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The authors examine the relation between noise trading in equity markets and stochastic volatility by estimating a two-factor jump diffusion model. Their analysis shows that contemporaneous price deviations in the derivatives market are statistically significant in explaining movements in index futures prices and option-market volatility measures.

To understand the impact noise may have in the S&P 500 derivatives market, the authors first measure and evaluate the influence noise exerts on futures prices and then investigate its influence on option volatility.

In the period from 1996 to 2003, this study finds significant changes in the volatility and mean reversion in the noise level and a significant increase in its relation to implied volatility in option prices. The results are consistent with a bubble in technology stocks that occurred with significant increases in noise trading.

This study provides estimates for this model during the periods preceding and during the technology bubble. The study analysis shows that the volatility and mean reversion in the noise level are much stronger during the bubble period. Furthermore, the relation between noise trading and implied volatility in the futures market was of a significantly larger magnitude during this period. The study results support the importance of noise trading in market bubbles.

Bloomfield, O'Hara and Saar (2009) find that noise traders lower bid–ask spreads and improve liquidity through increases in trading volume and market depth. Such improved market conditions could have positive effects on market quality, and this impact could be evidenced by lower implied volatility when noise traders are more active. Indeed, the results in this study indicate that the level and characteristics of noise trading are fundamentally different during the technology bubble, and this noise trading activity has a larger impact during this period on implied volatility in the options market.

This paper uniquely analyzes derivatives on the S&P 500 Index in order to detect the presence and influence of noise traders. The authors derive and implement a two-factor jump diffusion noise model. In their model, noise rectifies the difference of analysts' opinions, market information and beliefs among traders. By incorporating a reduced-form temporal expression of heterogeneities among traders, the model is rich enough to capture salient time-series characteristics of equity prices (i.e. stochastic volatility and jumps). A singular feature of the authors’ model is that stochastic volatility represents the random movements in asset prices that are attributed to nonmarket fundamentals.

The purpose of this paper is to illustrate the effectiveness of integrating a portfolio simulation‐based trading program with the top‐down approach to fundamental analysis in a security analysis course. The simulation allows for the application of class material using a combination of group and individual projects.

Students enrolled in the class completed a survey about the integrated approach and the required simulated trading.

Over 87 per cent of students agreed that the economic analysis provided more educational value as a group project than as an individual project, while over two‐thirds of the students disagreed that the trading simulation had more education value as a group project.

Although the authors focus on the top‐down approach, the concepts of technical analysis, hedging, and income generation could be more formally incorporated into the trading simulation.

The outline of how to integrate a trading simulation into the top‐down approach, using a combination of group projects and a cumulating project completed by each student, can be used as a guide for how to make the top‐down approach a more meaningful task.

The integration of the portfolio simulated trading program with the top‐down approach makes the course more applied and more enjoyable for both the students and the faculty.

The paper outlines how to integrate a trading simulation and the top‐down approach and reports the finding that students preferred the group approach to economic analysis and individual projects for the simulation and the company analysis.

This paper jointly examines how firm size and idiosyncratic risk impact momentum returns.

Using regression analysis, the authors investigate how firm size and idiosyncratic risk impact price momentum. The authors review firm price data in 25 country markets in the Thomson Financial Datastream database from 1979 to 2009.

This study’s findings suggest price momentum is more significant among stocks with smaller size and higher idiosyncratic risk. The authors find that winner and loser portfolios have significantly smaller size and higher idiosyncratic risk than portfolios in the middle quintiles.

This study’s results are consistent with the notion that firm size matters in price momentum and mispricing is greatest for small firms because of the greater risk potential to arbitrageurs. In addition, this finding that firms with higher idiosyncratic risk have greater price momentum supports the idea that investors underreact to firm-specific information.

This work finds evidence that investors underreact to firm-specific information. As such, these findings are of particular interest for investors looking to exploit opportunities for abnormal returns through price momentum trading.

This paper jointly examines the effects of firm size and idiosyncratic risk on momentum returns. This investigation considers these effects in the global markets. This work adds to the research base by illustrating that both winner and loser portfolios have significantly smaller size and higher idiosyncratic risk than portfolios in the middle quintiles. Also unique to this study, the authors capture the time-variation of expected IdioRisk and the asymmetric effects of volatility by using an exponential general autoregressive conditional heteroskedastic (EGARCH) model to calculate conditional idiosyncratic risk.

