Learning paths

The turn-of-the-month anomaly is a challenging phenomenon to explain academically. While it’s more noticeable in small-cap and low-price stocks, it also affects large-cap and high-price stocks. This effect occurs both at month-end and throughout other times of the year, not just during calendar-year quarter-ends.

The saying “Don’t fight the FED” is backed by research, which shows that S&P 500 returns during Federal Open Market Committee meetings are over five times higher than on average days. This means that a significant portion of the index’s annual returns comes from just a few days.

During option-expiration weeks, large-cap stocks with actively traded options show significantly higher average returns. A potential strategy is to hold these stocks during these weeks and stay in cash the rest of the time.

The turn-of-the-month anomaly challenges the idea of market efficiency and offers a tradable pattern for investors. Research shows that abnormal returns also exist around the 16th of each month, likely due to retirement contributions being invested in broad-market funds like the S&P 500.

Despite the theory that financial markets are efficient, numerous studies have uncovered anomalies. This case study highlights strategies from Quantpedia’s database, showing how they remain effective over an extended backtesting period and demonstrating how to use the database’s free strategies.

In this article, we build on our previous exploration of calendar and seasonal trading strategies by enhancing a composite strategy with additional elements. We combine calendar anomalies such as the Turn of the Month and FOMC Meeting Effect with a trend filter, using a 200-day moving average to significantly reduce drawdowns and improve performance.

Seasonal anomalies are documented mainly in equity markets, but recent research suggests they are not isolated to this market. At least one seasonal effect is present also in the Treasury market. Holders of Treasuries earn a monthly return, which peaks in the early fall and declines monotonically until the late spring. This pattern is the exact opposite of the equity seasonality effect. This negative correlation between the seasonality in equities and bonds makes sense since bonds are a natural substitute to stocks; therefore, periods of high investor nervosity and low equity returns should be linked to higher bond returns (which usually prosper in such stressful times).

Vasileiou (Sep 2022) examines a well-known calendar anomaly (CA) that challenges Efficient Market Hypothesis (EMH) called the Turn of the Month (TOM) effect in crypto(currencie)s space. It builds on the notion that certain inefficiencies exist in BTH and ETH markets. According to the authors, the optimization algorithm they developed shows that the most profitable 4-day intra-month investment periods are those near the end of each month and the beginning of the next one. The TOM-based strategy is an investment strategy for investors who want to bear investment risk but not in risky assets like cryptocurrencies.

Recent research reveals a significant within-month pattern in long-maturity Treasury security prices, with notable positive returns in the final days of each month. This trend, likely driven by insurers’ buying activity, suggests that holding Treasuries during these days can yield a high annualized Sharpe ratio and offers a profitable trading opportunity.

US holidays lead to higher returns and lower volatility in EU equity markets, especially after a positive US market close. This anomaly offers a promising market timing strategy that can be further improved with leverage.

Tax law changes in 1974 and 1981 made IRAs popular by deferring taxes on capital gains. Many people wait until the last minute to contribute, causing brokers to delay buying stocks, which creates a predictable price drift in US equities the day after Tax Day.

This article explores Bitcoin’s behavior around futures expiration events, revealing that BTC spot prices and the BITO ETF are affected by these expirations. A strategy suggests avoiding trading on the expiration day itself and instead focusing on the days before and after, particularly the weekend and Monday, when performance tends to improve.

The asset class trend-following strategy uses momentum and moving averages to improve returns while minimizing volatility and drawdowns. It provides a flexible, risk-reducing approach that can be tailored to individual investor needs.

TMomentum strategies, including trend-following and relative strength techniques, have been widely researched and used for over a century. A simple approach involves applying momentum filters to individual asset classes and then combining them into a single portfolio, as demonstrated in the “#1 – Asset Class Trend Following” strategy.

Tactical asset allocation strategies are popular for their crisis resilience. One effective method combines different techniques to weight assets with high past momentum, using short-term predictability in correlations and volatilities, and adjusts for a target volatility level.

Antonacci’s paper challenges the efficient market hypothesis by using both absolute and relative momentum to create diversified portfolios. This GTAA (global tactical asset allocation) strategy focuses on broad market movements to build resilient portfolios that manage risk and adapt to various economic conditions.

Keller and Keuning’s Protective Asset Allocation (PAA) strategy combines dual-momentum with crash protection, offering higher returns and lower risk than the traditional 60/40 stock/bond model. Our variant enhances performance further by using shorter-maturity bond ETFs or combinations based on momentum.

Keller and Keuning’s VAA (Vigilant Asset Allocation) strategy builds on their PAA approach, aiming for higher returns with stricter crash protection. We recommend the VAA-G12 variant for the best balance of risk and reward.

