （large caps） under stressed market conditions and less liquid stocks （small caps） under normal conditions.

Binomial Tree Pricing Model of Convertible Bond with Default Risk

In this paper we use a binomial tree to price convertible bond with default risk. A new way about pricing convertible bonds is proposed, which belongs to the deduced form approach. Firstly an inhomogeneous Possion process is used to describe default event and definition of default time. Secondly we combine the stock binomial tree with default intensity and obtain a new tree, then convertible bonds are priced according to the combined tree. It is worth pointing out that the model have following characters： simple, intuitive and having the strong ability to combine other items in convertible bonds＇ indenture.