Yield Curve Risk Research Articles

HAS SECONDARY MORTGAGE MARKET PROMOTE HOUSE AFFORDABILITY? EVIDENCE FROM INDONESIA

The advantage of secondary mortgage market establishment to decrease housing cost, theoretically, had been mentioned frequently in domestic and international research. However, research on this matter in Indonesia is still limited to narrative descriptive. This research engages sequential explanatory design by utilizing empirical evidence from financial perspective to analyse the impact of securitization to the yield spread premium from monthly data ranging from June 2017-April 2021. In quantitative phase, this research found that either securitization volume or the launch of new series of asset backed securities (ABS) significantly affects mortgage rate, contrary to aggregate mortgage volume, prepayment risk, and yield curve risk. In the qualitative phase, it is explored that the reason of securitization’s stagnation is market unreadiness.

Yield curve risks in currency carry forwards

AbstractWe provide empirical evidence that cross‐country yield curve gaps (parallel gap, twist gap, and butterfly gap) are predictive to the expected currency carry premiums using currency forward contracts. We find that the expected currency gains are more notable as these yield curve risk factors at time t indicate short‐term bond prices of investment currencies to go up (positive parallel movement, negative twist, and positive butterfly). We also find carry gains are more sensitively affected by cross‐country monetary shocks than currency‐country inflation pressures and business cycles. Our findings support that cross‐country yield curve risk premiums still exist even after considering transaction costs.

Cross Currency Swap Trading & Pricing Formulae - A PowerPoint Overview with Excel Pricing Examples

This document provides a summary of the more detailed cross pricing paper, see https://ssrn.com/abstract=3278907. We present a PowerPoint overview of cross currency swaps (Xccy Swaps) and the pricing formula as seen from a trading perspective. Firstly we outline swap preliminaries, reviewing interest rate swaps, yield curve construction, rates trading, pricing & risk. Secondly we outline and give a breakdown of the cross currency swap pricing formula and provide Excel pricing examples.

The Empirical Measurement of Interest Rate Risk of China’s Commercial Banks in the Process of Interest Rate Liberalization

With China’s financial system reform deepening, interest rate liberalization reform has sharply entered an accelerating course. This paper focuses on the interest rate risk of China’s commercial banks in the process of interest rate liberalization. Based on the literature review on interest rate risk management of commercial banks, this paper carries out an empirical analysis on four forms of interest rate risk under the certain background of China, repricing risk, basis risk, optional risk and yield curve risk. Based on the Interest Rate Sensitive Gap Approach and Duration Model, this paper carries out an empirical measurement of interest rate risk of China’s commercial banks in the process of interest rate liberalization. In the end, this paper proposes the countermeasures and suggestions for the interest rate risk management practice of China’s commercial banks.

Alternative models for hedging yield curve risk: An empirical comparison

We test alternative models of yield curve risk by hedging US Treasury bond portfolios through note/bond futures. We show that traditional implementations of models based on principal component analysis, duration vectors and key rate duration lead to high exposure to model errors and to sizable transaction costs, thus lowering the hedging quality. Also, this quality randomly varies from one model and hedging problem to the other. We show that accounting for the variance of modeling errors substantially reduces both hedging errors and transaction costs for all considered models. Additionally, it leads to much more stable weights in the hedging portfolios and – as a result – to more homogeneous hedging quality. On this basis, error-adjusted principal component analysis is found to systematically and significantly outperform alternative models.

A Guide to Duration, DV01, and Yield Curve Risk Transformations

Duration and DV01 (dollar duration) measure price sensitivity and provide the basic risk measure for bonds, swaps, and other fixed income instruments. When valuing instruments off a yield curve, duration and DV01 naturally extend to a vector of partial DV01s or durations (key rate durations) and these are widely used in the finance industry. But partial DV01s or durations can be measured with respect to different rates: forwards, par rates, zero yields, or others. This paper reviews the concepts of partial DV01 and duration and then discusses a simple method for transforming partial DV01s between different rate bases and provides examples. The benefit of this transformation method is that it only requires calculating the risk of a small set of alternate instrument and does not require re-calculating the original portfolio risk. (This paper is also available in an interactive version with enhanced digital content - see references.)

