AI Investments and Computer Trading Algorithms

Artificial intelligence is no longer a distant idea in investing. Robo-advisors, machine-learning models, quantitative funds, and algorithmic trading systems already influence how money moves through the market every day. But can AI be trusted and can it be a part of your decision tree?

But for average people, does AI have a place in your investment decisions? For everyday investors, especially those at or near retirement, the question is not whether AI is changing investing. The better question is how AI can be used thoughtfully, responsibly, and in a way that supports your long-term financial life.

Quantitative models with AI investments may dramatically improve investment performance

Please click on the AI Investment short YouTube video above.

Artificial Intelligence, AI investments, and computer automation can play an important role in investing. But the goal should not be for the sake of having the most modern trading system. The goal should be discipline, risk-aware decision making, and a process that may help investors respond to changing markets without emotional guesswork.

AI investment strategies do not guarantee better returns. AI does not remove investment risk. But when used properly, an AI investment strategy may help review market conditions, organize data, back-test ideas, and support a more consistent investment process.

Why AI Investing and Computer Automation is Desirable

There are many practical reasons an investor may want AI and computer automation involved in investment decisions.

• AI and computer automation may free up time for more important tasks.
• You may not have time to monitor your investments every day.
• You may not have the knowledge or tools to direct every investment decision yourself.
• You may be more focused on earning money than spending your life studying how to invest it.
• AI automation may help reduce some investment management costs.
• AI automation may respond more quickly when market conditions change.
• You may feel your account is not large enough to justify full-time professional wealth management attention.

Markets can react to news within seconds. Interest rates, inflation, unemployment, political events, investor sentiment, market momentum, and trading volume can all affect investment decisions.

A person may struggle to monitor all of these conditions at once. AI and computer automation can review a much larger amount of information much faster than a person could manually.

For the average investor, the main benefit is not that AI sounds exciting. The main benefit is that AI may help reduce emotional decision-making.

Many investors buy after markets have already gone up and sell after markets have already gone down. A disciplined computer-assisted process may help reduce that emotional reaction.

How to Integrate AI Into Your Investment Decisions

The first question is simple: should AI be allowed to directly and automatically determine your investment decisions? When AI learns a new thing, this new thing could dramatically and negatively affect your investment if AI is directly controlling your investment.

For many investors, this may be too much risk. Yes, AI can make fast decisions. A trained AI solution may even show a strong historical record. But do you really want an artificial intelligence system that is constantly learning new things to make important real-time investment decisions with your retirement money?

A better approach may be to use AI as a research tool. That means AI can help:

• Study market conditions
• Review large amounts of historical data
• Identify which conditions have affected stock indexes in the past
• Back-test those conditions
• Help build a steady investment algorithm
• Support a rules-based process instead of emotional decision-making

In other words, AI should not be treated as a magic investment brain that controls everything. It should be used as a tool to help determine which market conditions should matter most before making an investment decision.

AI can be a significant tool used to construct a steady, back-tested, rules-based computer algorithm for timing market transactions.

Allow AI to Determine What Market Conditions are Most Favorable

Wall Street often teaches us that we should invest for the long-term. A frequent theme they preach is that we should Buy-and-Hold and simply ride out the ups and downs of the stock market. But who benefits most for this overly simple approach: Wall Street firms, or you, the individual investor? 

Many sophisticated investors are abandoning long-term investment themes and are instead focusing on the short-term. Simply put, many successful short-term investments can provide a better long-term result.

This is where AI can be especially useful. Many short-term momentum investments can total to more significant market performance. AI can scan thousands of market conditions and help determine which conditions have historically affected certain stock indexes.

These conditions may include:

• Stock market inflows and outflows
• Interest rate movements and inflation trends
• Unemployment data and political issues
• Market momentum, volatility, and trading volume
• Investor sentiment and credit market signals
• Cross-asset movement between stocks, bonds, commodities, and currencies
• And hundreds of other conditions

A person may find it difficult to identify and understand how all of these conditions affect future market movement. AI can process these relationships faster and more consistently. AI can find relationships we may have not thought to look for.

The goal is not to predict the future perfectly. No system can do that. The goal is to study which conditions have historically aligned with stronger markets, weaker markets, or sideways markets.

