Narrative Asset Pricing: Interpretable Systematic Risk Factors from News Text

2021 ◽  
Author(s):  
Leland Bybee ◽  
Bryan T. Kelly ◽  
Yinan Su
Keyword(s):  
Risk Factors ◽  
Asset Pricing ◽  
Systematic Risk ◽  
Systematic Risk Factors

The diverging role of the systematic risk factors: evidence from real estate stock markets

2015 ◽  
Vol 33 (1) ◽  
pp. 81-106 ◽  
Author(s):  
Stephan Lang ◽  
Alexander Scholz
Keyword(s):  
Risk Factors ◽  
Time Series ◽  
Asset Pricing ◽  
Real Estate ◽  
Systematic Risk ◽  
Content Type ◽  
Risk Return ◽  
Systematic Risk Factors ◽  
Relationship Of

Purpose – The risk-return relationship of real estate equities is of particular interest for investors, practitioners and researchers. The purpose of this paper is to examine, in an asset pricing framework, whether the systematic risk factors play a significantly different role in explaining the returns of listed real estate companies, compared to general equities. Design/methodology/approach – Running the difference test of the Fama-French three-factor and the liquidity-augmented asset pricing model, the authors analyze the effect of the systematic risk factors related to market, size, BE/ME and liquidity in a time-series setting over the period July 1992 to June 2012. By applying the propensity score matching (PSM) algorithm, the authors bypass the “curse of dimensionality” of traditional matching techniques and identify a comparable control sample of general equities, in terms of the relevant firm characteristics of size, BE/ME and liquidity. Findings – The empirical results indicate that European real estate equity returns load significantly differently on the size, value and liquidity factor, while the influence of the market factor seems to be equivalent. In addition, the authors find an economically and statistically significant underperformance of European real estate equities, after accounting for the diverging role of systematic risk factors. Running the conditional time-series regression, the authors further reveal that these findings are predominately caused by the divergent risk-return behavior of real estate equities in economic downturns. Practical implications – Due to the diverging role of the systematic risk factors in pricing real estate equities, the authors provide evidence of potential diversification benefits for investors and portfolio managers. Originality/value – This is the first real estate asset pricing study to dissect the unique risk-return relationship of real estate equities by employing propensity score matching.

scholarly journals Forecasting, Reporting, And Coping With Systematic Risk

2011 ◽  
Vol 3 (2) ◽  
pp. 24
Author(s):  
Gail E. Farrelly ◽  
Marion G. Sobol
Keyword(s):  
Risk Factors ◽  
Interest Rate ◽  
Interest Rates ◽  
Inflation Rate ◽  
Systematic Risk ◽  
Fortune 500 ◽  
Corporate Executives ◽  
Systematic Risk Factors ◽  
And Coping

A sample of 123 corporate executives, from the Fortune 500 Industrial Corporations list, evaluate nine common systematic risk factors such as rate of inflation, long-term interest rates, level of money supply, price of crude oil, etc. Executives indicate their views on the significance of these risk factors as well as their ability to cope with, and report on, these factors. Future interest rate changes and inflation rate changes are considered to be the most significant risks. There is a high negative correlation between the significance of particular risks and the ability to cope with these risks.

Liquidity and real estate asset pricing: a pan-European study

2014 ◽  
Vol 7 (1) ◽  
pp. 59-86 ◽  
Author(s):  
Alexander Scholz ◽  
Stephan Lang ◽  
Wolfgang Schaefers
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Asset Pricing ◽  
Real Estate ◽  
Stock Returns ◽  
Systematic Risk ◽  
Time Series Regression ◽  
Content Type ◽  
Market Factors ◽  
The Impact

Purpose – Understanding the pricing of real estate equities is a central objective of real estate research. This paper aims to investigate the impact of liquidity on European real estate equity returns, after accounting for well-documented systematic risk factors. Design/methodology/approach – Based on risk factors derived from general equity data, the authors extend the Fama-French time-series regression approach by a liquidity factor, using a pan-European sample of 272 real estate equities. Findings – The empirical results indicate that liquidity is a significant pricing factor in real estate stock returns, even after controlling for market, size and book-to-market factors. In addition, the authors detect that real estate stock returns load predominantly positively on the liquidity risk factor, suggesting that real estate equities tend to behave like illiquid common equities. These findings are underpinned by a series of robustness checks. Running a comparative analysis with alternative factor models, the authors further demonstrate that the liquidity-augmented asset-pricing model is most appropriate for explaining European real estate stock returns. Research limitations/implications – The inclusion of sentiment and downside risk factors could provide further insights into real estate asset pricing in European capital markets. Originality/value – This is the first study to examine the role of liquidity as a systematic risk factor in a pan-European setting.

