The Hedge Fund Investment Strategy Retail Investors need to Steal in 2025

If you're a retail investor who thinks watching CNBC and drawing trendlines on charts will turn you into the next Jim Simons — stop reading.

Seriously. Go back to YouTube and enjoy your daily dose of "Head and Shoulders", and as I like to say, "Knees and Toes" patterns and doji candles. This post isn’t for you.

But if you're finally ready to play the game like the institutions do — if you're sick and tired of being the liquidity for someone else’s gains — then buckle up. Because I’m about to show you how we really trade at my quant hedge fund using AI, Machine Learning, and Big Data-driven strategies the average retail investor doesn’t even know exist.

Welcome to my world. I’m Nizar Assanie, a 5-time technology founder and have 2 exits under my belt. Over the course of my career, I have sold financial data analytics products and my companies to the likes of Goldman Sachs, JP Morgan, Morgan Stanley, and other bulge bracket banks including Nomura, Citigroup and UBS. And several hedge funds…. So I know how the big boys operate.

Why Most YouTube Bro Investment Strategy Examples Are Trash

I’ve seen it all — mutual fund managers flaunting 8% returns in bull markets. CNBC hosts whose track record is questionable at best, yet get national and international media coverage. Reddit bros sharing their “Sample Investment Strategy” based on vibes and memes, and YouTubers evangelizing about candlestick formations and signals that have never been proven statistically to work.

Let me be blunt: retail investing is broken because it's built on information entertainment, not information advantage.

And in 2024, the numbers were brutal. According to JP Morgan data, in 2024:

S&P 500: +25%

Average retail investor: +3.7%

Why? Because retail investors do five things consistently wrong. And institutional players like us? We do the opposite. Over the next few blogs I will outline these 5 things that retail investors get wrong.

TruthSayer’s Valuations AI© Strategy: The Real Deal

Let me walk you through our Valuations AI© strategy — one of the 3 proprietary quant trading strategies we've deployed inside TruthSayer AI since September/October 2024.

Our Valuation AI model ingests real-time data across:

Price-to-Earnings (P/E) Ratios

EV/EBITDA metrics

Analyst earnings beats/misses

Dark pool activity

Options implied volatility post earnings

Proprietary Post Earnings Announcement Drift models.

Then, we apply machine learning classifiers to isolate stocks that are undervalued and likely to surprise to the upside.

Sample Investment Strategy Breakdown (Real Trade Data):

Let’s talk actual performance. Since we posted our first public trade on September 25, 2024, this strategy has shown the following performance:

Valuations AI©, ROI %: +62.59%
S&P 500,ROI %: +9.74%
Valuations AI©, Beta: 0.60
Valuations AI© Sharpe Ratio: 2.22
Win Rate, %: 86.1%

On average, the Valuations AI strategy posted a daily expectancy of 0.09% with a Sharpe ratio of 2.2 and a Beta of just 0.60 — that’s almost market neutral, folks.

Compare that to the garbage your favorite finance influencer is peddling. Can they tell you what their Sharpe Ratio is for their strategy? Can they tell you what the positive expectancy is for their results?

Quant Investing Isn’t a Buzzword — It’s a Weapon

Let’s debunk another lie: that quant investing is only for billion-dollar firms. I had an investor tell me why do I want to sell my strategies to individual investors? Why not just raise money from wealthy investors and trade these strategies?

Our entire mission at TruthSayer AI is to democratize institutional-quality quant tools. For a modest monthly subscription fee, you can access the same signal models we run in our hedge fund portfolio. And we take EVERY SINGLE ONE of the alerts our AI generates.

Here’s what our other quant trading strategies do:

Dark Pools AI©: We look for statistical anomalies by tracking whether or not a dark pool trade is more than a 2-Sigma move above a stock’s average trading volume over the last 30 days. We then track all the transactions of that stock over the last year and see whether that transaction is in the top 5 transactions for that stock. Our AI then waits to see the price reaction of the stock. Whether it goes up or down a few hours later. We then enter the trade. Based on historical big data, our ML models track the impulse response functions and the optimal time to sell the position. Our AI also scores for company fundamentals.

An the performance of our Dark Pools AI? We have an ROI of +30.52% and a beta of 1.32.

Earnings AI©: We scan all of the stocks that are about to announce their earnings. We then track factors that we know are important that determine whether a stock goes up or down post earnings. These factors included in the decision tree model of our Earnings AI© include: it’s market cap, how many times the stock has met or exceeds analyst expectations, the valuation of the company, any dark pools before earnings, short interest in the company, and the options expected move of the stock.

Our Earnings AI has a STATISTICAL Win Rate of 80% and a positive expectancy of 0.07% per day. Keep that number in mind. It’s also outperforming the S&P 500 and since we publicly started giving out signals on this strategy, it has returned +12.90% ROI, compared to the S&P 500’s ROI of 8%. Another point of this strategy is that its beta, or the correlation of this strategy with markets is only 0.23.

And you want to know the best part? We publish our brokerage statements every month to our members. Public. Transparent. Auditable.

Short Term Investment Strategy: We Don’t Gamble, We Probability Stack

Retail investors love the idea of "short term gains." I've seen some competitor AI investing apps even tout 300%+ overnight profits on options trades!

Good luck to you with that. As I have always said, its like giving a retail investor a blow torch and then telling them to go burn down their house.

The problem is, retail investors don’t understand volatility. Or probability. Or the stochastic nature of markets.

For TruthSayer AI, short-term means 2 to 20 trading days, and within that range we:

Maintain max position size of 5% of our portfolio

Use a 3x ATR trailing stop on non-core trades

Average down ONLY on 2-3 std dev price reversion moves on core trades

The result? consistently high alpha with beta that is close to market neutral.

The Truth? Most of You Will Never Make It

Unless you change your mindset, you're done before you start.

We aren’t playing a “game” here. We are arbitraging inefficiencies in market microstructure, crowd behavior, and options pricing with cold, ruthless, machine-trained precision. I hardly even look at charts while YouTube bros show the type of charts in the header of this post.

If you want to follow a strategy that:

Has positive expectancy

Is statistically backtested

Has real capital behind it

Then stop listening to Jim Cramer and start learning what alpha actually looks like.

Ready to Stop Getting Played?

If you’re finally tired of being the last one to know, the last one to buy, and the first one to lose — TruthSayer AI is your edge.

Check out our full platform and start your free 1-week trial.

Or learn more about how our AI Hedge Fund-in-a-Box works in this press article.

Let’s change the game. For good.