Once those conditions are identified, they can be programmed into an automatic stock market algorithm. That algorithm can then help determine what indexes to buy, when to buy, when to sell, when to move to cash, and when to become more cautious.

This creates a steady algorithm making investment decisions instead of an AI engine that is constantly changing its concepts about the stock market.

Why AI Investments in Stock Market Indexes Instead of Individual Stocks

Individual stocks can have unexpected changes. A company can report surprise negative earnings. Management can change suddenly. A new competitor can appear. Accounting issues, lawsuits, or regulatory problems can hurt a stock very quickly.

One unexpected event can cause an individual stock to fall sharply the next day. Stock market indexes are different. Indexes are highly diversified and are not usually affected as dramatically by one company’s problem.

That is why AI stock market index prediction may be more practical than individual stock prediction. Indexes may offer:

• Greater diversification
• Less exposure to single-company shocks
• More reliable historical data
• More stable short-term patterns
• Deeper trading markets
• A better foundation for algorithmic investing

Typical index trades may focus on well-known stock indexes, including the S&P 500, Nasdaq, Nasdaq-100, and Russell 2000.

These indexes cover a meaningful part of the U.S. equity market. They also provide the kind of broad market data that may be useful for automated investing and AI portfolio management.

Why Use AI for Short-Term Market Predictions

Wall Street often teaches us that we should invest for the long-term. A frequent theme that Wall Street often teaches us is that we should Buy-and-Hold and simply ride out the ups and downs of the stock market. Not all of your money should be in long-term investments.

They asked a famous bank robber why he robbed banks. His simple answer was, “That is where they keep the money.” The same idea can be applied to stock market movement.

A meaningful part of market return can come from short periods of upward movement. If you add up the short-term stock market upward moves of 2 to 5 days in length, they can often represent a very important part of the market’s total return for the year.

The difficulty, of course, is knowing which days to be invested. It is easy to say, “Just invest on the up-days.” However, that perfect timing is very hard to actually accomplish, particularly without automation.

That is where AI may help. AI can review market signals such as momentum, volatility, interest rates, index strength, market breadth, investor sentiment, fund inflows and outflows, short-term trend changes, and historical patterns around similar conditions.

The bottom line is that it may be easier to predict the next few days than to predict the next full year. That does not mean short-term investing is easy. It can be wrong, and it can also be expensive if trading costs are not managed closely.

What If an AI-Developed Algorithm Gets it Wrong?

What if the AI algorithm gets it wrong sometimes? It certainly will be wrong at times. So, what.

No AI-developed algorithm can always accurately predict the next short-term trend. Markets are too complex for that. Unexpected events happen. Conditions change. Historical patterns can weaken.

The better question is not whether the algorithm is always right. The better question is what the algorithm does when it is wrong.

A disciplined algorithm should have rules for trades that are not working. It should not simply sit there and hope. It should not become emotionally attached to a position. It should not follow a buy-and-hold philosophy if the purpose of the strategy is short-term momentum.

A rules-based strategy may exit trades that are not proving profitable, move to cash when market conditions weaken, reduce exposure when risk signals appear, and follow the process instead of reacting emotionally.

The purpose is not perfection. The purpose is automatic discipline! It is important to have quick unemotional decisions and recognition that the algorithm is wrong on that particular day. No emotional attachment to the wrong prediction.

Be Careful with Traditional Buy-and-Hold Strategies

Traditional buy-and-hold investing has real strengths. It is simple, usually low cost, and can be appropriate for many investors.

But buy-and-hold also has a major limitation. It generally keeps you invested during all market conditions, including major declines.

For a younger investor, that may be acceptable. For a retiree taking withdrawals, it may create a much bigger problem. When a retiree withdraws income from a portfolio while the portfolio is falling, the account may have a harder time recovering. This is called sequence-of-returns risk.

“Invest for the long-term” can be good advice. But it should not be used as a reason to ignore changing risk conditions.

A more active AI-supported investment strategy may attempt to participate during favorable market conditions, move to the sidelines during unfavorable conditions, and use cash as a defensive position. In summary, avoid some major market declines, and follow market data instead of just hope.

