Fast Calibration of Interest Rate Claims in the Quadratic Gaussian Model : 2 the Swaptions

2009 ◽  
Author(s):  
Daniel Alexandre Bloch
Keyword(s):  
Interest Rate ◽  
Gaussian Model

Sensitivities under G2++ model of the yield curve

2017 ◽  
Vol 04 (01) ◽  
pp. 1750008
Author(s):  
H. Jaffal ◽  
Y. Rakotondratsimba ◽  
A. Yassine
Keyword(s):  
Interest Rate ◽  
Yield Curve ◽  
Gaussian Model ◽  
Interest Rate Derivatives ◽  
Market Participants ◽  
Liability Management ◽  
Analytic Expressions ◽  
Text Model ◽  
The Interest Rate ◽  
Coupon Bond

The two-additive-factor Gaussian model G2[Formula: see text] is a famous stochastic model for the instantaneous short rate. It has functional qualities required in various practical purposes, as in Asset Liability Management and in Trading of interest rate derivatives. Though closed formulas for the prices of various main interest-rate instruments are known and used under the G2[Formula: see text] model, it seems that references for the corresponding sensitivities are not clearly presented over the financial literature. To fill this gap is one of our purposes in the present work. We derive here analytic expressions for the sensitivities of zero-coupon bond, coupon-bearing bonds, portfolio of coupon bearing bonds. The sensitivities under consideration here are those with respect to the shocks linked to the unobservable two-uncertainty shock risk/opportunity factors underlying the G2[Formula: see text] model. As a such, the hedging of a position sensitive to the interest rate by means of a portfolio (in accordance with the market participants practice) becomes easily transparent as just resulting from the balance between the various involved sensitivities.

scholarly journals Term Structure Estimation with Survey Data on Interest Rate Forecasts

2011 ◽  
Vol 47 (1) ◽  
pp. 241-272 ◽  
Author(s):  
Don H. Kim ◽  
Athanasios Orphanides
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Term Structure ◽  
Market Price ◽  
Gaussian Model ◽  
Small Sample ◽  
Expectations Hypothesis ◽  
No Arbitrage ◽  
Short Run ◽  
Small Sample Problem

AbstractThe estimation of dynamic no-arbitrage term structure models with a flexible specification of the market price of risk is beset by severe small-sample problems arising from the highly persistent nature of interest rates. We propose using survey forecasts of a short-term interest rate as an additional input to the estimation to overcome the problem. To illustrate the methodology, we estimate the 3-factor affine-Gaussian model with U.S. Treasury yields data and demonstrate that incorporating information from survey forecasts mitigates the small-sample problem. The model thus estimated for the 1990–2003 sample generates a stable and sensible estimate of the expected path of the short rate, reproduces the well-known stylized patterns in the expectations hypothesis tests, and captures some of the short-run variations in the survey forecast of the changes in longer-term interest rates.

scholarly journals The Gauss2++ model: a comparison of different measure change specifications for a consistent risk neutral and real world calibration

2021 ◽  
Author(s):  
Christoph Berninger ◽  
Julian Pfeiffer
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Real World ◽  
Risk Premium ◽  
Risk Measures ◽  
Insurance Industry ◽  
Gaussian Model ◽  
Interest Rate Models ◽  
Risk Neutral

AbstractEspecially in the insurance industry interest rate models play a crucial role, e.g. to calculate the insurance company’s liabilities, performance scenarios or risk measures. A prominant candidate is the 2-Additive-Factor Gaussian Model (Gauss2++ model)—in a different representation also known as the 2-Factor Hull-White model. In this paper, we propose a framework to estimate the model such that it can be applied under the risk neutral and the real world measure in a consistent manner. We first show that any time-dependent function can be used to specify the change of measure without loosing the analytic tractability of, e.g. zero-coupon bond prices in both worlds. We further propose two candidates, which are easy to calibrate: a step and a linear function. They represent two variants of our framework and distinguish between a short and a long term risk premium, which allows to regularize the interest rates in the long horizon. We apply both variants to historical data and show that they indeed produce realistic and much more stable long term interest rate forecast than the usage of a constant function, which is a popular choice in the industry. This stability over time would translate to performance scenarios of, e.g. interest rate sensitive fonds and risk measures.

