r/algotradingcrypto

What realiable vps to you algo traders use?

I’ve been exploring how to enhance AI's logical reasoning by testing unconventional "Logic Prompts" to see if there’s a significant difference in output. Using Gemini as the core engine and Crude Oil (CL1!) K-line charts as the target, here are the results of the comparison.

最近我一直在思考如何提升 AI 的邏輯思維，測試了不同於一般的「邏輯提示詞」，看看 AI 是否有明顯的差異性。我以 Gemini 為測試目標，並以石油 K 線圖作為主要的分析標的。

https://preview.redd.it/3l2mcqcgi8xg1.jpg?width=1775&format=pjpg&auto=webp&s=4ae77231cb3ed9cb58136849ae7ee7661dbab179

1. Standard AI Analysis (The "Surface" Reporter)

一般的 AI：【分析特點：水平條列、現狀描述、兩頭堵】

• Trend Status: Describes a "high-level consolidation phase" after a major rally, with prices retracing from $115 in March to around $94.40.

趨勢現狀： 描述目前處於大漲後的「高檔震盪修正期」，價格從 3 月的 $115 回落至 $94.40 附近。

• Support/Resistance: Simply marks psychological levels: Resistance at $100-$120, Support at $85-$90.

支撐/壓力位： 簡單標註心理關卡，上方看 $100-$120，下方看 $85-$90。

• Technical Pattern: Observes shrinking volume and wicks, labeling it a "overbought correction" rather than a reversal.

技術形態： 觀察到成交量萎縮與上下影線，判定為「漲多修正」而非反轉。

• Strategy: Typical "if-then" ambiguity. Advises bullishness if $90$ holds, and bearishness if $85$ breaks.

操作策略： 典型的「如果漲就看多、如果跌就看空」，建議守穩 $90$ 看漲，跌破 $85$ 看跌。

• Core Flaw: Data stacking without prediction; lacks logical "weight distribution" or conviction.

核心缺陷： 只有資料的堆砌，沒有預判，也沒有給出邏輯上的「權重分配」。

2. Logic-Enhanced AI (The "Strategic" Commander)

有提示詞的 AI：【分析特點：時間定位、位階判斷、路徑演算法、三位一體】

• Temporal Energy Node: Moves beyond simple dates to the "Grain Rain" (Gu-Yu) phase. Defines current volatility as a transition from "moisture to tangible growth"—a wash-out period before energy erupts at "Early Summer" (Li-Xia).

時間能量點： 脫離單純日期，定位為「穀雨中氣」，定義目前的震盪是「濕氣轉化為實質生長」的洗盤期，預判能量將在「立夏」噴發。

• Game Theory (LV7 Tier): Identifies the $94.40$ dip not as retail panic, but as LV7 Arbitrageur-level "contract rollover" behavior. Capital has not exited the field.

位階博弈 (LV7)： 洞察目前 $94.40$ 的下跌並非散戶恐慌，而是 LV7 套利師級別 的「移倉換月」行為，看穿資金並未撤離。

• Trinity Resonance: Synchronizes "Price, Time, and Space." Determines the market is in a "vibration before stillness" rather than random fluctuation.

三位一體共振： 鎖定「價格、時間、空間」的交叉點，判定市場處於「靜止前的顫動」，並非隨機波動。

• Path Algorithm (Probability Forecasting):

路徑演算法 (機率預判)：

• Path A (65%): Consolidation breakout, targeting the $100$ mark by early May.

路徑 A (65%)： 蓄勢突破，5 月初直取 $100$ 大關。

• Path B (35%): Bear trap/Deep correction. Retesting $88-$90 before rising during "Lesser Grain" (Xiao-Man).

路徑 B (35%)： 誘空洗盤，回測 $88$-$90$ 後延至「小滿」再起。

• Strategic Directives: Provides clear execution signals—Volume below 250K as a trigger and $92.00 as the final line of defense. This is an actionable "Battle Manual."

核心指令： 給出明確的觀察指標（成交量 $250\text{K}$ 以下）與防線（$92.00$），這是一份可執行的「作戰手稿」。

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Would love feedback from Monero users and developers.

(Team behind MRC Global Pay)

Everyone talks about the benefits of accepting crypto payments: low fees, fast transactions, and global reach. However, I am more curious about the downsides that often go unmentioned. Every system has trade-offs, and I’d rather know them upfront.

If you’ve been using a crypto payment gateway or processor, what has been the most frustrating part for you so far? Trying to get a realistic picture before I fully commit to switching.

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Would love feedback from bot developers and algo traders. Feel free to test it and let me know how it works for you.

#cryptocurrency #solana #btc #ethereum

(We are the team behind MRC Global Pay)

Just ran a short experiment, tetsing how different regression models perform for GEM (momentum) based crypto portfolio selection during a real bear market (May-Dec 2022)

The Luna collapse (May 9), 3AC liquidation (June), and FTX collapse (November) all fall within this window, so it's *really* bear.

Setup: Hand-curated safe-haven universe (tokenized gold, EUR/USD stablecoins), and two competing approaches -- compounding vs linear for fitting the price momentum.

Findings:

• The regression model choice made almost zero difference.
• What mattered was the fitting window. Full-history fits refused to enter the market -- the strategy sat in cash for 8 months, missing oppportunities
• At a 30-day rolling window this small experiment seems to be finding a sweet spot: +6.4% return, Sharpe 1.59, max drawdown -1.39%.
• The winning config sat in cash for 6.5 months, then caught a EUR rally and a short gold rally, before going into EUR again - all in the final 7 weeks.

https://blog.nodrama.io/gem-bear-market-models/