diff --git a/.gitignore b/.gitignore index c49b2dd2..67efdd5d 100644 --- a/.gitignore +++ b/.gitignore @@ -218,4 +218,5 @@ __marimo__/ # Cache **/data_cache/ -/y \ No newline at end of file +/y +/tradingagents.egg-info \ No newline at end of file diff --git a/cli/main.py b/cli/main.py index adda48fc..e1898b81 100644 --- a/cli/main.py +++ b/cli/main.py @@ -498,6 +498,18 @@ def get_user_selections(): box_content += f"\n[dim]Default: {default}[/dim]" return Panel(box_content, border_style="blue", padding=(1, 2)) + # Step 0: Select language + console.print( + create_question_box( + "Step 0: Report Language", "Choose the language for the analysis report" + ) + ) + from cli.utils import select_language + selected_language = select_language() + console.print( + f"[green]Selected language:[/green] {'English' if selected_language == 'en' else '繁體中文'}" + ) + # Step 1: Ticker symbol console.print( create_question_box( @@ -576,6 +588,7 @@ def get_user_selections(): reasoning_effort = ask_openai_reasoning_effort() return { + "language": selected_language, "ticker": selected_ticker, "analysis_date": analysis_date, "analysts": selected_analysts, @@ -902,6 +915,7 @@ def run_analysis(): # Create config with selected research depth config = DEFAULT_CONFIG.copy() + config["language"] = selections.get("language", "en") config["max_debate_rounds"] = selections["research_depth"] config["max_risk_discuss_rounds"] = selections["research_depth"] config["quick_think_llm"] = selections["shallow_thinker"] diff --git a/cli/utils.py b/cli/utils.py index aa097fb5..55927489 100644 --- a/cli/utils.py +++ b/cli/utils.py @@ -326,3 +326,24 @@ def ask_gemini_thinking_config() -> str | None: ("pointer", "fg:green noinherit"), ]), ).ask() + + +def select_language() -> str: + """Select report language: English or Traditional Chinese.""" + choice = questionary.select( + "Select Report Language:", + choices=[ + questionary.Choice("English", "en"), + questionary.Choice("繁體中文 (Traditional Chinese)", "zh_TW"), + ], + instruction="\n- Use arrow keys to navigate\n- Press Enter to select", + style=questionary.Style([ + ("selected", "fg:yellow noinherit"), + ("highlighted", "fg:yellow noinherit"), + ("pointer", "fg:yellow noinherit"), + ]), + ).ask() + + if choice is None: + return "en" # Default to English + return choice diff --git a/reports/GOOG_20260310_025400/1_analysts/fundamentals.md b/reports/GOOG_20260310_025400/1_analysts/fundamentals.md new file mode 100644 index 00000000..bebd9e3f --- /dev/null +++ b/reports/GOOG_20260310_025400/1_analysts/fundamentals.md @@ -0,0 +1,106 @@ +### Alphabet Inc. (GOOG) X Comprehensive Fundamental Analysis Report +**Date of Analysis**: 2026-03-06 + +--- + +#### 1. qpP򥻭` +Alphabet Inc.]GOOG^@ypPޥYA~Ȳ[\jMBsiBݪAȡBYouTubeBHuzhAO޲~ФqC2026~3몺ȹF 36,445.8 Aݩ󷾳qAȡ]Communication Services^OA~uePHvC + +- **ղv]TTM^**G27.90 +- **wղv**G22.44 +- **ѻbȤ]P/B^**G8.77 +- **CѬվl]EPS TTM^**G10.8]w EPS 13.42^ +- **ѮާQv**G0.28% +- **Beta**G1.11]PjLʤݦXzdAIA^ + +#### 2. ]ȳӳѪR + +##### 2.1 lq]Income Statement^ +- **禬PQ**]2025~ĥ|u^G + - 禬ֳtA2025Q4 J $1138.3 Ah~PۼWC + - ~Q $359.3 A~Qvíwb 31.6% kC + - bQ|uíwb $280~$350 A{jjQOC + - EPS Pgվ EPS 򴣤ɡ]2025Q4ADiluted EPS 2.82AP2024Q42.15^C + +- **cPO**G + - oO]2025Q4^G$185.7 Aݩ򰪧JAO~/޳NvOC + - ~`OΥ|uíw$230~$320Ae禬ҰdC + - Qvh~b60%WUAu(2025Q4)$680.6 /禬AY60%C + +##### 2.2 겣tŪ]Balance Sheet^ +- **겣WPc**G + - `겣2025~ $5,952.8 A2024~ $4,502.6 jTWC + - {BuP䵥] $1,268.4 ^RAꥻuʷC + - bںíAabdzƥRAyʤv]Current Ratio^íA2025Q42.00C + +- **ѪFvqPt**G + - ѪFvqjTɡA$3,250.8(2024Q4)$4,152.6(2025Q4)AܬէQ^mPíꥻ޲zC + - `tŴɡ]$1,251.7$1,800.2^Ab줴C]tvq0.43^A]ȭICC + - uŰȤꥻX|ɡAb쵦OuAuʡC + +##### 2.3 {yq]Cash Flow Statement^ +- **g{y**G + - |ug{y$391.1~$524A2025Q4F $524AjlAꥻXC + - ̷suۥѲ{y]FCF^WL $245.5 AOVC + +- **/ꥻt**G + - jWҸꥻX]2025Q4 $278.5 ^AJAIBƤߡBXC + - Ѳ^íwACu^ʪBb$55~$155C + - wtAíwFAóvBũMWC + +- **ĸꬡ**G + - oũΦAĸAcXGꥻXWC + - {򴣤ɡA2025~{lB $307]h~P $234^Ajư]ȦwC + +#### 3. ]ȾvPct +- **BPQsh~W**AYϩyiʤUi{ʡC +- **ꥻXí**AAIBƤߡBݻPw찪JATOaC +- **ѪF^y]t+^ʡ^**AUPѪF^šC +- **tŻPbũMB{yjj**Ai]β~¤ZƥC + +#### 4. XRPQ + +| ] | p/ƾ | R | +|:---------------|:------------------------------------|:----------------------------------------------------------------------------------------------| +| /~a | $3.64 ]yTMTsY^ | ysYAiJAIɥNڥʨq̡C | +| 禬/Q | 禬~WơAbQíB | g@e`AYouTubeBݡBjMsiʯjlC | +| Q/~Q | Qv60%BQv31%AQv | ӷ~ҦꥻIJvuC | +| ]ȵc | 겣íAtŤC | {A겣tŪdAOjΨʡC | +| {y | ۥѲ{yjT | jl{ͦAꥻtmFC | +| ꥻX | ꥻJAIPs¦س] | ŦX~ԲɯŻPӼWʯC | +| ѪF^ | ^+tyB@ | ޲zhѪFvqtAQHHߡC | +| ]Ȥv | tŤ16.1%Byʤ2.0 | ]ȦwʷAܭIʨΡC | +| Ȥ | TTM PE 27.9AForward PE 22.4 | qTAȲ~Xz϶AiC | + +--- + +### Markdown]ȺKn + +| | 2025Q4 | 2025Q3 | 2025Q2 | 2025Q1 | 2024Q4 | +|:----------------------|:------------------------|:------------------------|:------------------------|:------------------------|:------------------------| +| 禬() | 1138.29 | 1023.46 | 964.28 | 902.34 | 964.69 | +| bQq() | 344.55 | 349.79 | 281.96 | 345.40 | 265.36 | +| Qv | 59.8% | 59.6% | 59.5% | 59.7% | 57.9% | +| EPS (}) | 2.82 | 2.87 | 2.31 | 2.81 | 2.15 | +| g{y() | 524.02 | 484.14 | 277.47 | 361.50 | 391.13 | +| ۥѲ{y() | 245.51 | 244.61 | 53.01 | 189.53 | 248.37 | +| ѪFvq() | 4152.65 | 3868.67 | 3629.16 | 3452.67 | 3250.84 | +| `겣() | 5952.81 | 5364.69 | 5020.53 | 4753.74 | 4502.56 | +| {εu() | 1268.43 | 984.96 | 951.48 | 953.28 | 956.57 | +| `t() | 1800.16 | 1496.02 | 1391.37 | 1301.07 | 1251.72 | +| ꥻX() | -278.51 | -239.53 | -224.46 | -171.97 | -142.76 | +| Ѳ^() | -54.99 | -115.04 | -136.38 | -150.68 | -155.51 | +| Cѱb (Book Value) | 34.35 | X | X | X | X | +| ѮާQv | 0.28% | X | X | X | X | +| tvq | 16.13% | X | X | X | X | + +--- + +### ֤ߵ׻Pij +- Alphabet gíB{yRKB겣tŪdAAIɥNꥻJjTɦOۥѲ{yVC +- էQP禬íVWBѪF^FTAȦXzAsb]ȭIC +- 겣cOuAܶ^ʷΡAB~ȨƪuʯAOuЪC + +--- + +pݰwȩεuuiʶi@BRAЧiC \ No newline at end of file diff --git a/reports/GOOG_20260310_025400/1_analysts/market.md b/reports/GOOG_20260310_025400/1_analysts/market.md new file mode 100644 index 00000000..ef153635 --- /dev/null +++ b/reports/GOOG_20260310_025400/1_analysts/market.md @@ -0,0 +1,54 @@ +### Rпܲz +F GOOG bثeҤU̧㪺޳NRAܤFUC 8 ӫСAû䤬ɧ@ΡG + +1. **close_50_sma]50SMA^**GͶաAUP_{qjPͶաAAX줤q伵OC +2. **close_200_sma]200SMA^**GuͶհѦҡAUP_O_Bj/jC +3. **close_10_ema]10EMA^**GuuʯiʡAϬMʦVC +4. **macd]MACDDu^**GʯPͶT{AiqܰʡC +5. **macdh]MACDWϡ^**GP_ʯܤƧֺCAרbiʩj/ĮɥiıưʯC +6. **rsi]RSI^**GTOWR/W檬AAlܰʯi෥ݭȡC +7. **boll_ub]LWy^**GXiʩʻPOѦҡAĵܹLά}iC +8. **boll_lb]LUy^**GΩ󰻴uuLP߰LױΡC + +oզXл\uuͶաvBuuuʯvBuL/LNP_vBu}PĴĵܡvBLlC + +--- + +## hŵcP޳NӽoR + +### 1. Ͷա]SMA^ +- **50SMA { 320.2AƤwBU**Gtܦ۰Ԧ^whWɰʯAhѺK/U50SMACثeHzC +- **200SMA { 253.6AOíBwɥBC{**GhcMsbA|LjHAȵuΪiqץC + +### 2. uuʯ]10EMA^ +- **10EMAG305.3AsUƩ**AثeLKƦܧCEMAAuuŤODAثes^ɹL{C + +### 3. ʯPiʵc]MACD/macdh/RSI^ +- **MACD ̷s -5.60 B@VU**Gʯu@CA^}sbYʯWjC +- **MACD W -0.93As򬰭tͽw**GtȬWATפwѳ̤j -4.35]2/17^vBzANŤʯvBhAuwv{HC +- **RSI ثe 34.23**]C󤤭ȡ^B@qC϶A2뤤@תW <31A^ɦLܱjհϡAhũԿ|ơC + +### 4. iʻPOa]LaWUy^ +- **LWyG323.4ALUyG295.1A{ 300.91 aUyB**]ƦܦhIJ/{ɤUy^AܵujBiTīᦳHzo|C +- JUyquLש߰vĵAݱK[LX{wY^ɩεuuϼuC + +### Ͷ`PӽoPŪ +- **u]200 SMA^AݤjץC** +- **/uu]50 SMAB10 EMABMACD^zAʯtwC** +- **RSI C϶rޡAjPϼu]YC** +- **LUyhե}A޳NWHɥiX{uuhŰfΤjTϼuAרYaqHAY^ɥiC** + +--- + +## hűһPij + +- **ŤuթvBzAuui@Bj^ICAϼuvCC** +- **ާ@W[ 10EMA O_íW]ps򦬽L^305W^A MACD WॿBRSI ^ɦ40-50 MhTA_hijOuεݩT^HC** +- **Yuu^}LUyBaqRSI<30AiդpmuAuY]lvN~CuhݩTϧTAi[ܡC** + +--- + +### Xij +ثe GOOG ޳NcšA϶vBX{ܶ^{HBALTϧTAwiJ[ϼuemqCijOuѡA[TX{C + +**pASwInBާ@gλݷft򥻭wP]p]/~^AwɥRAUi@BqǶiXI** \ No newline at end of file diff --git a/reports/GOOG_20260310_025400/1_analysts/news.md b/reports/GOOG_20260310_025400/1_analysts/news.md new file mode 100644 index 00000000..8a64c418 --- /dev/null +++ b/reports/GOOG_20260310_025400/1_analysts/news.md @@ -0,0 +1,41 @@ +bLh@P]2026-02-28 2026-03-06^AwGOOG]Google/Alphabet^SwsDATƥέjiCMӡAqy[g٩MʺAӬݡAh|ުѩM^򲣥ͼvTnͶթMsDG + +## y[gٻPͶդR + +### 1. ʺAPyV +- SGOOGtsDέjAܸӤqBíALoFB]κʺޭIC +- yyʥDnEJ[KfζDzΪѲ겣tmCìҥҥqi@B`J[KAܥDyľcƦr겣צbɡAQީMзs~ȡC + +### 2. ygټƾڻPѥ +- ̷sN~iQŪѥQhAN~i{ʡAOM~QíwC +- ~]psyMޡ^]Ww]ҡGInterace, Mohawk Industries^A{~򥻭^šAU󴣮HHߡC + +### 3. FPʺ +- ̷s׻EJT|Twʡ]"Tariff Roller Coaster"^AMYMFbIA{qhƸTyުѪlޤOASOOުO]`PˡC + +### 4. H欰 +- ָ`Hhݦnhӻ]]tުѡ^AiAyVjޥ~AQnGOOGȡC +- HʶR]Culpרҡ^ѥdҪTAܥHߥb_C + +### 5. LjtsD] +- bLh@gA䤣Tw Google/Alphabet tsDάFIAܾҧQBjުѬ۹wC + +--- + +## 䥫ʺAPsDz + +| Iƥ/Ͷ | vT{ | p | Ƶ | +|------------------------------------|------------|------------|-----------------------------------------------------------| +| GOOGLjsD | íw | | qLoQšA~ȤάFí | +| N~ƾڧQh | n | | UjƮOPH | +| NYSE`ѥ[K | n | | 伵ުѻPзs겣 | +| ު | | | ɬުOȪŶAE^y | +| |άFTw | | C- | uΦvTATVíw | +| Dn~~]Ρ]DGOOG^ | n | | ϬM~Pj^Vn | +| HW/H߫_ | | | W[HH | + +--- + +WAثeGOOGΨ䲣~í򥻭P[QhvTAʥFI]Ajުѧ@íw겣lޤOCYLtIJoAi~[ᥫoiAɦVíC + +pݮھڨL޳NB򥻭Υ~צ]վ㵲סAii@BRC \ No newline at end of file diff --git a/reports/GOOG_20260310_025400/1_analysts/sentiment.md b/reports/GOOG_20260310_025400/1_analysts/sentiment.md new file mode 100644 index 00000000..7f8eabf5 --- /dev/null +++ b/reports/GOOG_20260310_025400/1_analysts/sentiment.md @@ -0,0 +1,24 @@ +å˯GOOG]GoogleqAlphabet Inc.^2026~2282026~36餧sDΪC魫jQ׬C + +## RP + +### 1. sDh +- gGOOGDysDεoAܤqLjƥBiΦMA`׳B`AǡC + +### 2. Cֽ +- ȵL˯Wzɶd򤺪CQ׼IC +- oq`NۥHAzoέtQ׼AHjTiʡC + +### 3. +- CPTFANGOOGܤƴݭȰCAΤqDXjC +- qγ\B~íwqAHɦV[桨ӫDEPRC + +#### ξ[ +| | gI | bNq | +|:-------------|:-----------------------------------------------------|:-------------------------------| +| sD | LjsDƥ | qB祭íALsQ/Qh | +| CQ | Lֽ׼I | {q`A | +| | H/[ | HhĨ[A | + +## +GOOGפηsDn׸CA㭷IΧQnAHiܫʺAAĨ@[浦ARݤqӰ]β~sʺAaӷsͶܤơC \ No newline at end of file diff --git a/reports/GOOG_20260310_025400/2_research/bull.md b/reports/GOOG_20260310_025400/2_research/bull.md new file mode 100644 index 00000000..e69de29b diff --git a/results/GOOG/2026-03-06/reports/final_trade_decision.md b/results/GOOG/2026-03-06/reports/final_trade_decision.md new file mode 100644 index 00000000..430b0f81 --- /dev/null +++ b/results/GOOG/2026-03-06/reports/final_trade_decision.md @@ -0,0 +1,97 @@ +非常感謝三位分析師提出明確、深入且強而有力的論據。作為投資組合經理與辯論協調者，我將針對Google (GOOG) 的交易決策，採取審慎與權衡利弊的立場——依據多空雙方和中立觀點所提供之邏輯與證據，做出直接且具有執行力的建議。 + +--- + +### 一、**關鍵論證摘要**： + +#### 1. **激進型分析師主張（買入）：** +- **左側機會強調**：在多項技術指標極度低迷之際，市場情緒冰點正是高勝率的超額報酬區。過度等待等於主動讓出利差。 +- **基本面堅強**：全球領先的現金流、AI與雲端長足投入，多元業務護城河構築不可摧之核心價值。 +- **機會成本高昂**：歷史數據證明，未於谷底預先布局，轉強時已被提前資金抬升，反彈收益大幅縮水。 +- **量價結構與大戶行為**：技術面雖尚未明顯轉折，但MACD負值收斂、大量低吸初現，應積極提前配置。 + +#### 2. **保守型分析師主張（賣出/觀望）：** +- **技術面未洗清**：死叉排列明確、量能衰退、無明顯止穩與回補訊號。失敗抄底反成“最後一波出清盤”。 +- **極端慎防黑天鵝**：消息真空時實為所有突發大利空具最大殺傷力。嚴格控倉乃長期資產安全的唯一保證。 +- **成長放緩與估值疑慮**：FAANG溢價減弱、短線資金主題明顯不在GOOG，未來一段仍陷橫盤或下跌泥沼。 +- **強調時間/機會成本**：過往死多在盤整期套牢，錯過其他主題性行情，賭底部得不償失。 + +#### 3. **中立型分析師主張（分批持有/可調整佈局）：** +- **分批布局重於極端押注**：左側小量預佈局，可攤低成本，又不致於單一價位全數套牢。 +- **進可攻退可守**：技術面如進一步溢價放量、RSI修復、量能明顯回補再加碼——兩段驅動。 +- **20%倉控+嚴格資金管理**：主動配置、嚴守風控，每步均設停損與檢驗，不屬於消極觀望，也非冒進躁進。 +- **聚焦基本面、技術面動態配合**：歷史證明平衡取捨能降低波動、同時卡位超額報酬。 + +--- + +### 二、**綜合理由與對辯**： + +1. **基本面**：三方均認同GOOG的長期結構優勢。任何非系統性因素導致的短線修正，都難動搖其現金流、營收成長與多元競爭力。因此，長期下檔風險有限，並非易出現根本性崩潰。 + - 引用多方：「強勁雙位數營收增長、自由現金流全球頂尖。」 + +2. **技術面**：目前明確偏空，尚無止穩大訊號，左側進場雖博取極佳價差，但尚未完全洗清恐慌盤，冒進抄底會面對被動套牢與資金效率損耗風險。 + - 引用空方：「MACD主線負、量價結構虛弱，歷史證明此時進場易被再殺。」 + +3. **機會成本/風險平衡**：單一壓注容易大幅承擔系統/突發風險；但若空倉觀望，反彈時難以迅速補獲低位紅利。最佳策略為動態跟蹤，分批攤低，見明顯轉強信號再逐步擴大倉位。 + - 引用中立方：「模糊入場、清晰控倉、動態加倉，是系統性提升長期勝率的關鍵。」 + +4. **交易心理與過往經驗**： + - 單純“死多”或“死空”均可能拖累資金週轉。紀律化分批、與市場動能順勢調整持有部位為降低錯判的關鍵教訓。 + - 引用自省：「過度自信基本面與單點豪賭都曾造成長期資金效率損失；動態策略效果最佳。」 + +--- + +### 三、**明確執行建議（最可行策略）：** + +#### **結論：** +**選擇“持有，動態分批進場”，嚴格控倉，暫不All in，亦不盲目賣出。** + +---- + +#### **實際操作流程（建議可直接採行）：** + +1. **嚴禁追高與過度加碼，持有不賣** + - 有原始持倉者維穩，不切割加碼，也不因負面市場情緒盲目賣出。 + - 如帳面有豐厚利潤、風險承受度差者，可減碼10-20%適度鎖利，保護部分盈利。 + +2. **設立三段式分批買入機制：** + - 預計新一輪投入資金分三份，僅在技術面出現關鍵訊號時分次買進。 + - **第一批**：MACD柱狀收斂且RSI<35，大單低吸顯現，進入第一筆（約三分之一）。 + - **第二批**：若再創新低且放量下殺，RSI更接近超賣（30上下），進行第二筆。 + - **第三批**：日K站回20日均線、MACD正轉、量價配合時，將剩餘資金進場。 + +3. **整體GOOG單一持倉比例不超20%，慎防產業/新聞型突發。** + +4. **嚴格執行移動止損與動態風險監控：** + - 如見公司本質性惡化（營收大幅衰退、AI主題出現“市占流失”黑天鵝），在任何技術型態下皆主動減碼。 + - 若市場動能明顯提升（放量突破或主題全市場回暖），可有條件加大配置。 + +5. **主動設技術/訊息監控提醒，避免錯過第一波底部反彈。** + - 每日盤後檢查關鍵技術點、產業新聞動態，重大催化或板塊資金回流及時響應。 + +--- + +### 四、**總結與經驗反思：** + +- **錯誤一：過度基本面信仰，忽略短線技術循環，易被長期套牢。** +- **錯誤二：技術極端追漲殺跌，錯失價值低點進場時機。** +- **優化行為：堅守分批進場和資金控管，不“水龍頭思維”、動態調整，聚焦紀律和系統判斷，兼顧收益與資本安全。** + +--- + +### **最終建議（明確）**： + +> **持有GOOG，慎防下行，僅於技術面關鍵訊號分批布局，不追價、不恐慌賣出。保持現有持倉，擬增資者以三段確認、動態加碼。單一權重不超20%，嚴格移動停損與新聞監控，優先考慮安全與靈活兼顧，拒絕兩端押寶。** + +### **可執行SOP（圖表化）：** +- **現持有**：繼續持有，設停利/停損線。 +- **準備加碼**：三分法：
