scholarly journals Determinant Factors of Liquidity Risk Premium on Indonesian Government Bonds

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Eka Rathmanty Merry Hartini ◽  
Dewi Hanggraeni
Keyword(s):  
Risk Premium ◽  
Liquidity Risk ◽  
Government Bonds ◽  
Indonesian Government ◽  
Determinant Factors

Measuring inflation expectations in Russia using stock market data

2017 ◽  
pp. 111-122 ◽  
Author(s):  
M. Zhemkov ◽  
O. Kuznetsova
Keyword(s):  
Stock Market ◽  
Risk Premium ◽  
Liquidity Risk ◽  
Information Policy ◽  
Inflation Expectations ◽  
Government Bonds ◽  
Inflation Risk ◽  
Market Data ◽  
Inflation Risk Premium ◽  
The Difference

This paper is devoted to the measurement of inflation expectations in Russia based on stock market data for the period from July 2015 to December 2016. It calculates the difference between the yields of the nominal and inflation-indexed government bonds and adjusts it to the inflation risk premium and liquidity risk premium to obtain inflation expectations. This net indicator represents inflation expectations of the participants of the stock market. The estimated inflation expectations can be used to analyze the effectiveness of the information policy.

Liquidity-Risk-Premium Free Price Models of Government Bonds and Currency Forwards in Persistently Informed Markets

2017 ◽  
Author(s):  
Aryo Sasongko ◽  
Cynthia Afriani ◽  
Buddi Wibowo ◽  
Zaafri A. Husodo
Keyword(s):  
Risk Premium ◽  
Liquidity Risk ◽  
Government Bonds

The nineteenth-century US whaling industry: Where is the risk premium? New materials facilitate updated view

2021 ◽  
Vol 33 (2) ◽  
pp. 344-363
Author(s):  
Barbara L. Coffey
Keyword(s):  
Nineteenth Century ◽  
Risk Premium ◽  
Financial Returns ◽  
New Materials ◽  
Government Bonds ◽  
Us Government ◽  
Whaling Industry ◽  
The Mean ◽  
Printed Materials

Materials that were born digital, and printed materials that have been digitized, have aided an updated examination of nineteenth-century US whaling voyages’ financial returns. Items included the American Offshore Whaling Voyages dataset from whalinghistory.org , The Whalemen’s Shipping List and Merchant’s Transcript, a congressman’s speech and a state’s census reports. These works and others, with analysis, showed that for the 11,257 analysable voyages ending in the 1800s, the mean return was 4.7% and 4.6% for whaling and US government bonds, respectively. Ideally, this work will place the nineteenth-century US whaling industry returns in context of other investments.

scholarly journals A Balanced Portfolio Can Have a Higher Geometric Return than the Risky Asset

2021 ◽  
Vol 14 (9) ◽  
pp. 409
Author(s):  
Miriam Arden ◽  
Tiemen Woutersen
Keyword(s):  
Risk Premium ◽  
Large Fraction ◽  
Developed Countries ◽  
Policy Implications ◽  
Government Bonds ◽  
Stock Portfolios ◽  
Bond Portfolio ◽  
Target Date ◽  
Stock Portfolio ◽  
The U.S

In the U.S., the geometric return on stocks has been higher than the geometric return on bonds over long periods. We study whether balanced portfolios have a larger geometric return (and expected log return) than stock portfolios when the risk premium is low. We use a theoretical model and historical data and find that this is the case. This low-risk premium is often observed in other developed countries. Further, in the past two decades, a balanced portfolio with 70% or 90% invested in the U.S. stock market (with the remainder invested in U.S. government bonds) performed better than a 100% stock or bond portfolio. The reason for this is that a pure stock portfolio loses a large fraction of its value in a downturn. We show that this result is not driven by outliers, and that it occurs even when the returns are log normally distributed. This result has broad policy implications for the construction of pension systems and target-date mutual funds.

scholarly journals Pricing Liquidity Risk with Heterogeneous Investment Horizons

2020 ◽  
pp. 1-36 ◽  
Author(s):  
Alessandro Beber ◽  
Joost Driessen ◽  
Anthony Neuberger ◽  
Patrick Tuijp
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Liquidity Risk ◽  
Asset Returns ◽  
Spillover Effects ◽  
Expected Returns ◽  
Pricing Model ◽  
Liquidity Premium ◽  
Asset Pricing Model ◽  
Illiquid Asset

We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk) premium of illiquid assets is determined by investor horizons and the correlation between liquid and illiquid asset returns. We estimate our model for the cross-section of U.S. stock returns and find that it generates a good fit, mainly due to a combination of a substantial expected liquidity premium and segmentation effects, while the liquidity risk premium is small.

Optimal Portfolios For Different Holding Periods

2010 ◽  
Vol 8 (10) ◽  
Author(s):  
Byeongyong Paul Choi ◽  
Sandip Mukherji
Keyword(s):  
Risk Premium ◽  
Bootstrap Method ◽  
Investment Horizon ◽  
Financial Assets ◽  
Small Company ◽  
Optimal Portfolios ◽  
Treasury Bills ◽  
Government Bonds ◽  
Holding Period ◽  
Random Samples

<p class="MsoBodyText" style="text-align: justify; line-height: normal; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="color: black; font-size: 10pt; mso-themecolor: text1;"><span style="font-family: Times New Roman;">This study uses a block bootstrap method to construct random samples of returns of six major financial assets and identifies optimal portfolios for three different objectives relating to risk and return for short, medium, and long holding periods. Optimal portfolios minimizing risk consist solely of Treasury Bills and small company stocks for all periods, with an increasing allocation to small company stocks as the investment horizon lengthens. Optimal portfolios minimizing risk relative to return, as well as those maximizing the risk premium relative to risk, contain intermediate-term government bonds and stocks for all horizons, and the proportions of stocks in these portfolios increase with the investment horizon, small company stocks becoming the major component of the optimal portfolios for 10 years. These results indicate that, for investors optimizing any of these three objectives, the optimal portfolios contain increasing allocations of riskier assets, and decreasing allocations of safer assets, as the holding period increases.<strong style="mso-bidi-font-weight: normal;"></strong></span></span></p>

Liquidity Risk Premia in Corporate Bond Markets

2012 ◽  
Vol 02 (02) ◽  
pp. 1250006 ◽  
Author(s):  
Frank de Jong ◽  
Joost Driessen
Keyword(s):  
Risk Premium ◽  
Corporate Bonds ◽  
Liquidity Risk ◽  
Risk Premia ◽  
Market Liquidity ◽  
Corporate Bond ◽  
Expected Returns ◽  
Bond Returns ◽  
Treasury Bond ◽  
Investment Grade

This paper explores the role of liquidity risk in the pricing of corporate bonds. We show that corporate bond returns have significant exposures to fluctuations in treasury bond liquidity and equity market liquidity. Further, this liquidity risk is a priced factor for the expected returns on corporate bonds, and the associated liquidity risk premia help to explain the credit spread puzzle. In terms of expected returns, the total estimated liquidity risk premium is around 0.6% per annum for US long-maturity investment grade bonds. For speculative grade bonds, which have higher exposures to the liquidity factors, the liquidity risk premium is around 1.5% per annum. We find very similar evidence for the liquidity risk exposure of corporate bonds for a sample of European corporate bond prices.

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