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Stock Portfolio System FAQ

股票投资组合系统常见问题

Definitions

Low Tide Upside – This is the price of when the sentiment shifts and the "tide goes down". We see what the company is actually worth. This is the most basic way of calculating price and is applied to all companies.

High Tide Upside – This is my best attempt to replicate how the Market-Makers estimate stock prices. There are no official or formal ways to do this, and THIS VALUE DOES NOT REPRESENT FAIR VALUE. This often comes with high sentiment, especially during upcycles. During downcycles this can actually be below Low Tide! This takes into account things like sentiment, "brand value" or loose words like "moat". The more often these words are used during what should be analytical valuations, generally it means sentiment is high. We quantify everything, to 2 decimals.

During a correction, these are the first things to disappear. Companies that have a huge % of their market cap in High Tide historically go down the hardest. A good example of the above is Nike (NKE).

NKE stock drawdown showing sentiment collapse
Figure 1: NKE – High sentiment premium evaporates during correction

Sentiment Indicator – This is a custom oscillating indicator that I've made. It's good at capturing bottoms (don't use it for finding tops). It works best for stocks with ~5+ years of data. Hence my universe of long stocks is stocks with longer history. The value will typically range from 0–100, with 0 being rock bottom. It's an exponential indicator, meaning that the path from 0 to 20 can be 50%–100%, and from 20 to 40 another 50%–100%, etc. Values can occasionally go under 0, but only during extreme market conditions (super buy zones).

Putting it all together

When all 3 align:

1) Low Tide Upside > 40%
2) High Tide Upside > 40%
3) Sentiment Indicator < 10

We have typically found the bottom of a stock's drawdown and can invest. And a green tree will appear.

Green Tree Signal - Buy Confirmation
Figure 2: Green Tree Signal – All conditions met, buy confirmed

During extreme market conditions (e.g. China / US tech stocks in 2022–2023), or during the Great Financial Crisis, both upsides can reach 100%+, even 200%+ with negative Indicator Values. At these rare points in history, we recommend selling everything you own and buy stocks.

This is an automated recommendation engine. If you follow these exact rules, you expect to generate the portfolio historical return (which does not include dividends — for example, buying Oil and Bank stocks in 2020 yielding 8–12%, as well as selling covered calls to close positions). In the real world, and if you time the recommendations differently (e.g. you have extra info or just time it better), you can easily outperform the recommendations. The portfolio generates ~5–10% above historical portfolio shown. The historical portfolio only shows price change. Hence the years we invest in tech only, the returns appear higher than when we invest in dividend stocks.
Charts

When looking at charts we recommend Log Scale view. Looking at something that compounds exponentially (e.g. stocks) through a linear scale is nonsense as all old data gets squeezed out due to current "higher" prices.

Linear scale chart - misleading
Figure 3: Linear Scale – Old data gets compressed, misleading

Looks more reasonable in this form:

Log scale chart - accurate compounding
Figure 4: Log Scale – Accurate representation of compounding

Log scale captures the time it takes for anything to double (or 10x). So the gap between 1 to 10 is the same as the gap between 10 to 100 and the same as 100 to 1000 etc.… Whereas in a regular chart the large numbers today make the earlier actions of the stock irrelevant (which they clearly are not!)

200 SMA (Single moving average) - Overall, the 200 SMA is a robust long-term trend filter (e.g., stocks/indices above it outperform significantly risk-adjusted), but simple crossover timing signals are noisy and low-precision without enhancements. Backtests emphasize regime filters and risk management over relying on raw crosses.

RSI 14 - Relative Strength Index (RSI) with a standard 14-period setting (RSI(14)) is a momentum oscillator that identifies overbought conditions (typically above 70, suggesting potential pullbacks or reversals) and oversold conditions (below 30, suggesting potential bounces or reversals). It works best in range-bound markets for mean-reversion trades but often generates false signals in strong trending markets—where RSI can remain overbought in uptrends or oversold in downtrends for extended periods, leading to premature entries/exits.

Combined - Strong in sideways/ranging conditions; weak in trends (e.g., RSI can hover >70 in bull runs like 2020-2021 tech stocks). Adding filters (e.g., only buy oversold if price >200-day MA or in confirmed uptrend) boosts win rates to 65-75%+ in optimized tests.

Further Combined – Adding our high tide and low tide valuation will remove false buy signals (eg, 1999 USA tech stocks, or 1989 Japan) and protect you from false sell signals (eg, 2001 USA tech, and 1991 Japan crash, both of which lasted many more years, due to the extreme overvaluation).