We Turn Market Factors into Investment Performances

Market Factors Utilized by WallStreetCourier

All our services are designed to specifically exploit certain market factor. Below, you’ll find a brief description of five scientifically well documented and tradable market factors utilized by the research of WallStreetCourier.com and covered by our services. Each section contains a list of relevant research papers covering the specific market factor.

We rely on input factors with an economic rationale and a large body of evidence from the academic literature

Time Series Momentum Effect

The time series momentum effect shows that each asset’s own past return is a strong positive predictor for future returns. The empirical literature examining evidence for a momentum effect is vast. Levy (1967) was the first to highlight that stocks with higher than average past returns exhibit significant abnormal future returns. Subsequently, Grinblatt and Titman (1989), Jegadeesh and Titman (1993) as well as Jegadeesh, Lakonishok and Chan (1996) have found that the time-series momentum effect is remarkably consistent across hugely different asset classes and markets, and is associated with positive abnormal returns.

The trend is your friend!

Other longer-term studies have confirmed that the momentum effect has existed for well over a century. In 2014, AQR Capital Management published a paper called “A Century of Evidence on Trend-Following Investing”. They have found that a time-series momentum strategy had been consistently profitable throughout the past 134 years.

The fundamental reasons for this anomaly are behavioral biases like investor herding and the investors’ initial underreaction and delayed overreaction applied to information dissemination. That means, if applied correctly, exploiting the time-series momentum anomaly is an outright profitable strategy.

Relevant Research Papers:

Cross Sectional Momentum

“Cut losses short and let winners run,” is an old, well-known stock market saying. Academic research has found that on average, assets with strong recent performance, relative to other assets in the cross section of returns, tend to generate superior positive returns (Jegadeesh and Titman, 1993).

Cut losses short and let winners run

This anomaly was termed cross-sectional momentum. The fundamental reasons for this anomaly are based on long-standing behavioral biases exhibited by investors, such as anchoring and herding, as well as the trading activity of non-profit-seeking participants, such as central banks and corporate hedging programs.

Smart Money Effect

The first studies to address the phenomenon that a specific group of investors could predict mutual fund performance and invested accordingly was conducted by Gruber (1996) as well as Zheng (1998). This market anomaly was termed the “smart money” effect. More up-to-date research, however, has found that the “smart money” effect can partly be explained by the momentum effect (Sapp and Tiwari, 2004).

Do not remain seated when the pilot is jumping out of the plane with a parachute!

This also applies to the trading activity of speculators within the Commitments of Traders Report (Moskowitz, Ooi and Pedersen, 2012). The “smart money” effect is consistent across various markets and is associated with positive abnormal returns. Consequently, trends and trend reversals can recognized in a timely manner by following the investment behavior of “smart money” in a systematic way.

Learn how our Smart Money Flow Index has called every major top and bottom since we have been online!

Relevant Research Papers:

The Flaws of a Market Capitalization-Weighted Index

The main premise of the modern portfolio theory is that “markets are efficient”. By efficient market, the academic literature means a capitalization-weighted index. The main flaw is that the methodology has a strong tendency to favor expensive stocks over cheap stocks, which results in excessive concentration on a small number of stocks (Perold, 2007). Consequently, stocks with higher market capitalizations have a greater impact on the value of the underlying index than companies with a smaller market cap.

The top 10 percent or the top 50 constituents of the S&P 500
account for approximately more than 50 % of its weight

For instance, the top 10 percent or the top 50 constituents of the S&P 500 account for approximately more than 50 % of its weight. Therefore, the price information of the index could cause a false perception of the underlying trend force (time-series momentum), especially in times when those heavy-weighted stocks move in the opposite direction of the broad market.

In such a situation, the degree of confidence in the continuation of the current price trend (time-series momentum) decays significantly. This often correlates with dumb money being invested heavily, even though smart money is taking the opposite trade at the same time, making those painful momentum crashes quite forecastable.

Relevant Research Papers:


The practice of spreading money among different investments in order to reduce risk is known as diversification. The modern understanding of diversification originates in the scientific work of Harry Markowitz in the 1950s. An effectively diversified portfolio is constructed of securities and/or asset classes that are not based on common risk factors (WallStreetCourier, 2012).

There is no free lunch, but diversification offers a cheap one!

Therefore, they tend to move independently, as the underlying risk factors are uncorrelated to each other. If implemented correctly, this reduces the portfolio risk significantly, while the expected return of each investment within the portfolio remains unchanged

Relevant Research Papers: