Bond Price Volatility Research Articles

Do foreign investors affect the volatility of local currency bond prices? Empirical evidence from China

How does the participation of foreign investors on local bond markets impact the volatility of bond prices and yields? An answer to this question is important for policy makers from emerging markets in their attempts to liberalize access to financial markets. However, empirical literature gives inconclusive answers to this question. Reasons are that studies analyze diverse types of bonds and apply their analyses to different samples of countries and for different phases in the opening up of markets. We add to existing knowledge by empirically investigating the impact of foreign investors' participation on the volatility of prices of two types of Chinese bonds, government bonds and policy bank bonds, as well as for three stages in the liberalization of the Chinese bond market. We find that foreign investors' participation does not exert significant effects on volatility until late in the opening of the bond market. In addition, we uncover that those bonds which are more influenced by government policies, policy bank bonds, are also more strongly affected by international capital flows. From a policy perspective, our results emphasize the importance of increasing the openness of China's local currency bond market, of stabilizing foreign investors' expectations and, in turn, international capital flows.

On a multiple credit rating migration model with stochastic interest rate

In this paper, we explore a pricing model for corporate bond accompanied with multiple credit rating migration risk and stochastic interest rate. The bond price volatility strongly depends on potentially multiple credit rating migration and stochastic change of interest rate. A free boundary problem of partial differential equation is presented, which is the equivalent transformation of the pricing model. The existence, uniqueness, and regularity for the free boundary problem are established to guarantee the rationality of the pricing model. Due to the stochastic change of interest rate, the discontinuous coefficient in the free boundary problem depends explicitly on the time variable but is convergent as time tends to infinity. Accordingly, an auxiliary free boundary problem is constructed, whose coefficient is the convergent limit of the coefficient in the original free boundary problem. With some constraint on the risk discount rate satisfied, we prove that a unique traveling wave exists in the auxiliary free boundary problem. The inductive method is adopted to fit the multiplicity of credit rating. Then we show that the solution of the original free boundary problem converges to the traveling wave in the auxiliary free boundary problem. Returning to the pricing model with multiple credit rating migration and stochastic interest rate, we conclude that the bond price profile can be captured by a traveling wave pattern coupling with a guaranteed bond price with face value equal to one at the maturity.

Drivers of Corporate Bond Market Liquidity: Evidence from Pakistan

This study examines the factors that contribute to corporate bond market liquidity using the data of Term Finance Certificates from March 2009 to March 2018. The results of summary statistics indicate that majority of trades are carried out in large issue and high credit rating corporate bonds. The regression results indicate that the most important derivers of bond trading volume are the issue size of bond, bond market rating, market interest rate, bond price volatility and equity market conditions. The results of this study lead to the implications that authorities should take steps to improve the bond market in general and promote the flow of trading of these bonds in a centralized way. This will help the policy makers as well as the market participant for making investment decisions.

ENDOGENOUS CREDIT AND INVESTMENT CYCLES WITH ASSET PRICE VOLATILITY

It is commonly accepted that credit market frictions are an important source of macroeconomic fluctuations. But what is the link between the two? And what is the driving factor of asset prices volatility? To answer these questions, we have introduced a specific credit friction, limited commitment, in a general equilibrium model with production and investment in productive capital, where agents can trade bonds. The model always displays a stationary equilibrium where bonds are traded. More importantly, limited commitment may generate stochastic endogenous fluctuations driven by self-fulfilling volatile expectations (sunspots), yielding credit and investment cycles and bond price volatility consistent with data.

A Walrasian Theory of Sovereign Debt Auctions with Asymmetric Information

Sovereign bonds are highly divisible, usually of uncertain quality, and auctioned in large lots to a large number of investors. This leads us to assume that no individual bidder can affect the bond price, and to develop a tractable Walrasian theory of Treasury auctions in which investors are asymmetrically informed about the quality of the bond. We characterize the price of the bond for different degrees of asymmetric information, both under discriminatory-price (DP) and uniform-price (UP) protocols. We endogenize information acquisition and show that DP protocols are likely to induce multiple equilibria, one of which features asymmetric information, while UP protocols are unlikely to sustain equilibria with asymmetric information. This result has welfare implications: asymmetric information negatively affects the level, dispersion and volatility of sovereign bond prices, particularly in DP protocols.

