⚡️Market Strategy Flash
July 2, 2026
Every investment professional – including me – is familiar with the ubiquitous compliance disclaimer: “Past performance does not guarantee future results.” While it’s intended to protect market participants from dangerous extrapolation, that legal warning has unintentionally fostered a narrative that stock market history is nothing but a “random walk” with zero explanatory power.
To be clear, the purpose of this fun summer Flash is to refine, not challenge, the interpretation of the compliance disclaimer. In that spirit, nearly a century of experience suggests that past returns on US large market capitalization stocks contain a faint yet statistically significant signal that may help explain how share prices evolve over time.
Ubiquitous Disclaimer vs. Historical Reality
Do the past 12 months of performance influence this month’s return? To answer that question, I built a standard log-log Autoregressive Model – an AR(12) specification – using the natural logarithm of month-over-month (M/M) price ratios on the S&P 500 from January 1929 to June 2026 (i.e., 1,170 months). Price ratios solve the negative return problem with log transformations.
Empirical Framework
To avoid the illusion of “spurious” regressions caused by the long-term uptrend of the S&P 500, I transformed the raw index levels into logged, stationary, continuously compounded, non-overlapping price ratios. The tested model is specified as follows:
rt = α + β1rt-1 + β2rt-2 + β3rt-3 + … + β12rt-12 + εt
Where rt is the logged M/M price ratio of the S&P 500 in the current month, calculated as LN(Pt / Pt-1), α represents structural upward market drift, β1 through β12 denote the lagged coefficients for months 1 through 12 and εt is the error term.
Verdict: What the Regression Statistics & ANOVA Table Say
The evidence suggests that lagged stock market returns contain detectable, albeit modest, information about subsequent returns. Specifically, past performance explains 3%, not 0%, of the variation in future performance. While history isn’t a crystal ball, it’s statistically relevant, which is a notable distinction.
Fortunately for macro strategists like me, these results also mean that the overwhelming majority (97%) of share price movements are driven by external information, such as the economy, earnings, monetary and fiscal policy, geopolitical events and other factors that can’t be explained by price action alone. Sorry, technicians (see the tables below).
Sources: WCG, 6/30/26. Notes: R2 = R square. SE = Standard error. ANOVA = Analysis of variance. df = Degrees of freedom. SS = Sum of squares. MS = Mean square. F = F statistic. SF = Significance F or the P-value of F. P-value = The probability of observing your results if the null hypothesis is true.
Sources: WCG, 6/30/26. Notes: t-stat = t statistic. Variables X 1-12 were lagged by 1-12 months, sequentially. Interval of estimation = Jan-1929 to Jun-2026.
History Matters
Not-So Supermodel (F-Statistic = 2.53 | Significance F = 0.00): With a high degree of certainty (p < 0.01), we can reject the null hypothesis that all lagged coefficients are simultaneously zero. The probability that the collective 12 months of past performance has no explanatory power is virtually non-existent. In other words, history isn’t just noise.
Structural Drift
Intercept (Coefficient = 0.00399 | P-value = 0.01 | t-Stat = 2.46): A positive intercept is consistent with the long-term uptrend of US large-cap stocks over the sample period. Plain English: Stocks seem to benefit from a structural, upward drift of 0.4% per month.
“Memory Lane” Hypothesis
While a given 12-month sequence of returns may be meaningful, the individual t-stats and P-values suggest that the stock market’s memory isn’t perfectly linear. Rather, an interesting wave pattern forms that requires further analysis. Specifically, the one-, three- and five-month lags emerge as statistically significant in this specification. Whether they represent stable features of stock market behavior, regime-dependent effects or statistical artifacts deserves additional scrutiny, but those are stories for another day:
- 1-Month “Momentum” (Lag 1)
o Coefficient = 0.07387 | P-value = 0.01 | t-Stat = 2.51
o A positive coefficient at the one-month horizon points to serial correlation (or autocorrelation), short-term trend persistence and tactical momentum. Plain English: Last month’s performance could spill over into this month.
- 3-Month “Reversal” (Lag 3)
o Coefficient = -0.07865 | P-value = 0.01 | t-Stat = -2.67
o A negative coefficient at the three-month horizon implies a potential “rubber band” effect or quarterly “mean reversion.” Plain English: Performance from three months ago may drag on this month.
- 5-Month “Echo” (Lag 5)
o Coefficient = 0.08247 | P-value = 0.01 | t-Stat = 2.79
o A positive coefficient at the five-month horizon suggests a secondary wave of positive momentum that resurfaces nearly half a year later. Plain English: Performance from almost two quarters ago can have a “ripple” effect on this month.
Every other lag (months 2, 4 and 6-12) fails the standard significance test (p > 0.05).
Bottom Line
The hedge clause, “Past performance does not guarantee future results,” is true but statistically incomplete. The evidence is consistent with a stock market memory that persists modestly and unevenly across time horizons, although additional testing is required to determine whether this pattern is stable across market regimes. These findings suggest that historical returns may contain incremental information that could complement broader investment frameworks.
While compliance guidelines treat equity trends as decoupled sequences, my quantitative approach follows a long lineage of academic literature. To wit, the seminal work of Lo and MacKinlay (1988) pioneered the formal mathematical rejection of the “random walk” hypothesis for US stock prices, and Jegadeesh and Titman (1993) documented the enduring structural presence of short-term serial return dependencies.
References
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Lo, A. W., & MacKinlay, A. C. (1988). Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test. Review of Financial Studies, 1(1), 41-66.
Definitions
Random walk: A mathematical process where future steps or values are completely unpredictable and determined by pure chance. In finance, it represents the theory that stock price movements are random and cannot be predicted using historical data.