Stochastic volatility asymptotics of defaultable interest rate derivatives under a quadratic Gaussian model

2016 ◽  
Vol 17 (01) ◽  
pp. 1750003
Author(s):  
Ji-Hun Yoon ◽  
Jeong-Hoon Kim ◽  
Sun-Yong Choi ◽  
Youngchul Han
Keyword(s):  
Interest Rate ◽  
Stochastic Volatility ◽  
Term Structure ◽  
Default Risk ◽  
Gaussian Model ◽  
Quadratic Term ◽  
Interest Rate Derivatives ◽  
Term Structure Model ◽  
Quadratic Term Structure ◽  
The Interest Rate

Stochastic volatility of underlying assets has been shown to affect significantly the price of many financial derivatives. In particular, a fast mean-reverting factor of the stochastic volatility plays a major role in the pricing of options. This paper deals with the interest rate model dependence of the stochastic volatility impact on defaultable interest rate derivatives. We obtain an asymptotic formula of the price of defaultable bonds and bond options based on a quadratic term structure model and investigate the stochastic volatility and default risk effects and compare the results with those of the Vasicek model.

Multidimensional, Nonthreshold Gaussian Model of Source Memory

2004 ◽  
Author(s):  
William P. Banks ◽  
Clayton Stephenson ◽  
Nisha Gottfredson ◽  
Andrew A. Sparrow
Keyword(s):  
Source Memory ◽  
Gaussian Model

Dampak Kebijakan Moneter Pada Output Di Negara-Negara ASEAN Tahun 1980-2014

2017 ◽  
Vol 4 (1) ◽  
pp. 58-70
Author(s):  
Nur Widiastuti
Keyword(s):  
Monetary Policy ◽  
Interest Rate ◽  
Fixed Effects ◽  
Empirical Studies ◽  
Negative Relationship ◽  
Least Square ◽  
Fixed Effects Model ◽  
State Data ◽  
Ordinary Least Square ◽  
The Impact

The Impact of monetary Policy on Ouput is an ambiguous. The results of previous empirical studies indicate that the impact can be a positive or negative relationship. The purpose of this study is to investigate the impact of monetary policy on Output more detail. The variables to estimatate monetery poicy are used state and board interest rate andrate. This research is conducted by Ordinary Least Square or Instrumental Variabel, method for 5 countries ASEAN. The state data are estimated for the period of 1980 – 2014. Based on the results, it can be concluded that the impact of monetary policy on Output shown are varied.Keyword: Monetary Policy, Output, Panel Data, Fixed Effects Model

Economic effects of monetary policy in Russia: What do large datasets tell us?

2020 ◽  
pp. 31-53 ◽  
Author(s):  
Anna A. Pestova ◽  
Natalia A. Rostova
Keyword(s):  
Monetary Policy ◽  
Interest Rate ◽  
Interest Rates ◽  
Economic Activity ◽  
Global Financial Crisis ◽  
Exchange Rate Regime ◽  
Aggregate Demand ◽  
Economic Effects ◽  
Theoretical Concepts ◽  
Empirical Estimates

Is the Bank of Russia able to control inflation and, at the same time, manage aggregate demand using its interest rate instruments? In other words, are empirical estimates of the effects of monetary policy in Russia consistent with the theoretical concepts and experience of advanced economies? This paper is aimed at addressing these issues. Unlike previous research, we employ “big data” — a large dataset of macroeconomic and financial data — to estimate the effects of monetary policy in Russia. We focus exclusively on the period after the 2008—2009 global financial crisis when the Bank of Russia announced the abandoning of its fixed ruble exchange rate regime and started to gradually transit to an interest rate management. Our estimation results do not confirm standard responses of key economic activity and price variables to tightening of monetary policy. Specifically, our estimates do not reveal a statistically significant restraining effect of the Bank of Russia’s policy of high interest rates on inflation in recent years. At the same time, we find a significant deteriorating effect of the monetary tightening on economic activity indicators: according to our conservative estimates, each of the key rate increases occurred in March and December 2014 had led to a decrease in the industrial production index by about 0.2 percentage points within a year.

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