Average Monthly Return Research Articles

Private Equity (PE) Performance in The United States

We use the Thomson Reuters Venture Capital and Thomson Reuters Buyout indices as proxies for U.S. Private Equity (PE) performance and compare them to U.S. stocks and bonds. Both PE indices have outperformed stocks and bonds and they have higher average and median monthly returns. However, PE indices also had higher risk compared to stocks and bonds. On a risk-adjusted basis, PE has outperformed stocks but underperformed bonds. PE has also created more wealth compared to stocks and bonds. Both the PE indices also have significantly positive four-factor alpha. Our results indicate that PE has created tremendous value.

Good News, Bad News, No News: The Media and the Cross Section of Stock Returns

We examine the relationship between the tonality of news flow and the cross section of expected stock returns. We use a comprehensive definition of media coverage that includes both financial newspapers and mass media, represented by TV broadcasts. Using the total news flow with positive and negative tonality, we build a Media Tonality Indicator (MTI) with higher values reflecting a more positive tonality. Our sample consists of U.S. companies that were constituents of the S&P 500 index from January 2006 to October 2016. We use MTI to sort companies into portfolios and find an average monthly return spread in the order of 3% between the most positive and the most negative MTI-portfolio. This spread amplifies further when a company’s valuation, size or ESG scores are taken into account, disappears however when we use the MTI from the previous month to sort stocks. Foresighted investors can benefit from the tonality premium in overweighting stocks with high valuation, low market capitalization or a high ESG if they expect negative news and vice versa.

Expected Jumps and the Cross-Section of Equity Returns

We investigate how individual equity prices react to stock specific expected jump components. We find that a portfolio buying stocks with negative expected jump component and selling stocks with positive expected jump component earns significant returns, equal to 51 basis points per month. The returns of the spread portfolio cannot be explained by traditional risk factors and are robust to different model specifications. Furthermore, the associated risk premium is very close to the average monthly return, and remains significant after controlling for portfolio characteristics.

How about selling commodity futures losers?

AbstractThis paper explores the benefits of extending the investment universe to commodity futures, from the perspective of momentum traders. We find that the growth‐optimal portfolio includes negative (positive) weights on commodity futures losers (stock winners). Motivated by this finding, we construct a joint momentum strategy, buying stock winners and selling commodity futures losers, and show that it generates an average monthly return of up to 1.91% and provides much lower skewness (0.04) and kurtosis (1.27) than a traditional stock momentum strategy. It also greatly improves profitability, especially in unfavorable market states, and thus effectively manages tail risk.

The Profitability of Momentum Strategies : A Study of Indonesian Stock Exchange

We investigate the profitability of style and price momentum strategy in the Indonesian stock market from the year 2000 to 2015. We find the style momentum strategy yields significant positive returns while the price momentum strategy tends to produce negative returns. This result confirms the findings of Lewellen (2002) that style momentum returns are generally stronger than the conventional momentum. The average monthly returns of the double-sorted size-B/M style momentum are ranging from 1.98% to 2.64% and persistent after controlling for market factor using JSX index. Our findings suggest investors should utilize publicly available information such as size and book-to-market ratio on their investment decision in the Indonesian stock market.

Are Item 1A Risk Factors Priced?

Public companies report “the most significant factors that make” their common stock ”speculative or risky” in section “Item 1A. Risk Factors” of their annual filings. This paper uses textual analysis to estimate common risks from Item 1A texts and study these risks’ effect on public companies stock returns. I find the textual relevance of common Item 1A risks to the cross-section of firms’ Item 1A texts predicts the cross-section of expected stock returns. A factor portfolio aggregating information about returns from fifty individual Item 1A risks has an average monthly return of 0.97% and a risk adjusted return of 1.06%. Factor portfolios for nineteen individual Item 1A risks have significant average returns. Eighteen individual Item 1A risks provide independent information about stock returns.

Adoption of Identity Theft Countermeasures and its Short- and Long-Term Impact on Firm Value

Identity theft has impaired e-commerce. To combat the crime, many identity theft countermeasures (ITC) have been proposed. As investments in ITC are substantial and the benefits of such investments are intangible, companies are often hesitant to adopt such measures. This was the motivation for this study of the impact of 526 ITC adoption announcements on short- and long-term market value. The event study shows that such announcements result in positive market return of about U.S. $583 million around the date of announcement. Calendar-time portfolio analysis (CPA) is used for the long-term impact analysis and shows that the adoption of ITC generates positive and significant average monthly return up to 1.5% with control of market risk factors in a year. Subsampling analysis and interaction analysis show that U.S. listing, early ITC adoption, and two- factor authentication may moderate the market value of ITC adopters differently. A number of robustness checks (e.g., Heckman model, cross-sectional regression on Tobin’s Q, firm-specific risk factor analysis, subsampling analysis by ICT development, and analysis of security statements in annual reports) are performed. The research provides quantitative evidence of financial gain resulting from adoption of ITC and aspires to raise ITC awareness among industrial practitioners.

