Estimating the Long-Run Risk Asset Pricing Model with a Two-Step Indirect Inference Approach

2016 ◽  
Author(s):  
Joachim Grammig ◽  
Eva-Maria KKchlin
Keyword(s):  
Asset Pricing ◽  
Indirect Inference ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Long Run ◽  
Long Run Risk

Asset Pricing with Growth

2019 ◽  
pp. 45-55
Author(s):  
Harold L. Cole
Keyword(s):  
Asset Pricing ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Long Run ◽  
Risk Neutral

This chapter extends the risk-neutral asset pricing model to account for long-run growth.

scholarly journals LOCK-IN OF EXTRAPOLATIVE EXPECTATIONS IN AN ASSET PRICING MODEL

2006 ◽  
Vol 10 (3) ◽  
pp. 317-348 ◽  
Author(s):  
KEVIN J. LANSING
Keyword(s):  
Asset Pricing ◽  
Stock Prices ◽  
Forecast Errors ◽  
Time Varying ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Market Crashes ◽  
Long Run ◽  
Lock In ◽  
Predictability Of Returns

This paper examines an agent's choice of forecast method within a standard asset pricing model. A representative agent may choose: (1) a fundamentals-based forecast that employs knowledge of the dividend process, (2) a constant forecast that is based on a simple long-run average, or (3) a time-varying forecast that extrapolates from the last observation. I show that an agent who is concerned about minimizing forecast errors may inadvertently become “locked-in” to an extrapolative forecast. In particular, the initial use of extrapolation alters the law of motion of the forecast variable so that the agent perceives no accuracy gain from switching to one of the alternative forecast methods. The model can generate excess volatility of stock prices, time-varying volatility of returns, long-horizon predictability of returns, bubbles driven by optimism about the future, and sharp downward movements in stock prices that resemble market crashes.

Performances of liquidity factors in the stock market cycle: evidence from the Tokyo Stock Exchange

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xin Zhong
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Exchange ◽  
Regression Method ◽  
Pricing Model ◽  
Content Type ◽  
Asset Pricing Model ◽  
Long Run ◽  
Market Trends ◽  
Japanese Stock Market

PurposeThe purpose of this study is to examine the performances of liquidity factors in the stock market cycle. It aims to investigate whether the contribution of liquidity factors changes with stock market trends.Design/methodology/approachSix liquidity proxies and two-factor construction methods are compared in this study. The spanning regression method was applied to examine the contribution of liquidity factors to the asset pricing model, while the Fama and MacBeth regression method was used for examining the pricing power of liquidity factors.FindingsThe result shows that liquidity factors are accretive to models explaining returns in bull markets but not accretive to models in bear markets. The most appropriate method of constructing liquidity factors in the Japanese stock market has also been clarified.Originality/valueIn the Japanese stock market, there has never been a comprehensive test of the role of the liquidity risk factor in different market trends using the long-run data. This study helps with identifying the importance of liquidity pricing risk in different market trends. It also fills the gaps by comparing liquidity factors that are constructed through different methods and proxies and provides evidence for further confirming the correct asset pricing model in the future.

scholarly journals Updating Wealth in an Asset Pricing Model with Heterogeneous Agents

2010 ◽  
Vol 2010 ◽  
pp. 1-27 ◽  
Author(s):  
Serena Brianzoni ◽  
Cristiana Mammana ◽  
Elisabetta Michetti
Keyword(s):  
Asset Pricing ◽  
Heterogeneous Agents ◽  
Wealth Distribution ◽  
Three Dimensional ◽  
Trading Strategies ◽  
Adaptive Model ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Long Run ◽  
Dimensional Dynamical System

We consider an asset-pricing model with wealth dynamics in a market populated by heterogeneous agents. By assuming that all agents belonging to the same group agree to share their wealth whenever an agent joins the group (or leaves it), we develop an adaptive model which characterizes the evolution of wealth distribution when agents switch between different trading strategies. Two groups with heterogeneous beliefs are considered: fundamentalists and chartists. The model results in a nonlinear three-dimensional dynamical system, which we have studied in order to investigate complicated dynamics and to explain wealth distribution among agents in the long run.

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