In recognition of National Earth Day earlier this week (4/22), we turn our attention to ESG investing and its growing relevance for investors. ESG (Environmental, Social, and Governance) investing gained prominence as investors increasingly came to view these factors as material drivers of long‑term financial performance rather than merely a reflection of values‑based preferences. Exposure to climate risk, labor practices, and governance failures began to be recognized as tangible sources of market volatility, regulatory and litigation risk, and reputational damage. As a result, ESG evolved into a framework for risk‑aware investing, positioning sustainability metrics as tools for identifying potential return drivers and downside risks—not simply an expression of ethical investing.

The ESG Top 10 Stock Model (TR) (ESG10.TR) seeks to capture these dynamics by identifying leadership trends within a universe of 150 U.S.-listed companies that demonstrate strong sustainability performance and disclosure. The model systematically selects the top 10 qualifying stocks and maintains exposure to them until they fall out of favor, ensuring continuous alignment with companies exhibiting sustained ESG leadership.

Across multiple performance horizons, the model has consistently outperformed its benchmark, TR.SPXX, at every measured interval. Most notably, the model’s one‑year return stands at approximately 138.8%, significantly surpassing the benchmark’s 36.7% return over the same period. Since its inception in 2008, the model has delivered a compound annual growth rate of 20.8%, outperforming the benchmark by more than 9.5% on an annualized basis.

As experienced model builders recognize, the most rigorous test of a strategy comes through out‑of‑sample performance—how well the model performs once deployed in live trading conditions rather than in a historical backtest. The model’s in‑sample backtest spans from early 2008 through late 2020, a period of approximately 13 years, with out‑of‑sample performance beginning on December 4, 2020. Since going live on the platform, the model has generated a cumulative return of 191.8%, exceeding its benchmark by 83%, reinforcing the robustness and durability of the underlying investment framework.

An examination of the model’s portfolio statistics shows that its historical volatility, with a standard deviation of approximately 21.9%, exceeds that of the benchmark, which stands at 15.6%. Despite this higher level of risk, the model delivers a superior risk‑adjusted outcome, as reflected by a Sharpe Ratio of 0.82 compared with the benchmark’s 0.59. This indicates that the model has been more efficient in converting additional risk into incremental returns, demonstrating that the higher volatility has been compensated by disproportionately stronger performance.

In closing, model holdings can serve as a valuable input for idea generation, as examining their components often helps identify high‑conviction names within a particular sector or thematic group. The model purchased Applied Materials, Inc. (AMAT) at the end of December 2025. Since then, AMAT has had an absolute performance (asset performance since it has been held in the model) of 57%. The 4 for 5’er is up 59% year-to-date and belongs to the semiconductors sector, which currently ranks 1st out of 41 groups in the NDW Group Matrix Rank. The stock reversed back into a buy signal after completing a double top break at $360 and is currently facing resistance at $400, its previous all-time high. Long exposure can be made here, given the normalization of the 10-week trading band. Initial support is at $380, with additional support at $340.

From its low on March 30, to the high it reached last Friday (4/17) the S&P 500 gained more than 13% and is now up a little over 4% for the year (through 4/22). Meanwhile, the Nasdaq-100 (NDX) has had an even sharper rally as it has risen more than 17% from its low. Given its speed, investors who didn’t get in before the rally started may have found it difficult to find an entry point as there were few, if any, pullbacks from the time the market bottomed to when it hit a new all-time high. And, if they have money to put to work, these people may now be reticent to buy into a market trading at all-time highs.

In this situation, it can be tempting to simply layer in exposure – it provides flexibility to buy lower if the market exhales. But while it may be a seem like an attractive option, unfortunately we usually pay for that flexibility in the form of lower returns. To illustrate the effects of layering or averaging in versus putting all your money to work now, we looked at two hypothetical scenarios for 10-year holding periods. We calculated the returns for both scenarios every month from January 1985 through April 2016, the last month for which we could calculate a 10-year forward return.

The “All In” Strategy - This scenario assumes you invested all available funds in the S&P 500 (SPX) at the beginning of the period. So, for example, in January 1985 all available funds would be invested in SPX for the next 10 years. We then calculated the returns for a hypothetical start date of February 1985, March 1985, and so on, through April 2016.

The “Average In” Strategy – This scenario assumes you invested an equal amount of the portfolio in the S&P 500 each month over the entire 10-year period. As with the “All In” strategy, we calculated the returns for the “Average In” strategy for hypothetical start dates at the beginning of every month from January 1985 through April 2016.

Our test shows that, historically, going “All In” has clearly been superior to the “Average In” strategy. This may not be terribly surprising, after all, the market generally goes up over time, and with the “All In” strategy, you have the power of compounding on your side. What may be surprising, however, is the magnitude of the difference.

On average, the “All In” strategy outperformed the “Average In” strategy by more than 75% on a cumulative basis. There was also a dramatic difference in the best performance for each strategy - going ‘All In’ in October 1990 generated a maximum 10-year return of over 370%, meanwhile the best return for the “Average In” strategy” was a relatively paltry 145%. Not only did the “All In” strategy generate higher average, median, and maximum returns, but it also produced positive returns more consistently, albeit by a slim margin. The “All In” strategy produced positive returns just over 92% of the time.

There were 376 months in our test period, giving us 376 observations or hypothetical portfolios. Of these, only 28 produced a negative 10-year return. Interestingly, all 28 came in consecutive months from October 1998 through January 2001, near the height of the dot com bubble. The “All In” strategy also outperformed the “Average In” strategy with notable consistency – out of our 376 observations, “All In” outperformed “Average In” 345 times. Said another way, out of the 376 starting points we looked and all the different market conditions that existed then, you would have been better off going “all in” more than 90% of the time.

Missing “the dip” is undoubtedly frustrating and putting money into a market trading at all-time highs can be uncomfortable. But, historically, you’ve been better to go ahead and put your money to work rather than trying to hedge your bets by layering in exposure.

Daily Option Ideas for April 23, 2026