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Give Me Strong Moments and Time: Combining GMM and SMM to Estimate Long-run Risk Asset Pricing Models

Give Me Strong Moments and Time: Combining GMM and SMM to Estimate Long-run Risk Asset Pricing Models
Author: Joachim Grammig
Publisher:
Total Pages:
Release: 2014
Genre:
ISBN:

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The long-run consumption risk (LRR) model is a promising approach to resolve prominent asset pricing puzzles. The simulated method of moments (SMM) provides a natural framework to estimate its deep parameters, but caveats concern model solubility and weak identification. We propose a two-step estimation strategy that combines GMM and SMM, and for which we elicit informative macroeconomic and financial moment matches from the LRR model structure. In particular, we exploit the persistent serial correlation of consumption and dividend growth and the equilibrium conditions for market return and risk-free rate, as well as the model-implied predictability of the risk-free rate. We match analytical moments when possible and simulated moments when necessary and determine the crucial factors required for both identification and reasonable estimation precision. A simulation study - the first in the context of long-run risk modeling - delineates the pitfalls associated with SMM estimation of a non-linear dynamic asset pricing model. Our study provides a blueprint for successful estimation of the LRR model.


Give Me Strong Moments and Time

Give Me Strong Moments and Time
Author: Joachim Grammig
Publisher:
Total Pages: 56
Release: 2014
Genre:
ISBN:

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The long-run consumption risk (LRR) model is a promising approach to resolve prominent asset pricing puzzles. The simulated method of moments (SMM) provides a natural framework to estimate its deep parameters, but caveats concern model solubility and weak identification. We propose a twostep estimation strategy that combines GMM and SMM, and for which we elicit informative macroeconomic and financial moment matches from the LRR model structure. In particular, we exploit the persistent serial correlation of consumption and dividend growth and the equilibrium conditions for market return and risk-free rate, as well as the model-implied predictability of the risk-free rate. We match analytical moments when possible and simulated moments when necessary and determine the crucial factors required for both identification and reasonable estimation precision. A simulation study|the first in the context of long-run risk modeling|delineates the pitfalls associated with SMM estimation of a non-linear dynamic asset pricing model. Our study provides a blueprint for successful estimation of the LRR model.


Give Me Strong Moments and Time

Give Me Strong Moments and Time
Author: Joachim Grammig
Publisher:
Total Pages: 63
Release: 2016
Genre:
ISBN:

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The long-run consumption risk (LRR) model is a popular approach to resolve various asset pricing puzzles, but its econometric analysis is complicated and often relies on simulation-based methods. This study addresses inherent identification problems and offers a solution by proposing a two-step GMM/SMM estimation strategy that exploits the recursive LRR model structure. We motivate macroeconomic and financial moment matches and show possibilities and limits for a successful econometric analysis of the LRR model. A simulation study and an empirical application reveal the estimation quality, in terms of feasibility and precision, that reasonably can be expected.


Multi-moment Asset Allocation and Pricing Models

Multi-moment Asset Allocation and Pricing Models
Author: Emmanuel Jurczenko
Publisher: John Wiley & Sons
Total Pages: 274
Release: 2006-10-27
Genre: Business & Economics
ISBN:

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While mainstream financial theories and applications assume that asset returns are normally distributed and individual preferences are quadratic, the overwhelming empirical evidence shows otherwise. Indeed, most of the asset returns exhibit “fat-tails” distributions and investors exhibit asymmetric preferences. These empirical findings lead to the development of a new area of research dedicated to the introduction of higher order moments in portfolio theory and asset pricing models. Multi-moment asset pricing is a revolutionary new way of modeling time series in finance which allows various degrees of long-term memory to be generated. It allows risk and prices of risk to vary through time enabling the accurate valuation of long-lived assets. This book presents the state-of-the art in multi-moment asset allocation and pricing models and provides many new developments in a single volume, collecting in a unified framework theoretical results and applications previously scattered throughout the financial literature. The topics covered in this comprehensive volume include: four-moment individual risk preferences, mathematics of the multi-moment efficient frontier, coherent asymmetric risks measures, hedge funds asset allocation under higher moments, time-varying specifications of (co)moments and multi-moment asset pricing models with homogeneous and heterogeneous agents. Written by leading academics, Multi-moment Asset Allocation and Pricing Models offers a unique opportunity to explore the latest findings in this new field of research.


Measuring "Dark Matter” in Asset Pricing Models

Measuring
Author: Hui Chen
Publisher:
Total Pages: 81
Release: 2019
Genre: Assets (Accounting)
ISBN:

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We introduce an information-based fragility measure for GMM models that are potentially misspecified and unstable. A large fragility measure signifies a GMM model's lack of internal refutability (weak power of specification tests) and external validity (poor out-of-sample fit). The fragility of a set of model-implied moment restrictions is tightly linked to the quantity of additional information the econometrician can obtain about the model parameters by imposing these restrictions. Our fragility measure can be computed at little cost even for complex dynamic structural models. We illustrate its applications via two models: a rare-disaster risk model and a long-run risk model.