Динамический портфельный анализ мировых фондовых индексов

The article provides quantitive evaluation of the world stock markets with the «Return-Risk» Model, which is based on the fundamental principles of the porfolio theory. The analysis undertaken is aimed at revealing the most attractive world stock markets in regard to shaping of the future investment policy in the short term as well as determining the countries which securities (stocks, bonds, financial derivatives, etc.) should be included into the extended diversified investment portfolio. In other words, the world stock markets under study are not only considered as the status displays of the national economies of the corresponding countries but also as the potential instruments for investment portfolios. The synthesized «Return-Risk» Model is applicable in investment practice. The model shows that the attempt of 1% increase in return leads to the increase of risk by 3%. The computing experiments to testify the proposed model on independent material (verification of the model with permanent structure based on sliding verification) proved its practical applicability for revealing the leading indexes and dynamics estimate of their return within the closest investment horizon, with the win-loss ratio accounting for over three to one (3,2:1). The average monthly return is 1,1% per tool.

Investment Performance of Credit Risk Transfer Securities (CRTs): The Early Evidence

Credit risk transfer (CRT) securities were introduced by Fannie Mae and Freddie Mac in 2013. As of the end of 2017, in combination, the two government sponsored housing enterprises had issued a total of $53 billion in CRTs linked to residential mortgage loans with a total face value of $1.79 trillion. The goal is to shift mortgage risk from tax payers to the private sector. In return, investors expect to be compensated. The authors document the returns earned by investors in the various CRT tranches since their inception. The most senior tranches have provided an average representative return of 0.26% per month. The most junior tranches have provided an average representative return of 1.71% per month. These compare with average monthly returns of 0.03%, 0.15%, and 0.87% to T-bills, 15-year agency mortgage-backed securities, and 10-year high-yield corporate bonds, respectively, over the same time periods.

Month-of-the-year Effects in Nepalese Stock Market

The study investigates the month-of-the-year effects in Nepalese stock market employing composite index along with other nine sub-indices between mid-July 17, 2007 and mid-July 15, 2017. The study finds statistically significant highest average monthly returns in the month of Ashad (mid-June - mid-July) among other eleven months. On contrary, the significantly negative return is found in the month of Bhadra (mid-August - mid-September). It indicates that the Nepalese stock market has specific returns patterns showing inefficient in weak-form of market efficiency.

Oil Jump Risk

We show that the innovation in the risk-neutral probability of large downward and upward jumps in oil prices has a considerable predictive power for important economic indicators such as GDP growth, consumption growth, and total investment. In addition, we observe that the upside jump risk probability is a significant predictor of stock market index return and the returns of oil futures. Furthermore, the upside jump probability is a significant and relatively strong predictor of oil market fundamentals including inventory growth, demand growth, and OPEC’s production growth. Upside jump risk is also a driver of the cross-section of stock returns before the U.S. oil production increase in 2011. The average monthly return for the high-low upside jump risk exposure portfolio is -0.94% and -1.13%, using the 1996-2014 and 1996-2011 time periods respectively. The implications of the variance risk for the cross-section of stock returns vanishes after controlling for the large upside and downside jump risks. The shale revolution and considerable increase of the US oil production have killed the effect of upside risk premium after 2011. During the sub-period 2011-2014, the variance risk premium gets significant again, like it was before 2000.

Investor Sentiment and the Cross-Section of Corporate Bond Returns

This paper constructs an investor sentiment measure at both individual bond and aggregate levels, uncovering the first evidence that investor sentiment has strong predictive power for the entire cross-section of corporate bond returns. We find that high bond investor sentiment leads to low future returns. A portfolio that longs low sentiment bonds and shorts high sentiment ones generates an average monthly return of 0.64% for high-quality bonds, and 1.57% for speculative-grade bonds. The results are robust to controlling for various risk factors and bond characteristics. The cross-sectional predictability of bond returns is countercyclical, and appears to stem from its predictive power for macroeconomic conditions.

Primacy in stock market participation: the effect of initial returns on market re-entry decisions

ABSTRACTWe examine whether initial returns influence investors’ decisions to return to the stock market following withdrawal. Using a survival analysis technique to estimate Finnish retail investors’ likelihood of stock market re-entry reveals that investors who experience lower initial returns are less likely to return, even after controlling for returns in the last month and average monthly returns for the duration of investing. This primacy effect is robust to accounting for endogeneity in investors’ exit decisions, and other behavioural biases such as recency and saliency of investment experience. Individual investors appear to be subject to primacy bias and tend to put a significant weight on initial experiences in re-entry decisions.

