Our Investment Philosophy
Updated: Nov 15, 2022
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.
We automate key portfolio management functions to optimize our KPIs.
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.
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.
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.
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 those of traditional buy-and-hold strategies.
Passive, buy-and-hold strategies are the baseline.
The conventional advice for the average investor is to employ a passive, buy-and-hold strategy. These strategies typically involve buying a market-index ETF (such as the S&P 500) and simply holding it for a long time period. However, such strategies are suboptimal because the market isn’t static, so why should an investment strategy also be static? The bear market of 2022 has been a perfect example of where a buy-and-hold approach fails.
So if passive strategies aren’t the best, then what is? We believe that portfolio management can significantly enhance returns over a comparable buy-and-hold approach. Think of buy-and-hold as the baseline. If we add portfolio management automation on top of that, there can be three possible outcomes. In a baseline scenario, we outperform buy-and-hold after fees. In a worst-case scenario, we don’t outperform buy-and-hold, but our losses are still in line with the market since we hold market-based ETFs. In a best-case scenario, we significantly outperform buy-and-hold. We achieve this through two types of tried-and-true strategies: tactical asset allocation and absolute return.
Tactical Strategies: Managing risk levels according to market conditions
Tactical asset allocation (TAA) is an investment strategy that seeks to exploit short-term market opportunities through the strategic repositioning of a portfolio's asset mix. There are many methods to implement TAA, but we are primarily focused on responsive risk management.
The idea is simple. When market conditions are poor, our tactical strategies gain exposure to an inverse ETF to profit from market declines. When conditions are uncertain, we adopt a conservative risk profile to minimize losses. Under normal market conditions, we take on a moderate, well-balanced risk profile. When conditions are ideal, we assume an aggressive risk profile to maximize gains.
Tactical strategies have typically only been available to sophisticated investors, but through automation and ETFs, we have made them available to all. We currently have a variety of tactical long-only and long-short strategies available for a low fee.
Absolute Return Strategies: Generating consistent returns regardless of the market environment
Absolute return strategies (ARS) are a bit different from more traditional approaches in that ARS aren’t focused on benchmarking performance against a specific index. Instead, the goal of ARS is to simply generate positive returns in any kind of market environment. Like TAA, there are many ways to go about ARS, but we are mainly focused on long-short exposure management.
Long-short strategies use both long and short positions to profit from market movements. Long positions profit when the market goes up, and short positions profit when the market goes down. Long and short positions offset each other, which has the added benefit of significantly reducing a strategy’s volatility, beta, and R2. When market conditions are good, we increase long exposure to maximize gains. When conditions are bad, we increase short exposure to minimize losses and, in some instances, profit from market declines.
ARS are usually run by hedge funds and have typically only been available to sophisticated investors. However, through automation, ETFs, and inverse ETFs, we have made them available to everyone for a low fee. You can learn more about our absolute return strategies here.
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 and ETFs, we are able to make strategies, that have typically only been available to sophisticated investors, available to everyone for a low fee.