Risks For the Long Run

Risks For the Long Run
Author: Ravi Bansal
Publisher:
Total Pages:
Release: 2012
Genre: Assets (Accounting)
ISBN:

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The long-run risks (LRR) asset pricing model emphasizes the role of low-frequency movements in expected growth and economic uncertainty, along with investor preferences for early resolution of uncertainty, as an important economic-channel that determines asset prices. In this paper, we estimate the LRR model. To accomplish this we develop a method that allows us to estimate models with recursive preferences, latent state variables, and time-aggregated data. Time-aggregation makes the decision interval of the agent an important parameter to estimate. We find that time-aggregation can significantly affect parameter estimates and statistical inference. Imposing the pricing restrictions and explicitly accounting for time-aggregation, we show that the estimated LRR model can account for the joint dynamics of aggregate consumption, asset cash flows and prices, including the equity premia, risk-free rate and volatility puzzles.


A Two-step Indirect Inference Approach to Estimate the Long-run Risk Asset Pricing Model

A Two-step Indirect Inference Approach to Estimate the Long-run Risk Asset Pricing Model
Author: Joachim Grammig
Publisher:
Total Pages:
Release: 2017
Genre:
ISBN:

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The long-run consumption risk model provides a theoretically appealing explanation for prominent asset pricing puzzles, but its intricate structure presents a challenge for econometric analysis. This paper proposes a two-step indirect inference approach that disentangles the estimation of the model's macroeconomic dynamics and the investor's preference parameters. A Monte Carlo study explores the feasibility and efficiency of the estimation strategy. We apply the method to recent U.S. data and provide a critical re-assessment of the long-run risk model's ability to reconcile the real economy and financial markets. This two-step indirect inference approach is potentially useful for the econometric analysis of other prominent consumption-based asset pricing models that are equally difficult to estimate.


Asset Pricing Factor Models in the German Stock Market

Asset Pricing Factor Models in the German Stock Market
Author: Julian Fischer
Publisher: GRIN Verlag
Total Pages: 109
Release: 2021-06-14
Genre: Business & Economics
ISBN: 3346420094

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Master's Thesis from the year 2021 in the subject Business economics - Investment and Finance, grade: 1,7, University of Hannover (Institut für Finanzwirtschaft und Rohstoffmärkte), language: English, abstract: In this paper, we examine how various modern multifactor models, such as the Carhart factor model, five-factor model and its complement six-factor model by Fama and French, the q-factor model by Hou, Wue and Zhang, and the mispricing factor model by Stambaugh and Yuan perform in the German stock market. It is discernible that, depending on the application model, like factor spanning tests, different sortings, return anomalies, sector- and equity fund investigation, they often provide quite similar explanatory power, while in individual cases sometimes one and sometimes the other model performs better. The underlying factors contribute differently to the explanatory power depending on the time period. Thus, in case of doubt, the six-factor model is preferable, as it is the most versatile model. Since the establishment of the capital asset pricing model as a cornerstone of modern capital market theory in the 1960s, new investigations and studies have been built on this model on an ongoing basis. This continuously leads to extensions and modifications of the asset pricing models since then. These models can be used in various ways, for example to explain the pricing of risky financial assets under restrictive assumptions or to gain important insights into the relationship between expected return and risk of securities. These can be used in various ways, for example to explain the pricing of risky financial assets under restrictive assumptions or to gain important insights into the relationship between expected return and risk of securities. In this paper, we aim to answer the overarching research question of how modern asset pricing models perform for the German stock market. For this purpose, we first discuss the characteristics of the German stock market, followed by the milestones of the development of factor models, their empirical evidence and their factors, as well as internationally known return anomalies. In the subsequent part, five modern asset pricing models are tested in different scenarios of the German stock market, including factor spanning tests, different sortings, anomalies, sectors and in equity funds. For this purpose, various analytical methods are used and performed with the software “Stata”. Finally, the comprehensive results are summarized and concluded.


Filtering Methods for the Estimation of the Long-Run Risk Asset Pricing Model

Filtering Methods for the Estimation of the Long-Run Risk Asset Pricing Model
Author: Eva-Maria Küchlin
Publisher:
Total Pages: 49
Release: 2016
Genre:
ISBN:

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Previous attempts to estimate the long-run risk (LRR) model revealed serious methodological issues and low estimation precision of the existing econometric approaches. However, this study shows that despite the presence of latent variables asymptotically efficient maximum likelihood (ML) estimation is possible through application of filtering methods. A three-step estimation strategy is suggested that involves ML estimation relying on the Kalman filter and a particle filter, which allows to identify all LRR model parameters. A Monte Carlo study assesses the estimation precision for different sample sizes, an empirical application presents estimation results obtained from U.S. data.


Asset Pricing Tests with Long Run Risks in Consumption Growth

Asset Pricing Tests with Long Run Risks in Consumption Growth
Author: George M. Constantinides
Publisher:
Total Pages: 76
Release: 2011
Genre:
ISBN:

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A novel methodology in testing the long-run risks model of Bansal and Yaron (2004) is presented based on the observation that, under the null, the potentially latent state variables, long-run risk and the conditional variance of its innovation, are known affine functions of the observable market-wide price-dividend ratio and risk free rate. In linear forecasting regressions of consumption growth and returns by the price-dividend ratio and risk free rate, the model implies much higher forecastability than what is observed in the data over 1931-2009. The co-integrated variant of the model by Bansal, Gallant, and Tauchen (2007), also implies much higher forecastability of returns than what is observed in the data. Finally, we reject the models' implications in jointly pricing the cross-section of returns and fitting the unconditional time series moments of consumption and dividend growth. The results suggest that either some important state variable is missing or that the models should be generalized in a way that the lagged price-dividend ratio and risk free enter the regressions in a non-linear fashion.