Creating favorite opinions

  Win to lose or Lose to win I searched some data about Japan stock markets. I have thought that individual investors give their money and pro investors take them. It may be wrong. I found that every investors cannot avoid to lose their money, but pro investors may be good at limit their losses. To limit losses may result to lose to win.

  Cafe au lait: Can we separate it for Milk and Coffee? Cafe au lait(Milk Coffee), I think that we can’t separate it for Milk and Coffee. Further, I prefer Cafe au lait more than Milk or Black Coffee. I imagine about how Milk feels when Milk is mixed with Coffee. (In this article, Cafe au lait = Milk 50% : Coffee 50%.) Milk may think Milk itself is swallowed by something different things. How about Coffee? I imagine about how Coffee feels when Milk is mixed. Coffee may think Coffee itself is swallowed by something different things. Now if we want to enjoy good taste Cafe au lait, we need syrup. Syrup must be not so much amount, because when too much, Cafe au lait loses its good taste. Further more, when we are in hot weather, we need ice for Cafe au lait. This Cafe au lait is one example for the world. If someone try to separate Cafe au lait for Milk and Coffee, it will be wasteful, and the effort will be no use crying over split milk. Then syrup will be economica...

  Typhoon person I saw the Mexico and Canada stock prices went down from May 9, 2025. If this fall is not the whim of the market, this is signal for Trade war. In my experience, typhoon person is there. Typhoon person tends to have an ally nearby, attack people who keep their distance, and if enough far, there are no damage. Mexico and Canada will be damaged stronger than other far countries. 

 Correlation between features and USD/Japanese Yen(JPY) I wrote Python code for searching about correlation between features and USD/JPY. Combined_Price = (Gold × 1 + Oil × 2.5) × DGS10 DGS10 means 10-Year Treasury Constant Maturity Rate. Correlation was 0.93975.

  How to know the decisions as mistakes by one's self? How people, including me, know the decisions as mistakes by ourselves is to feel the pains from results from the mistakes. No pain, no gain. Actions/Results Successes Mistakes Decisions Increase risks Balance If decisions result as successes, people learn less than mistakes. Big and many successes will lead next bigger and more mistakes. In my experience, to fix mistakes as soon as possible results better than late. The bad actions are that to repeat and continue decisions which will be mistakes. If I find my mistakes, I will be careful for to repeat same mistakes and not to continue them. (But I sometimes do gamble, it may be my bad habit.)

 correlation-features-USA(corr=0.9645) df["Combined_Price"] = (     df["Gold"] * 10                              # 安全資産、価値保存     + (df["Copper"] - df["Zinc"]) * 0.75         # 工業金属の需給差（精錬コスト的な差？）     - (df["Wheat"] + df["Corn"]) * 2.5           # 食料インフレ圧力（消費者・企業のコスト増）     + (df["Oil"] - df["Uranium"]) * 30           # 化石燃料 vs 原子力（エネルギーのパラダイム） ) I found correlation(corr=0.9645) between combined features and DJI. This is from FRED data, so that some delays are included. https://medium.com/@takapoko182/a-personal-attempt-to-reconstruct-djia-using-commodity-prices-2015-2025-638e4375919c

  The Chinification of America vs the Americanization of China Hummm… https://www.reuters.com/world/us/trump-deflects-blame-economy-contraction-says-be-patient-2025-04-30/ I thought about the Chinification of America vs the Americanization of China. Simply, the Americanization of China seems to be more exciting. Further, I thought about double-sided transaction. If America market is bear trend, China market will be bull trend, so that there may be chances in both markets. (I don’t have enough money to do it, and I am not good at trading.) [Additional news] Military parade on Trump's birthday could include more than 6,500 troops https://www.reuters.com/world/us/military-parade-trumps-birthday-could-include-more-than-6500-troops-2025-05-02/ [Further Additional] I searched with Python code. I may be wrong about the markets. Correlation between China market and USA market becomes stronger than I expected.