Expected Returns: Systematic Risk of Firm Characteristics?

2016 ◽  
Author(s):  
Flavio Nardi
Keyword(s):  
Systematic Risk ◽  
Expected Returns ◽  
Firm Characteristics

scholarly journals Testing Beta-Pricing Models Using Large Cross-Sections

2019 ◽  
Vol 33 (6) ◽  
pp. 2796-2842 ◽  
Author(s):  
Valentina Raponi ◽  
Cesare Robotti ◽  
Paolo Zaffaroni
Keyword(s):  
Cross Sections ◽  
Risk Premia ◽  
Expected Returns ◽  
Firm Characteristics ◽  
Pricing Models ◽  
Cross Sectional ◽  
Misspecified Models ◽  
Oxford University ◽  
Fama French Factors ◽  
Published Paper

Abstract We propose a methodology for estimating and testing beta-pricing models when a large number of assets is available for investment but the number of time-series observations is fixed. We first consider the case of correctly specified models with constant risk premia, and then extend our framework to deal with time-varying risk premia, potentially misspecified models, firm characteristics, and unbalanced panels. We show that our large cross-sectional framework poses a serious challenge to common empirical findings regarding the validity of beta-pricing models. In the context of pricing models with Fama-French factors, firm characteristics are found to explain a much larger proportion of variation in estimated expected returns than betas. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Cash Flow and Discount Rate Risk in the Investment Effect: A Downside Risk Approach

2018 ◽  
Vol 08 (03) ◽  
pp. 1850002
Author(s):  
Ehab Yamani ◽  
David Rakowski
Keyword(s):  
Cash Flow ◽  
Discount Rate ◽  
Systematic Risk ◽  
Downside Risk ◽  
Expected Returns ◽  
Financing Constraints ◽  
Rate Risk ◽  
Market State ◽  
Risk Approach ◽  
High Investment

We examine whether sensitivities to cash flow and discount rate risk in down markets explain the investment effect, in which low-investment stocks earn higher expected returns than high-investment stocks. We show how productivity and financing constraints asymmetrically impact the systematic risk of low-investment and high-investment firms, conditional on market state. Our evidence is consistent with both productivity constraints and financing constraints as explanations for the investment effect, but, contrary to expectations, more when prices are rising than falling.

scholarly journals Century Bonds: Debt Or Equity Securities?

2011 ◽  
Vol 19 (3) ◽  
Author(s):  
Kam C. Chan ◽  
P.V. Viswanath ◽  
Annie Wong
Keyword(s):  
Systematic Risk ◽  
Tax Avoidance ◽  
The Other ◽  
Formal Structure ◽  
Relative Importance ◽  
Firm Characteristics ◽  
Font Size ◽  
Other Hand ◽  
Equity Securities

<p class="MsoBlockText" style="margin: 0in 0.5in 0pt;"><span style="font-style: normal; mso-bidi-font-style: italic;"><span style="font-size: x-small;"><span style="font-family: Times New Roman;">In this study, we examine the characteristics of firms that have issued century bonds and the debt-versus-equity classification of these bonds.<span style="mso-spacerun: yes;">&nbsp; </span>Although it is commonly assumed that such bonds are issued for tax-avoidance purpose, an examination of firm characteristics suggests that firms have non-tax related motives in issuing century bonds.<span style="mso-spacerun: yes;">&nbsp; </span>The formal structure of century bonds also suggests that century bonds are similar to debt.<span style="mso-spacerun: yes;">&nbsp; </span>On the other hand, our analysis of the systematic risk of issuing firm's equity shows that century bonds are more similar to equity than to debt.<span style="mso-spacerun: yes;">&nbsp; </span>Thus, ultimately, the relative importance of these three factors will have to determine whether they are to be considered debt or equity.<span style="mso-spacerun: yes;">&nbsp; </span></span></span></span></p>

How do firm and market characteristics affect airports’ Beta risk?

2020 ◽  
Vol 21 (3) ◽  
pp. 297-312
Author(s):  
Tobias Binz
Keyword(s):  
Systematic Risk ◽  
Capacity Constraints ◽  
Price Control ◽  
Rate Of Return ◽  
Firm Characteristics ◽  
Policy Makers ◽  
Return On Capital ◽  
Beta Risk ◽  
Operating Leverage ◽  
The Impact

I present a graphical framework based on Subrahmanyam and Thomadakis (1980) that allows to study the impact from firm and market characteristics on systematic risk associated with the return on capital, i.e. Beta risk, for utilities under price control. Within this framework, Beta risk is driven by the magnitude of profit fluctuations following demand shocks. The framework is then applied to airport firm characteristics and airport market environment features. I find that the frequency of price control resets, the level of operating leverage, the extent of capacity constraints, and the degree of market power all have an unambiguous effect on the level of Beta risk. The scope of the regulatory perimeter and the type of traffic mix may also affect Beta risk; however, the magnitude and direction of their impact rely on the specifics of the case. The article may assist policy makers to formulate economically sound recommendations on how the regulatory rate of return for airport operators should be determined. Specifically, my findings suggest criteria that can be used to choose adequate peer companies of comparable systematic risk.

Getting Paid to Hedge: Why Don’t Investors Pay a Premium to Hedge Downturns?

