In our context, a technical trading indicator can be considered as a combination of a specific technical trading rule with a particular moving average of prices. In two preceding blog posts we showed that there [...]
Similar to some better-known factors like size and value, time-series momentum is a factor that historically has demonstrated above average excess returns. Time-series momentum, also called trend-momentum or absolute momentum, is measured by a portfolio long assets that have had recent positive returns and short assets that have had recent negative returns. Compare this to the traditional (cross-sectional) momentum factor that considers recent asset performance only relative to other assets. The academic evidence suggests that inclusion of a strategy targeting time-series momentum in a portfolio improves the portfolio’s risk-adjusted returns.
In this post we aim to give an overview of some specific types of moving averages. Specifically, we cover "ordinary" moving averages and mention some examples of exotic moving averages.
One of the basic principles of technical analysis is that ``prices move in trends". Traders firmly believe that these trends can be identified in a timely manner and used to generate profits and limit losses. Consequently, trend following is the most widespread market timing strategy; it tries to jump on a trend and ride it. Specifically, when stock prices are trending upward (downward), it's time to buy (sell) the stock. Even though trend following is very simple in concept, its practical realization is complicated. One of the major difficulties is that stock prices fluctuate wildly due to imbalances between supply and demand and due to constant arrival of new information about company fundamentals. These up-and-down fluctuations make it hard to identify turning points in a trend. Moving averages are used to ``smooth" the stock price in order to highlight the underlying trend.
If you've been reading our blog for a number of years you're 1) probably a finance geek, and you're 2) probably tired of us discussing the following themes: Value investing: buy cheap stocks (see our [...]
In 2015, Cliff Asness made the case that to earn attractive returns with proper risk-based diversification and low correlation to traditional markets, investors need to embrace ‘the three dirty words in finance,’ which he defined [...]
Jack did a nice recap on a momentum paper last week that looks at using fundamentals (revenue volatility, low cost of goods, and B/M) to help identify the best price momentum stocks. This paper sounds similar to the paper Jack reviewed, but there is a key difference: the researchers are looking at the momentum of the fundamentals, not the absolute value of the fundamentals. The authors compile a fundamental momentum variable by calculating the moving averages of 7 elements: return on equity return on assets earnings per share accrual-based operating profitability cash-based operating profitability gross profitability net payout ratio
How do we identify who is a flash in the pan blogger versus the next Michael Kitces, Josh Brown, or Ben Carlson? We've tried to do our part and help to promote and share research from up and coming "undiscovered" bloggers/writers out there. In our early days, we were helped by long-time bloggers such as Meb Faber and Tadas Viskanta, so we try and return the favor. Recent examples of up and coming guest writers we've highlighted include Dan Sotiroff (now heading to Morningstar!), Aaron Brask, Andrew Miller, Elisabetta Basilico, and Dan Grioli -- all of whom have written interesting and insightful pieces!
Skewness is a statistical measure of how returns behave in the tails of a probability distribution. Wikipedia has a more robust definition of skewness with some good visuals here. If an investment (e.g., stocks) has negative [...]
After reviewing the 2016 performance of trend-following (-18.15%), its unclear why anyone would mention the word "trend following" in a public forum. But we'll give it a whirl anyway... The comedian Victor Borge once famously observed, [...]
Media and Google: The Impact of Information Supply and Demand on Stock Returns by Yanbo Wang Yanbo identifies information into two buckets: News releases (supply) and Google search traffic (demand). A very rough synthesis of how the supply [...]
The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and [...]
Hello readers, we have a new contributing author. Tianzi is her name and reading cool academic papers is here game. Here is her first post. She'll be posting updates and analysis throughout the summer. If [...]
Recently, I've been investigating various risk management systems. A lot of the work we've done is beyond the scope of the blog and/or is related to things we do with our investment management business. Nonetheless, [...]
Note: This is a guest post by Tom Cleveland A New Anomaly: The Cross-Sectional Profitability of Technical Analysis Yufeng Han, Ke Yang, and Guofu Zhou A version of the paper can be found here. Live [...]