Low-risk investment strategy: sector bets or stock bets?

PurposeThe portfolio of low-risk stocks outperforms the portfolio of high-risk stocks and market portfolios on a risk-adjusted basis. This phenomenon is called the low-risk effect. There are several economic and behavioral explanations for the existence and persistence of such an effect. However, it is still unclear whether specific sector orientation drives the low-risk effect. The study seeks to answer the following important questions in Indian equity markets: (a) Whether sector bets or stock bets mainly drive the low-risk effect? (b) Is it a mere proxy for the well-known value effect? (c) Does the low-risk effect prevail in long-only portfolios?Design/methodology/approachThe study is based on all the listed stocks on the National Stock Exchange (NSE) of India from December 1994 to September 2018. It classifies them into 11 Global Industry Classification Standard (GICS) sectors to construct stock-level and sector-level BAB (Betting Against Beta) and long-only low-risk portfolios. It follows the study of Asness et al. (2014) to construct various BAB portfolios. It applies Fama–French (FF) three-factor and Fama–French–Carhart (FFC) four-factor asset pricing models in addition to Capital Asset Pricing Model (CAPM) to examine the strength of BAB, sector-level BAB, stock-level BAB and long-only low-beta portfolios.FindingsBoth sector- and stock-level bets contribute to the return of the low-risk investing strategy, but the stock-level effect is dominant. Only betting on safe sectors or industries will not earn economically significant alpha. The low-risk effect is unique and not a value effect in disguise. Both long-short and long-only portfolios within sectors and industry groups deliver positive excess returns. Consumer staples, financial, materials and healthcare sectors mainly contribute to the returns of the low-risk effect in India. This study offers empirical evidence against the Samuelson (1998) micro-efficient market given the strong performance of the stock-level low-risk effect.Practical implicationsThe superior performance of the low-risk investment strategies at both stock and sector levels offers investors an opportunity to strategically invest in stocks from the right sectors and earn high risk-adjusted returns with lower drawdowns over an entire market cycle. Besides, it paves the way for stock exchanges and index manufacturers to launch sector-specific low-volatility indices for relevant sectors. Passive funds can launch index funds and exchange-traded funds by tracking these indices. Active fund managers can espouse sector-specific low-risk investment strategies based on the results of this and similar other studies.Originality/valueThe study is the first of its kind. It offers insights into the portfolio characteristics and performance of the long-short and the long-only variant of low-risk portfolios within sectors and industry groups. It decomposes the low-risk effect into sector-level and stock-level effects.

The Role of Predictability During Negation Processing in Truth-Value Judgment Tasks

In experiments investigating the processing of true and false negative sentences, it is often reported that polarity interacts with truth-value, in the sense that true sentences lead to faster reaction times than false sentences in affirmative conditions whereas the same does not hold for negative sentences. Various reasons for this difference between affirmative and negative sentences have been discussed in the literature (e.g., lexical associations, predictability, ease of comparing sentence and world). In the present study, we excluded lexical associations as a potential influencing factor. Participants saw artificial visual worlds (e.g., a white square and a black circle) and corresponding sentences (i.e., “The square/circle is (not) white”). The results showed a clear effect of truth-value for affirmative sentences (true faster than false) but not for negative sentences. This result implies that the well-known truth-value-by-polarity interaction cannot solely be due to long-term lexical associations. Additional predictability manipulations allowed us to also rule out an explanatory account that attributes the missing truth-value effect for negative sentences to low predictability. We also discuss the viability of an informativeness account.

Why does the probe value effect emerge in working memory? Examining the biased attentional refreshing account

People are able to prioritize more valuable information in working memory. The current study examined whether this value effect is due to the more valuable items being refreshed more frequently or for a longer period of time than the other items during maintenance. To assess this possibility, we combined a probe value manipulation with a guided-refreshing procedure. Arrays of colored shapes were presented, and after a brief delay, participants reported the color of one randomly probed shape on a continuous color wheel. To manipulate probe value, one item was indicated as more valuable than the rest prior to encoding (i.e., worth more notional points), or all items were indicated as equally valuable. To guide refreshing, in some trials, a sequence of two arrows was presented during maintenance, thereby cueing the spatial location of an item. Participants were told to “think of” (i.e., refresh) the cued item. If value boosts are driven by attentional refreshing, cueing an item to be refreshed should enhance performance for items that are of low or equal value, but not items of high value, as these items would be refreshed regardless of the cue. This pattern of outcomes was observed, providing support for the hypothesis that attentional refreshing at least partially accounts for probe-value effects in working memory.

Single-trial modeling separates multiple overlapping prediction errors during reward processing in human EEG

Learning signals during reinforcement learning and cognitive control rely on valenced reward prediction errors (RPEs) and non-valenced salience prediction errors (PEs) driven by surprise magnitude. A core debate in reward learning focuses on whether valenced and non-valenced PEs can be isolated in the human electroencephalogram (EEG). We combine behavioral modeling and single-trial EEG regression to disentangle sequential PEs in an interval timing task dissociating outcome valence, magnitude, and probability. Multiple regression across temporal, spatial, and frequency dimensions characterized a spatio-tempo-spectral cascade from early valenced RPE value to non-valenced RPE magnitude, followed by outcome probability indexed by a late frontal positivity. Separating negative and positive outcomes revealed the valenced RPE value effect is an artifact of overlap between two non-valenced RPE magnitude responses: frontal theta feedback-related negativity on losses and posterior delta reward positivity on wins. These results reconcile longstanding debates on the sequence of components representing reward and salience PEs in the human EEG.

Value Investment Strategies and Asset Pricing: A Case of Pakistan Stock Exchange (PSX)

The Capital Asset Pricing Model (CAPM) measures only a linear relationship between the Risk and the Return. However, market dynamics and anomalies calls for understanding the relationship in between risk and return from non-linear perspective. Thus, current study explores an opportunity to study asset value anomalies by Constructing Decile Portfolio for the period starting from 2001 to 2018 with 900 firms listed. GMM (Generalized method of moment and Wald test are applied to see the robustness of results. For further analysis, Risk Adjusted CAPM, Fama French 3 Factor (FF3) and 5 Factor (FF5) are applied. Empirical results indicate that value effect and debt to equity ratio are essential factors and genuinely explain what CAPM fails to explain. The findings from the study recommend that investing in High value and high leverage firm will generate abnormal returns to investors. Taking long position in high value firm and short position in low value firms and same with debt to equity anomaly. The results will help financial analyst develop investment strategies for well diversified and efficient portfolios. These results can also be helpful to financial firm and security analyst in the financial market where they can take appropriate capital budget decisions while investing.

Shareholder Value Effects of Ethical Sourcing: Comparing Reactive and Proactive Initiatives

With the advent of responsible business, ensuring social responsibility in sourcing is of interest to both academics and practitioners. In this study, we examine one way of achieving this goal: ethical sourcing initiatives (ESIs). ESIs refer to a firm’s formal and informal actions to manage sourcing processes in an ethical and socially responsible manner. While ESIs have been established as an important part of corporate social responsibility, it is unclear whether, how, and when this corporate effort is economically beneficial. We conduct an event study estimating the shareholder value effect of 159 publicly traded firms’ ESIs and find that the stock market reacts positively to ESIs in general. We also compare market reactions under different conditions including reactive versus proactive ESIs, and their interactions with initiative timing, firm size, and financial risk. Additionally, we find that ESIs are associated with long-term stock price and operating performance. Overall, our findings clarify the potential economic benefits of corporate ESIs and encourage buying firms to take these initiatives selectively according to business contexts.