Autoregressive model: A statistical model that predicts future values of a variable by looking at its own past values. It uses a linear combination of previous data points to forecast the next step in a time series.
Natural logarithm: A mathematical function that represents the power to which the constant e (approximately 2.718) must be raised to equal a specific number. It is widely used in finance and science to model continuous growth or compounding returns.
S&P 500: A stock market index that tracks the performance of 500 of the largest companies listed on stock exchanges in the United States. It is widely used as a reliable gauge for the overall health of the US stock market.
Spurious: A term describing a statistical relationship where two variables appear to be causally linked but are actually unrelated. This false connection is usually a coincidence or driven by a hidden third variable.
Regression: A statistical method used to estimate and analyze the relationship between a dependent variable and one or more independent variables. It helps determine how much the dependent variable changes when an independent variable is modified.
ANOVA: A statistical test used to compare the means of three or more independent groups. It determines if at least one group mean is significantly different from the others.
Serial or auto correlation: A statistical phenomenon where error terms or data points in a time series are correlated with their own past values over time. It indicates that past patterns are repeating in the data.
Disclosures
The views expressed are for informational and educational purposes only and are subject to change without notice.
This material is not intended as, and should not be interpreted as, individualized investment advice or a recommendation to buy, sell, or hold any security, sector, industry, or investment strategy.
References to specific companies, securities, sectors, or industries are for illustrative purposes only and should not be construed as investment recommendations.
Investing involves risk, including the possible loss of principal. Investments in a specific industry or sector may involve greater risk and volatility than more diversified investments.
Past performance is not indicative of future results. No investment strategy can guarantee a profit or protect against loss.
Forward-looking statements, including views about future demand, pricing, supply, or industry cycles, are based on current expectations and assumptions and are subject to risks and uncertainties. Actual results may differ materially.
Data and information are believed to be reliable, but accuracy, completeness, and timeliness are not guaranteed. Source documents should be retained for factual claims, third-party research references, and company-specific data.
Portfolio holdings, allocations, and risk budgets are subject to change based on market conditions, client objectives, and investment guidelines.
The author, firm, clients, or related persons may hold positions in securities mentioned and may buy or sell those securities without notice, subject to applicable policies and regulations.
Securities offered through LPL Financial, Member FINRA/SIPC. Investment Advice offered through WCG Wealth Advisors, LLC, an SEC Registered Investment Advisor. WCG Wealth Advisors, LLC and The Wealth Consulting Group are separate entities from LPL Financial. Index performance is shown for illustrative purposes only and does not predict or depict the performance of any investment. Past performance does not guarantee future results.
All information in this report is believed to be from reliable sources; however, WCG Wealth Advisors, LLC, makes no representation as to its completeness or accuracy.
In general, stock values fluctuate, sometimes widely, in response to activities specific to the companies as well as broad market, economic and political conditions. Stock investing involves risks, including fluctuating prices and loss of principal. Value investments can perform differently from the market as a whole. They can remain undervalued by the market for long periods of time. (135-LPL) International investing involves special risks such as currency fluctuation and political instability and may not be suitable for all investors. These risks are often heightened for investments in emerging markets. (93-LPL)
The fast price swings in commodities will result in significant volatility in an investor’s holdings. Commodities include increased risks, such as political, economic, and currency instability, and may not be suitable for all investors. (122-LPL)
Rebalancing a portfolio may cause investors to incur tax liabilities and/or transaction costs and does not assure a profit or protect against a loss. (28-LPL)
There is no guarantee that a diversified portfolio will enhance overall returns or outperform a non-diversified portfolio. Diversification does not protect against market risk. (26-LPL)
Standard deviation is a historical measure of the variability of returns relative to the average annual return. If a portfolio has a high standard deviation, its returns have been volatile. A low standard deviation indicates returns have been less volatile. (131-LPL)
This is for educational / general purposes only, does not constitute investment, tax or legal advice and should not be relied on as such. This is not to be construed as an offer to buy or sell any financial instruments. Any strategies discussed are not intended to be relied upon as the sole factor in making an investment decision for any individual. As with all investments there are associated inherent risks. Please obtain and review all financial material carefully before investing. All material presented is compiled from sources believed to be reliable and current, but accuracy cannot be guaranteed. The opinions voiced in this material are for general information only and are not intended to provide specific advice or recommendations for any individual. All performance referenced is historical and is no guarantee of future results. All indices are unmanaged and may not be invested in directly. These comments should not be construed as recommendations but as an illustration of broader themes.
Forward-looking statements are not guarantees of future results. They involve risks, uncertainties and assumptions; there can be no assurance that actual results will not differ materially from expectations. In addition, forward-looking statements, including index targets or market scenarios, are hypothetical in nature, reflect current views and assumptions and are subject to change based on market and economic conditions and are not guarantees of future performance. This is a hypothetical example and is not representative of any specific investment. Your results may vary. (88-LPL) Scenario outcomes are illustrative and not predictive. This does not constitute a recommendation of any investment strategy or product for a particular investor. Investors should consult a financial professional before making any investment decisions.
The S&P 500 is a stock market index tracking the stock performance of 500 of the largest companies listed on stock exchanges in the United States. Indexes are unmanaged and cannot be invested in directly. (102-LPL)
Government bonds and Treasury bills are guaranteed by the US government as to the timely payment of principal and interest and, if held to maturity, offer a fixed rate of return and fixed principal value.
Publication Date: July 2, 2026
For Public Use in the US
The Wealth Consulting Group
LPL 1133961