To The Moon

I would like to try to build a habit of reviewing my trades regularly, starting from this post.

Not sure how long this practice can last, but I hope to stick with it and make it a long-term habit.

For every review, I will ask myself these 5 core questions:

1.What I did right

2.What I did wrong (mistakes or practice shifts)

3.What I can improve

4.What I would like to try next

5.What I don't know (welcome feedback from AI / other traders)

Here is the thoughts for the first 9 months of the year.

In Q4 2024, I finally took action to clear out the historical "dead weight" in this account—cutting losses and selling off positions I couldn't clearly justify holding.

​I spent significant time thinking through how to properly position and utilize my different trading accounts, which turned out to be one of my best strategic moves so far. In early 2025, I clearly designated my Tiger account as a dedicated Alpha account, separating it entirely from my core, stable portfolio. This separation made my overall trading strategy much clearer and more execution-efficient.

​The Alpha strategy is performing strongly. Since January 2025, it has achieved a money-weighted return (MWR) of ~105%, outperforming QQQ with a Sharpe ratio of 1.74.

​Top Profit Contributors: Marvell Technology (MRVL), Broadcom (AVGO), Invesco QQQ, Eli Lilly (LLY), and NVIDIA (NVDA).

​Primary Drivers: The majority of gains were generated by AI/semiconductor growth leaders, complemented by broad market growth ETFs and healthcare growth stocks.

​The strategy continues to evolve, and my focus going forward is finding the right balance between risk management and capital efficiency.

Looking at my top losses, 4 out of the 5 positions, NIO ,Tiger Brokers, Chewy, Nano Dimension, were legacy holdings entered in 2021 when I first started trading US equities.

Legacy Mistakes (2021 Speculative Wave):

Buying on Hearsay: I entered speculative retail/growth names without a deep understanding of their business fundamentals, earnings drivers, or competitive moats.

Absence of Stop-Losses: I allowed unprofitable positions to bleed into massive drawdowns rather than cutting losses early and preserving capital.

Misapplied Strategy (Walmart, 2026):

Recognizing that my portfolio was heavily concentrated in high-beta AI tech stocks, I attempted to diversify into mature consumer staples with Walmart (WMT).

The Lesson: Momentum and high-growth trading tactics do not directly apply to value or slow-growth defensive stocks. While the trade resulted in a -$1,993 loss, I consider it a valuable experiment in testing my circle of competence outside tech.

Core Takeaways:

Respect Your Knowledge Boundary: Only deploy capital into assets where you thoroughly understand the catalyst and valuation drivers.

Enforce Hard Stop-Losses: Never let a tactical idea turn into a long-term involuntary holding.

Adapt Valuation Frameworks by Sector: Growth/momentum rules cannot be blindly copied onto mature, low-beta companies.

Having spent the past year establishing a solid macro framework (separating my core portfolio from the Alpha strategy), my focus must now shift toward refining micro-execution to optimize the balance between capital efficiency and downside risk.

1.Position Sizing & Concentration Management

2.Asset Selection rule

​First review down. Macro framework is set; micro-execution is next. Future posts will follow the 5-question structure. Onward!