Investment Performance of Credit Risk Transfer Securities (CRTs): The Early Evidence

Credit Risk Transfer (CRT) securities were introduced by Fannie Mae and Freddie Mac in 2013. As of the end of 2017, in combination, the two Government Sponsored housing Enterprises (GSEs) had issued a total of $53 billion in CRTs linked to residential mortgage loans with a total face value of $1.79 trillion. The goal is to shift mortgage risk from tax payers to the private sector. In return, investors expect to be compensated. We document the returns earned by investors in the various CRT tranches since their inception. The most senior tranches have provided an average representative return of 0.26% per month. The most junior tranches have provided an average representative return of 1.71% per month. These compare with average monthly returns of 0.03%, 0.15%, and 0.87% to T-bills, 15-year agency MBS, and 10-year high-yield corporate bonds, respectively, over the same time periods.

Product Market Competition and the Profitability Premium

This paper studies the impact of product market competition on the well-documented positive relation between firms' current profitability and future stock returns. I find that this relation is robust only in competitive industries. A long-short portfolio sorted on profitability earns an average monthly return of 1.1% in competitive industries and only 0.14% in concentrated industries. Firms' differential exposure to investment-specific technology shocks explains this gap. To understand this result, I build a production-based model with imperfect competition. Market power reduces a firm's investment response to these shocks and thus lowers risk exposure. Empirical tests confirm the model's predictions.

Performance of Female CEOs

The authors examine the performance of companies led by women from January 1996 to December 2014. The results show that companies headed by women outperformed the U.S. market, as proxied by the S&P 1500 and Russell 3000 indexes. Firms with female CEOs have higher average and median monthly returns, higher risk (standard deviation of monthly returns), and higher risk-adjusted performance (Sharpe, Sortino, and Omega ratios). Female-led companies also have significantly positive alphas with both the Carhart four-factor model and the Fama–French five-factor model when they form equally weighted and value-weighted portfolios of these firms. These results indicate that firms led by women have created significant value for their investors during the period of our study.

Can microstructure noise explain the MAX effect?

Bali et al. (2011) first find and investigate the MAX effect using raw returns (calculated by recorded closing prices), which include microstructure noise from bid-ask measurement errors. Motivated by this, we use noise-adjusted returns (which remove bid-ask errors) to examine the MAX effect and find microstructure noise is an important source of the effect. Average monthly return and five-factor alpha differences between the highest and lowest MAX stock portfolios are not significant in statistics. Most importantly, the negative five-factor alpha differences have no negative significance both in economics and statistics over equal-weighted portfolios.

Investor recognition and stock returns: evidence from China

PurposeMerton’s model of capital market equilibrium under incomplete information predicts that contemporaneous stock returns are positively related to investor recognition and that future stock returns are negatively related to investor recognition. The purpose of this paper is to empirically investigate whether Merton’s theory holds true for the Chinese stock market.Design/methodology/approachThis paper proposes the degree of shareholder base growth (SBG) as a proxy for investor recognition and examines the relationship between investor recognition and stock returns through a univariate analysis and Fama-Macbeth cross-sectional regressions based on A-Share listed firms.FindingsThe results show that investor recognition is nonlinearly and positively related to contemporaneous stock returns and is negatively related to future stock returns in contrast to the conclusions of Merton’s theory. A long-short trading strategy that involves buying stocks with the lowest SBG rate and that sells stocks with the highest SBG rate will earn an average monthly return of 3.615 percent.Research limitations/implicationsThough Merton’s theory is not fully reflected in the Chinese stock market, investor recognition is considered an important risk factor in the Chinese stock market.Originality/valueNo works have yet investigated the validity of Merton’s “investor cognition hypothesis” in relation to the Chinese stock market. This paper strives to fill this gap.

Another look at anchoring and stock return predictability

The superior performance of a momentum strategy long in stocks trading near their 52-week high prices and short in stocks trading far from their 52-week high prices is well-documented. In contrast, recent research finds that a similar strategy based on historical high prices exhibits subsequent reversals instead. This paper shows that after excluding low-priced stocks and/or January returns from the sample, the stocks trading near their historical high prices, in fact, exhibit significant outperformance. In particular, in a sample without low-priced stocks, a strategy long in 10% of the stocks with prices nearest to their historical high prices and short in 10% of the stocks with prices furthest from their historical high prices earns an average monthly return of 0.93% in non-January months. The performance of 52-week high momentum strategy also improves significantly upon exclusion of low-priced stocks and/or January returns. These findings have important implications for the anchoring-based behavioral explanations of these return patterns.

Initial Returns and Stock Market Re-Entry Decisions

We examine whether initial returns influence investors’ decisions to return to the stock market following withdrawal. Using a survival analysis technique to estimate Finnish retail investors’ likelihood of stock market re-entry reveals that investors who experience lower initial returns are less likely to return, even after controlling for returns in the last month and average monthly returns for the duration of investing. This primacy effect is robust to accounting for endogeneity in investors’ exit decisions, and other behavioural biases such as recency and saliency of investment experience. Individual investors appear to be subject to primacy bias and tend to put a significant weight on initial experiences in re-entry decisions.