Alternative Models for Hedging Yield Curve Risk: An Empirical Comparison

We develop alternative models for hedging yield curve risk and test them by hedging US Treasury bond portfolios through note/bond futures. We show that traditional implementations of models based on principal component analysis, duration vectors and key rate duration lead to high exposure to model errors and to sizable transaction costs, thus lowering the hedging quality. Also, this quality varies from one test case to the other, so that a clear ranking of the models is not possible. We show that accounting for the variance of modeling errors substantially reduces both hedging errors and transaction costs for all considered models. Also, this allows to clearly rank these models: error‐adjusted principal component analysis systematically and significantly outperforms alternative models.

Currency carry trade regimes: Beyond the Fama regression

We show that carry trade strategies resemble FX option strategies that sell out of the money puts on high interest rate currencies. Both strategies collect premiums to generate persistent excess returns that unwind sharply when volatility increases. We also show that the widely documented negative slope coefficient in regressions of exchange rate depreciation on forward currency premiums is an artifact of the volatility regime. In high volatility regimes, the so-called Fama regression produces a positive coefficient greater than unity. We finally document the existence of an intuitive co-movement between currency risk premiums and yield curve risk factors.

Yield curve risk management: adjusting principal component analysis for model errors

Yield curve risk management: adjusting principal component analysis for model errors

Yield Curve Factors, Yield Volatility, and the Predictability of Bond Excess Returns

We study the predictability of U.S. government bond excess returns using yield curve factors as well as yield volatility components. The yield curve factors are the level, slope and curvature factors extracted from a dynamic Nelson and Siegel (1987) framework. The yield volatility factors correspond to stochastic volatility components associated with the Nelson-Siegel factors, and capture time-varying risk inherent to the yield curve. The model is estimated using Markov chain Monte Carlo techniques based on U.S. government yields.We find that the slope and curvature yield factors explain up to 36% of the variation in future yearly bond excess returns revealing the same predictability as the return-forecasting factor proposed by Cochrane and Piazzesi (2005). Moreover, it turns out that the volatility factors parsimoniously and effectively capture yield curve risk. Including them in forecasting regressions for bond return premia increases the forecasting R-Squared to up to 50%. It is shown that the predictive power of the volatility factors is neither subsumed by Nelson-Siegel type yield curve factors nor the Cochrane-Piazzesi return-forecasting factor. Moreover, we illustrate that the extracted yield curve factors and volatility factors are closely connected to underlying macroeconomic fundamentals.

Endogenous Yield Curve Risk from Central Bank Policy Uncertainty

Due to economic feedback the actual risk in bonds from changes in Federal Reserve policy should generally be smaller than measured using conventional duration measures. We introduce the notion of Federal Reserve policy durations. For example, target inflation duration, which measures the change in the price of a treasury bond that arises from a change in Central Bank target inflation rate that occurs at some time in the future before the maturity of the bond. For Central Banks following a policy setting rule such as a Taylor rule, we derive a simple analytic expression for the target inflation duration of zero coupon Treasury bonds in terms of model economic parameters and the parameters in the Taylor rule. The correction to the traditional duration of a zero coupon bond is proportional, at leading order, to the product of three terms: the Taylor rule output gap coefficient, the coefficient in the economy that determines the response of the output gap to the real rate, and the square of the maturity of the zero coupon bond.

Managing Yield-Curve Risk with Combination Hedges

The method presented here to evaluate and regulate the risk exposure of default-free bonds generalizes the traditional duration concept by taking nonparallel changes in the term structure of interest rates into account. The article shows how to immunize a default-free bond by hedging with two standard hedging instruments (a combination hedge) and how to replicate a diversified bond portfolio by using a few standard hedging instruments. This standard hedging instrument representation can provide comprehensive information about the risk structure of the portfolio, and trading the standard hedging instruments can help fine-tune a position.