On a Corporate Bond Pricing Model with Credit Rating Migration Risksand Stochastic Interest Rate

In this paper we study a corporate bond-pricing model with credit rating migration and a stochastic interest rate. The volatility of bond price in the model strongly depends on potential credit rating migration and stochastic change of the interest rate. This new model improves the previous existing models in which the interest rate is considered to be a constant. The existence, uniqueness and regularity of the solution for the model are established. Moreover, some properties including the smoothness of the free boundary are obtained. Furthermore, some numerical computations are presented to illustrate the theoretical results.

Pricing Mid-Curve Money Market Future Options in Lognormal LIBOR Model

Abstract In this note we describe the one factor HJM(LLM) model for pricing Mid-Curve Money Market Future Options. The model is based on assuming a lognormal process for the relevant forward money market (“LIBOR”) rates and imbedding it into the general no-arbitrage HJM interest rate modeling framework (understood in the most general sense as a manifestly self-consistent framework for formulating interest rate models in terms of any type of interest rate, including the observable market rates [2, 3, 4]). The relevant convexity adjustment factor is calculated by leveraging on the known functional form for the discount bond price volatility in any no-arbitrage lognormal “LIBOR” rate model and approximating it with a leading order deterministic approximation. This makes it possible to derive an analytic expression for the HJM(LLM) model Discount Propagator using the path integral techniques and leads to the explicit analytic pricing formula for the Mid-Curve future options.

War-related risks and the İstanbul bourse on the eve of the First World War

The lack of well-documented information in the historical literature on the relationship between war-related expectations and their effects on the bond market in the Ottoman Empire motivates this paper's three contributions. First, this paper is the first empirical study to investigate the break points in the volatility of Ottoman bond prices from a historical point of view. Second, we use the econometric technique developed by Inclan and Tiao (1994) to identify the structural breaks. Last, we use a manually collected dataset from the daily newspapers of the time on daily Ottoman bond prices from 1910 to 1914. Subsequently, we identify five structural break dates, each of them corresponding to important war-related events. When we investigate the commentaries in the Ottoman newspapers, we see that the outbreak of several wars might not have been a surprise for investors in the Ottoman Empire, as reflected by government bond prices.

Exploring Determinant Factors of Bond Trading with Inventory Management Theory (Case Study of Indonesian Capital Market, January – March 2009)

This paper studies trading volume of 206 recorded and publicly traded bonds in Indonesian Capital Market on January 4th - March 9th 2009 observed period. The data covers almost all trading data in the market and all brokers that exist. The microstructure data used in this study is a complete understanding for almost every phenomenons in the market, and thus could explain more about bond liquidity. We ind that some bonds are actively traded and most are rare. We also construct some determinant facto tests of bond trading volume, included descriptive statistic, GLS, and other formal test. We ind that bonds with larger par value and more seasoned tend to have smaller trading volume. We also ind that private bonds are actively traded more than public bonds (both government institution and private institution bond). Interest rate risk and bond price volatility are positively inluence bond trading volume, but opposite for bond rating. We ind that bond with higher probability to default have smaller trading volume. While comparing the bond volume data with stock price data, we ind that the relationship in two markets is not linier as the convenient theory in inance said. );} // --> activate javascript

Confidence Erosion and Herding Behavior in Bond Markets: An Essay on Central Bank Communication Strategy

This paper examines the distinctive behavior of long-term interest rates observed after the Bank of Japan’s introduction of quantitative and qualitative monetary easing, by focusing on changes in traders’ confidence and herding behavior. When participants in bond markets lose confidence in their outlook for future interest rates, their investment decision depends heavily on the developments of market prices. This often leads to herding behavior among traders and destabilizes market prices: demand fuels further demand, or supply fuels further supply. This study develops a theoretical model and employs it for stochastic simulations to show that volatility of bond prices and trading volumes is affected by a number of factors, such as investors’ confidence in the financial environment, the usefulness or value of information available in the market, and the market liquidity of bonds. In addition, the model is fitted to actual data to specify the driving forces underlying the changes in long-term interest rate volatility observed in 2013. The analysis shows that the key to understanding the developments in long-term interest rates during this period lies in how traders interpreted information flows in the market, especially the announcement by the Bank of Japan regarding its policy change, and in capturing the extent to which their confidence was weakened or strengthened by those information flows. The findings of the analysis highlight the importance of formulating a communication strategy as part of the conduct of monetary policy and the challenges in implementing such a strategy.

