BEST OF THE BEST INVESTMENT MODEL DATA CARD

The following information is hypothetical and simulated. It does not represent actual trading results. Hypothetical performance has inherent limitations and does not reflect real investment outcomes. Past performance does not guarantee future results. This material is intended solely for educational purposes and does not constitute investment advice or a recommendation to buy or sell any security. Please consult a qualified financial advisor before making any investment decisions.

 The purpose of the BOTB Data Card is to provide a concise, authoritative summary of key highlights, facts, and notable outcomes for the specified reporting period. It is designed to function as a quick-reference resource that consolidates essential information into a clear, accessible format. The Data Card supports consistent communication, informed decision-making, and efficient reuse of validated data for the strategic alignment with investor goals.

The performance data of the BOTB model is given in relation to the benchmark S&P 500 Total Return Index.

These results are best simulated when the investor is using the best practices of application. (See below)

Best Practices in order to simulate the Best of the Best Investment Model

The BOTB investment model run provides the 10 most highly probable, global all cap stocks for the upcoming seasonal quarter (Feb, May, Aug, Nov).

The model is reconstituted on the 1st day of each seasonal quarter (February 1st, May 1st, August 1st, November 1st). Trades should be placed before or as close to market open on that day. Only the 10 stocks identified should be held for that seasonal quarter. This is a reconstitution of the model.

It assumes equal weighting across all 10 securities (10% each in a non-cash account).

No other trading shall occur until the next reconstitution.

The model incorporates an assumptive 50 basis point investment fee.

Due to short-term capital gain taxation the best account types are IRAs, 403(b) & 401(k) & other Qualified Plans.

DATA CARD DEFINITIONS

S&P 500 TR:

The S&P 500 TR (Total Return) is a version of the classic S&P 500 index that measures the complete investment return an investor would receive — not just price appreciation, but also the reinvestment of dividends.

S&P 1500:

The S&P 1500 Index is designed to measure the performance of the large-, mid-, and small-capitalization segments of the U.S. equity securities universe.

CAGAR / COMPOUND ANNUAL GROWTH RATE:

CAGR is an abbreviation for Compound Annual Growth Rate. It is a metric used to calculate the average yearly growth rate of an investment over a given time period while accounting for compounding. The compounding effect, which implies that the returns gained in each year are reinvested and contribute to the overall growth of the investment, provides a more accurate picture of investment performance.

CAGR is a widely used metric in the financial industry as it allows for better evaluation and
comparison of investment performance than average annual return.

STANDARD DEVIATION:

Standard deviation is a statistical measure that helps us understand the variability or risk associated with an investment's returns. In simple terms, it tells us how much the returns of an investment can deviate from the average or expected return. Think of it as a measure of how volatile or fluctuating an investment's performance can be.

Let's break it down. Imagine you have an investment that provides an average annual return of 8%. However, the actual
returns from year to year may not be exactly 8%. Some years, the returns may be higher than 8%, and other years, they
may be lower. The standard deviation gives us an idea of how much those returns might deviate from the 8% average. Think of it as the "average difference" from the "average expectation".

A higher standard deviation indicates greater variability in returns, which means the investment's performance can be
more unpredictable or volatile. On the other hand, a lower standard deviation suggests more stability and less fluctuation in returns. Investors often consider the standard deviation as a measure of risk because higher volatility implies a higher chance of experiencing both positive and negative returns.

ULCER INDEX:

The Ulcer Index is a risk measurement metric that quantifies the depth and duration of drawdowns (price declines) in an investment, focusing specifically on downside risk — the kind of loss that causes investors stress, hence the name.

The Ulcer Index measures how far and for how long a portfolio or security has fallen from its most recent peak. Unlike standard deviation (which treats upside and downside volatility equally), the Ulcer Index only penalizes losses, making it a more intuitive measure of investor discomfort.

SHARPE RATIO:

The Sharpe ratio is a popular financial metric that helps investors estimate an investment's risk adjusted return (and
efficiency). It was created by Nobel winner William F. Sharpe and is widely utilized in the financial industry.

The ratio provides useful information about how well an investment has done in relation to its level of risk. In simple terms, the Sharpe ratio compares the excess return of an investment (the return above the risk free rate of US Treasury Securities) to the volatility or risk taken to achieve that return. It quantifies the additional return earned per unit of risk assumed. A higher Sharpe ratio indicates a better risk adjusted performance, as it suggests that the investment generated more return for each unit of risk taken.

To calculate the Sharpe ratio, subtract the risk free rate of return from the investment's average return and divide it by
the standard deviation of the investment's returns. The resulting ratio tells us how much excess return the investment
generated for each unit of risk.

A positive Sharpe ratio implies that the investment has provided a higher return than the risk free rate, while a negative ratio suggests the investment has underperformed the risk free rate.

SKEW or SKEWNESS:

Skewness is a statistical measure that helps us understand the asymmetry or "lopsidedness" of a distribution. In simpler terms, it tells us whether the data is more concentrated on one side of the mean compared to the other.

Skewness provides valuable descriptive insights into the shape of a dataset and the likelihood of extreme values.

