Trend-Following Filters – Part 10
1. Introduction Two previous articles, “Trend-Following Filters – Part 7” [1] and “Trend-Following Filters – Part 9” [2], examined, from a digital signal processing (DSP) [...]
1. Introduction Two previous articles, “Trend-Following Filters – Part 7” [1] and “Trend-Following Filters – Part 9” [2], examined, from a digital signal processing (DSP) [...]
It is well-known that box spreads offer investors the ability to lend via the options market at similar rates to Treasury Bills. But there is another, less popular side of the box spread market – borrowing money. This articles dives into the mechanics of how to use box spreads to borrow at low costs.
A historical review of Buffett’s implementation of diversification and concentration in practice, as well as his perspective on these concepts, documents a long tradition of heterodox thinking and application.
This article examines and compares, from a digital signal processing (DSP) time domain perspective, several filters that are modeled on the assumption that the input follows a second order process, i.e., the input contains a linear trend. These filters are, by design, better able to track linear trends than some other more commonly-used filters, such as moving average, exponential smoothing, etc., which exhibit lag, or a time delay, in response to trends. Filters modeled on a second order process are commonly referred to in the technical analysis literature as “zero lag” filters.
The following guest piece outlines the SIMPLE framework (SIMPLE) for making better decisions. SIMPLE was developed by a Navy SEAL with combat and business experience. An application of the SIMPLE framework, applied to financial advisors, is at the end of the piece.
This article describes digital filters derived from time series regression models that can be used as technical analysis tools. The filters are analyzed from a digital signal processing (DSP) frequency domain perspective to illustrate their properties. Example charts of the filters applied to the S&P 500 index are also included.
Without question the topic of greatest debate among investors, including investment professionals, and financial economists, is whether or not the market, and the technology sector in particular, is overvalued. There are two very strong conflicting views regarding not only the current valuation of technology stocks, but also the valuation of the entire asset class of large-cap growth stocks. One side, I’ll call the “new paradigm” or “it’s different this time” school. The other side, I’ll call “the been there, done that” school. Its theme is those that don’t learn from the past are doomed to repeat the same mistakes. No two sides could have more different viewpoints. To understand each side, let’s imagine a dialogue between the two schools.
As a result of the trading required to capture the premiums that drive factor strategies investors may face significant tax liabilities. The challenge for the [...]
Wallstreetbets has become an increasingly prominent source of investment research. Do their recommendations have value?
The amortization of volatility should be of concern for private capital asset classes. In order to properly budget for beta risks, it is critical that investors in private assets understand the amount of systemic (beta) risk that will “wash” into their private portfolios.
An efficient way to improve the expected performance of an equity strategy would be to systematically exclude penny stocks, as well with high asset growth and extreme past returns, especially if they have low profitability (and exclude funds that don’t screen out such stocks).
Atilgan, Demirtas, and Gunaydin found that there has been a pollution premium for US stocks and that the premium translated into superior investment performance.
While both the S&P 500 and the Nikkei indices have recently hit all-time highs, the valuation and balance sheet data we have reviewed indicate that the downside risks in Japanese stocks appear to be far less than the risks in U.S. stocks. Evidence such as this helps explain why legendary investor Warren Buffett has been buying Japanese stocks.
The finding that the recommendations from SA articles resulted in statistically significant risk-adjusted alphas (returns unexplained by conventional academic models using factors such as the market, size, value, momentum, profitability, and quality for equity portfolios) is surprising given that the empirical evidence shows how difficult it is for institutional investors such as mutual funds to show outperformance beyond the randomly expected (as can be seen in the annual SPIVA Scorecards) because of market efficiency.
To date, the best metric we have for forecasting future equity returns and the ERP is current valuations. An interesting question is whether more complicated methods using newly developed machine learning models can provide superior forecasts.
Momentum continues to receive much attention from researchers because of the strong empirical evidence.
Hibbert, Kang, Kumar and Mishra provided us with yet another explanation: social media is providing analysts with information that reduces their forecasting errors. The result has been an increase in market efficiency, leading to a reduction in the PEAD anomaly. The bottom line is that the ability to generate alpha continues to be under assault—trying to outperform the market by stock selection is becoming even more of a loser’s game.
Short squeezes are often associated with a large positive jump in the price of a stock. Filippou, Garcia-Ares, and Zapatero demonstrated that skewness-seeking investors try to identify securities that could experience a short squeeze in the near future and are willing to pay a premium for them. That results in an overvaluation of the options and, on average, negative returns. Investors are best served to avoid investments with lottery-like distributions. One way to do that is to turn a blind eye to social media sites like Robinhood and Reddit so you don’t get caught up in the hype and excitement. That’s another example of why retail investors are called “dumb money.” Forewarned is forearmed.
Making a bet on biotech/pharma firms that have not yet achieved significant revenue is the equivalent of buying a lottery ticket—with the same poor risk/return relationship.
While the evidence makes clear that active management is a loser’s game (one that it is possible to win but so unlikely you should not try), we don’t want active managers to disappear. Hope should continue to triumph over evidence, wisdom, and experience because active managers help eliminate market anomalies and inefficiencies created by the misbehavior of investors (such as noise traders). That helps to ensure that capital is allocated efficiently.
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