2018 ◽  
Vol 54 (3) ◽  
pp. 1157-1192
Author(s):  
Nishad Kapadia ◽  
Barbara Bennett Ostdiek ◽  
James P. Weston ◽  
Morad Zekhnini
Keyword(s):  
Gross Domestic Product ◽  
Business Cycle ◽  
Expected Returns ◽  
Firm Characteristics ◽  
Cycle Frequency ◽  
Gross Domestic Product Growth ◽  
Market Index ◽  
Ex Ante ◽  
Out Of Sample ◽  
The Business Cycle

Stocks that hedge sustained market downturns should have low expected returns, but they do not. We use ex ante firm characteristics and covariances to construct a tradable safe minus risky (SMR) portfolio that hedges market downturns out of sample. Although downturns (peaks to troughs in market index levels at the business-cycle frequency) predict significant declines in gross domestic product growth, SMR has significant positive average returns and 4-factor alphas (both around 0.8% per month). Risk-based models do not explain SMR’s returns, but mispricing does. Risky stocks are overpriced when sentiment is high, resulting in subsequent returns of -0.9% per month.

Structural innovation in state variables and expected stock returns

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Prodosh E. Simlai
Keyword(s):  
Risk Factors ◽  
Stock Returns ◽  
Systematic Risk ◽  
Expected Returns ◽  
State Variables ◽  
Cross Sectional ◽  
Content Type ◽  
Wide Range ◽  
The Cross ◽  
Structural Innovation

PurposeThe purpose of this study is to investigate whether the surprise components of systematic risk, which are useful in forecasting future investment opportunities, help explain the cross-section of average returns associated with portfolios sorted on size, book-to-market and accruals. This study also aims to examine the mispricing attributes of the size, value and accrual effects by investigating the relative economic relevance of aggregate risk factors, which are related to exogenous shocks in state variables, in the cross-sectional returns of triple-sorted portfolios.Design/methodology/approachThis study uses innovations of systematic risk, which affect the cash flows and risk-adjusted discount rates of all firms in an economy and determines the expected returns of portfolios based on firm characteristics. This study uses independent sorts based on size, book-to-market and total accruals – all of which are measured at the firm level – and construct three-dimensional test portfolios. For unobserved innovations, this study estimates a triangular structural vector autoregressive system and obtain the exogenous innovations in state variables. The author uses Fama-MacBeth two-pass cross-sectional regressions and examines whether the structural innovations explain a significant part of the cross-sectional variation in the average returns of the test portfolios.FindingsThis study finds that variations in expected returns of testing assets are determined by differences in the underlying assets’ exposure to systematic risk innovation. The empirical evidence also shows that exogenous innovation in Fama-French (FF) risk factors leaves out important cross-sectional information about expected returns, and additionally, the FF-factor betas have lower cross-sectional power than the proxy for innovation betas. The cross-sectional differences in the test portfolios’ sensitivity to instruments such as the short-term Treasury bill rate and term spread survive the presence of FF-factor betas.Originality/valueIn contrast to the existing literature, this study uses structural innovations that are uncorrelated and thus exogenous in nature. The author creates test portfolios that display a wide range of average returns and are unlikely to show spurious variability in risk exposures. Unlike the existing research, where size, value and accrual anomalies have been analyzed in isolation, this study examine these pricing patterns jointly, focusing on the possible contributing role of structural innovation in economy-wide predictor variables. To the best of the author’s knowledge, this paper is the first attempt to link the sensitivity of portfolios sorted on size, book-to-market and accruals to exogenous structural innovation.

Pengaruh Faktor Fundamental, Risiko Sistematis Dan Ekonomi Makro Terhadap Return Saham Syariah Yang Tergabung Di Jakarta Islamic Index (JII) Pada Periode 2010 – 2014

2017 ◽  
Vol 24 (1) ◽  
pp. 54-70
Author(s):  
Hasanah Setyowati ◽  
Riyanti Ningsih
Keyword(s):  
Exchange Rate ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Secondary Data ◽  
Analysis Model ◽  
Macroeconomic Factors ◽  
Return On Equity ◽  
Equity Ratio ◽  
Regression Techniques ◽  
The Exchange Rate

This study aimed to obtain empirical evidence on the influence of fundamental factors, systematic risk and macroeconomics on the returns Islamic stock of companies incorporated in the Jakarta Islamic Index in 2010-2014. The variables used were the fundamental factors that are proxied by Earning Per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER); Systematic risk is proxied by Beta Shares; macroeconomic factors is proxied by the inflation rate and the exchange rate. The samples of this study are the enterprises incorporated in Jakarta Islamic Index (JII) at the Indonesian Stock Exchange. The sampling method was using purposive sampling. There were 12 samples of Islamic stocks that meet the criteria to be used as samples. The analysis model used is multiple linear regression techniques and the type of data used is secondary data. The study found that all variables, which are Earning Per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER), Beta stock, inflation and the exchange rate do not significantly affect the return of sharia stock either simultaneously or partially.

Risk Factors of Collateralized Loan Obligations and Corporate Bonds

2020 ◽  
Vol 32 (6) ◽  
pp. 347-355
Author(s):  
Mark Wahrenburg ◽  
Andreas Barth ◽  
Mohammad Izadi ◽  
Anas Rahhal
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Asset Pricing ◽  
Systemic Risk ◽  
Corporate Bonds ◽  
Risk Exposure ◽  
Expected Returns ◽  
Yield Spreads ◽  
Pricing Factors ◽  
Return Difference

AbstractStructured products like collateralized loan obligations (CLOs) tend to offer significantly higher yield spreads than corporate bonds (CBs) with the same rating. At the same time, empirical evidence does not indicate that this higher yield is reduced by higher default losses of CLOs. The evidence thus suggests that CLOs offer higher expected returns compared to CB with similar credit risk. This study aims to analyze whether this return difference is captured by asset pricing factors. We show that market risk is the predominant risk factor for both CBs and CLOs. CLO investors, however, additionally demand a premium for their risk exposure towards systemic risk. This premium is inversely related to the rating class of the CLO.

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