Our Investment Philosophy

In investing, there is no shortage of beliefs, theories, and strategies. Although there isn’t one single right answer, some methods do tend to work better than others. At alphaAI, our investment philosophy is based on tried-and-true principles that have been proven by many to work time and time again. But the spin is that we add automation to the process.

What are our investment goals?

When it comes to investing, we have one, simple goal: to consistently deliver better risk-adjusted returns than the market.

If the market is down, we want to be down less (or even up with certain types of strategies). If the market is up, we also want to be up. The concept seems deceptively simple, but, in reality, is incredibly difficult to execute. So how do we do it? Well, it all starts by optimizing our KPIs.

What are our KPIs?

KPIs, otherwise known as key performance indicators, are a set of quantifiable measurements we use to gauge our performance. All of our KPIs are measured against the “market,” which is typically the S&P 500. Think of the S&P 500 as the gold standard. If a strategy can consistently beat the S&P 500 over the long-term, then you know you’ve got something special on your hands.

These are the top KPIs that we track:

Sharpe Ratio: The Sharpe Ratio quantifies an investment’s risk-adjusted return. We are focused on maximizing Sharpe Ratio. We prefer the Sharpe Ratio over total return because total return doesn't tell the whole story. If a strategy had a high total return but took an excessive amount of risk to get there, is it really a good strategy? We don’t think so. The ideal strategy will deliver returns better than the amount of risk involved.

Alpha: Alpha, also known as the “holy grail” of investing, quantifies an investment strategy’s ability to beat the market. You can think of it as the additional value added by an investment strategy when compared to a similar buy-and-hold approach. For that reason, we are focused on maximizing alpha. Fun fact: alpha is actually the inspiration behind our name alphaAI.

Beta: You can think of beta as the sensitivity of an investment strategy to market movements. So for example, if a strategy has a beta of 1.0 and the market moves 1%, then the strategy can be expected to also move 1%. If a strategy has a high beta, then its returns are highly dependent on the market. The big risk here is that if the market performs poorly, the strategy will also perform poorly. For this reason, we are focused on minimizing beta.

R2: You can think of R2 (pronounced r-squared) as the correlation of an investment strategy with the market. So if a strategy has an R2 of 1, it is perfectly correlated with the market. Similar to beta, if a strategy has a high R2, then its returns are highly dependent on the market. We are focused on minimizing R2 because we want to deliver returns that are uncorrelated with the market.

Volatility: A strategy’s volatility is quantified by the standard deviation of returns. In general, higher volatility levels are associated with more risk. Going back to our Sharpe Ratio example, we always prefer a strategy that returns more than the risk involved. For this reason, we are focused on minimizing volatility.

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We optimize our KPIs through risk management.

Now that we’ve defined our KPIs, how do we optimize them? This would typically be a job reserved for a portfolio manager. Through our time working as professional investors on Wall Street, we realized that portfolio management can be broken down into a few key functions. We are focused on automating these functions in order to optimize our KPIs.

Portfolio Construction: Based on your investor profile, we build a personalized portfolio that fits your goals and preferences. Your portfolio is fully customizable and can be adjusted at any time to ensure it continues to be the best fit.

‍Dynamic Portfolio Adjustments: We adjust your portfolio in response to the ebbs and flows of the market. Regardless of market conditions, our goal is to make sure your portfolio is optimized for your investment goals and preferences. Risk management and downside protection (described below) are two of the main ways we do this.

‍Risk Management: We adjust risk levels in response to market conditions. When conditions are uncertain, risk is reduced to minimize losses. In some strategies, we buy an inverse ETF to profit from market declines. When conditions are ideal, risk is increased to maximize gains.

Downside Protection: Market exposure refers to how much capital you have invested in the market. We manage market exposure to maximize returns during favorable conditions and reduce losses during periods of uncertainty.

Portfolio Diversification: We diversify our portfolios across a wide variety of sectors, industries, market-caps, and other factors. A well-diversified portfolio is more resilient and can better weather market volatility.

Asset Allocation: We allocate more capital to assets that have a higher probability to perform well and less to assets that have a higher probability to perform poorly.

By automating these key portfolio management functions, we aim to deliver better risk-adjusted returns than traditional buy-and-hold strategies.

Closing Thoughts

Hopefully, you now have a better understanding of our investment philosophy. To summarize, our main goal is to consistently deliver better risk-adjusted returns than the market and comparable buy-and-hold strategies. We do this by using portfolio management automation to optimize our KPIs. Through automation, we are able to make strategies, that have typically only been available to sophisticated investors, available to everyone for a low fee.

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