The purpose of this paper is to analyze security-market returns relative to the political party of the president, the Federal Reserve’s monetary policy, the year of the president’s term, and the state of political gridlock. Contrary to prior studies, which evaluated the influences separately, the authors jointly evaluate these variables.

The analysis supports the notion that security returns are significantly related to shifts in Fed monetary policy, political gridlock, and the year of the presidential term; however, returns are generally invariant to the president’s political party affiliation. Overall, the findings suggest that investors should focus less attention on the party of the president and instead more closely monitor Fed actions.

It appears that political harmony should be welcomed by equity investors, but not debt investors. Finally, regardless of the political outcome, if the past serves as a guide, investors may have to wait until year three of the next presidential term to enjoy the fruits of the current political season.

The academic literature is rich with studies that consider the aforementioned political effects and the influence that monetary policy have on the markets. To date, however, these factors have not been jointly considered when examining returns. This paper considers several dimensions of the political landscape – the party of the president, the presence or absence of political gridlock, and the presidential term cycle effect – in conjunction with Fed monetary policy in examining long-term security returns. By examining the relationship between security returns and both political and monetary conditions, the authors provide robust evidence regarding the relationships.

This paper describes how two academic health science librarians exposed graduate students to health literacy concepts in a graduate-level nutrition course. This paper aims to present an easy method for librarians to expose students in the health professions to concepts of health literacy.

The Information and Health Literacy course is an online course co-taught by nutrition faculty and librarians at Rosalind Franklin University of Medicine and Science. The librarian-led one-week health literacy module begins with readings that define health literacy and continues with two online discussion board activities. One activity is identifying an example of low health literacy in their personal or professional lives, and the other is using criteria from the readings in their analysis of a consumer health website.

Students often comment that prior to taking this course, they had not considered how patients might think about and understand their own health care, but they will now take it into account going forward. Many students also felt that the assignment made them view Web resources for patients differently and with a more critical eye.

Those in allied health professions like registered dietitians often have direct contact with patients and have the ability to make a significant impact. If students are exposed to health literacy concepts through online activities within the curriculum, they may be more aware of this important concept when working with patients in the future.

The purpose of this paper is to investigate the absolute and risk-adjusted stock return performance of the US health care industry conditional upon the presidential administration’s political party and the Federal Reserve’s monetary policy stance. It evaluates this return behavior across the 60-year time period from 1954 to 2013, and sub-divides this entire period into the pre-Medicare period (1954-1964), Medicare period (1965-1984), and Medicare-plus-high-health-care-inflation period (1985-2013).

The study uses monthly returns to the health care industry and overall market, characterizing each sample month as either having a Republican or Democratic president and either a contractionary or expansionary monetary policy regime determined by whether the Federal Reserve is increasing or decreasing interest rates, respectively. It incorporates univariate and multivariate analysis to quantify the return behavior of both the health care industry and the overall market during the entire period and all three sub-periods. Additionally, it utilizes a common four-factor multivariate regression model and associated hypothesis testing to characterize risk-adjusted excess returns (i.e. α) to the health care industry during the entire period and all three sub-periods.

The health care industry has earned robust, positive risk-adjusted returns with the magnitude of the returns sensitive to the political party of the administration and the monetary policy regime. The authors find that prior to 1965 (1954-1964), when the president was a Republican, during times of monetary contraction, health care earned an excess risk-adjusted return. There was no association between Democratic administrations and excess health care returns prior to 1965. In contrast, the authors find that after 1965 this relationship changes. The authors find that returns to health care were positive for Republicans during times of monetary expansion and positive for Democrats during monetary contraction. The authors also find this relationship has become more pronounced after 1984.

The study extends prior literature, which has shown that the health care industry is a priced factor in the US stock market and that it provides significant risk-adjusted returns in the recent past. Uniquely, this study shows that the excess returns to health care vary considerably over the past 60 years, and that these excess returns are quite sensitive to political policy, proxied by the presidential administration party, and monetary policy, as measured using Fed discount rate changes. These findings have implications for management and shareholders of highly regulated and subsidized industries and firms.