+ - 訊號一：MACD/RSI雙重極端＋大單低吸→買第一筆
+ - 訊號二：技術再破底、放量超賣→買第二筆
+ - 訊號三：技術全面反轉、主題回暖→買第三筆 +- **倉控**：不超20% +- **監控**：每日複查技術+產業新聞，見黑天鵝或主題破壞即減碼 + +--- + +**此策略吸取多空與過往經驗教訓，動態管理，既可降低極端風險，又最大化低位布局與反彈機會。** \ No newline at end of file diff --git a/results/GOOG/2026-03-06/reports/fundamentals_report.md b/results/GOOG/2026-03-06/reports/fundamentals_report.md new file mode 100644 index 00000000..f1c011b2 --- /dev/null +++ b/results/GOOG/2026-03-06/reports/fundamentals_report.md @@ -0,0 +1,106 @@ +### Alphabet Inc. (GOOG) — Comprehensive Fundamental Analysis Report +**Date of Analysis**: 2026-03-06 + +--- + +#### 1. 公司概況與整體基本面總覽 +Alphabet Inc.（GOOG）作為全球互聯網與科技巨頭，其業務涵蓋搜尋、廣告、雲端服務、YouTube、人工智慧等多元領域，是科技產業的指標公司。2026年3月的市值達約 36,445.8 億美元，屬於溝通服務（Communication Services）板塊，產業為「網路內容與信息」。 + +- **市盈率（TTM）**：27.90 +- **預期市盈率**：22.44 +- **股價淨值比（P/B）**：8.77 +- **每股盈餘（EPS TTM）**：10.8（預期 EPS 13.42） +- **股息殖利率**：0.28% +- **Beta**：1.11（與大盤相關性中偏高但仍屬合理範圍，風險適中） + +#### 2. 近期財務報表細部解析 + +##### 2.1 損益表（Income Statement） +- **營收與利潤**（2025年第四季）： + - 營收快速成長，2025Q4 收入 $1138.3 億美元，較去年同期顯著增長。 + - 營業利潤 $359.3 億，營業利潤率穩定維持在 31.6% 左右。 + - 淨利潤近四季穩定在 $280~$350 億之間，顯現強大獲利能力。 + - EPS 與經調整 EPS 持續提升（2025Q4，Diluted EPS 2.82，同期2024Q4為2.15）。 + +- **成本結構與費用**： + - 研發費（2025Q4）：$185.7 億，屬於持續高投入，保持產品/技術競爭力。 + - 營業總費用四季穩定於$230~$320億，占營收比例健康。 + - 毛利率多年維持在60%上下，本季(2025Q4)為$680.6 億/營收，即約60%。 + +##### 2.2 資產負債表（Balance Sheet） +- **資產增長與結構**： + - 總資產於2025年底為 $5,952.8 億，較2024年底的 $4,502.6 億大幅增長。 + - 現金、短期投資與其等價物（約 $1,268.4 億）充足，資本彈性極高。 + - 應收帳款維持穩健，壞帳準備充足，流動比率（Current Ratio）穩健，2025Q4約2.00。 + +- **股東權益與負債**： + - 股東權益大幅提升，由$3,250.8億(2024Q4)至$4,152.6億(2025Q4)，顯示盈利貢獻與穩健的資本管理。 + - 總負債提升（由$1,251.7億至$1,800.2億），但槓桿仍低（負債權益比約0.43），財務風險低。 + - 長短期債務中部分為資本支出而舉借，槓桿策略保守，有彈性。 + +##### 2.3 現金流量表（Cash Flow Statement） +- **經營現金流**： + - 近四季經營現金流$391.1~$524億，2025Q4達 $524億，極為強勁，遠高於資本支出。 + - 最新單季自由現金流（FCF）超過 $245.5 億，保持正向。 + +- **投資/資本分配**： + - 持續大規模資本支出（2025Q4 $278.5 億），投入AI、資料中心、雲端擴產。 + - 股票回購穩定執行，每季回購金額在$55~$155億間。 + - 定期配息，維持穩定政策，並逐步溫和增長。 + +- **融資活動**： + - 偶有發債或再融資，結構合乎資本支出規劃。 + - 現金水位持續提升，2025年末現金餘額 $307億（去年同期 $234億），強化財務安全。 + +#### 3. 財務歷史與結構演變 +- **營運與獲利連續多年增長**，即使於全球景氣波動下仍能展現韌性。 +- **資本支出策略穩健**，AI、資料中心、雲端與硬體領域高投入，確保持續領先地位。 +- **股東回報雙軌（配息+回購）**，兼顧成長與股東回報平衡。 +- **負債與槓桿溫和、現金流極強大**，可因應景氣或產業黑天鵝事件。 + +#### 4. 綜合評析與討論 + +| 因素 | 狀況/數據 | 分析 | +|:---------------|:------------------------------------|:----------------------------------------------------------------------------------------------| +| 市值/產業地位 | $3.64 兆（全球TMT龍頭） | 全球龍頭，進入AI時代根本性受益者。 | +| 營收/利潤成長 | 營收年增雙位數，淨利穩步提升 | 經營護城河深，YouTube、雲端、搜尋廣告動能強勁。 | +| 毛利/營業利潤 | 毛利率60%、營利率31%，利潤率高 | 商業模式資本效率優異。 | +| 財務結構 | 資產穩健，負債比低 | 現金水平高，資產負債表健康，有能力支持大型投資或併購。 | +| 現金流 | 自由現金流持續大幅正數 | 強勁現金生成，資本配置靈活。 | +| 資本支出 | 高資本投入AI與新基礎建設 | 符合產業戰略升級與未來增長動能。 | +| 股東回報 | 回購+配息長期雙軌運作 | 管理層重視股東權益分配，有利中長期投資人信心。 | +| 財務比率 | 負債比16.1%、流動比2.0 | 財務安全性極高，抗風險性佳。 | +| 估值水準 | TTM PE 27.9，Forward PE 22.4 | 通訊服務產業合理偏中區間，成長可期。 | + +--- + +### Markdown關鍵財務摘要表 + +| 指標 | 2025Q4 | 2025Q3 | 2025Q2 | 2025Q1 | 2024Q4 | +|:----------------------|:------------------------|:------------------------|:------------------------|:------------------------|:------------------------| +| 營收(億美) | 1138.29 | 1023.46 | 964.28 | 902.34 | 964.69 | +| 淨利益(億美) | 344.55 | 349.79 | 281.96 | 345.40 | 265.36 | +| 毛利率 | 59.8% | 59.6% | 59.5% | 59.7% | 57.9% | +| EPS (稀釋) | 2.82 | 2.87 | 2.31 | 2.81 | 2.15 | +| 經營現金流(億美) | 524.02 | 484.14 | 277.47 | 361.50 | 391.13 | +| 自由現金流(億美) | 245.51 | 244.61 | 53.01 | 189.53 | 248.37 | +| 股東權益(億美) | 4152.65 | 3868.67 | 3629.16 | 3452.67 | 3250.84 | +| 總資產(億美) | 5952.81 | 5364.69 | 5020.53 | 4753.74 | 4502.56 | +| 現金及短期投資(億美) | 1268.43 | 984.96 | 951.48 | 953.28 | 956.57 | +| 總負債(億美) | 1800.16 | 1496.02 | 1391.37 | 1301.07 | 1251.72 | +| 資本支出(億美) | -278.51 | -239.53 | -224.46 | -171.97 | -142.76 | +| 股票回購(億美) | -54.99 | -115.04 | -136.38 | -150.68 | -155.51 | +| 每股帳面價值 (Book Value) | 34.35 | — | — | — | — | +| 股息殖利率 | 0.28% | — | — | — | — | +| 負債權益比 | 16.13% | — | — | — | — | + +--- + +### 核心結論與交易員建議 +- Alphabet 經營穩健、現金流充沛、資產負債表極為健康，面對AI時代資本投入大幅提升但仍保持自由現金流正向。 +- 盈利與營收持續穩中向上、股東回報政策明確，市場估值合理，不存在明顯財務風險。 +- 資產結構保守，抗跌性極佳，且業務具備長線成長動能，是優質長期成長投資標的。 + +--- + +如需針對估值或短線波動進一步分析，請告知。 \ No newline at end of file diff --git a/results/GOOG/2026-03-06/reports/investment_plan.md b/results/GOOG/2026-03-06/reports/investment_plan.md new file mode 100644 index 00000000..1133d4ac --- /dev/null +++ b/results/GOOG/2026-03-06/reports/investment_plan.md @@ -0,0 +1,75 @@ +感謝雙方清楚有力的陳述。讓我以投資組合經理、辯論協調者的視角，做一個審慎評估： + +--- + +**雙方要點摘要：** + +**看漲分析師主張：** +- **基本面極度穩健**：強勁雙位數營收增長、世界級現金流與極低負債、AI和雲端投入巨大且見成效。 +- **產業優勢明顯**：搜尋、廣告、YouTube、AI四大支柱，有多重護城河與抗週期能力。 +- **估值尚稱合理**：市盈率與全球領先企業相比並不過高。 +- **技術面反彈跡象**：雖然短線偏空，但底部型態開始形成。 +- **過去買在冷清時屢創超額收益**，主張長線持有甚至逢低加碼。 + +**看跌分析師主張：** +- **技術面惡化**：多重死叉、量價弱、缺乏任何止穩訊號，歷史證據「不宜搶進」。 +- **缺乏短期催化**：新聞和話題寂靜，流動性與市場資金輪動不利。 +- **估值其實不便宜**：增長放緩、FAANG溢價太高，一旦成長、AI未交出答卷，估值將壓縮。 +- **產業創新與競爭漸露疲態**：AI&雲端並不領先，YouTube有成長極限、資本效率下降，巨頭不再「不可戰勝」。 +- **時間與機會成本高**：套牢耗資金、過去死多頭往往錯過其他黃金股超額收益。 +- **宏觀與產業監管風險隨時爆雷**，不宜因公司過往榮光而忽視即將到來的階段性風險。 + +--- + +**最有說服力證據（我認為）：** + +空方**對短期技術面趨勢和機會成本的分析**切近交易實務，過去大牛股（Meta/AMZN/GOOG）在無明顯止穩/利多時長時間橫盤甚至下跌，是事實，也是很多人慘痛學到的教訓——錯過動能更強的板塊輪動、浪費資金效率。 + +多方則**對GOOG基本面、現金流、產業長期價值的陳述無懈可擊**——這家公司確實難以出現根本性衰退，且歷來於「冷靜無聲」的底部區域是最好進場點，有充分歷史數據支持。 + +--- + +**我的明確立場與建議：** + +**選擇：持有，謹慎分批佈局，暫不主張激進「買入」但堅決反對恐慌出清。** + +**理由：** +- GOOG的基本面極為扎實，長線確實具投資價值，但**當下技術面與市場情緒的惡化並未緩解，短線下行風險與時間成本真實存在**，如同空方所警示，這段空窗期可能持續數月，特別在資金主題快速輪動的環境下，過早All in未必劃算。 +- **不進場會錯失未來底部，All in又難忍時間熬煉**。但分批入場、等待明確止穩訊號（如MACD正轉，RSI脫離超賣、大單進場等），可以兼顧安全邊際與潛在超額報酬。 +- 如果過度迴避，只等短線全轉強才追進，往往會踏空偉大公司的絕佳買點（這也是我過去反思後的重要領悟）。 + +--- + +**交易員投資計劃（可實際執行）：** + +1. **立刻停止追價和加碼，但也勿因恐慌砍倉。** + - 已有部位者：維持基本持倉，不追高、不急於補倉。 + - 有大幅利潤、想鎖定績效者可減碼一成獲利。 + +2. **設定分批買入計劃，預留現金等候超賣訊號。** + - 例：將預計投入GOOG的資金拆成3份，小量分批布局。 + - 第一步：等MACD柱狀體明顯收斂、RSI進入超賣（<35）且伴隨大單低吸時，買入第一筆（約30%）。 + - 第二筆：若再有下殺（如布林帶下軌放量跌破、RSI接近30），再補30%。 + - 第三筆：待技術面正式反轉（日K站回20日均線、動能明顯增強），補最後30%。 + +3. **若短期市場大幅反彈且量價齊揚（出現轉強訊號）再行大倉位加碼。** + - 反之如遇大盤爆發流動性風險，GOOG快速回測去年主要支撐區，可選擇加大倉位，抓住本質型價值坑。 + +4. **嚴守止損與資金管理原則。** + - 單一個股最大持倉不超過總投資組合20%。持有過程嚴密觀察技術面與宏觀風險——如AI主題爆出嚴重負面、反壟斷意外進展，立即評估調整。 + +5. **嚴格自律避免情緒影響。** + - 若出現技術弱勢但基本面急劇惡化（廣告大幅失速、AI/雲端嚴重落後），考慮即時出場。反之若估值進一步低估、基本面無虞，正是「逢恐慌布局」時刻。 + +--- + +**借鏡過去錯誤：** +- 曾因只信基本面、不理技術面，結果長期被套費時費力；也因只看技術不敢抄底，最後錯過好公司便宜區間。 +- 這次採動態審慎追蹤，堅守分批、數據和紀律，加強止損和資金管理，不「死多」也不「死空」——專注於**結構性價值和進場訊號的動態配合**。 + +--- + +**總結：** +GOOG仍值得長線青睞，但現下環境技術面偏弱，建議「分批、耐心、等訊號」，千萬勿因莊股無聲而麻痺，也不必因短痛就空頭死抱。耐心等底部訊號，逐步建倉，才是最優策略。 + +如需進一步細談板塊主題輪動、產業催化的即時跟蹤，建議設好技術面/新聞監測提醒，把握第一轉強契機——讓自己的選擇比市場情緒更早、更穩、更有紀律。 \ No newline at end of file diff --git a/results/GOOG/2026-03-06/reports/market_report.md b/results/GOOG/2026-03-06/reports/market_report.md new file mode 100644 index 00000000..05e99cd4 --- /dev/null +++ b/results/GOOG/2026-03-06/reports/market_report.md @@ -0,0 +1,54 @@ +### 分析指標選擇理由 +為了給 GOOG 在目前市場情境下最完整的技術面分析，選擇了下列 8 個指標，並說明其互補作用： + +1. **close_50_sma（50期SMA）**：中期趨勢，能協助判斷現階段市場的大致趨勢，適合抓中段支撐壓力。 +2. **close_200_sma（200期SMA）**：長線趨勢參考，能幫助判斷是否處於大牛市/大熊市。 +3. **close_10_ema（10期EMA）**：捕捉短線動能波動，反映近期價格動向。 +4. **macd（MACD主線）**：動能與趨勢轉折確認，抓波段變動。 +5. **macdh（MACD柱狀圖）**：判斷動能變化快慢，尤其在波動放大/收斂時可視覺化動能轉折。 +6. **rsi（RSI）**：明確辨別超買/超賣狀態，追蹤動能可能極端值。 +7. **boll_ub（布林上軌）**：結合波動性與壓力參考，警示過熱或突破可能。 +8. **boll_lb（布林下軌）**：用於偵測短線撐盤與拋售過度情形。 + +這組合覆蓋「中長線趨勢」、「短線動能」、「過熱/過冷判斷」、「突破與收斂提早警示」且無冗餘。 + +--- + +## 近期市場多空結構與技術細緻分析 + +### 1. 中長期趨勢（SMA） +- **50日SMA 現值 320.2，近期數日緩步下滑**：暗示自高位拉回後已失去上升動能，價格多天緊貼/下穿50日SMA。反應目前市場信心轉弱。 +- **200日SMA 現值 253.6，保持穩步緩升且遠低於現價**：長多結構仍然存在，尚無大型反轉跡象，僅短期或波段修正。 + +### 2. 短線動能（10日EMA） +- **10日EMA：305.3，連續下滑明顯**，目前收盤價緊貼甚至低於EMA，短線空方力道明顯，推測目前為連續回檔過程。 + +### 3. 動能與波動結構（MACD/macdh/RSI） +- **MACD 最新值 -5.60 且一路向下**：動能線一路走低，跌破零軸後空頭動能增強。 +- **MACD 柱狀圖 -0.93，連續為負但收斂趨緩**：負值柱持續，但幅度已由最大值 -4.35（2/17）逐步減弱，代表空方動能逐步消退，有「賣壓減緩」現象。 +- **RSI 目前值 34.23**（低於中值）且維持一段偏低區間，2月中一度近超賣 <31，近期略回升但無明顯反轉至強勢區，說明多空拉鋸但賣壓尚未完全消化。 + +### 4. 波動與壓力帶（布林帶上下軌） +- **布林上軌：323.4，布林下軌：295.1，現價 300.91 靠近下軌運行**（甚至多次觸及/臨界下軌），顯示短期賣壓大、波幅收斂後有隨時爆發機會。 +- 遇到下軌通報「過度拋售」警號，需密切觀察有無出現針對空頭回補或短線反彈。 + +### 趨勢總結與細緻判讀 +- **長線（200 SMA）仍健全，屬牛市大修正。** +- **中/短線（50 SMA、10 EMA、MACD）轉弱明顯，動能負面但賣壓正減緩。** +- **RSI 長期偏低區間徘徊，未見強烈反轉但有反彈苗頭。** +- **布林下軌多次測試未破，技術上隨時可能出現短線多空逆轉或大幅反彈，尤其若有帶量收長紅信號，空頭回補可期。** + +--- + +## 多空情境與交易策略建議 + +- **空方優勢明顯但賣壓逐步減弱，短線進一步大跌風險降低，反彈條件逐漸醞釀。** +- **操作上觀察 10EMA 是否止穩轉上（如連續收盤站回305之上），或 MACD 柱狀圖轉正、RSI 回升至40-50 尋找多方測底訊號，否則建議持續保守或等待明確止跌信號。** +- **若短線跌破布林下軌且帶量殺至RSI<30，可嘗試小部位搶短，「嚴設停損」防意外急殺。中線則待明確底部反攻訊號再進行加倉。** + +--- + +### 綜合建議 +目前 GOOG 技術結構偏空，但底部區間逐步出現抗跌現象、賣壓減輕，雖無明確反攻訊號，但已進入觀察反彈的前置階段。建議保守持股，觀察關鍵轉折訊號出現。 + +**如你有特定風險偏好、操作週期或需搭配基本面預判（如財報/產業消息等），歡迎補充，有助進一步制訂精準進出策略！** \ No newline at end of file diff --git a/results/GOOG/2026-03-06/reports/news_report.md b/results/GOOG/2026-03-06/reports/news_report.md new file mode 100644 index 00000000..96884e80 --- /dev/null +++ b/results/GOOG/2026-03-06/reports/news_report.md @@ -0,0 +1,41 @@ +在過去一周（2026-02-28 至 2026-03-06），針對GOOG（Google/Alphabet）的特定新聞，未找到明確事件或重大公告。然而，從全球宏觀經濟和市場動態來看，仍有多項會對科技股和整體交易氛圍產生影響的重要趨勢和新聞： + +## 全球宏觀經濟與交易趨勢分析 + +### 1. 市場動態與資金流向 +- 近期沒有關於GOOG的負面新聞或重大衝擊，顯示該公司處於平穩期，無突發政策、財報或監管風險。 +- 全球資金流動主要聚焦於加密貨幣及傳統股票市場間的資產配置。紐約證交所母公司進一步深入加密市場，顯示主流金融機構對數字資產的接受度在提升，有利於科技和創新產業的估值。 + +### 2. 全球經濟數據與股市情緒 +- 美國最新就業報告被市場解讀為股市利多，就業市場仍展現韌性，支持消費和企業利潤穩定成長。 +- 部分產業（如製造和科技）財報超預期（例：Interace, Mohawk Industries），顯現企業基本面回溫，有助於提振投資人信心。 + +### 3. 政策與監管環境 +- 最新評論聚焦於貿易關稅的不確定性（"Tariff Roller Coaster"），雖然美中關係和相關政策具潛在風險，但現階段多數資訊仍支持環球科技股的吸引力，特別是中國科技板塊也迎來關注與推薦。 + +### 4. 投資人行為 +- 不少資深市場人士看好多個領域（包含科技股），資金可能再次流向大型美國科技企業，間接利好GOOG價值。 +- 內部人購買（Culp案例）為股市健康環境的正面訊號，顯示市場信心正在恢復。 + +### 5. 無重大負面新聞因素 +- 在過去一週，找不到明確針對 Google/Alphabet 的負面新聞或政策風險，顯示整體環境利於持續持有、大型科技股相對安全。 + +--- + +## 關鍵市場動態與新聞整理 + +| 重點事件/趨勢 | 影響程度 | 關聯性 | 備註 | +|------------------------------------|------------|------------|-----------------------------------------------------------| +| GOOG無重大新聞 | 穩定 | 高 | 公司無突發利空，業務及政策面平穩 | +| 美國就業數據利多 | 積極正面 | 中 | 有助於強化消費與市場信心 | +| NYSE深耕加密市場 | 積極正面 | 中 | 支撐科技股與創新資產估值 | +| 中美科技股獲推薦 | 正面 | 中 | 提升科技板塊估值空間，刺激資金回流 | +| 關稅及政策不確定性 | 較中性 | 低-中 | 長線或有影響，但近期資訊偏向穩定 | +| 主要產業企業財報佳（非GOOG直接） | 積極正面 | 間接 | 反映產業與大市氣氛向好 | +| 內部人增持/市場信心恢復 | 正面 | 間接 | 增加投資人信心 | + +--- + +綜上，目前GOOG及其產業鏈受穩健基本面與宏觀利多影響，缺乏直接風險因素，大型科技股作為穩定資產仍具吸引力。若無明顯負面觸發，可繼續觀察後市發展，策略傾向穩健持有。 + +如需根據其他技術、基本面或外匯因素調整結論，可進一步分析。 \ No newline at end of file diff --git a/results/GOOG/2026-03-06/reports/sentiment_report.md b/results/GOOG/2026-03-06/reports/sentiment_report.md new file mode 100644 index 00000000..d9ec7353 --- /dev/null +++ b/results/GOOG/2026-03-06/reports/sentiment_report.md @@ -0,0 +1,24 @@ +近期並未檢索到GOOG（Google母公司Alphabet Inc.）於2026年2月28日至2026年3月6日之間的新聞或社交媒體重大討論紀錄。 + +## 分析與見解 + +### 1. 新聞層面 +- 本週未有關於GOOG的主流新聞或發布，顯示公司近期無重大事件、公告或危機，市場關注度處於常態水準。 + +### 2. 社交媒體輿論 +- 暫無檢索到於上述時間範圍內的相關社交媒體討論熱點。 +- 這通常意味著市場情緒較為平淡，未有爆發正面或負面討論熱潮，投資人情緒未見大幅波動。 + +### 3. 公眾情緒 +- 媒體與社交訊息匱乏，代表市場對GOOG近期變化期待值偏低，或公司未主動釋出重大消息。 +- 公司或許正處於業務穩定階段，投資人傾向“觀望”而非激烈買賣。 + +#### 統整觀察 +| 項目 | 本週關鍵點 | 潛在意義 | +|:-------------|:-----------------------------------------------------|:-------------------------------| +| 新聞 | 無重大新聞事件 | 公司運營平穩，無新利空/利多 | +| 社交媒體討論 | 無明顯輿論熱點 | 市場認為公司近期維持常態 | +| 情緒 | 平淡/觀望 | 投資人多採取觀望態度 | + +## 結論 +GOOG近期社交熱度及新聞曝光度較低，未見明顯風險或利好，投資人可持續跟蹤後續動態，採取耐心觀望策略，靜待公司未來財報或產業新動態帶來新的趨勢變化。 \ No newline at end of file diff --git a/results/GOOG/2026-03-06/reports/trader_investment_plan.md b/results/GOOG/2026-03-06/reports/trader_investment_plan.md new file mode 100644 index 00000000..799bc0d5 --- /dev/null +++ b/results/GOOG/2026-03-06/reports/trader_investment_plan.md @@ -0,0 +1,19 @@ +根據你提供的分析師團隊全面評估，我進行如下整合與決策： + +### 綜合考慮 +1. **基本面**：GOOG擁有持續強勁的營收增長、多元業務線、穩健現金流和極低負債率，核心競爭力未見動搖，長線價值顯著。 +2. **技術面**：近期走勢偏弱，量價結構疲軟、主要均線空頭排列、暫無明顯止穩訊號，短線下行及時間成本風險較高。 +3. **市場情緒與機會成本**：目前全市場資金流動頻繁轉向AI、半導體等板塊，GOOG階段性缺乏明確催化劑，短線追價風險遠高於獲利潛力。 +4. **過去經驗教訓**：死守名股往往折損時間效率，但無視基本面與價值區逢低總是被動補漲也非高手作風。最佳策略來自靈活分批、嚴守紀律、不感情用事。 + +### 交易建議行動 +- **持有現有部位**。不急於出清，也不追高加碼。 +- **暫緩大倉進場，等待具體技術轉強訊號**（如MACD翻正、RSI脫離超賣區且量能配合）。 +- **採用定額分批低吸法**：計劃將預配置GOOG資金分為三等份，遇明顯超賣與資金大單承接時逐步進場；若再出現技術破底或極端恐慌，預留彈性彈性加碼。 +- **嚴格控倉**：單一個股配置不超組合20%，隨時追蹤產業重大風險（如監管、廣告業務突變、AI/雲進展明顯落後競品時需快刀斬倉）。 +- **避免情緒波動與短期雜訊主導判斷，聚焦數據與紀律。** + +### 結論 +GOOG具備中長期價值與護城河，但短線趨勢及市場資金面反覆，追高或恐慌出清皆非最佳策略。最優解為：「信基本面，但尊重技術面」、分批低吸、耐心等待確認訊號。此為過去交易經驗反思後最佳應對模型，歷經牛熊多次驗證。 + +FINAL TRANSACTION PROPOSAL: **HOLD** \ No newline at end of file diff --git a/results/NVDA/2026-03-05/reports/final_trade_decision.md b/results/NVDA/2026-03-05/reports/final_trade_decision.md new file mode 100644 index 00000000..20b141a8 --- /dev/null +++ b/results/NVDA/2026-03-05/reports/final_trade_decision.md @@ -0,0 +1,89 @@ +**Risk Management Judge & Debate Facilitator — Final Recommendation** + +--- + +### 1. Summarizing Key Arguments + +**Aggressive Analyst (Sell/Trim Now):** +- **Technical Breakdown:** Short-term signals (10-EMA rollover, MACD negative, RSI sub-50) flag near-term momentum exhaustion. +- **No Catalyst/Buzz:** Lack of news/social interest means no spark for a rebound; path of least resistance is consolidation or pullback. +- **Protect Gains, Redeploy:** By trimming a substantial chunk (1/3 to 1/2), you lock in profits and keep capital flexible for better entries—**“You make outsized alpha by not sitting through every consolidation or correction.”** +- **Stops for Remaining Position:** Use tactical stop-losses to limit risk if technicals worsen. + +**Conservative Analyst (Hold & Rebalance Slowly):** +- **Tech Signals Not Catastrophic:** Yes, technicals are ‘soft,’ but not broken—long-term trends strong (50SMA > 200SMA, fundamentals intact). +- **Risks of Overtrading:** Reacting too hard to short-term volatility risks whipsaws, tax drag, and potentially missing abrupt rebounds. +- **Core Compounder:** NVDA has world-class, resilient growth—worth holding a strong core; only trim cautiously, don’t overreact to every dip. +- **News Silence Isn’t a Sell:** Quiet periods often precede rebounds, not collapses. + +**Neutral Analyst (Moderate Trim & Tactical Risk Controls):** +- **Both Sides Valid—Find Middle Ground:** Acknowledge technical caution, but don’t swing to extremes. +- **Active, Not Hyperactive:** Modest trim (15–25%) to acknowledge warning signs, but maintain a meaningful position to capture upside when trend resumes. +- **Set Logical Stops:** Not too tight (avoid whipsaw), but protect against deeper technical breakdown. +- **Don’t Rush to Redeploy:** Wait for clearer resets or new positives before buying back or reallocating. + +--- + +### 2. Rationale for the Decision + +#### Why NOT to "Hold" fully: + +- **Short-term risk/reward no longer compelling:** Technical momentum has flipped negative, and history shows even best-in-class stocks like NVDA can correct 10–20% or churn for extended periods after runs like this, **even with fundamental strength**. +- **Aggressive analyst strong point:** “Technicals dictate trade timing … every alert in the short-to-medium timeframe is blinking red.” +- **Risk of passivity:** Experience (and debate history) show failure to act on such signals often leads to avoidable drawdowns or periods of dead money. + +#### Why NOT to "Sell Everything" or Go Ultra-Aggressive: + +- **Long-term fundamentals STILL intact:** The conservative and neutral analysts correctly argue the uptrend (50/200-day SMAs, macro backdrop) is unbroken, and previous overreactions to technical dips often result in missed upside or whipsaws. +- **Caution against over-trading:** Neutral analyst’s warning: “The technical reset periods in high-quality leaders are often followed by just-as-sharp recoveries the aggressive trader may miss.” +- **No major negative news/catalyst yet:** Silence is a risk, but it’s not confirmation of imminent collapse. + +#### Optimal Solution — Blend the Best Elements: + +- **Trim (Reduce) exposure:** Both the neutral and aggressive analysts agree on the prudence of taking partial profits given technical deterioration. +- **Do NOT abandon the long-term winner:** The conservative and neutral arguments show that maintaining a meaningful core in NVDA is wise. +- **Active risk controls:** Place stop-losses (not too tight) near recent technical pivot points ($180–$185), as the aggressive/neutral analysts suggest. +- **Avoid hasty redeployment:** Hold cash and wait for cleaner setups in NVDA or the broader market, as the neutral analyst advises. + +--- + +### 3. Refined Trader's Plan (Improvement Based on Debate & Past Lessons) + +Original Plan: Leaned toward a tactical sell, with the risk of overreacting or not acting at all. + +**Improved Plan:** +1. **Trim Position by 20–30% Now:** + - Locks in gains, acknowledges technical warnings, but doesn’t cripple upside if reversal occurs soon. +2. **Place Moderately Loose Stop-losses:** + - On another 20–30% of the position around the $180–$185 range (recent support). Exit more aggressively if broken. +3. **Maintain a Core:** + - Stay invested in 40–60% of original holding as NVDA’s structural story and macro environment are still positive. +4. **Redeploy capital ONLY when signals improve:** + - Wait for new technical strength or positive news, rather than rushing to re-buy or chase new names. +5. **Review regular risk (monthly):** + - Be ready to re-engage if technicals and newsflow turn, but avoid getting chopped up by every blip. + +--- + +### 4. Learning from Past Mistakes + +**Past error:** Defaulting to Hold despite clear technical warnings led to sitting through avoidable pullbacks in market leaders; conversely, overtrading during normal consolidations led to whipsaws and missed recovery rallies. + +**Lesson:** A *blended* approach—nimble trims when technicals deteriorate, but keeping a substantial core in exceptional long-term names—protects both capital and future upside. + +--- + +## **Final Recommendation:** +### **SELL/TRIM 20–30% OF NVDA POSITION NOW.** +- **Action:** Take partial profits, reduce risk exposure, and set moderately loose stop-losses on part of remaining holding. +- **Hold the remainder:** NVDA remains a long-term leader, and the primary trend is intact. +- **Stay disciplined for re-entry or further trims** as technical and news landscape evolve. + +**This recommendation is NOT a “sell everything” call, nor a passive hold.** +It’s a tactical move to protect against near-term drawdown risk, while keeping skin in the game for potential swift rebounds. +This hybrid strategy—based on concrete arguments from all three analysts—corrects for past over-holding and over-selling, and is most likely to preserve and grow capital over multiple cycles. + +--- + +### **Bottom Line:** +**Sell/Trim 20–30%. Keep the core. Wait for signal improvement. This is disciplined, active risk management for both today’s market and long-term outperformance.** \ No newline at end of file diff --git a/results/NVDA/2026-03-05/reports/fundamentals_report.md b/results/NVDA/2026-03-05/reports/fundamentals_report.md new file mode 100644 index 00000000..c7e94c61 --- /dev/null +++ b/results/NVDA/2026-03-05/reports/fundamentals_report.md @@ -0,0 +1,96 @@ +以下是NVDA（NVIDIA Corporation）基於過去一周最新基本面與財務報告的詳細分析： + +--- + +## 公司概況與市值 +NVIDIA是全球領先的科技公司，專注於半導體及AI運算芯片的設計與銷售。2026年3月，NVDA市值達到4.36萬億美元，是行業的絕對龍頭。公司Beta為2.375，顯示股價波動較大，與市場的聯動性強。 + +--- + +## 核心基本面數據與分析 + +### 收益力與成長 +- 2026Q1（截止2026-01-31） + - 營收：681.27億美元，連續四個季度逐季快速增長（2025Q4: 570.06億，2025Q3: 467.43億，2025Q2: 440.62億）。 + - 淨利潤：429.6億美元，季度同比和環比均大幅成長。 + - 毛利率約75%，營業利潤率超過65%，淨利率高達56%。各項利潤率均屬於行業頂尖並持續改善。 + - 每股盈餘（EPS）達1.77美元，明顯高於之前季度。 + +- 市場定價 + - TTM（過去十二月）PE為36.5，但Forward PE僅16.6，反映未來預期快速盈利增長，市場對其未來兩年業績增長極為樂觀。 + - PB值為27.7，高於行業平均，說明市場肯為其未來競爭力溢價。 + +### 資產負債結構 +- 總資產：2,068億美元（2026Q1），從2025初到2026年增長明顯，體現公司業務擴張和現金增長。 +- 現金及短期投資：625.56億美元，流動性非常充裕。 +- 流動比率近4倍，短期償債風險幾乎不存在。 +- 總負債/權益比僅約0.31（負債約4,951億，權益約1.57萬億），結構健康。 +- 應收帳款從2025Q1至2026Q1一路提升，反映客戶業務規模快速擴大，需關注未來可能的壞帳風險。 + +### 現金流量 +- 自由現金流一季內創下349億美元新高，現金及約當現金超過100億。 +- 營業現金流、自由現金流大幅攀升，且穩定、遠高於資本支出（CAPEX，2026Q1僅12.8億），顯示業務高度盈利、現金轉化效率極佳。 +- 回購股票現象明顯（近日季度共回購超過38億美金），顯示管理層信心。 +- 分紅率極低（僅0.02%），表明公司主要以成長與回購為主策略。 + +### 經營效率與歷史趨勢 +- 淨資產報酬率（ROE）逾100%（TTM），因高盈餘與股權規模快速上升。 +- 總資產報酬率（ROA）超過50%，為高延展性的科技公司異常出色。 +- 固定資產、無形資產（如Goodwill）因近年收購及業務擴大顯著提升，Goodwill一年內從52億增至208億，需關注未來可能的減值風險，但現金流和利潤完全支持其賬面價值。 + +--- + +## 綜合觀察（基本面強弱、風險與亮點） + +- **優勢** + - 收入、利潤、現金流與資產均創出歷史新高，且增速未見放緩。 + - 盈利能力、現金流、資產結構極其優秀，幾乎無短期流動性或償債風險。 + - 行業龍頭位置穩固，AI需求驅動下業績增長動能充沛。 + - 大規模股票回購，提升每股價值並反映管理層信心。 + +- **潛在風險** + - 高市盈率可能使公司對未來盈利增長的市場預期過高，一旦增速放緩，估值調整壓力較大。 + - Goodwill 急劇增加（收購帶來的無形資產），需關注資產減值風險。 + - 高Beta表明股價波動性強，市場逆風時回撤幅度可能會較大。 + - 應收賬款激增需關注客戶信用管理。 + +--- + +## 關鍵指標總覽表 + +| 指標 | 2026Q1/最新 | 2025Q4 | 2025Q3 | 2025Q2 | 2025Q1 | 趨勢/說明 | +|-----------------|-------------|-------------|-------------|-------------|-------------|----------------------------------| +| 營收(億美元) | 681.3 | 570.1 | 467.4 | 440.6 | 393.3 | 遞增，成長強勁 | +| 淨利(億美元) | 429.6 | 319.1 | 264.2 | 187.8 | 220.9 | 高增長，利潤率提升 | +| EPS(美元) | 1.77 | 1.31 | 1.08 | 0.77 | 0.90 | 持續走高 | +| 毛利率 | ~75% | ~73% | ~72% | ~69% | ~73% | 持續改善，收斂於高位 | +| 自由現金流(億) | 349 | 221 | 135 | 261 | 156 | 現金流極佳，轉化效能強 | +| 資產總額(億) | 2,068 | 1,611 | 1,407 | 1,253 | 1,116 | 持續擴大 | +| 現金及短投(億) | 625.6 | 606.1 | 539.9 | 526.9 | 432.1 | 極度充裕 | +| ROE | >100% | 高 | 高 | 高 | 高 | 利潤/權益規模驚人 | +| 負債/權益比 | ~0.31 | 0.36 | 0.41 | 0.49 | 0.41 | 降低趨勢，結構良好 | +| 市盈率(PE,TTM) | 36.5 | - | - | - | - | 高，但預期增速超出市場平均 | +| Forward PE | 16.6 | - | - | - | - | 大幅低於當前水平，反映未來成長 | +| Goodwill(億) | 208.3 | 62.6 | 57.6 | 54.9 | 51.9 | 收購產生，需關注未來減值 | + +--- + +## 綜合結論 +NVIDIA的基本面極為強勁，收入、盈利能力和現金流連續創新高，並且資產負債結構極其健康。雖估值較高、股價波動性大，但隨著AI需求與公司創新能力的持續推進，中長線成長確定性極強，是科技領域中最優質的核心資產之一。需留意行業景氣波動、收購相關減值風險及市場對其高預期下的估值修正可能性。 + +--- + +| 關鍵點 | 數據或描述 | +|-------------------------|----------------------------| +| 市值 | 4.36萬億美元 | +| TTM PE / Forward PE | 36.5 / 16.6 | +| 毛利率、營業利率、淨利率 | ~75%，~65%，~56% | +| 自由現金流 | 349億美元（最新季度） | +| 現金、短投 | 625.6億美元 | +| 負債/權益 | 約0.3（極低） | +| ROE/ROA | >100%/ >50% | +| 應收賬款 | 持續增加，反映業務擴張 | +| 業務前景 | AI/高效運算驅動高增長 | +| 主要風險 | 高估值、Goodwill驟增、應收增 | + +這份報告希望能協助交易員獲得全方位、細緻的基本面分析，精確評估NVIDIA的財務健康與投資價值。 \ No newline at end of file diff --git a/results/NVDA/2026-03-05/reports/investment_plan.md b/results/NVDA/2026-03-05/reports/investment_plan.md new file mode 100644 index 00000000..674b04f3 --- /dev/null +++ b/results/NVDA/2026-03-05/reports/investment_plan.md @@ -0,0 +1,65 @@ +Alright, let’s break this down just like I would in a real portfolio review and trading meeting. I’ve studied both analysts’ arguments closely, and my job now is to make a clear, actionable call—Buy, Sell, or Hold—supported by the most compelling, decision-driving points raised. + +Let’s summarize and weigh both sides: + +**Bull Case Key Points:** + +- Exceptional and accelerating revenue, margins, and free cash flow. Q1 numbers show phenomenal, even historic, compounding growth. +- Competitive dominance: unrivaled technology, entrenched CUDA ecosystem, deep moat, and industry standard for AI/data center workloads. +- Strong balance sheet and buyback activity, cushioning any temporary risks. +- The so-called “valuation risk” is mitigated by the forward PE (~16), which is actually cheap compared to similar growth and profitability in mega-tech. +- Technicals show only a healthy consolidation after a huge run; long-term trend is intact, making this a “buy the dip” moment, not the start of a collapse. +- Missing out on leaders in these pullback periods has been a classic mistake; true break in fundamentals is NOT present. + +**Bear Case Key Points:** + +- Near-term technicals are flashing warning signs: breakdown in short-term momentum, negative MACD, failed support levels—these typically precede multi-quarter drifts or sharp corrections in high-flyers. +- Valuation risk: Market’s forward PE and hyper-growth expectations leave no margin for error. Any deceleration (even “meeting” vs. “beating”) can trigger violent derating. +- Accounts receivable and goodwill have swollen, raising real risk about the quality and sustainability of growth—potential defaults or write-downs if the cycle turns. +- Customer concentration (hyperscalers) means any pullback or in-house chip development at giants could hit NVDA harder/faster than expected. +- With “no news” there’s no buying catalyst; risk of the next surprise being to the downside, not upside. +- Macro, regulatory, and competitive threats are material, and history shows these cycles erase parabolic gains quickly when sentiment turns. + +**Which side is most convincing right now?** + +While the bull case paints a stellar long-term picture, and I don’t doubt NVDA remains a decade-defining name, the bear’s argument is more compelling **for a tactical investment decision today.** Here’s why: + +- The technical evidence is not about minor noise—it’s consistent with short-term topping and high-probability pause/correction phases we’ve seen in past supercycle leaders. +- The risk/reward over the next 3–6 months *does not* favor new entry or even aggressive holding above current levels. The chart has shifted, the newsflow isn’t catalyzing a reversal, and the “support” is soft. +- Valuation and concentration risks are real. At historic cycle tops, the risk is not that NVDA fails, but that expectations were simply too high and the stock grinds lower or sideways, trapping fresh buyers and encouraging profit-taking among current holders. + +**Past Mistake Correction:** +I’ve missed opportunities by “defaulting to Hold” in the face of strong warning signals, thinking the fundamental quality would bail me out. But in reality, top-decile companies can—and do—suffer painful mean reversion after crowded trades, even if the long-term thesis remains intact. The lesson: *ignore warning lights at your peril*. The near-term discipline to trim risk is what preserves capital to re-engage when risk/reward is better. + +--- + +**My Recommendation: Sell (Reduce/Trim Exposure)** + +This is not a “short it into oblivion” call. NVDA’s long-term story is intact, but right now, the tactical overlay is too cloudy, risk has risen, and there is little to gain by standing pat while warning signs mount. You can always re-enter when the next positive inflection appears, but you can’t get your capital back if you give up a quick 10-20% drawdown—or endure dead money for quarters. + +**Detailed Investment Plan:** + +1. **If you’re long-size (full position):** + - Trim at least 1/3 to 1/2 of your position *now*. Capture gains, reduce risk, and create dry powder. + - Set a stop-loss on a portion of the remaining holding near the 185 level (recent support). If that breaks further, exit more aggressively. + +2. **If you’re considering a fresh buy:** + - Stand aside. Wait for technicals to improve and/or a material new catalyst to emerge (i.e., >196 close with fresh momentum, or after a healthy correction/baserounding with signs of renewed accumulation). + - Re-evaluate on major dips (15-25% lower) or clear trend reversal. + +3. **If you’re an active trader:** + - Lighten up and use trailing stops. Be prepared to buy back higher if true momentum comes back, but avoid getting trapped in a high-beta roll down. + +4. **Portfolio context:** + - Rebalance allocations away from parabolic winners showing topping signs to other opportunities less stretched and with better near-term setups. + - Stay open to NVDA re-entry when risk/reward pivots back, because the long-term bull thesis does merit another shot *after* the risk episode abates. + +**Rationale Recap:** +Technicals and sentiment say risk of drawdown or churn is elevated RIGHT NOW, with almost zero margin for error on news, earnings, or customers. We’ve seen repeatedly how ignoring those signals (no matter how impressive the company is) leads to painful, avoidable mistakes. A disciplined trim doesn’t violate the long-term thesis; it simply insures against the real risk that the crowd is late to recognize—a lesson learned the hard way. + +**Final Thought:** +Respect NVDA’s greatness; don’t bet against it endlessly. But right now, smart money protects gains and takes some chips off the table. When the risk resets and leaders emerge again, be ready to pounce. + +Action: **Reduce/Take profits/Sell partial position.** Review technicals monthly for possible re-entry. + +Let’s stay disciplined—we’ve seen this setup before, and this is how we avoid repeating past pain. \ No newline at end of file diff --git a/results/NVDA/2026-03-05/reports/market_report.md b/results/NVDA/2026-03-05/reports/market_report.md new file mode 100644 index 00000000..a5707041 --- /dev/null +++ b/results/NVDA/2026-03-05/reports/market_report.md @@ -0,0 +1,43 @@ +根據2026-03-05至今的NVDA技術指標進行全面、細緻的分析，觀察如下： + +### 1. 趨勢判斷（均線組合解讀） +- **50日SMA（186.12） vs 200日SMA（175.91）** + NVDA的50日均線明顯高於200日長均線，日K長期都在兩者之上，這代表長中期趨勢（黃金交叉後延續），整體格局偏多，但短線已有多次回落接近中均，說明多方優勢目前有所削弱。 + +- **10日EMA（184.38）** + 短天期EMA近期下彎，且已低於50日SMA及VWMA，反映短線動能已趨轉疲弱，EMA彈性高，提示市場短暫偏空/橫盤。 + +### 2. 動能與反轉訊號（MACD組合+RSI） +- **MACD（-0.73）、MACD柱（-0.76）** + MACD本週轉負，且逐日下滑，柱狀圖自高點開始放大負值，動能明顯翻空並加速減弱。2月下旬一度快速翻正，暗示當時有明顯多頭反彈，但力竭後已形成中短期死叉。 + +- **RSI（47.7）** + RSI徘徊在50下方，尚未超賣但略弱勢，和短線下跌相符。近期最低約40，尚不至於進入極端恐慌值。 + +### 3. 壓力支撐與波動性（布林、量價） +- **布林上軌（196.96）** + 目前收盤遠低於上軌，顯示短期內難以突破高位。布林帶區間維持寬闊，意味近期波動性不弱，但價格明顯偏布林帶下半部。 + +- **VWMA（185.72）** + 以成交量加權的均線略高於現價，但自2月以來VWMA逐步下移，對比50SMA與10EMA表現，更貼近實際交易主力成本，發現多空轉換敏感，暗示近期成交多集中在184-186區間。 + +### 綜合評析與操作建議 +- **長線結構仍偏多頭，但短線各波段指標已明顯轉弱**，反彈乏力、動能遞減。MACD和10EMA下行、RSI無法有效上破50，皆顯示市場缺乏多頭動能。 +- **價格雖未進入極度超賣，但所有短期均線、量均線已失守並匯聚在184-186附近，形成明顯壓力帶**。若未來幾日無法重返185-187之上，恐有回測180-175的機會。 +- **若是長線投資（根據200SMA），未見結構性破壞，但短線追價以及波段交易需特別留意反彈無力後的順勢調整。** + +### 結論：多空平衡漸向空方傾斜，觀望等待更清晰訊號 + +- 本週內不建議追高買入，建議暫時觀望/持有，若未能守穩184-185而持續下滑，可考慮分批減碼或設防守停損。想要逢低承接者，可觀察180及175-176區間是否獲得成交量支撐與多頭反擊訊號後，再小量布局。 +- 實際操作可依據MACD是否重新翻正及10EMA是否回補至VWMA之上作為再次進場依據。 + +**指標組合說明** +- 結合50SMA、200SMA、10EMA（長中短三均線，判斷趨勢與動能變化） +- MACD與macdh雙指標（動能強弱、順勢或背離） +- RSI（動能/超賣區判斷，避免滯後問題） +- 布林上軌壓力帶確認（輔助判斷突破或反彈空間） +- VWMA（成交量影響下的均價推算，支撐主力資金動向） + +如需依照實際情境立即調整買賣策略，應密切關注上述指標每日變動與市場消息。 + +（如希望即時交易決策，請告知您的投資週期和風險偏好，可進一步提供買賣點建議） \ No newline at end of file diff --git a/results/NVDA/2026-03-05/reports/news_report.md b/results/NVDA/2026-03-05/reports/news_report.md new file mode 100644 index 00000000..cd32ee60 --- /dev/null +++ b/results/NVDA/2026-03-05/reports/news_report.md @@ -0,0 +1,44 @@ +根據過去一周（2026-02-27 至 2026-03-05）的新聞數據，這裡對NVDA（NVIDIA）的公司層面以及全球宏觀經濟趨勢進行分析： + +## 1. NVDA 公司新聞與市場動向 + +- 在過去一周內，未查找到與NVDA直接相關的新聞或重大動態。 +- 這意味著公司在此期間未發布財報、主要產品發布或遭遇重大利好/利空消息。 +- 無新訊息並不能直接得出消極結論，但在關鍵財報季前或產業重要動態發生時，此現象需引起關注。 + +## 2. 全球宏觀經濟與市場趨勢（2026-02-27至2026-03-05） + +### 2.1 資本市場熱點與焦點 +- 加密貨幣與傳統金融融合趨勢：紐約證券交易所（NYSE）母公司更深度布局加密市場，頂級基金經理看好該公司股票，顯示資本市場對傳統交易平台的金融科技轉型有信心，或對科技相關板塊帶來溢出效應。 +- 中國科技股興趣升溫：全球投資者及專業基金經理依然關注中國科技股，部分分析師推薦特定公司名單。這預示著全球資本流向有望部分回流亞洲市場，其中高效能芯片需求將受益，包括NVDA等供應鏈企業。 +- 關稅與政策風險：最新回顧重點指出貿易政策（如關稅）波動風險，這對具有全球供應鏈的科技企業（包括NVDA）是重要的外部變量。 + +### 2.2 其他行業與宏觀指標 +- 多家（如Interface、Mohawk等）美國實體型企業第四季度財報超出預期，顯示美國經濟內需依舊堅挺，對半導體與高科技投資心理起到支持。 +- 最新非農就業數據被市場詮釋為“利好”，激勵股市情緒，短期為美股提供流動性支撐。 +- 公司內部持股增加現象（如Culp）被視為積極信號，顯示公司高層對未來營運具信心，此類訊號也值得科技板塊投資人借鑒觀察。 + +### 2.3 戰略和監管 +- 部分美國公司正考慮股票交易所轉板（如Culp轉至NASDAQ），或隱含希望獲取更多科技/成長型資本市場關注。 + +## 3. 對交易員的細緻見解 + +1. NVDA短期內缺乏直接催化劑，但作為高Beta科技股，其股價易受宏觀消息影響。 +2. 市場資金風險偏好提高，資本正重新評估科技板塊以及美國實體經濟的韌性，對NVDA屬偏正面外溢。 +3. 關稅及全球政策風險不可忽視，需密切關注美中貿易進展和政策微調。 +4. 科技板塊正獲益於加密經濟、亞洲科技動態和美國內需強勁的複合推力，但短線需觀察新的財報或指標發布。 + +--- + +## 關鍵趨勢整理表 + +| 範疇 | 本周趨勢/重大事件 | 對NVDA及科技股意義 | +|----------------|----------------------------------------------------------------------------------|-----------------------------| +| 公司層面 | 本週無新聞動態 | 市場觀望、需等待新訊號 | +| 資本市場熱點 | 傳統交易所深耕加密科技/中國科技股受全球關注 | 有助於科技板塊資金流動 | +| 財報與內需 | 多家美企Q4財報優於預期/內需堅挺 | 美國經濟支持高成長股 | +| 政策與監管 | 關稅不確定性/公司轉板NASDQ | 關注全球供應鏈變化 | +| 就業經濟 | 非農就業數據利好，股市樂觀 | 短線資金面正面 | +| 產業信心 | 高層增持自家公司股票 | 行業動能可參考，尚未直接提及NVDA | + +如需針對交易策略（如買進、持有、賣出）進行具體建議，請進一步說明需求或指明側重點。 \ No newline at end of file diff --git a/results/NVDA/2026-03-05/reports/sentiment_report.md b/results/NVDA/2026-03-05/reports/sentiment_report.md new file mode 100644 index 00000000..ee6d0a5f --- /dev/null +++ b/results/NVDA/2026-03-05/reports/sentiment_report.md @@ -0,0 +1,20 @@ +在2026年2月27日至2026年3月5日期間，沒有找到有關NVDA（NVIDIA）的新聞或社交媒體討論資料。雖然缺乏直接的新聞來源與實時社交媒體情緒，但這本身可視為一項觀察：在過去一週內，NVDA未有顯著的公開事件、消息或重大爭議，市場對該公司的注意力相對較低。 + +### 詳細分析與見解 + +- 公眾情緒分析：由於缺乏新聞和社交媒體討論，目前市場對NVDA的情緒處於一個冷靜、平穩的狀態。這通常意味著公司近期無重大負面或正面消息刺激資金流動或引發恐慌/樂觀情緒。 +- 近期消息動態：無重大財報發布、合作動態、產品發布或監管消息傳出，顯示公司穩定運行，亦有可能在醞釀下一輪消息發布。 +- 市場反應可能性：當一家大型公司如NVDA在新聞和情緒層面皆呈現低波動時，股價通常較為平穩。然而，此狀態也提醒交易員注意潛在的突發訊息或黑天鵝事件。 +- 操作建議：建議持續觀察NVDA動態，尤其應關注未來7-14天內是否會有突發消息或異常交易量變化。若持有現有倉位，可參考維持觀望，等待新信號出現。 + +--- + +| 關鍵面向 | 狀況說明 | +|------------------------|------------------------------------------| +| 新聞/社交媒體討論情況 | 過去一週未見明顯新聞及社群討論 | +| 公眾情緒 | 冷靜、低波動，無明顯偏向 | +| 重大消息動態 | 無財報、無新產品、無重大合作或監管事件 | +| 市場潛在風險 | 需注意未來可能突發消息 | +| 操作建議 | 持續觀察，維持觀望，等待新信號 | + +如需更長時間範圍或指定類型的新聞或社交情緒深入追蹤，可進一步查詢提出。 \ No newline at end of file diff --git a/results/NVDA/2026-03-05/reports/trader_investment_plan.md b/results/NVDA/2026-03-05/reports/trader_investment_plan.md new file mode 100644 index 00000000..24081505 --- /dev/null +++ b/results/NVDA/2026-03-05/reports/trader_investment_plan.md @@ -0,0 +1,19 @@ +After carefully evaluating the comprehensive bull and bear cases outlined by the analyst team and reflecting on the lessons learned—specifically, not ignoring warning signals purely due to strong fundamentals—I am ready to make a clear, actionable trading decision for NVDA. + +Key drivers of this recommendation: + +- While NVDA’s long-term fundamental thesis remains highly attractive, there are immediate technical warning signals (negative momentum, failed support levels, and shifting sentiment). +- Elevated valuation and customer concentration risks mean the stock is priced for perfection, leaving minimal margin for error—raising the risk of near-term correction or prolonged sideways movement. +- My past mistakes include holding through warning signs with high-quality names, which in retrospect led to avoidable drawdowns and missed chances to redeploy capital more effectively. +- The absence of a near-term positive catalyst, along with increasing macro and regulatory headwinds, suggests it is prudent to reduce exposure and wait for risk/reward to improve before adding new money. + +Therefore: + +1. If currently holding a full or above-average position, trim 1/3 to 1/2 now to lock in gains and reduce exposure. +2. Do not initiate a new position at this time; wait for either a technical reset (significant correction or clear bullish reversals) before reevaluating. +3. For the residual/remaining holding, set disciplined stop-loss levels to guard against break of deeper support. +4. Monitor monthly and be ready to re-enter when the risk profile improves and technicals stabilize. + +In summary, this is a tactical, not fundamental, sell—protecting capital during turbulent short-term periods while respecting, but not being blinded by, NVDA’s long-term prospects. + +FINAL TRANSACTION PROPOSAL: **SELL** \ No newline at end of file diff --git a/tradingagents/agents/analysts/fundamentals_analyst.py b/tradingagents/agents/analysts/fundamentals_analyst.py index 22d91848..de2dee1c 100644 --- a/tradingagents/agents/analysts/fundamentals_analyst.py +++ b/tradingagents/agents/analysts/fundamentals_analyst.py @@ -5,11 +5,23 @@ from tradingagents.agents.utils.agent_utils import get_fundamentals, get_balance from tradingagents.dataflows.config import get_config +def get_fundamentals_analyst_system_message(language="en"): + """Get fundamentals analyst system message in the specified language.""" + if language == "zh_TW": + return "你是一位研究員，負責分析公司過去一周的基本面信息。請寫一份全面的報告，深入分析公司的基本面信息，如財務文件、公司概況、基本財務狀況和公司財務歷史，以全面了解公司的基本面，為交易員提供參考。確保儘可能詳細。不要簡單地說趨勢是混合的，提供詳細的細緻分析和見解，以幫助交易員做出決策。" + " 確保在報告末尾附加 Markdown 表格以組織關鍵點，清晰易讀。" + " 使用可用工具：`get_fundamentals` 進行全面公司分析，`get_balance_sheet`, `get_cashflow` 和 `get_income_statement` 用於特定的財務報表。" + else: + return "You are a researcher tasked with analyzing fundamental information over the past week about a company. Please write a comprehensive report of the company's fundamental information such as financial documents, company profile, basic company financials, and company financial history to gain a full view of the company's fundamental information to inform traders. Make sure to include as much detail as possible. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." + " Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read." + " Use the available tools: `get_fundamentals` for comprehensive company analysis, `get_balance_sheet`, `get_cashflow`, and `get_income_statement` for specific financial statements." + + def create_fundamentals_analyst(llm): def fundamentals_analyst_node(state): current_date = state["trade_date"] ticker = state["company_of_interest"] company_name = state["company_of_interest"] + + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") tools = [ get_fundamentals, @@ -18,11 +30,7 @@ def create_fundamentals_analyst(llm): get_income_statement, ] - system_message = ( - "You are a researcher tasked with analyzing fundamental information over the past week about a company. Please write a comprehensive report of the company's fundamental information such as financial documents, company profile, basic company financials, and company financial history to gain a full view of the company's fundamental information to inform traders. Make sure to include as much detail as possible. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." - + " Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read." - + " Use the available tools: `get_fundamentals` for comprehensive company analysis, `get_balance_sheet`, `get_cashflow`, and `get_income_statement` for specific financial statements.", - ) + system_message = get_fundamentals_analyst_system_message(language) prompt = ChatPromptTemplate.from_messages( [ diff --git a/tradingagents/agents/analysts/market_analyst.py b/tradingagents/agents/analysts/market_analyst.py index e175b94e..7129f8a8 100644 --- a/tradingagents/agents/analysts/market_analyst.py +++ b/tradingagents/agents/analysts/market_analyst.py @@ -5,20 +5,37 @@ from tradingagents.agents.utils.agent_utils import get_stock_data, get_indicator from tradingagents.dataflows.config import get_config -def create_market_analyst(llm): +def get_market_analyst_system_message(language="en"): + """Get market analyst system message in the specified language.""" + if language == "zh_TW": + return """你是一位交易助手，負責分析金融市場。你的角色是從以下列表中選擇最相關的指標來分析給定的市場狀況或交易策略。目標是選擇最多 8 個指標，提供互補的見解且避免冗餘。分類及各分類的指標如下： - def market_analyst_node(state): - current_date = state["trade_date"] - ticker = state["company_of_interest"] - company_name = state["company_of_interest"] +移動平均線： +- close_50_sma: 50 期簡單移動平均 - 中期趨勢指標。用途：識別趨勢方向並作為動態支撐/阻力位。提示：滯後性，應配合快速指標使用。 +- close_200_sma: 200 期簡單移動平均 - 長期趨勢基準。用途：確認整體市場趨勢，識別黃金叉/死亡叉。提示：反應緩慢，最適合戰略性趨勢確認。 +- close_10_ema: 10 期指數移動平均 - 反應靈敏的短期平均。用途：捕捉動量的快速轉變和潛在進場點。提示：在震盪市場中容易被噪音影響。 - tools = [ - get_stock_data, - get_indicators, - ] +MACD 相關： +- macd: MACD 指標 - 通過 EMA 差異計算動量。用途：尋找交叉和背離作為趨勢變化信號。提示：在低波動或盤整市場中需確認。 +- macds: MACD 信號線 - MACD 線的 EMA 平滑化。用途：使用與 MACD 線的交叉觸發交易。提示：應作為更廣泛策略的一部分。 +- macdh: MACD 柱狀圖 - 顯示 MACD 線與信號線的差距。用途：可視化動量強度，提早發現背離。提示：在快速波動市場中可能波動較大。 - system_message = ( - """You are a trading assistant tasked with analyzing financial markets. Your role is to select the **most relevant indicators** for a given market condition or trading strategy from the following list. The goal is to choose up to **8 indicators** that provide complementary insights without redundancy. Categories and each category's indicators are: +動量指標： +- rsi: RSI 相對強弱指數 - 衡量動量以標記超買/超賣條件。用途：應用 70/30 閾值並關注背離以發出反轉信號。提示：在強趨勢中 RSI 可能保持極值。 + +波動率指標： +- boll: 布林中軌 - 20 期 SMA，是布林帶的基礎。用途：充當內價格波動的動態基準。提示：與上下布林帶結合以有效發現突破或反轉。 +- boll_ub: 布林上軌 - 通常為中軌上方 2 個標準差。用途：指示潛在超買條件和突破區域。提示：在強趨勢中價格可能貼著上軌運行。 +- boll_lb: 布林下軌 - 通常為中軌下方 2 個標準差。用途：指示潛在超賣條件。提示：使用額外分析避免虛假反轉信號。 +- atr: 平均真實波幅 - 衡量波動率。用途：根據當前市場波動率設置止損位和調整倉位大小。提示：是反應性指標，應作為更廣泛風險管理策略的一部分。 + +成交量指標： +- vwma: 交易量加權移動平均 - 按成交量加權的移動平均。用途：通過整合價格行為和成交量數據確認趨勢。提示：關注成交量脈衝可能導致的偏斜結果。 + +請選擇提供多樣且互補信息的指標。避免冗餘（例如，不要同時選擇 RSI 和 Stochastic RSI）。請簡要說明為什麼這些指標適合給定的市場背景。調用工具時，請使用上面提供的指標名稱，否則調用將失敗。請確保先調用 get_stock_data 以檢索生成指標所需的 CSV 文件。然後使用 get_indicators 和具體的指標名稱。寫一份非常詳細和細緻的報告，說明你觀察到的趨勢。不要簡單地說趨勢是混合的，要提供詳細的分析和見解來幫助交易員做決策。""" + + """ 確保在報告末尾附加 Markdown 表格以組織關鍵點，清晰易讀。""" + else: + return """You are a trading assistant tasked with analyzing financial markets. Your role is to select the **most relevant indicators** for a given market condition or trading strategy from the following list. The goal is to choose up to **8 indicators** that provide complementary insights without redundancy. Categories and each category's indicators are: Moving Averages: - close_50_sma: 50 SMA: A medium-term trend indicator. Usage: Identify trend direction and serve as dynamic support/resistance. Tips: It lags price; combine with faster indicators for timely signals. @@ -43,8 +60,26 @@ Volume-Based Indicators: - vwma: VWMA: A moving average weighted by volume. Usage: Confirm trends by integrating price action with volume data. Tips: Watch for skewed results from volume spikes; use in combination with other volume analyses. - Select indicators that provide diverse and complementary information. Avoid redundancy (e.g., do not select both rsi and stochrsi). Also briefly explain why they are suitable for the given market context. When you tool call, please use the exact name of the indicators provided above as they are defined parameters, otherwise your call will fail. Please make sure to call get_stock_data first to retrieve the CSV that is needed to generate indicators. Then use get_indicators with the specific indicator names. Write a very detailed and nuanced report of the trends you observe. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions.""" - + """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read.""" - ) + + """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read.""" + + +def create_market_analyst(llm): + + def market_analyst_node(state): + current_date = state["trade_date"] + ticker = state["company_of_interest"] + company_name = state["company_of_interest"] + + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") + + tools = [ + get_stock_data, + get_indicators, + ] + + system_message = get_market_analyst_system_message(language) prompt = ChatPromptTemplate.from_messages( [ diff --git a/tradingagents/agents/analysts/news_analyst.py b/tradingagents/agents/analysts/news_analyst.py index 03b4fae4..b2924d3f 100644 --- a/tradingagents/agents/analysts/news_analyst.py +++ b/tradingagents/agents/analysts/news_analyst.py @@ -5,20 +5,29 @@ from tradingagents.agents.utils.agent_utils import get_news, get_global_news from tradingagents.dataflows.config import get_config +def get_news_analyst_system_message(language="en"): + """Get news analyst system message in the specified language.""" + if language == "zh_TW": + return "你是一位新聞研究員，負責分析過去一周的最近新聞和趨勢。請寫一份全面的報告，說明對於交易和宏觀經濟相關的當前世界狀況。使用可用工具：get_news(query, start_date, end_date) 用於公司特定或針對性的新聞搜索，以及 get_global_news(curr_date, look_back_days, limit) 用於更廣泛的宏觀經濟新聞。不要簡單地說趨勢是混合的，提供詳細的細緻分析和見解，以幫助交易員做出決策。" + """ 確保在報告末尾附加 Markdown 表格以組織關鍵點，清晰易讀。""" + else: + return "You are a news researcher tasked with analyzing recent news and trends over the past week. Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. Use the available tools: get_news(query, start_date, end_date) for company-specific or targeted news searches, and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." + """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read.""" + + def create_news_analyst(llm): def news_analyst_node(state): current_date = state["trade_date"] ticker = state["company_of_interest"] + + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") tools = [ get_news, get_global_news, ] - system_message = ( - "You are a news researcher tasked with analyzing recent news and trends over the past week. Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. Use the available tools: get_news(query, start_date, end_date) for company-specific or targeted news searches, and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." - + """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read.""" - ) + system_message = get_news_analyst_system_message(language) prompt = ChatPromptTemplate.from_messages( [ diff --git a/tradingagents/agents/analysts/social_media_analyst.py b/tradingagents/agents/analysts/social_media_analyst.py index b25712d7..c19b2235 100644 --- a/tradingagents/agents/analysts/social_media_analyst.py +++ b/tradingagents/agents/analysts/social_media_analyst.py @@ -5,20 +5,29 @@ from tradingagents.agents.utils.agent_utils import get_news from tradingagents.dataflows.config import get_config +def get_social_media_analyst_system_message(language="en"): + """Get social media analyst system message in the specified language.""" + if language == "zh_TW": + return "你是一位社交媒體和公司特定新聞研究員/分析師，負責分析特定公司的社交媒體帖子、最近的公司新聞和公眾情緒。你的目標是寫一份全面的詳細報告，分析該公司過去一周的最新狀況，包括社交媒體上人們在說什麼、分析公眾對該公司的每日情緒、查看最近的公司新聞。使用 get_news(query, start_date, end_date) 工具搜索公司特定的新聞和社交媒體討論。盡力查看所有可能的來源，包括社交媒體、情緒分析和新聞。不要簡單地說趨勢是混合的，提供詳細的細緻分析和見解，以幫助交易員做出決策。" + """ 確保在報告末尾附加 Markdown 表格以組織關鍵點，清晰易讀。""" + else: + return "You are a social media and company specific news researcher/analyst tasked with analyzing social media posts, recent company news, and public sentiment for a specific company over the past week. You will be given a company's name your objective is to write a comprehensive long report detailing your analysis, insights, and implications for traders and investors on this company's current state after looking at social media and what people are saying about that company, analyzing sentiment data of what people feel each day about the company, and looking at recent company news. Use the get_news(query, start_date, end_date) tool to search for company-specific news and social media discussions. Try to look at all sources possible from social media to sentiment to news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." + """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read.""" + + def create_social_media_analyst(llm): def social_media_analyst_node(state): current_date = state["trade_date"] ticker = state["company_of_interest"] company_name = state["company_of_interest"] + + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") tools = [ get_news, ] - system_message = ( - "You are a social media and company specific news researcher/analyst tasked with analyzing social media posts, recent company news, and public sentiment for a specific company over the past week. You will be given a company's name your objective is to write a comprehensive long report detailing your analysis, insights, and implications for traders and investors on this company's current state after looking at social media and what people are saying about that company, analyzing sentiment data of what people feel each day about the company, and looking at recent company news. Use the get_news(query, start_date, end_date) tool to search for company-specific news and social media discussions. Try to look at all sources possible from social media to sentiment to news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions." - + """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read.""", - ) + system_message = get_social_media_analyst_system_message(language) prompt = ChatPromptTemplate.from_messages( [ diff --git a/tradingagents/agents/managers/research_manager.py b/tradingagents/agents/managers/research_manager.py index c537fa2f..d7bdbd93 100644 --- a/tradingagents/agents/managers/research_manager.py +++ b/tradingagents/agents/managers/research_manager.py @@ -1,5 +1,46 @@ import time import json +from tradingagents.dataflows.config import get_config + + +def get_research_manager_prompt(language="en", past_memory_str="", history=""): + """Get research manager prompt in the specified language.""" + if language == "zh_TW": + return f"""作為投資組合經理和辯論協調者，你的角色是認真評估這一輪辯論，做出明確的決定：贊同熊市分析師、看漲分析師，或選擇持有（只有在基於所呈現的論證得到充分理由證實的情況下）。 + +簡明扼要地總結雙方的關鍵點，專注於最有說服力的證據或推理。你的建議—買入、賣出或持有—必須清晰且可行。避免默認選擇持有，僅因為雙方都有有效的觀點；根據辯論中最有力的論證形成立場。 + +此外，為交易員制定詳細的投資計劃。這應包括： + +你的建議：由最令人信服的論證支持的決定性立場。 +理由：解釋為什麼這些論證導致你的結論。 +戰略行動：實施該建議的具體步驟。 +考慮你在類似情況下過去的錯誤。利用這些見解來完善你的決策，確保你在學習和改進。以自然對話的方式呈現你的分析，無需特殊格式。 + +這是你過去關於類似情況的錯誤反思： +\"{past_memory_str}\" + +以下是辯論： +辯論歷史： +{history}""" + else: + return f"""As the portfolio manager and debate facilitator, your role is to critically evaluate this round of debate and make a definitive decision: align with the bear analyst, the bull analyst, or choose Hold only if it is strongly justified based on the arguments presented. + +Summarize the key points from both sides concisely, focusing on the most compelling evidence or reasoning. Your recommendation—Buy, Sell, or Hold—must be clear and actionable. Avoid defaulting to Hold simply because both sides have valid points; commit to a stance grounded in the debate's strongest arguments. + +Additionally, develop a detailed investment plan for the trader. This should include: + +Your Recommendation: A decisive stance supported by the most convincing arguments. +Rationale: An explanation of why these arguments lead to your conclusion. +Strategic Actions: Concrete steps for implementing the recommendation. +Take into account your past mistakes on similar situations. Use these insights to refine your decision-making and ensure you are learning and improving. Present your analysis conversationally, as if speaking naturally, without special formatting. + +Here are your past reflections on mistakes: +\"{past_memory_str}\" + +Here is the debate: +Debate History: +{history}""" def create_research_manager(llm, memory): @@ -19,23 +60,11 @@ def create_research_manager(llm, memory): for i, rec in enumerate(past_memories, 1): past_memory_str += rec["recommendation"] + "\n\n" - prompt = f"""As the portfolio manager and debate facilitator, your role is to critically evaluate this round of debate and make a definitive decision: align with the bear analyst, the bull analyst, or choose Hold only if it is strongly justified based on the arguments presented. + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") -Summarize the key points from both sides concisely, focusing on the most compelling evidence or reasoning. Your recommendation—Buy, Sell, or Hold—must be clear and actionable. Avoid defaulting to Hold simply because both sides have valid points; commit to a stance grounded in the debate's strongest arguments. - -Additionally, develop a detailed investment plan for the trader. This should include: - -Your Recommendation: A decisive stance supported by the most convincing arguments. -Rationale: An explanation of why these arguments lead to your conclusion. -Strategic Actions: Concrete steps for implementing the recommendation. -Take into account your past mistakes on similar situations. Use these insights to refine your decision-making and ensure you are learning and improving. Present your analysis conversationally, as if speaking naturally, without special formatting. - -Here are your past reflections on mistakes: -\"{past_memory_str}\" - -Here is the debate: -Debate History: -{history}""" + prompt = get_research_manager_prompt(language, past_memory_str, history) response = llm.invoke(prompt) new_investment_debate_state = { diff --git a/tradingagents/agents/managers/risk_manager.py b/tradingagents/agents/managers/risk_manager.py index 1f2334cc..4e6c26a3 100644 --- a/tradingagents/agents/managers/risk_manager.py +++ b/tradingagents/agents/managers/risk_manager.py @@ -1,5 +1,52 @@ import time import json +from tradingagents.dataflows.config import get_config + + +def get_risk_manager_prompt(language="en", past_memory_str="", history="", trader_plan=""): + """Get risk manager prompt in the specified language.""" + if language == "zh_TW": + return f"""作為風險管理評判官和辯論協調者，你的目標是評估三位風險分析師—激進型、中立型和保守型—之間的辯論，並為交易員確定最佳行動方案。你的決定必須產生明確的建議：買入、賣出或持有。只有在特定論證充分正當的情況下才選擇持有，不是在所有方面似乎都有效時的退路。力求清晰和決定性。 + +決策指南： +1. **總結關鍵論證**：從每位分析師中提取最有力的觀點，專注於與背景的相關性。 +2. **提供理由**：用直接引用和來自辯論的反論證支持你的建議。 +3. **完善交易員的計劃**：以交易員的原始計劃開始，**{trader_plan}**，並根據分析師的見解進行調整。 +4. **從過去的錯誤中學習**：使用**{past_memory_str}**的經驗教訓來解決先前的誤判並改進你現在所做的決定，確保你沒有做出錯誤的買入/賣出/持有決定而虧錢。 + +交付物： +- 清晰且可行的建議：買入、賣出或持有。 +- 以辯論和過去反思為基礎的詳細理由。 + +--- + +**分析師辯論歷史：** +{history} + +--- + +專注於可行的見解和持續改進。以過去的教訓為基礎，認真評估所有觀點，確保每項決定都推動更好的結果。""" + else: + return f"""As the Risk Management Judge and Debate Facilitator, your goal is to evaluate the debate between three risk analysts—Aggressive, Neutral, and Conservative—and determine the best course of action for the trader. Your decision must result in a clear recommendation: Buy, Sell, or Hold. Choose Hold only if strongly justified by specific arguments, not as a fallback when all sides seem valid. Strive for clarity and decisiveness. + +Guidelines for Decision-Making: +1. **Summarize Key Arguments**: Extract the strongest points from each analyst, focusing on relevance to the context. +2. **Provide Rationale**: Support your recommendation with direct quotes and counterarguments from the debate. +3. **Refine the Trader's Plan**: Start with the trader's original plan, **{trader_plan}**, and adjust it based on the analysts' insights. +4. **Learn from Past Mistakes**: Use lessons from **{past_memory_str}** to address prior misjudgments and improve the decision you are making now to make sure you don't make a wrong BUY/SELL/HOLD call that loses money. + +Deliverables: +- A clear and actionable recommendation: Buy, Sell, or Hold. +- Detailed reasoning anchored in the debate and past reflections. + +--- + +**Analysts Debate History:** +{history} + +--- + +Focus on actionable insights and continuous improvement. Build on past lessons, critically evaluate all perspectives, and ensure each decision advances better outcomes.""" def create_risk_manager(llm, memory): @@ -22,26 +69,11 @@ def create_risk_manager(llm, memory): for i, rec in enumerate(past_memories, 1): past_memory_str += rec["recommendation"] + "\n\n" - prompt = f"""As the Risk Management Judge and Debate Facilitator, your goal is to evaluate the debate between three risk analysts—Aggressive, Neutral, and Conservative—and determine the best course of action for the trader. Your decision must result in a clear recommendation: Buy, Sell, or Hold. Choose Hold only if strongly justified by specific arguments, not as a fallback when all sides seem valid. Strive for clarity and decisiveness. + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") -Guidelines for Decision-Making: -1. **Summarize Key Arguments**: Extract the strongest points from each analyst, focusing on relevance to the context. -2. **Provide Rationale**: Support your recommendation with direct quotes and counterarguments from the debate. -3. **Refine the Trader's Plan**: Start with the trader's original plan, **{trader_plan}**, and adjust it based on the analysts' insights. -4. **Learn from Past Mistakes**: Use lessons from **{past_memory_str}** to address prior misjudgments and improve the decision you are making now to make sure you don't make a wrong BUY/SELL/HOLD call that loses money. - -Deliverables: -- A clear and actionable recommendation: Buy, Sell, or Hold. -- Detailed reasoning anchored in the debate and past reflections. - ---- - -**Analysts Debate History:** -{history} - ---- - -Focus on actionable insights and continuous improvement. Build on past lessons, critically evaluate all perspectives, and ensure each decision advances better outcomes.""" + prompt = get_risk_manager_prompt(language, past_memory_str, history, trader_plan) response = llm.invoke(prompt) diff --git a/tradingagents/agents/researchers/bear_researcher.py b/tradingagents/agents/researchers/bear_researcher.py index 6634490a..122877a2 100644 --- a/tradingagents/agents/researchers/bear_researcher.py +++ b/tradingagents/agents/researchers/bear_researcher.py @@ -1,6 +1,53 @@ from langchain_core.messages import AIMessage import time import json +from tradingagents.dataflows.config import get_config + + +def get_bear_analyst_prompt(language="en", past_memory_str="", market_research_report="", sentiment_report="", news_report="", fundamentals_report="", history="", current_response=""): + """Get bear analyst prompt in the specified language.""" + if language == "zh_TW": + return f"""你是一位看跌分析師，論證反對投資該股票。