Keller and Keuning’s DAA (Defensive Asset Allocation) builds on VAA by using a “canary” universe for crash protection, improving returns and reducing cash holdings. It offers better risk management with the G12 asset universe and Protective P2=VWO/BND.

Flexible Asset Allocation (FAA) extends traditional momentum models by integrating Relative, Volatility, and Correlation momentum factors. Our example features a four-month lookback with 100/50/50% factor weights and a monthly rebalanced, long-only portfolio.

Zambrano and Rizzolo’s (2022) multi-asset momentum strategy delivers strong risk-adjusted returns and consistent performance by avoiding optimization of measures and look-back periods, while leveraging low asset class correlations to handle macroeconomic shifts.

Keller’s Lethargic Asset Allocation (LAA) strategy uses a Growth-Trend model to switch infrequently between a static portfolio and cash based on bearish trends. It boasts low transaction costs and minimal drawdowns compared to the 60/40 SPY-IEF benchmark.

Keller’s Resilient Asset Allocation (RAA) is a more aggressive version of LAA, characterized by its minimal trading frequency, averaging only one month per year.

Keller’s Bold Asset Allocation (BAA) combines slow relative and fast absolute momentum filters with rapid crash protection, allowing limited risky exposure. The BAA-G12/T6 variant, or ‘balanced’ BAA, is noted for its low volatility.

The “Sell in May and go away” or Halloween effect suggests stocks deliver minimal returns from May to October, with most gains occurring from November to April. Research confirms the profitability of this anomaly, and it can be enhanced for even better results globally.

A paired switching strategy involves alternating between two negatively correlated assets based on performance, offering potential for better returns than a static portfolio. Its simplicity makes it appealing for various investment approaches.

The FED Model forecasts equity returns by comparing earnings yields to bond yields. This strategy uses the yield gap to guide market timing decisions and can be refined with additional variables.

Gold, known for its safe-haven status, offers diversification and inflation protection due to its low or negative correlation with other assets. A straightforward timing model can enhance profitability in gold investments.

The “3rd-year effect” suggests better stock returns in the third year of a presidential term. A simple strategy is to invest in equities during this year and avoid them in the other years.

Recessions are hard to predict due to delays in official identification and varying dates. However, a potential indicator is the decline in full-time employment coupled with an increase in part-time jobs, which often signals a recession.

Bitcoin’s price volatility can be managed with a trading strategy using moving averages, like the 10-day. This approach outperforms buy-and-hold by reducing drawdowns and improving the Sharpe ratio, and also works well with Ripple.

Market timing aims to avoid large declines by using indicators like the Treasury spread and macroeconomic data. Ďurian and Vojtko’s 2023 strategy significantly improves returns and reduces drawdowns by predicting and avoiding major bear markets.

Thrasher’s 2023 award-winning paper suggests using the time for a 5% equity decline and a 200-day Simple Moving Average as signals for market declines or buying opportunities. This method aids in developing trading strategies based on annual volatility.

The Book-to-Market effect compares a company’s book value to its stock price, indicating fundamental value. Once overshadowed by Efficient Market Theory, it regained prominence as research confirmed its relevance, notably in Fama and French’s 1993 paper.

The small-cap premium shows that small-cap stocks typically outperform large-caps. Despite past severe drawdowns, small-cap factors remain beneficial for long-only portfolios. This is supported by Fama and French (1993) and updated by Alquist, Israel, and Moskowitz (2018).

Dividends were once a strong predictor of equity returns, but recent research indicates that their effectiveness has declined. Stock repurchases have become a more significant factor, making comprehensive shareholder yield measures more relevant today.

The net current asset value (NCAV/MV) strategy, popularized by Benjamin Graham, involves investing in stocks where net current assets per share exceed the market value. This method was highly profitable from the 1930s to the 1950s.

Stocks with low asset growth significantly outperform high asset growth stocks on a risk-adjusted basis, with this effect consistent across different time periods and market caps. The strategy is cost-effective and practical to implement.

Paying dividends signals a company’s financial strength and leads to higher returns in the month dividends are expected. A strategy going long on dividend payers and short on non-payers shows statistically significant returns and low correlation with broad equity indexes.

Stocks with recent big price jumps are often overvalued due to investor bias. Shorting these “lottery stocks” can be highly profitable, though they are typically small and illiquid, making them challenging to trade.

In large-cap stocks, profitability (gross profits-to-assets) complements the value effect, providing a lower-volatility, higher-return strategy compared to using value or growth alone.

The short-term reversal anomaly indicates that buying stocks far from their 52-week highs and selling those near their highs can be more profitable.

Research shows that the distance between short-term (21-day) and long-term (200-day) moving averages, known as the Moving Average Distance (MAD), effectively predicts equity returns.

Documented anomalies may have biases and unrealistic assumptions. For practical investing, focus on a few robust factors and create a liquid, long-only portfolio.