BEYOND Buy and Hold - A Deeper Dive
Many years ago before we started Equity Sciences, we were researching everything from known strategies, concepts, methodologies, historical failures of other strategists, models, firms, along with studying every area that is or could be connected to the financial markets. Such as economics, game theory, data analysis, behavioral finance, herd psychology, price characteristics, etc. While in the quest of professional improvement and knowledge acquisition, we began to identify some common underlying signatures for strategic or model failure.
Time and time again strategic or model failure reverted to some singularity... Meaning, strategy outcomes were somehow, or in some way, strongly dependent on a single factor. Whether this be a single model, a single strategy, a single source of alpha, or individual market regime. You see when you look across the investment landscape, the one commonality you see with all funds, firms, asset managers, etc is they all believe in the power of diversification. As they should, given its ability to improve consistency and reduce risks. However, many fail to integrate it into their actual strategies. Meaning each asset's outcome is heavily dependent on a single factor. They can diversify with the assets they allocate to and the % that’s allocated to each asset, but that’s simply a rebalancing scheme. When you boil things down, the individual models are exploiting something of a singular nature. Often overly complex models which exploit some extremely nuanced source of alpha. Which on a personal level is not something we align with, as the world we live in and all the economic relationships, connections, & correlations are evolving so rapidly. So, some nuanced source of alpha can fall out of sync faster than upper management can design a new pitch deck for their new "unique" discovery. That single alpha source can also be heavily correlated to a single market condition or price behavior, so when changes occur the model fails.
There is also a misconception within the industry that one needs to deploy both Long and Short models in order to extract alpha or to diversify outcome. This belief is simply due to limited concept exposure. As you will see below, there are numerous ways to exploit multiple market conditions and to even generate consistent positive outcome in random, reverting, consolidation, cyclic, & oversold conditions from the Long Only perspective. One simply must ensure the level or depth of value exploited is reflective of the condition & characteristics within the market. Dynamic processes have to be integrated in every layer to maintain optimal response efficiency otherwise it can be challenging to mimic changes in flow.
While researching we had a moment of insight, what if...... What if we took the most basic principles of investing and found different ways to integrate diversification into each model. Each asset's outcome would not be heavily dependent on anything of a singular nature. We began work designing solutions that magnified outcome diversification while compounding signal probabilities. We developed many unique ways to integrate this objective strategically and structurally of course, and when Equity Sciences was launched we had general concepts that would allow us to offer quality solutions for those curious enough to keep an open mind and look beyond traditional perspectives.
One of those solutions is the SPY Long Only. A diversified multiverse approach to value identification. There are two basic commonalities with all strategies, models, or methodologies.
1. They all exploit some form of value--- This can be predictive value, like a momentum strategy when multiple analytics provide a signal that shows some predictive robustness price will continue in that direction for X time & Y duration. Theres also random, reverting, or oversold value, when price is temporarily deviated from its normal range. An asset is underpriced, for whatever reason, and that is what a strategist is aiming to exploit.
2. Classification. It doesn’t matter what style or type of signal, model, or methodology, essentially every strategy uses classification. A strategy is a form of classifying the asset somehow to identify a repetitive condition that one can exploit.
There are endless ways to pursue both and no way from the other is the same. Each small and subtle change can offer endless decision trees and perspectives to pursue one's objective. SPY uses a unique method of classification to break down the market into repetitive conditions. Then we identify which variation of value is best to exploit in each condition. We designed the model to also allow multiple entries per position. This allows for a dynamic allocation module to be overlayed, so the allocation activated for each entry is reflective of the level of value the asset is exuding.
When you combine value-based entry logic and value-based allocation module, this helps isolate a pathway to out forming while reducing the overall risk profile. Aiming for the model to not be heavily allocated near cyclical highs. Placing a heavy weight on being able to reflect the flow of the market and asset, the solutions applied are all dynamic.
The entire goal of any strategy is to offer solutions that seek high outcome consistency while mitigating many of the known risks associated with the financial markets, volatility, randomness, but also the shortcomings and limitations of quantitative models. We understand there really isn’t much value is looking at historical performance. While that is what one uses in the development process, as a strategy to have to look beyond the limitations of historical data. As the markets will never behave exactly how they did historically. Conditional sequencing, volatility, movement durations and amplitudes will never match up. We realized this and placed a higher weight on response, to apply solutions that reflect the problem given.
This may sound incredibly complex. However, one can benefit from the intelligence of layered analytics without increasing the risks of complexity. Finding solutions that aim to offer an organic path to producing alpha while offering a lower risk profile, when compared to buy & hold. The concepts and structures are designed to work in unison, a symbiotic relationship between strategic concepts & systematic structures.
SPY has exceeded expectations since its OOS(Out of Sample) date of October 2019 for this specific variant. Outperforming and doing so in a rather consistent manner while also offering a superior overall risk profile. Higher Returns with lower annual drawdowns, lower max drawdowns, less time between new equity highs, less positional drawdown, less time capital at risk, lower % of capital at risk. also much less if you account for days when zero capital is at risk.
Equity Sciences programs offer investors an alternative to traditional passive buy and hold models. Visit our website at www.equitysciences.com or email email@example.com for more information.
Here is a sample of performance on our available programs from January 2020-November 2023 on a $100,000 investment.* These programs are offered as a signal service and are delivered daily by email. They can be executed manually or automated with one of our partners.
Program Performance Index Returns Difference
SPY (S&P 500) $ 180,096 $ 141,365 $ + 39,731
QQQ (Nasdaq Comp) 217,630 147,912 + 69,718
DIA (Dow Jones) 201,059 137,021 + 64,038
IWM (Russell 2000) 224,971 118,819 + 106,152
*Disclaimer: Historical Performance, whether Live or simulated, may not be indicative of Future performance. Trading Stocks, ETF's, or Futures involves significant risks of loss, which may not suitable for all investors. Investors should only choose to invest funds they can afford to lose, without negatively impacting lifestyle. Price characteristics are not predictable or repetitive, thus any strategy developed using historical data will be equally unpredictable. We do not guarantee nor claim our strategies will perform positively and/or reflect their historical results. In fact, there can be significant differences between historical & live results. Regardless of how adaptive or historically robust any strategy, model, or system can fail or generate substantial losses. Automated models, strategies, or systems should be monitored on a regular basis. Please consult your investment professional before choosing a trading or investing strategy, to ensure it meets your investment objectives & risk tolerances. All results shown are historically simulated, not live/real. This article is for educational purposes only, not to be considered investment advice, nor a solicitation of any individual product, service, market, and/or equity.