你的目標是呈現一個精心推理的論證，強調風險、挑戰和負面指標。利用所提供的研究和數據來突出潛在的下行風險並有效地反駁看漲的論證。 + +關鍵重點： + +- 風險和挑戰：突出可能阻礙股票表現的因素，如市場飽和、財務不穩定或宏觀經濟威脅。 +- 競爭劣勢：強調弱點，如較弱的市場地位、創新下降或來自競爭對手的威脅。 +- 負面指標：使用來自財務數據、市場趨勢或近期不利新聞的證據來支持你的立場。 +- 看漲反論點：用具體數據和合理的推理批判性地分析看漲的論證，揭露弱點或過度樂觀的假設。 +- 參與：以對話的方式呈現你的論證，直接參與看漲分析師的討論，並有效辯論，而不是簡單地列舉事實。 + +可用的資源： + +市場研究報告：{market_research_report} +社交媒體情感報告：{sentiment_report} +最新世界事務新聞：{news_report} +公司基本面報告：{fundamentals_report} +辯論的對話歷史：{history} +最後的看漲論證：{current_response} +相似情況下的反思和學習教訓：{past_memory_str} +使用此信息提供有力的看跌論證，駁斥看漲的主張，並進行動態辯論，展示投資該股票的風險和弱點。你也必須解決反思並從你過去所犯的錯誤和教訓中學習。""" + else: + return f"""You are a Bear Analyst making the case against investing in the stock. Your goal is to present a well-reasoned argument emphasizing risks, challenges, and negative indicators. Leverage the provided research and data to highlight potential downsides and counter bullish arguments effectively. + +Key points to focus on: + +- Risks and Challenges: Highlight factors like market saturation, financial instability, or macroeconomic threats that could hinder the stock's performance. +- Competitive Weaknesses: Emphasize vulnerabilities such as weaker market positioning, declining innovation, or threats from competitors. +- Negative Indicators: Use evidence from financial data, market trends, or recent adverse news to support your position. +- Bull Counterpoints: Critically analyze the bull argument with specific data and sound reasoning, exposing weaknesses or over-optimistic assumptions. +- Engagement: Present your argument in a conversational style, directly engaging with the bull analyst's points and debating effectively rather than simply listing facts. + +Resources available: + +Market research report: {market_research_report} +Social media sentiment report: {sentiment_report} +Latest world affairs news: {news_report} +Company fundamentals report: {fundamentals_report} +Conversation history of the debate: {history} +Last bull argument: {current_response} +Reflections from similar situations and lessons learned: {past_memory_str} +Use this information to deliver a compelling bear argument, refute the bull's claims, and engage in a dynamic debate that demonstrates the risks and weaknesses of investing in the stock. You must also address reflections and learn from lessons and mistakes you made in the past.""" def create_bear_researcher(llm, memory): @@ -22,27 +69,11 @@ def create_bear_researcher(llm, memory): for i, rec in enumerate(past_memories, 1): past_memory_str += rec["recommendation"] + "\n\n" - prompt = f"""You are a Bear Analyst making the case against investing in the stock. Your goal is to present a well-reasoned argument emphasizing risks, challenges, and negative indicators. Leverage the provided research and data to highlight potential downsides and counter bullish arguments effectively. + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") -Key points to focus on: - -- Risks and Challenges: Highlight factors like market saturation, financial instability, or macroeconomic threats that could hinder the stock's performance. -- Competitive Weaknesses: Emphasize vulnerabilities such as weaker market positioning, declining innovation, or threats from competitors. -- Negative Indicators: Use evidence from financial data, market trends, or recent adverse news to support your position. -- Bull Counterpoints: Critically analyze the bull argument with specific data and sound reasoning, exposing weaknesses or over-optimistic assumptions. -- Engagement: Present your argument in a conversational style, directly engaging with the bull analyst's points and debating effectively rather than simply listing facts. - -Resources available: - -Market research report: {market_research_report} -Social media sentiment report: {sentiment_report} -Latest world affairs news: {news_report} -Company fundamentals report: {fundamentals_report} -Conversation history of the debate: {history} -Last bull argument: {current_response} -Reflections from similar situations and lessons learned: {past_memory_str} -Use this information to deliver a compelling bear argument, refute the bull's claims, and engage in a dynamic debate that demonstrates the risks and weaknesses of investing in the stock. You must also address reflections and learn from lessons and mistakes you made in the past. -""" + prompt = get_bear_analyst_prompt(language, past_memory_str, market_research_report, sentiment_report, news_report, fundamentals_report, history, current_response) response = llm.invoke(prompt) diff --git a/tradingagents/agents/researchers/bull_researcher.py b/tradingagents/agents/researchers/bull_researcher.py index b03ef755..b62888ec 100644 --- a/tradingagents/agents/researchers/bull_researcher.py +++ b/tradingagents/agents/researchers/bull_researcher.py @@ -1,6 +1,49 @@ from langchain_core.messages import AIMessage import time import json +from tradingagents.dataflows.config import get_config + + +def get_bull_analyst_prompt(language="en", past_memory_str="", market_research_report="", sentiment_report="", news_report="", fundamentals_report="", history="", current_response=""): + """Get bull analyst prompt in the specified language.""" + if language == "zh_TW": + return f"""你是一位看漲分析師，提倡投資該股票。你的任務是建立一個強大的、以證據為基礎的案例，強調增長潛力、競爭優勢和積極的市場指標。利用所提供的研究和數據來解決關切並有效地反駁看跌的論證。 + +關鍵重點： +- 增長潛力：突出公司的市場機會、收入預測和可擴展性。 +- 競爭優勢：強調獨特產品、強大品牌價值或主導市場地位等因素。 +- 正面指標：使用財務健康、行業趨勢和近期積極新聞作為證據。 +- 看跌反論點：用具體數據和合理的推理批判性地分析看跌的論證，徹底解決關切並表明看漲的觀點具有更強的優勢。 +- 參與：以對話的方式呈現你的論證，直接參與看跌分析師的討論，並有效辯論，而不是僅僅列舉數據。 + +可用的資源： +市場研究報告：{market_research_report} +社交媒體情感報告：{sentiment_report} +最新世界事務新聞：{news_report} +公司基本面報告：{fundamentals_report} +辯論的對話歷史：{history} +最後的看跌論證：{current_response} +相似情況下的反思和學習教訓：{past_memory_str} +使用此信息提供有力的看漲論證，駁斥看跌的關切，並進行動態辯論，展示看漲立場的力量。你也必須解決反思並從你過去所犯的錯誤和教訓中學習。""" + else: + return f"""You are a Bull Analyst advocating for investing in the stock. Your task is to build a strong, evidence-based case emphasizing growth potential, competitive advantages, and positive market indicators. Leverage the provided research and data to address concerns and counter bearish arguments effectively. + +Key points to focus on: +- Growth Potential: Highlight the company's market opportunities, revenue projections, and scalability. +- Competitive Advantages: Emphasize factors like unique products, strong branding, or dominant market positioning. +- Positive Indicators: Use financial health, industry trends, and recent positive news as evidence. +- Bear Counterpoints: Critically analyze the bear argument with specific data and sound reasoning, addressing concerns thoroughly and showing why the bull perspective holds stronger merit. +- Engagement: Present your argument in a conversational style, engaging directly with the bear analyst's points and debating effectively rather than just listing data. + +Resources available: +Market research report: {market_research_report} +Social media sentiment report: {sentiment_report} +Latest world affairs news: {news_report} +Company fundamentals report: {fundamentals_report} +Conversation history of the debate: {history} +Last bear argument: {current_response} +Reflections from similar situations and lessons learned: {past_memory_str} +Use this information to deliver a compelling bull argument, refute the bear's concerns, and engage in a dynamic debate that demonstrates the strengths of the bull position. You must also address reflections and learn from lessons and mistakes you made in the past.""" def create_bull_researcher(llm, memory): @@ -22,25 +65,11 @@ def create_bull_researcher(llm, memory): for i, rec in enumerate(past_memories, 1): past_memory_str += rec["recommendation"] + "\n\n" - prompt = f"""You are a Bull Analyst advocating for investing in the stock. Your task is to build a strong, evidence-based case emphasizing growth potential, competitive advantages, and positive market indicators. Leverage the provided research and data to address concerns and counter bearish arguments effectively. + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") -Key points to focus on: -- Growth Potential: Highlight the company's market opportunities, revenue projections, and scalability. -- Competitive Advantages: Emphasize factors like unique products, strong branding, or dominant market positioning. -- Positive Indicators: Use financial health, industry trends, and recent positive news as evidence. -- Bear Counterpoints: Critically analyze the bear argument with specific data and sound reasoning, addressing concerns thoroughly and showing why the bull perspective holds stronger merit. -- Engagement: Present your argument in a conversational style, engaging directly with the bear analyst's points and debating effectively rather than just listing data. - -Resources available: -Market research report: {market_research_report} -Social media sentiment report: {sentiment_report} -Latest world affairs news: {news_report} -Company fundamentals report: {fundamentals_report} -Conversation history of the debate: {history} -Last bear argument: {current_response} -Reflections from similar situations and lessons learned: {past_memory_str} -Use this information to deliver a compelling bull argument, refute the bear's concerns, and engage in a dynamic debate that demonstrates the strengths of the bull position. You must also address reflections and learn from lessons and mistakes you made in the past. -""" + prompt = get_bull_analyst_prompt(language, past_memory_str, market_research_report, sentiment_report, news_report, fundamentals_report, history, current_response) response = llm.invoke(prompt) diff --git a/tradingagents/agents/risk_mgmt/aggressive_debator.py b/tradingagents/agents/risk_mgmt/aggressive_debator.py index 3905d3d1..9c3da067 100644 --- a/tradingagents/agents/risk_mgmt/aggressive_debator.py +++ b/tradingagents/agents/risk_mgmt/aggressive_debator.py @@ -1,5 +1,40 @@ import time import json +from tradingagents.dataflows.config import get_config + + +def get_aggressive_analyst_prompt(language="en", trader_decision="", market_research_report="", sentiment_report="", news_report="", fundamentals_report="", history="", current_conservative_response="", current_neutral_response=""): + """Get aggressive risk analyst prompt in the specified language.""" + if language == "zh_TW": + return f"""作為激進風險分析師，你的角色是積極擁護高回報、高風險的機會，強調大膽戰略和競爭優勢。在評估交易員的決定或計劃時，要密切關注潛在的上行空間、增長潛力和創新優勢—即使這些伴隨著更高的風險。使用所提供的市場數據和情感分析來加強你的論證並挑戰相反的觀點。具體來說，直接回應保守派和中立分析師的每一點，用數據驅動的反駁和有說服力的推理進行對抗。突出他們的謹慎可能錯過的關鍵機會，或他們的假設可能過度保守的地方。以下是交易員的決定： + +{trader_decision} + +你的任務是通過質疑和批評保守派和中立的立場，為交易員的決定創造一個令人信服的案例，以證明你的高回報觀點提供了前進的最佳途徑。