The risk of real estate ownership: evidence from German equities

2015 ◽  
Vol 8 (2) ◽  
pp. 107-129 ◽  
Author(s):  
Karim Rochdi
Keyword(s):  
Risk Factors ◽  
Real Estate ◽  
Risk Premium ◽  
Balance Sheet ◽  
Systematic Risk ◽  
Considerable Proportion ◽  
Content Type ◽  
Corporate Real Estate ◽  
Systematic Risk Factors ◽  
Estate Ownership

Purpose – This paper aims to investigate the repercussions and impact of corporate real estate on the returns of non-real-estate equities in a time-series setting. While the ownership of real estate constitutes a considerable proportion of most listed firms’ balance sheet, in the existing literature, whether or not the benefits outweigh the risks associated with corporate real estate, is the subject of controversy. Design/methodology/approach – The role of corporate real estate ownership in the pricing of returns is examined, after taking well-documented systematic risk factors into account. Employing a data sample from 1999 to 2014, the conditions and characteristics faced by firms with distinct levels of corporate real estate holdings are identified and analyzed. Findings – The findings reveal that corporate real estate intensity indeed serves as a priced determinant in the German stock market. Among other results, the real-estate-specific risk factor shows countercyclical patterns and is particularly relevant for companies within the manufacturing sector. Practical implications – The findings provide new insights into the interpretation of corporate real estate and expected general equity returns. Thus, the present analysis is of particular interest for investors, as well as the management boards of listed companies. Originality/value – To the best of the author’s knowledge, this is the first paper to investigate the ownership of corporate real estate as a priced factor for German equities, after accounting for the well-documented systematic risk factors, namely, market (market risk premium), size (small minus big) and book-to-market-ratio (BE/ME) (high minus low).

scholarly journals Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative study in the Mexican Stock Exchange

2021 ◽  
Vol 13 (2) ◽  
pp. 513-543
Author(s):  
Rogelio ◽  
Salvador Torra Porras ◽  
Enric Monte Moreno
Keyword(s):  
Risk Factors ◽  
Principal Component Analysis ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Principal Component ◽  
Component Analysis ◽  
Computational Techniques ◽  
Arbitrage Pricing Theory ◽  
Pricing Theory ◽  
Systematic Risk Factors

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

The Short-Run and Long-Run Components of Idiosyncratic Volatility and Stock Returns

2021 ◽  
Author(s):  
Yunting Liu
Keyword(s):  
Risk Factors ◽  
Stock Returns ◽  
Systematic Risk ◽  
Risk Exposure ◽  
Idiosyncratic Volatility ◽  
Growth Options ◽  
Long Run ◽  
Expected Stock Returns ◽  
Short Run ◽  
Systematic Risk Factors

To capture the dynamics of idiosyncratic volatility of stock returns over different horizons and investigate the relationship between idiosyncratic volatility and expected stock returns, this paper develops and estimates a parsimonious model of idiosyncratic volatility consisting of a short-run and a long-run component. The conditional short-run and long-run components are found to be positively and negatively related to expected stock returns, respectively. The positive relation between the short-run component and stock returns may be caused by investors requiring compensation for bearing idiosyncratic volatility risk when facing trading frictions and hold underdiversified portfolios. The negative relationship between the long-run component and stock returns may reflect the fact that stocks with high long-run idiosyncratic volatility are less exposed to systematic risk factors and, hence, earn lower returns. Moreover, the low-risk exposure of stocks characterized by high idiosyncratic volatility lends support to real-option-based mechanisms to explain this negative relation. In particular, the systematic risk of a firm with abundant growth options crucially depends upon the risk exposure of these options. The value of growth options could rise significantly because of convexity when the increase in idiosyncratic volatility occurs over long horizons. And growth options’ systematic risk could fall because the relative magnitude of their value in relation to systematic risk factors decreases. This paper was accepted by David Simchi-Levi, finance.

scholarly journals Systematic risk factors and stock return volatility

2017 ◽  
Vol 11 (1-2) ◽  
pp. 61-70
Author(s):  
Syed Kamran Ali Haider ◽  
Shujahat Haider Hashmi ◽  
Ishtiaq Ahmed
Keyword(s):  
Risk Factors ◽  
Stock Returns ◽  
Systematic Risk ◽  
Var Models ◽  
Macroeconomic Factors ◽  
Stock Return Volatility ◽  
Auto Regressive ◽  
Systematic Risk Factors ◽  
Jel Code ◽  
The Relationship

This study analyzes the transmission of systematic risk exhaling from macroeconomic fundamentals to volatility of stock market by using auto regressive generalized auto regressive conditional heteroskedastic (AR-GARCH) and vector auto regressive (VAR) models. Systematic risk factors used in this study are industrial production, real interest rate, inflation, money supply and exchange rate from 2000-2014. Results indicate that there exists relationship among the volatility of macroeconomic factors and that of stock returns in Pakistan. The relationship among the volatility of macroeconomic variables and that of stock returns is bidirectional; both affect each other in different dynamics. JEL code: C32, C58, G11, G12

Systematic risk factors in European real estate equities

2011 ◽  
Vol 4 (3) ◽  
pp. 185-224 ◽  
Author(s):  
Kai‐Magnus Schulte ◽  
Tobias Dechant ◽  
Wolfgang Schaefers
Keyword(s):  
Risk Factors ◽  
Real Estate ◽  
Systematic Risk ◽  
Systematic Risk Factors
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