This does not mean traditional buy-and-hold is wrong for everyone. It means every investor should understand the tradeoff. Traditional buy-and-hold strategies were necessary during the high trading cost of the past. Avoiding trading cost was important. But times have changed.

But Doesn’t a Higher Stock Market Return Equate to Higher Risk?

With the older buy-and-hold paradigm, higher returns are often assumed to come with higher risk. But in a more dynamic, active, AI-generated algorithmic trading strategy, the relationship may be different.

The goal is not necessarily to buy riskier investments. The goal is to avoid being fully invested during unfavorable market conditions.

If the market is declining, the strategy may move to cash or reduce exposure. You do not lose money while temporarily holding cash.

Avoiding large losses can be powerful because large losses are hard to recover from.

• A 10% loss requires about an 11% gain to recover
• A 20% loss requires about a 25% gain to recover
• A 30% loss requires about a 43% gain to recover
• A 40% loss requires about a 67% gain to recover
• A 50% loss requires about a 100% gain to recover

Short-term trading higher average returns may come not from taking higher risk, but from reducing participation in major down markets. No strategy can avoid every decline, and no AI model can guarantee higher returns.

In or nearing retirement, shouldn’t you consider having some of your nest-egg in a strategy that is actively trying to avoid stock market declines by quickly steep out of the stock market?

Doesn’t Frequent Short-Term Trading Increase Cost?

Yes, frequent short-term trading can increase costs. An short-term trading algorithm could create hundreds of trades per year, and in some active accounts it could generate 600 to 1,000 trades per year.

This is why the investment vehicle matters. The lowest cost vehicle to trade is institutional index mutual funds. Further, we should restrict our mutual fund families to only those that allow next-day exits to accommodate are frequent trading.

Yes, fees may be higher in very actively traded accounts. The real question is whether the potential historical and ongoing results justify those costs after all expenses are considered.

Give the Algorithm Permission to Trade Your SMA, Separately Managed Account

In order for an algorithmic strategy to be used in a client account, the investment manager must have permission to trade the account. This is commonly done through a Separately Managed Account, often called an SMA. Most investors with fee-based accounts are accustomed with this arrangement.

An SMA is an investment account held in your name, or in the name of your IRA or Roth IRA. The account is separate from other investors’ accounts.

In contrast, with a mutual fund, your money is pooled with many other investors. In an SMA, your account is your own account. You can typically go online and see the trades being made in your individual account.

An SMA may provide direct ownership of the investments, more transparency, the ability to see trades online, a separate account structure, more flexibility than a pooled fund, potential tax management benefits, and a clearer view of how your money is being managed.

You are not giving up ownership of your account. You are giving the manager permission to trade the account according to the agreed strategy. In this case the managing company is running the computer algorithm that is issuing the buy and sell mutual fund transactions.

Traditional Single-Directional vs. Multi-Directional Investments

Most investments are designed to make a profit only when the underlying investment goes up in value. That is a limitation many people understand and simply accept. Most people just accept that their investment strategy only makes money in one direction, when the stock market is going up.

If you own a traditional S&P 500 index fund, you generally make money when the S&P 500 goes up and lose money when the S&P 500 goes down. That is single-directional investing.

But when you are trying to capture shorter-term movement, measured in 1 to 5 day moves, the market may create opportunities in more than one direction.

Instead of only trying to make money when the market goes up, a multi-directional strategy may be designed to respond to rising markets, sideways markets, and declining markets.

This may include moving to cash during uncertain periods or using inverse index mutual funds during declining periods.

An inverse S&P 500 mutual fund is designed to move opposite to the S&P 500. For example, if the S&P 500 moves down 1% in a day, a simple inverse S&P 500 mutual fund is designed to move up approximately 1% that day.

This is not the same as shorting the market. Thus these kind of funds can be used in all accounts including retirement accounts including IRAs. Another advantage is that the investor is no longer tied only to making money when the market goes up. However, inverse funds have risk and should be used carefully.

Frequently Asked Questions About AI Investment Strategy

Question: What is an AI investment strategy?

