scholarly journals Is There A Difference Between Domestic And Foreign Risk Premium? The Case Of China Stock Market

2014 ◽  
Vol 30 (5) ◽  
pp. 1287
Author(s):  
Frederic Teulon ◽  
Khaled Guesmi ◽  
Salma Fattoum
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Market Price ◽  
Time Varying ◽  
Expected Return ◽  
Market Price Of Risk ◽  
Market Prices ◽  
Price Of Risk ◽  
Show Evidence ◽  
The Difference

This article studies the dynamic return and market price of risk for Chinese stocks (A-B shares). A Multivariate DCC-GARCH model is used to capture the feature of time-varying volatility in stock returns. We show evidence of different pricing mechanisms explained by the difference in the expected return and market price of risk between A and B shares. However, the significance of the difference between market prices of risk disappears if GARCH models are used.

TIME-VARYING MARKET PRICE OF RISK AND AUTOREGRESSIVE ERROR STRUCTURE OF OIL PRICES

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Carla Gomes Costa de Souza ◽  
Fernando Antonio Lucena Aiube
Keyword(s):  
Market Price ◽  
Commodity Prices ◽  
Factor Models ◽  
Time Varying ◽  
Market Price Of Risk ◽  
Error Structure ◽  
Price Of Risk ◽  
Different Types ◽  
Oil Contracts ◽  
Smith Model

In this paper we investigate the inclusion of a time-varying market price of risk in oil price factor models. Additionally an autoregressive error structure is adopted to filter this property of financial series. We use the Schwartz and Smith model, which is well established in the literature on commodity prices. The analysis is easily extended to different types of factor models. The empirical application considered the future oil contracts traded on the NYMEX. We find that considering a time-varying market price of risk and the autoregressive structure improves the fit of the empirical data.

EQUILIBRIUM WITH EXCESSIVE HOLDINGS CONSTRAINT: AN APPLICATION TO DC PENSION PLANS

2007 ◽  
Vol 10 (07) ◽  
pp. 1159-1190 ◽  
Author(s):  
ISSOUF SOUMARÉ
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Market Price ◽  
Pension Plans ◽  
Defined Contribution ◽  
Excess Returns ◽  
Market Price Of Risk ◽  
Price Of Risk ◽  
Special Case ◽  
Accurate Quantification

In this paper, I study the equilibrium implications when some investors in the economy overweight a subset of stocks within their portfolio. I find that the excess returns for the overweighted stocks are lower, all else being equal. This has strong testable implications for stock returns. In the special case of logarithmic preferences, the riskfree rate increases and the market price of risk for the overweighted stock decreases, which create extra incentive for unconstrained agents to exit the stock market and hold bonds, hence clearing the market. The changes of stocks' volatilities are ambiguous. Finally, I provide an accurate quantification for agents' welfare. I also discuss the implications of my model in the context of defined contribution pension plans where workers hold large shares of their employer.

scholarly journals Implicit incentives for fund managers with partial information

2021 ◽  
Author(s):  
Flavio Angelini ◽  
Katia Colaneri ◽  
Stefano Herzel ◽  
Marco Nicolosi
Keyword(s):  
Asset Allocation ◽  
Partial Information ◽  
Market Price ◽  
Investment Strategy ◽  
Expected Returns ◽  
Martingale Method ◽  
Fund Manager ◽  
Market Price Of Risk ◽  
Fund Managers ◽  
Price Of Risk

AbstractWe study the optimal asset allocation problem for a fund manager whose compensation depends on the performance of her portfolio with respect to a benchmark. The objective of the manager is to maximise the expected utility of her final wealth. The manager observes the prices but not the values of the market price of risk that drives the expected returns. Estimates of the market price of risk get more precise as more observations are available. We formulate the problem as an optimization under partial information. The particular structure of the incentives makes the objective function not concave. Therefore, we solve the problem by combining the martingale method and a concavification procedure and we obtain the optimal wealth and the investment strategy. A numerical example shows the effect of learning on the optimal strategy.

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