Bond Options and Swaptions Pricing: A Computational Investigation of Volatility Inference

Derivative pricing is especially challenging in novel and illiquid markets, where pricing relies greatly on assumptions and models, rather than on known flow of market prices. In the novel market of shekel bond options, the estimate of implied volatility for different strikes could be based on the information about other -- sometimes more liquid -- financial instruments in the market. Here we show relevance, but not equivalence, of the information from the market of swaps, (volatility of swap rates), to the market of bonds, (volatility of bond prices). In particular, we show why the proxy to bond's yield to maturity from the swap market should be based on the swap rate maturing simultaneously with the bond. Numerical simulations and analysis of historical data are applied to examine the approximation and assumptions which, in the presence of swaption market, can be applicable for inferring information about bond price volatility smile. Hypothetically, the procedure is invertible -- inferring information about swap rate volatility smile, based on the data from the bond options market. Our analysis is implemented for the Israeli market, while the rationale is relevant for similar instruments elsewhere.

Stochastic Optimization for Portfolios Consisting of Corporate Bonds in an Integrated Market and Credit Risk Framework

High credit spreads in 2009 have attracted a lot of interest from investors seeking higher yields outside of government bonds. Investment grade corporate bonds have indeed been a popular investment in 2009. The corporate bond market today is one of the largest and most liquid of the financial markets. Corporate bonds markets can be appealing as they are generally considered safer than stocks and they often provide higher yields and more liquidity than government bonds markets. After the World Financial Crisis central banks set interest rates at their historically low level affecting positively bonds’ prices. The question for a corporate bond portfolio manager is which decisions to take in order to hedge portfolio against volatility of interest rates. Additionally managers have to analyse the factors that affect bonds’ prices volatility and is due to credit risk. For this reasons managers have to implement a risk management framework in order to identify the factor that affect whole portfolio value and finally optimize its value. In an integrated market and risk perspective the future value of a corporate bond portfolio is decomposed into the risk that a bond issued by a firm downgraded by rating agencies and possible drives to default, the correlation between credit events, the risk that changes occur on the average spread of exposures with the same final rating as the firm and the effect of interest rate uncertainty.In chapter 1 we introducing the main types of bonds, analyzing how to valuate non-callable bonds and calculating their yielding and we present factors that affect bond process and price volatility when interest rates changes a bit in a parallel way.In chapter 2 we make an introduction to risk management by referring the risks that affect corporate bond prices. Then we explain the term structure of interest rates and how we can immunize a portfolio of bonds when interest rates changes in a parallel way. Then we introduce a multi-factor model for corporate bonds and present a portfolio immunization model based on factors to protect portfolio value against non-parallel changes of interest rates, introducing the appearance of shape risk.In chapter 3 we added an introduction of credit risk referring the main sources of credit risk in a portfolio of corporate bonds. Then we model credit risk based on a reduced-form approach which defines the default as the instantaneous likelihood of default, called the hazard rate. In chapter 4 we present an integrated market and credit risk framework using scenario generation in order later to optimize a corporate bond portfolio using stochastic programming models. Scenario generation is a tool to model the uncertainty. We develop a model for stochastic interest rates and credit spreads based on the Hull-White algorithm. Interest rates and credit spreads stochasticity based on extended Vasicek model and we produce scenarios of interest rates and credit spreads using trinomial lattice structures which capture the correlation between interest rates and default intensities. Finally we model the correlation between default and migration.In chapter 5 we present the necessity for Conditional Value-at-Risk as a coherent risk measure for corporate bond portfolios. The right risk measure is of paramount importance when we optimize corporate bond portfolios because of tail effects (heavy tails) in the distribution of returns that could result in significant losses and destroy portfolio efficiency. Then we present a linear program for minimizing portfolio risk using CVaR.In chapter 6 we implement portfolio optimization models using stochastic programming in a dynamic aspect. Initially we present an anticipative model where we only take into account stochasticity in future prices without taking recourse actions. Then we present a multistage recourse model where we can take recourse decisions at the preceding time periods based on information we take at discrete time in the future. We assume that there are transaction costs when we buy or sell bonds in order to make models more sophisticated. Finally we analyze one by one the equations of multistage recourse model.

