The model of capital asset pricing (CAPM) states that high-beta assets will have higher returns than low-beta assets, implying a positive correlation between systematic risk and expected return. However, the literature, beginning with Black in 1972 and continuing with Fama et al. (1972) as well as Fama and MacBeth (1973), repeatedly provides evidence that is not inconclusive and is known as”the beta anomaly. In general, the research literature has revealed evidence of irregularities with low risk and the beta anomaly, which is the term used to describe high-risk stocks with negative abnormal returns or having lower returns than those of less risky stocks (Ang and Pederson. (2006), 2009; Frazzini and Pederson, 2014). For low-risk anomalies, the literature suggests the possibility of uncertainty as a driver. Hong and Sraer (2016) have said macroeconomic uncertainty is a cause for the beta anomaly. The peculiar volatility anomaly is also closely linked to mispricing and disagreement (Stambaugh and Yuan. 2015; Stambaugh and Yuan, 2017) and suggests that it could be resolved when mispricing weakens.

However, recent studies have revealed a significant equity risk premium and a more robust risk-return correlation around Federal Open Markets Committee (FOMC) meetings (Savor and Wilson, 2014; Lucca and Moench, 2015; Brusa et al., 2020). This is an unusual phenomenon. Savor Wilson and Wilson (2014) claim that announcements cut down on uncertainty or conflict in order to provide more clear indicators of overall risk on days of announcement. In addition to Savor Wilson’s (2014) findings, Cieslak et al. (2019) examine the biweekly pattern of equity premium in those FOMC meetings. They discover an equity price that is especially high during a specific time which is weeks 0, 4 and 6, which begin from the previous FOMC session (so-called odd weeks). In line with Savor and Wilson’s (2014) study, they propose that any other information that is usually released in weeks with even numbers can help reduce risk of uncertainty, and hence the biweekly pattern. For instance, the Governors’ Board meeting usually takes place before a scheduled FOMC meeting, and the FOMC receives updated recommendations from the Reserve Banks over monetary policy within two weeks. Additional studies have suggested that there is a resolution of uncertainty surrounding FOMC meeting as a primary factor in the research literature (Chen and Clements 2007, Gu and al. 2018, 2018; Boguth et al. 2019, 2019; Hu et al. in 2019; Ai et al. 2022 Bodilsen and Bodilsen. 2021 Kurov et al. 2021). 1

In bridging these two parts of the literature, The paper explores the performance that changes over time of anomalies of low-risk across the FOMC cycle. Particularly, we look into whether they exhibit the biweekly pattern across the FOMC cycle, as Cieslak et al. (2019) suggest. In order to do this we construct betting-against risk (BAR) portfolios that resemble low-risk anomalies, based on four indicators of risk which include: that of the CAPM beta, unique volatility and total volatility as well as systematic volatility. For the scheduled FOMC meetings between 1994 and 2020, we observe that the returns from the BAR portfolios follow an irregular pattern of biweekly and a notable decrease in the even weeks during this FOMC cycle.

The biweekly pattern of low-risk irregularities during the FOMC cycle can have the benefit of practicality. The FOMC releases the schedule of its meetings in advance so that investors can be aware of this specific timeframe. This is believed to impact BAR’s performance. BAR strategy. Therefore, we suggest two BAR strategies that are dynamic using the biweekly pattern and making use of to make the FOMC meeting schedule, which is made available to the general public in advance. The first option is to purchase (sell) high-risk securities and then sell (buy) low-risk stocks during the even (odd) months during the FOMC cycle. Another option is to hold the BAR portfolio in its original BAR portfolio during odd weeks and to invest in risk-free investments in even weeks. Our research shows that our rules for trading dynamically dramatically improve the performance of BAR portfolios originally constructed. This study adds to the research of dynamic strategies for anomalies, proposing a novel approach that takes advantage of FOMC meeting schedules. FOMC agenda. The previous studies suggest dynamic strategies based on regular FOMC meetings, however, they have applied the rules of dynamic trading only using an index of the market (Lucca and Moench (2015); Cieslak et al. 2019, 2019; Huang et al. 2022). The existence of anomalies can be an interesting topic to investors since they can suggest strategies for trading that could yield significant gains. So, knowing the temporal variation performance of anomalies and using this information to improve their performance could be significant (Barroso and others. 2020; Moreira and Muir, 2017; Barroso and Santa-Clara, 2015). In focusing on low-risk anomalies, Kim and Kim (2022) propose dynamic BAR strategies for to reduce the downside risk associated with low-risk anomalies. However, we suggest simpler and non-parametric dynamic strategies that are influenced by the biweekly patterns that occur over that FOMC cycle.

Section A few snippets

Variables and data

We examine four different proxies to measure risk based on research. First, we consider the risk that is systematically associated with the stock based on the CAPM ( Beta) (Black and Pederson. 1972; Fama and MacBetch, 1973; Frazzini and Pederson, 2014). Ang et al. (2006) demonstrate that not just Beta but also volatility, too, has a an identical cross-sectional relationship to expected returns. Thus, we use three measures of volatility proposed by Ang and colleagues. (2006) The individualisyncratic variability ( Ivol) as well as Tvol, the total variability ( Tvol) as well as the

Biweekly pattern of BAR

Table 1 summarizes the data on the average daily return from the portfolios of BAR for the whole sample period (Panel A) and for the odd weeks (Panel B) and odd weeks (Panel C) each independently. In each of the panels we provide the daily number of observations (N) as well as the mean (Mean) the standard deviation (Stdev) Skewness (Skew) and the kurtosis (Kurt) of returns.

Panel A shows that BAR strategies, with the exception of Beta, have positive returns, on average. If we break down the data into FOMC odd and even weeks,

Conclusion

The FOMC meeting is one of the main topics in the field of economics and finance literature due to its distinctive significance and influence on global economics (Beckmeyer and co. 2020; Brusa et al. in 2020). On the other hand, the low-risk anomaly has been one of the longest-running issues in the finance literature that challenges conventional models of asset pricing (Black and 1972; Fama and MacBeth, 1973). This paper bridges the two major areas of research and presents