1,721,094 research outputs found
Discount rates and cash flows: A local projection approach
No full textPublisher Copyright: © 2024 The Author(s)We develop flexible local projections to quantify the relative contributions of expected discount rates and cash flows to the variation of dividend yields. Local projections enable the incorporation of large information sets, the use of monthly data along with annual data, and the consideration of time variation in the dividend yield decomposition. By expanding the set of state variables and allowing for time-varying parameters, our results show that the variation of expected discount rates remains the primary contributor to market volatility, whereas the contribution of expected cash flows is considerably smaller.Peer reviewe
Heterogeneity in Stock Pricing: A STAR Model with Multivariate Transition Functions
No full textStock prices often diverge from measures of fundamental value, which simple present value models fail to explain. This paper tries to find causes for these long-run price movements and their persistence by estimating a STAR model for the price-earnings ratio of the S&P500 index for 1961Q1 - 2009Q3, with a transition function that depends on a wider set of exogenous or predetermined transition variables. Several economic, monetary and financial variables, as well as linear combinations of these, are found to have nonlinear effects on stock prices. A two-step estimation procedure is proposed to select the transition variables and estimate their weights. This STAR model can be interpreted as a heterogeneous agent asset pricing model that makes a distinction between chartists and fundamentalists, where the set of transition variables is included in the agents’ information set.Heterogeneous agents, Regime switching, Stock prices, STAR models
Essays on expectations and the econometrics of asset pricing
Full text linkThe way in which market participants form expectations affects the dynamic properties of financial asset prices and therefore the appropriateness of different econometric tools used for empirical asset pricing. In addition to standard rational expectations models, this thesis studies a class of models in which boundedly rational agents may switch between various simple expectation rules. A well-known specific example features fundamentalists, who target the fundamental value of the asset, and chartists, who try to exploit recent trends in price movements. A crucial feature of these models is that not all agents have to follow the same expectation rule, but are allowed to form heterogeneous beliefs.
Chapters 2 and 3 present empirical estimations of two specific heterogeneous agent models. Since the data generating processes are assumed to be nonlinear, due to the agents' switching between expectation rules, nonlinear regression models are applied. By framing the empirical results in a heterogeneous agent framework, these chapters provide an alternative view on important topics in asset pricing, such as the prevalence of excess volatility and the relation between financial markets and the macro-economy.
The final two chapters deal with noncausal, or forward-looking, autoregressive models. Chapter 4 shows that US stock prices are better described by noncausal autoregressions than by their causal counterparts. This implies that agents' expectations are not revealed to an outside observer such as an econometrician observing only realized market data. Simulation results show that heterogeneous agent models are able to generate noncausal asset prices.
Chapter 5 considers the estimation of a class of standard rational expectations models. It is shown that noncausality of the instrumental variables does not have an impact on the consistency of the generalized method of moments (GMM) estimator, as long as agents form rational expectations.Ei saatavillaei saavutettav
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Mind the Basel gap
No full textFunding Information: We thank three anonymous referees, Katja Ahoniemi, Adriana Cornea-Madeira, Mikael Juselius, Ilkka Kiema, and seminar and conference participants at Aalto University, Aarhus University, De Nederlandsche Bank, the American Economic Association 2020, the Finnish Economic Association 2020, the International Conference on Computational and Financial Econometrics 2021, and the RiskLab/BoF/ESRB Conference on Systemic Risk Analytics 2019 for useful comments, and Henri Peltonen for excellent research assistance. This work was supported by the Finnish foundation for the advancement of securities markets under grant 202000039. Funding Information: We thank three anonymous referees, Katja Ahoniemi, Adriana Cornea-Madeira, Mikael Juselius, Ilkka Kiema, and seminar and conference participants at Aalto University, Aarhus University, De Nederlandsche Bank, the American Economic Association 2020, the Finnish Economic Association 2020, the International Conference on Computational and Financial Econometrics 2021, and the RiskLab/BoF/ESRB Conference on Systemic Risk Analytics 2019 for useful comments, and Henri Peltonen for excellent research assistance. This work was supported by the Finnish foundation for the advancement of securities markets under grant 202000039 . Publisher Copyright: © 2022 The Author(s)The Basel credit gap, the difference between a country's credit-to-GDP ratio and its estimated long-term trend, is used as a basis for setting countercyclical capital buffers under the Basel III regulatory framework. Using international data from the BIS, we show that the Basel credit gap, estimated by a one-sided HP filter, is nearly equivalent to a naive 16-quarter change in the credit-to-GDP ratio and performs equally well in terms of predicting banking crises. We demonstrate that the near-equivalence between deviations from trend and simple changes occurs when the one-sided HP filter is applied to a unit-root process. The goal of this paper is not to evaluate the performance of the Basel credit gap as an early-warning-indicator, but rather to demonstrate that its estimation method is unnecessarily complicated.Peer reviewe
Rational Speculators, Contrarians and Excess Volatility
Full text linkThe VAR approach for testing present value models is applied to a nonlinear asset pricing model with three types of agents, using historical US stock prices and dividends. Besides rational long-term investors, that value assets according to expected dividends, the model includes rational and contrarian speculators. Agents choose their regime based on evolutionary considerations. Supplementing the standard present value model with speculative agents dramatically improves the model's ability to replicate the observed market dynamics. In particular the existence of contrarians can explain some of the most volatile episodes including the 1990s bubble, suggesting this was not a rational bubble
GMM estimation with noncausal instruments under rational expectations
Full text linkThere is hope for the generalized method of moments (GMM). Lanne and Saikkonen (2011) show that the GMM estimator is inconsistent, when the instruments are lags of noncausal variables. This paper argues that this inconsistency depends on distributional assumptions, that do not always hold. In particular under rational expectations, the GMM estimator is found to be consistent. This result is derived in a linear context and illustrated by simulation of a nonlinear asset pricing model.generalized method of moments, noncausal autoregression, rational expectations
Noncausality and Asset Pricing
Full text linkMisspecification of agents' information sets or expectation formation mechanisms maylead to noncausal autoregressive representations of asset prices. Annual US stock prices are found to be noncausal, implying that agents' expectations are not revealed to an outside observer such as an econometrician observing only realized market data. A simulation study shows that noncausal processes can be generated by asset-pricing models featuring heterogeneous expectations
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