Yield Curve Risk in Japanese Government Bond Markets

This paper characterizes the nature of yield curve risk in the Japanese government bond (JGB) market, and explores the effectiveness of risk management based on a linear factor representation of yield curve risk. The implied optimal hedges against factor risk are related to duration‐based hedging strategies, which are shown in many cases to be substantially sub‐optimal. In addition, the drift over time in optimal hedge ratios due to the local nature of optimal hedging is investigated. The results show substantial drift especially for the weights on the factor representing the risk of a changing slope of the JGB yield curve. Though our focus is on government bond markets, the findings have implications for risk management for most interest‐sensitive instruments, especially those that are priced relative to government bonds (e.g. corporate bonds).

Portfolio Optimization

AbstractBased on the profit and loss account of an insurance company we derive a probabilistic model for the financial result of the company, thereby both assets and liabilities are marked to market. We thus focus on the economic value of the company.We first analyse the underwriting risk of the company. The maximization of the risk return ratio of the company is derived as optimality criterion. It is shown how the risk return ratio of heterogeneous portfolios or of catastrophe exposed portfolios can be dramatically improved through reinsurance. The improvement of the risk return ratio through portfolio diversification is also analysed.In section 3 of the paper we analyse the loss reserve risk of the company. It is shown that this risk consists of a loss reserve development risk and of a yield curve risk which stems from the discounting of the loss reserves. This latter risk can be fully hedged through asset liability matching.In section 4 we derive our general model. The portfolio of the company consists of a portfolio of insurance risks and of a portfolio of financial risks. Our model allows for a simultaneous optimization of both portfolios of risks. A theorem is derived which gives the optimal retention policy of the company together with its optimal asset allocation.Some of the material presented in this paper is taken from Schnieper, 1997. It has been repeated here in order to make this article self contained.

Risk Management under a Two-Factor Model of the Term Structure of Interest Rates

This paper presents several applications to interest rate risk management based on a two-factor continuous-time model of the term structure of interest rates previously presented in Moreno (1996). This model assumes that default free discount bond prices are determined by the time to maturity and two factors, the long-term interest rate and the spread (difference between the long-term rate and the short-term (instantaneous) riskless rate). Several new measures of generalized are presented and applied in different situations in order to manage market risk and yield curve risk. By means of these measures, we are able to compute the hedging ratios that allows us to immunize a bond portfolio by means of options on bonds. Focusing on the hedging problem, it is shown that these new measures allow us to immunize a bond portfolio against changes (parallel and/or in the slope) in the yield curve. Finally, a proposal of solution of the limitations of conventional duration by means of these new measures is presented and illustrated numerically.

Measuring Yield Curve Risk Using Principal Components, Analysis, Value, At Risk, And Key Rate Durations

Measuring Yield Curve Risk Using Principal Components, Analysis, Value, At Risk, And Key Rate Durations

The Risk-Point Method for Measuring and Controlling Yield Curve Risk

The duration of a fixed-income asset (or liability) is a measure of its price sensitivity relative to its own yield. It is well recognized that duration fails to capture the exposure of a portfolio to changes in the shape of the yield curve. This form of interest rate risk, referred to as yield curve risk, can be significant in portfolios containing options, some mortgage derivatives, and most exotic securities. The authors present a risk measure that is more complete than simple measures such as duration that can be used in measuring the yield curve. This “risk-point measure” can be applied to various active and structured portfolio strategies.

Managing Yield Curve Risk in an Index Environment

A fixed income market index can be viewed as a large set of future cash flows, divisible into any number of intervals. Each interval can be characterized by a forward rate-the implied rate earned over the interval. By measuring the sensitivity of the index to a change in each forward rate (holding all other forward rates constant), the partial derivative approach provides an accurate measure of the index's exposure to changes in the level and shape of the yield curve. To apply the PDA, one must first define appropriate yield curve intervals. Because changes in near forward rates have a much greater impact on value than changes in far forward rates, it is reasonable to use shorter intervals for the near term and longer ones for the far term. Next, one calculates the index's exposure to a series of forward rate changes, making separate calculations for each bond in the index. Risk exposures are similarly calculated for the bond fund constructed to track the index. The differences between the portfolio's and the index's risk exposures define the portfolio's deviation from the index. The portfolio can then be adjusted to balance the client's desired degree of risk exposure with the expectation of excess return.