Imagine a scenario where you have a dataset of housing prices in a city. If the majority of houses are priced below the
average, and there are a few very expensive luxury homes, the distribution of housing prices would be positively skewed. This means the tail of the distribution extends towards higher values, indicating that the dataset is lopsided with more low priced houses and a few high priced outliers. Conversely, if the majority of houses are priced above the average, and there are a few very cheap houses, the distribution of housing prices would be negatively skewed. This means the tail of the distribution extends towards lower values, indicating that the dataset is lopsided with more high priced houses and a few low priced outliers.

The "Tail" of a distribution shows the "lack of".

MAX DRAWDOWN:

Max drawdown is a measure used by investors to understand the largest decline or loss an investment has experienced from its peak value to its lowest point before a new peak is reached. In simple terms, it tells you how much an investment has dropped at its worst during a specific period. Imagine riding a roller coaster the max drawdown is like the steepest dip you experience before the ride starts climbing again.

To calculate max drawdown, you look at the percentage decline from the highest point to the lowest point in the investment's value. It helps advisors gauge the potential downside risk of an investment. For example, if an investment's value reached $10,000 and dropped to $7,000 before climbing back up, the max drawdown would be 30% ([$10,000 --$7,000] / $ investors pay attention to max drawdown as it provides insight into an investment's volatility and potential losses. A smaller max drawdown indicates a more stable investment with smaller fluctuations, which can be desirable for risk averse investors. On the other hand, a larger max drawdown suggests higher volatility and the potential for significant losses, which might be suitable for those comfortable with higher risk.

One drawback of using max drawdown as a measure of risk is that it focuses solely on the historical worst case scenario without considering the context or underlying reasons for the drawdown. Additionally, max drawdown calculations are based on past data, and future drawdowns may be influenced by unforeseen events, such as black swan events, making them difficult to predict or replicate.

ALPHA:

In simple terms, alpha represents the excess return generated by an investment after accounting for the expected return based on its level of risk. It is often seen as a measure of the investment manager's skill in generating returns beyond what can be attributed to the general market movements.

Alpha is a crucial concept because it helps evaluate the performance of a particular investment strategy or portfolio manager. A positive alpha indicates that the investment has generated higher returns than expected given its level of risk, suggesting successful stock selection. Conversely, a negative alpha implies that the investment has underperformed its expected returns, potentially indicating an ineffective investment strategy.

For example, let's consider a mutual fund that aims to track the performance of the S&P 500 index, which serves as the
benchmark. If the fund generates a return of 10% while the S&P 500 returns 8%, the fund has achieved a positive alpha of 2%. This implies that the fund's manager has made successful investment decisions, resulting in returns that surpass the market's performance. Conversely, if the fund returns 7% while the benchmark returns 8%, it indicates a negative alpha of 1%, suggesting that the fund underperformed the market.

BETA:

Investment beta, also known as beta coefficient or simply beta, is a measure of a stock or investment's sensitivity to
changes in the overall market. It helps advisors understand how much an investment's price tends to move in relation to movements in a benchmark, such as the overall stock market. In simple terms, beta provides insight into how volatile or risky an investment is compared to the broader market.

Imagine you're driving on a highway, and the market is like the flow of traffic. Some cars move faster or slower than the
average speed of traffic. Investment beta works in a similar way. If a stock has a beta of 1, it tends to move in line with the market, like a car traveling at the same speed as the traffic. A stock with a beta greater than 1 is more volatile than the market, like a car driving faster than the average flow. Conversely, a stock with a beta less than 1 is less volatile than the market, like a car driving slower than the average speed.

Investors use beta to assess an investment's risk and potential returns. A higher beta suggests higher potential volatility and risk, as the investment tends to magnify market movements. Conversely, a lower beta implies lower volatility and risk. It's important to note that beta is just one of many factors to consider when making investment decisions, and it should be evaluated alongside other fundamental and quantitative analysis.

KURTOSIS: 

Kurtosis is a statistical measure used to determine the shape of a distribution. It reveals the peakedness or flatness of a
dataset in comparison to a normal distribution. In layman's terms, kurtosis tells us whether the data has more or fewer
outliers or extreme values. Imagine a graph that represents the distribution of a dataset. If the graph is tall and narrow, it indicates a higher kurtosis value. This means the data is more concentrated around the mean, and there is a higher likelihood of extreme values or outliers. On the other hand, if the graph is flatter and wider, it indicates a lower kurtosis value. This suggests a more spread out distribution with fewer extreme values.

 
A higher kurtosis value implies a higher probability of extreme returns, indicating higher risk, while a lower kurtosis value suggests a lower probability of extreme returns, indicating lower risk. However, it's important to consider other measures alongside kurtosis to get a complete understanding of the dataset's characteristics and potential risks.

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This information is intended to be educational only and does not constitute any recommendation. It is up to the reader to make use of this material and should seek personal advice from their financial advisors. Past performance is not a guarantee of any future outcome.

Actual performance may result in lower or higher returns than the hypothetical Model performance presented. If actual portfolios had been managed, there can be no guarantee such portfolios would have achieved results similar to those portrayed.

Actual performance will vary from that of investing in the Model because it may not be fully invested at all times.

Historical data provided by iQuant.pro.

The Best of the Best Investment Model is presented by GBJ S Wealth. GBJS Wealth is the educational brand name of GBJ Scott Financial, Inc.

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