scholarly journals Explaining the Level of Credit Spreads: Option-Implied Jump Risk Premia in a Firm Value Model

2005 ◽  
Author(s):  
Martijn Cremers ◽  
Joost Driessen ◽  
Pascal J. Maenhout ◽  
David Weinbaum
Keyword(s):  
Firm Value ◽  
Risk Premia ◽  
Credit Spreads ◽  
Jump Risk ◽  
Value Model

scholarly journals Explaining the Level of Credit Spreads: Option-Implied Jump Risk Premia in a Firm Value Model

2008 ◽  
Vol 21 (5) ◽  
pp. 2209-2242 ◽  
Author(s):  
K.J. Martijn Cremers ◽  
Joost Driessen ◽  
Pascal Maenhout
Keyword(s):  
Firm Value ◽  
Risk Premia ◽  
Credit Spreads ◽  
Jump Risk ◽  
Value Model

On the Nature of Jump Risk Premia

2019 ◽  
Author(s):  
Piotr Orłowski ◽  
Paul Georg Schneider ◽  
Fabio Trojani
Keyword(s):  
Risk Premia ◽  
Jump Risk

Conditional equity risk premia and realized variance jump risk

2014 ◽  
Vol 40 (2) ◽  
pp. 295-317 ◽  
Author(s):  
Zhanglong Wang ◽  
Kent Wang ◽  
Zheyao Pan
Keyword(s):  
Risk Premia ◽  
Realized Variance ◽  
Jump Risk ◽  
Equity Risk

Information Content of Adjusted Implied Volatility in the KOSPI 200 Index Options Market

2009 ◽  
Vol 17 (4) ◽  
pp. 75-103
Author(s):  
Byung Jin Kang ◽  
Sohyun Kang ◽  
Sun-Joong Yoon
Keyword(s):  
Implied Volatility ◽  
Risk Premia ◽  
Risk Averse ◽  
Options Market ◽  
Jump Risk ◽  
Index Options ◽  
Volatility Risk ◽  
Model Free ◽  
Volatility Model ◽  
Forecasting Errors

This study examines the forecasting ability of the adjusted implied volatility (AIV), which is suggested by Kang, Kim and Yoon (2009), using the horserace competition with historical volatility, model-free implied volatility, and BS implied volatility in the KOSPI 200 index options market. The adjusted implied volatility is applicable when investors are not risk averse or when underlying returns do not follow a normal distribution. This implies that AIV is consistent with the presence of risk premia for other risk such as volatility risk and jump risk. Using KOSPI 200 index options, it is shown that the AIV outperforms other volatility estimates in terms of the unbiasedness for future realized volatilities as well as the forecasting errors.

Unconventional monetary policy in a nonlinear quadratic model

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Timm Faulwasser ◽  
Marco Gross ◽  
Willi Semmler ◽  
Prakash Loungani
Keyword(s):  
Monetary Policy ◽  
Financial Market ◽  
Great Recession ◽  
Central Banks ◽  
Risk Premia ◽  
Credit Spreads ◽  
Dynamic State ◽  
Quadratic Model ◽  
Unconventional Monetary Policy ◽  
The Great Recession

AbstractAfter the financial market meltdown and the Great Recession of the years 2007–9, the financial market-macro link has become an important issue in monetary policy modeling. We develop a dynamic model that contains a nonlinear Phillips curve, a dynamic output equation, and a nonlinear credit flow equation – capturing the importance of credit cycles, risk premia, and credit spreads. Our Nonlinear Quadratic Model (NLQ) model has three dynamic state equations and a quadratic objective function. It can be used to evaluate the response of central banks to the Great Recession in moving from conventional to unconventional monetary policy. We solve the model with a new numerical procedure using estimated parameters for the euro area. We conduct simulations to explore the (de)stabilizing effects of the nonlinearities in the model. We demonstrate that credit flows, risk premia, and credit spreads play an important role as an amplification mechanism and in affecting the transmission of monetary policy. We thereby highlight the importance of the natural rate of interest as an anchor for a central bank target and the weight it places on the credit flows for the effectiveness of unconventional monetary policy. Our model is similar in structure compared to larger scale macro-econometric models which many central banks employ.

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