8 Trading Strategies In My Pipeline To Be Built 2026+
I won the Quantiacs Q22 competition. That secured me a $1M allocation for my algorithmic system.
After winning, I moved on to building multiple trading systems for my own money.
In January 2026, I launched 4 systems live and 1 system in pilot. Those systems backtested with CAGR ranging from +23% to +74%.
But I didn’t stop there.
More ideas keep coming. New strategies I want to build on top of what’s already working in live.
Here are 8 strategies in my pipeline, why they matter, and what I need to figure out before I start building.
1. Thematic Investment Strategy
The concept: Buy and hold when a theme forms. Sell before it bursts.
Nothing complex. Just ride the wave and exit before the crash.
Imagine holding gold mining stocks in 2025. Imagine rotating into memory chip stocks in early 2026.
Why: If you pick the right theme, returns are massive. The strategy is simple. Buy the main theme stocks or ETFs. Sell at the right time. No complex signals. No advanced math. Just timing and theme selection
What I need to figure out:
- Which themes actually work
- How to filter out narrative-driven themes that don’t translate to returns
- What characteristics separate winning themes from losing ones
The challenge: Most “hot themes” are narrative-driven hype. Rare earth sounded great. Defense sounded logical. Nuclear made sense. But they are not the real hero in 2025. I need a systematic way to identify themes with real alpha, not noise.
2. Day Trade Strategy
The concept: Most of my strategies run on hourly timeframes. I want to explore 15-minute opportunities.
Why: Lower timeframes respond faster to news-driven events. Like the Iran conflict in March this year. If I can find edge at 15-minute bars, I can compound faster and deploy capital more efficiently.
The challenge: Higher frequency = higher costs. I may need 2–3x the edge just to break even after commissions and slippage. Plus, more data. More noise.
3. Long/Short Strategy
The concept: Long the strongest stocks. Short the weakest stocks. Market-neutral or beta-adjusted.
Classic hedge fund playbook.
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Why: My current systems are all long-only. Long/short gives me downside protection and reduces correlation to the broad market. If the market crashes, I’m not 100% exposed. The short leg becomes a hedge and a profit source.
The challenge: This strategy is decades old. Every quant fund runs some version of it. The question isn’t “does it work?” but “is there edge left after everyone else is trading it?”
4. Risk-Balanced Growth Strategy
The concept: Pick high quality stocks. Hold them in risk-balanced weighting.
Not equal weight. Not market-cap weight. Risk-parity weight.
Why: High quality stock have massive upside but also massive volatility. Risk-balancing lets me capture growth without overconcentrating in the most volatile names. It’s a smarter way to play growth without blowing up during drawdowns.
The challenge: Picking the high quality stocks are challenging. Risk-balancing helps in normal markets but might not save you in a crash. Also, it may be another beta strategy that I already got some.
5. Short Broad Market Strategy
The concept: if I can short the broad market profitably, and it has low correlation to my existing long strategies, it’s a hedge and an alpha source.
Why: Every long-only system bleeds during bear markets. If I can short the broad market with precision timing, I turn bear markets into profit opportunities instead of just survival mode. This is the ultimate portfolio diversifier.
The challenge: Shorting the market is statistically negative expectancy over long periods. I need precision timing or you bleed theta and opportunity cost.
Indeed, I tried to develop this strategy since day 1, but not so success for that.
6. AI Trading Bot
The concept: Use cutting-edge AI to build the trading system.
Why: Exploring how to leverage LLM to trade
The challenge: LLM is kind-of blackbox that it is not easy to understand their trading logic. And, if i tell them exact the logic i want to trade, why don’t I just code my logic?
So, I am not quite sure on this. But worth trying.
7. News-Driven Trading Strategy
The concept: News moves markets faster than any technical indicator.
If I can parse headlines, extract sentiment, and execute within seconds, I’m ahead of most of retail investors.
Why: Markets react to news before price action shows up on charts. If I can automate news parsing and execute fast, I capture the edge before technical traders even see the signal. Speed is alpha.
The challenge: The market may react differently on the news sentimental that the strategy may not be able to have consistent result.
8. Volatility-Related Strategy
The concept: Trade the volatility instead of the price movement.
Why: Guessing the price movement is difficult, but guessing the volatility is easier. And, this strategy should be low correlation to equity markets.
The challenge: Volatility is mean-reverting but spiky. You can be right on direction and still lose money on timing.