An AI investment strategy uses artificial intelligence, computer automation, and market data to support investment decisions. AI may review historical market conditions, identify patterns, and help build a rules-based automatic investment process. We do NOT recommend AI strategies that directly control and dictate trading and investment decisions.

Question: Does AI guarantee better investment returns?

No. AI does not guarantee higher returns or protection from losses. All investing involves risk. AI may support research and discipline, but it cannot predict the future perfectly. However, it can be used to find relationships and conditions that may be predictive of future market movements. This is particularly true of short-term trends of the next few days. Thus, AI can be used to help build rules-based computer trading algorithms.

Question: What is rules-based automated investing?

Rules-based computer automated investing uses computer systems to help make or execute investment decisions based on defined rules. It may help reduce emotional decision-making and create a more consistent investment process.

Question: Why use AI with stock market indexes?

Stock market indexes are diversified across many companies and may provide more reliable data for AI analysis than individual stocks. This can make indexes more practical for algorithmic investing and investment automation. Further, institutional index mutual funds can provide much lower trading cost. This is important if implementing a short-term trading system.

Question: What happens if the algorithm is wrong?

A disciplined strategy should have rules for exiting trades, reducing exposure, or moving to cash when conditions change. The goal is not to be right every time. The goal is to manage risk when the strategy is wrong. A disciplined exit strategy is just as important than a rules-based buying strategy. Protecting your principal is more important than average gains.

Question: What is multi-directional investing?

Short answer: Multi-directional investing means using strategies that may respond to rising, falling, or sideways markets. This may include moving to cash or using simple inverse index mutual funds when appropriate.

Talk With Serenity Wealth Management

If you are retired, nearing retirement, or wondering whether an AI investment strategy fits your financial plan, Serenity Wealth Management can help you review your options.

In a consultation, we can explain how AI portfolio management works, how automated investing may be used, why stock market indexes may be used instead of individual stocks, how algorithmic investing may support discipline, and whether a multi-directional strategy may fit your situation.

There is no pressure and no obligation. Just a calm, professional conversation about your retirement and the choices in front of you.

Schedule a consultation with Serenity Wealth Management today to discuss whether an AI investment strategy is appropriate for your retirement goals, risk tolerance, and long-term financial plan.

Summary and Conclusions About AI Investments and Alternative Investing

Wall Street often teaches us that we should invest for the long-term. A frequent theme they preach is that we should Buy-and-Hold and simply ride out the ups and downs of the stock market. But who benefits most for this overly simple approach: Wall Street firms, or you, the individual investor? 

The secret to answering this question is to look at what Wall Street actually does with their own money. 

Wall Street firms actively trade stocks for their own firm’s profits. It is estimated that 75% of NYSE trades are alternative computer-generated algorithm trades. Maybe our goal should be to learn how to trade the way Wall Street firms actively trade stocks. They use complex computer models with hundreds of inputs to track the momentum of the markets. These models find and execute short-term trades.

Many people approaching retirement are concerned that they may not have enough retirement savings to provide for a successful retirement. They are also concerned that a downturn in the economy or the stock market could deplete their retirement savings. Alternative investments may provide the extra investments gains they need for successful retirement. Being non-correlated with the stock market can provide protection from stock market declines. Serenity Wealth Management plus Curtis and Irina can show you how to implement computer-generated investment algorithms.

Navigating the complexities of investing can feel overwhelming, especially for those nearing retirement. It’s natural to worry about whether your savings will last and how market fluctuations might impact your financial future. By leveraging advanced computer trading algorithms, you can explore alternative investments that may help bolster your portfolio and provide stability. Curtis, Irina, and the team at Serenity Wealth Management are here to guide you through this innovative approach, empowering you to make informed decisions for a secure retirement.

Curtis Hill, CFP, IRA and Irina Hill, CPA, IRA, provide fiduciary financial advice, investment advice, retirement planning, and life insurance. They serve in the Long Beach, CA; Lakewood, CA; Carson, CA; Bixby Hills, CA; Signal Hill, CA; and Los Angeles, CA areas. Serenity Wealth Management has extensive experience with computer-generated trading that they can share with you.

Go to the Calendley.com calendar link below to schedule an appointment. Meet with Curtis Hill or Irina Hill, the author of this web site using the link below.