RECURSIVE BAYESIAN ESTIMATION IN FORWARD PRICE MODELS IMPLIED BY FAIR PRICING

In this paper we describe a recursive Bayesian algorithm for the estimation of forward price models. The forward price is modeled within the benchmark framework for a forward price volatility function which includes a stochastic variable; a forward price with a liquidly traded maturity. A relationship between the bond price, the spot price and certain forward prices is stated. We set up the stochastic real world dynamics for these discretely compounded market observed forward prices. We propose a dynamic Bayesian estimation algorithm for a Monte Carlo time-discretized version of the resulting forward prices dynamics. The parameter to be estimated is a vector consisting of the forward price volatility parameters and the benchmarked bond price volatility parameters.

Lower-grade municipal bond price risk and sensitivity of price volatility to level of yields

Price volatility (variance) is a common measure of bond risk. Previous analysis has shown price volatility to depend upon duration and the volatility of interest rates. A more complete and accurate second-order model shows that price volatility also depends on predicted changes in yield and convexity. Municipal bond price volatility estimated by the more accurate second-order model can be much larger (200 per cent) than estimated first-order volatility. Analysts using only a first-order model can make large errors. Additionally, the effect of yield level on price volatility can be very different in first and second-order models.

Trading Activity and Price Volatility in the Municipal Bond Market

ABSTRACTUtilizing a comprehensive database of transactions in municipal bonds, we investigate the volume–volatility relation in the municipal bond market. We find a positive relation between the number of transactions and a bond's price volatility. In contrast to previous studies, we find a negative relation between average deal size and price volatility. These results are found to be robust throughout the sample. Our results are inconsistent with current theoretical models of the volume–volatility relation. These inconsistencies may arise because current models fail to account for the effects of overall market liquidity on the costs of large transactions.

Trading Activity and Price Volatility in the Municipal Bond Market

Utilizing a comprehensive database of transactions in municipal bonds, we investigate the volume-volatility relationship in the muni market. We find a positive relationship between the number of transactions and a bond's price volatility. In contrast to previous studies, we find a negative relationship between average deal size and price volatility. These results are found to be robust throughout the sample. Our results are inconsistent with current theoretical models of the volume-volatility relationship. These inconsistencies may arise because current models fail to account for the effects of overall market liquidity on the costs of large transactions.

THE ENTROPY THEORY OF BOND OPTION PRICING

An informationally efficient price keeps investors as a group in the state of maximum uncertainty about the next price change. The Entropy Pricing Theory (EPT) captures this intuition and suggests that, in informationally efficient markets, perfectly uncertain market beliefs must prevail. When the entropy functional is used to index collective market uncertainty, then the entropy-maximizing consensus beliefs must prevail. The EPT resolves the ambiguity of arbitrage-free valuation in incomplete markets. The EPT produces a new bond option model that is similar to Black–Scholes' with the lognormal distribution replaced by a beta distribution. Unlike alternative models, the beta model is valid for arbitrary term structure dynamics and for arbitrary credit risk of the underlying bonds. Option replication and hedging under the beta model accounts for random changes in the underlying bond price, price volatility and short-term interest rates.

Trading Activity and Price Volatility in the Municipal Bond Market

Utilizing a comprehensive database of transactions in municipal bonds, we investigate the volume-volatility relationship in the muni market. We find a positive relationship between the number of transactions and a bond's price volatility. In contrast to previous studies, we find a negative relationship between average deal size and price volatility. These results are found to be robust throughout the sample. Our results are inconsistent with current theoretical models of the volume-volatility relationship. These inconsistencies may arise because current models fail to account for the effects of overall market liquidity on the costs of large transactions.

Investment Basics XLI: Duration and convexity

Extracted from text ... Number 51 - Part 5 * G Lwabona Investment Basics XLI: Duration and convexity * School of Management Studies, Faculty of Commerce, University of Cape Town, Private Bag, Rondebosch 7701, Republic of South Africa. Email:glwabona@commerce.uct.ac.za. 1. Introduction This is the second in a series of two articles dealing with measuring and managing the impact of interest rate changes on bond prices. Whereas the first article, which appeared in the previous issue, discussed bond price volatility; this article discusses the concepts of duration and convexity. 2. Duration The previous article identifies three key variables as determinants of bond price volatility, namely ..

Investment Basics XL: Bond price volatility

(1999). Investment Basics XL: Bond price volatility. Investment Analysts Journal: Vol. 28, No. 50, pp. 65-69.