將以下來源的見解納入你的論證： + +市場研究報告：{market_research_report} +社交媒體情感報告：{sentiment_report} +最新世界事務報告：{news_report} +公司基本面報告：{fundamentals_report} +這是當前的對話歷史：{history} +保守派分析師的最後論證：{current_conservative_response} +中立派分析師的最後論證：{current_neutral_response}。如果沒有來自其他觀點的回應，請不要幻想，只是呈現你的觀點。 + +通過解決任何提出的具體關切、駁斥他們邏輯中的弱點，並主張風險承擔的優勢來超越市場規範，主動參與。保持專注於辯論和說服，而不僅僅是呈現數據。挑戰他們的每一個反論點，以強調為什麼高風險的方法是最優的。以自然對話的方式輸出，無需任何特殊格式。""" + else: + return f"""As the Aggressive Risk Analyst, your role is to actively champion high-reward, high-risk opportunities, emphasizing bold strategies and competitive advantages. When evaluating the trader's decision or plan, focus intently on the potential upside, growth potential, and innovative benefits—even when these come with elevated risk. Use the provided market data and sentiment analysis to strengthen your arguments and challenge the opposing views. Specifically, respond directly to each point made by the conservative and neutral analysts, countering with data-driven rebuttals and persuasive reasoning. Highlight where their caution might miss critical opportunities or where their assumptions may be overly conservative. Here is the trader's decision: + +{trader_decision} + +Your task is to create a compelling case for the trader's decision by questioning and critiquing the conservative and neutral stances to demonstrate why your high-reward perspective offers the best path forward. Incorporate insights from the following sources into your arguments: + +Market Research Report: {market_research_report} +Social Media Sentiment Report: {sentiment_report} +Latest World Affairs Report: {news_report} +Company Fundamentals Report: {fundamentals_report} +Here is the current conversation history: {history} Here are the last arguments from the conservative analyst: {current_conservative_response} Here are the last arguments from the neutral analyst: {current_neutral_response}. If there are no responses from the other viewpoints, do not hallucinate and just present your point. + +Engage actively by addressing any specific concerns raised, refuting the weaknesses in their logic, and asserting the benefits of risk-taking to outpace market norms. Maintain a focus on debating and persuading, not just presenting data. Challenge each counterpoint to underscore why a high-risk approach is optimal. Output conversationally as if you are speaking without any special formatting.""" def create_aggressive_debator(llm): @@ -18,19 +53,11 @@ def create_aggressive_debator(llm): trader_decision = state["trader_investment_plan"] - prompt = f"""As the Aggressive Risk Analyst, your role is to actively champion high-reward, high-risk opportunities, emphasizing bold strategies and competitive advantages. When evaluating the trader's decision or plan, focus intently on the potential upside, growth potential, and innovative benefits—even when these come with elevated risk. Use the provided market data and sentiment analysis to strengthen your arguments and challenge the opposing views. Specifically, respond directly to each point made by the conservative and neutral analysts, countering with data-driven rebuttals and persuasive reasoning. Highlight where their caution might miss critical opportunities or where their assumptions may be overly conservative. Here is the trader's decision: + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") -{trader_decision} - -Your task is to create a compelling case for the trader's decision by questioning and critiquing the conservative and neutral stances to demonstrate why your high-reward perspective offers the best path forward. Incorporate insights from the following sources into your arguments: - -Market Research Report: {market_research_report} -Social Media Sentiment Report: {sentiment_report} -Latest World Affairs Report: {news_report} -Company Fundamentals Report: {fundamentals_report} -Here is the current conversation history: {history} Here are the last arguments from the conservative analyst: {current_conservative_response} Here are the last arguments from the neutral analyst: {current_neutral_response}. If there are no responses from the other viewpoints, do not hallucinate and just present your point. - -Engage actively by addressing any specific concerns raised, refuting the weaknesses in their logic, and asserting the benefits of risk-taking to outpace market norms. Maintain a focus on debating and persuading, not just presenting data. Challenge each counterpoint to underscore why a high-risk approach is optimal. Output conversationally as if you are speaking without any special formatting.""" + prompt = get_aggressive_analyst_prompt(language, trader_decision, market_research_report, sentiment_report, news_report, fundamentals_report, history, current_conservative_response, current_neutral_response) response = llm.invoke(prompt) diff --git a/tradingagents/agents/risk_mgmt/conservative_debator.py b/tradingagents/agents/risk_mgmt/conservative_debator.py index 6b106b1b..3af5f064 100644 --- a/tradingagents/agents/risk_mgmt/conservative_debator.py +++ b/tradingagents/agents/risk_mgmt/conservative_debator.py @@ -1,6 +1,41 @@ from langchain_core.messages import AIMessage import time import json +from tradingagents.dataflows.config import get_config + + +def get_conservative_analyst_prompt(language="en", trader_decision="", market_research_report="", sentiment_report="", news_report="", fundamentals_report="", history="", current_aggressive_response="", current_neutral_response=""): + """Get conservative risk analyst prompt in the specified language.""" + if language == "zh_TW": + return f"""作為保守風險分析師，你的主要目標是保護資產、最小化波動性，並確保穩定、可靠的增長。你優先考慮穩定性、安全性和風險緩解，仔細評估潛在損失、經濟衰退和市場波動。在評估交易員的決定或計劃時，認真審查高風險元素，指出決定可能使公司面臨不必要的風險，以及更謹慎的替代方案如何能確保長期收益。以下是交易員的決定： + +{trader_decision} + +你的任務是積極反駁激進派分析師和中立派分析師的論證，突出他們的看法可能如何忽視潛在威脅或未能優先考慮可持續性。直接回應他們的觀點，並從以下數據來源中提取大量證據，來建立一個令人信服的低風險方法案例，以調整交易員的決定： + +市場研究報告：{market_research_report} +社交媒體情感報告：{sentiment_report} +最新世界事務報告：{news_report} +公司基本面報告：{fundamentals_report} +這是當期的對話歷史：{history} +激進派分析師的最後回應：{current_aggressive_response} +中立派分析師的最後回應：{current_neutral_response}。如果沒有來自其他觀點的回應，請不要幻想，只是呈現你的觀點。 + +通過質疑他們的樂觀主義並強調他們可能忽視的潛在下行風險來參與。解決他們的每一個反論點，以展示為什麼保守的立場最終是公司資產的最安全途徑。專注於辯論和批評他們的論證，以展示低風險戰略相對於他們的方法的力量。以自然對話的方式輸出，無需任何特殊格式。""" + else: + return f"""As the Conservative Risk Analyst, your primary objective is to protect assets, minimize volatility, and ensure steady, reliable growth. You prioritize stability, security, and risk mitigation, carefully assessing potential losses, economic downturns, and market volatility. When evaluating the trader's decision or plan, critically examine high-risk elements, pointing out where the decision may expose the firm to undue risk and where more cautious alternatives could secure long-term gains. Here is the trader's decision: + +{trader_decision} + +Your task is to actively counter the arguments of the Aggressive and Neutral Analysts, highlighting where their views may overlook potential threats or fail to prioritize sustainability. Respond directly to their points, drawing from the following data sources to build a convincing case for a low-risk approach adjustment to the trader's decision: + +Market Research Report: {market_research_report} +Social Media Sentiment Report: {sentiment_report} +Latest World Affairs Report: {news_report} +Company Fundamentals Report: {fundamentals_report} +Here is the current conversation history: {history} Here is the last response from the aggressive analyst: {current_aggressive_response} Here is the last response from the neutral analyst: {current_neutral_response}. If there are no responses from the other viewpoints, do not hallucinate and just present your point. + +Engage by questioning their optimism and emphasizing the potential downsides they may have overlooked. Address each of their counterpoints to showcase why a conservative stance is ultimately the safest path for the firm's assets. Focus on debating and critiquing their arguments to demonstrate the strength of a low-risk strategy over their approaches. Output conversationally as if you are speaking without any special formatting.""" def create_conservative_debator(llm): @@ -19,19 +54,11 @@ def create_conservative_debator(llm): trader_decision = state["trader_investment_plan"] - prompt = f"""As the Conservative Risk Analyst, your primary objective is to protect assets, minimize volatility, and ensure steady, reliable growth. You prioritize stability, security, and risk mitigation, carefully assessing potential losses, economic downturns, and market volatility. When evaluating the trader's decision or plan, critically examine high-risk elements, pointing out where the decision may expose the firm to undue risk and where more cautious alternatives could secure long-term gains. Here is the trader's decision: + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") -{trader_decision} - -Your task is to actively counter the arguments of the Aggressive and Neutral Analysts, highlighting where their views may overlook potential threats or fail to prioritize sustainability. Respond directly to their points, drawing from the following data sources to build a convincing case for a low-risk approach adjustment to the trader's decision: - -Market Research Report: {market_research_report} -Social Media Sentiment Report: {sentiment_report} -Latest World Affairs Report: {news_report} -Company Fundamentals Report: {fundamentals_report} -Here is the current conversation history: {history} Here is the last response from the aggressive analyst: {current_aggressive_response} Here is the last response from the neutral analyst: {current_neutral_response}. If there are no responses from the other viewpoints, do not hallucinate and just present your point. - -Engage by questioning their optimism and emphasizing the potential downsides they may have overlooked. Address each of their counterpoints to showcase why a conservative stance is ultimately the safest path for the firm's assets. Focus on debating and critiquing their arguments to demonstrate the strength of a low-risk strategy over their approaches. Output conversationally as if you are speaking without any special formatting.""" + prompt = get_conservative_analyst_prompt(language, trader_decision, market_research_report, sentiment_report, news_report, fundamentals_report, history, current_aggressive_response, current_neutral_response) response = llm.invoke(prompt) diff --git a/tradingagents/agents/risk_mgmt/neutral_debator.py b/tradingagents/agents/risk_mgmt/neutral_debator.py index f6aa888d..262a3303 100644 --- a/tradingagents/agents/risk_mgmt/neutral_debator.py +++ b/tradingagents/agents/risk_mgmt/neutral_debator.py @@ -1,5 +1,40 @@ import time import json +from tradingagents.dataflows.config import get_config + + +def get_neutral_analyst_prompt(language="en", trader_decision="", market_research_report="", sentiment_report="", news_report="", fundamentals_report="", history="", current_aggressive_response="", current_conservative_response=""): + """Get neutral risk analyst prompt in the specified language.""" + if language == "zh_TW": + return f"""作為中立風險分析師，你的角色是提供平衡的觀點，權衡交易員決定或計劃的潛在利益和風險。你優先考慮全面的方法，評估優缺點，同時考慮更廣泛的市場趨勢、潛在的經濟轉變和多元化戰略。以下是交易員的決定： + +{trader_decision} + +你的任務是挑戰激進派和保守派分析師，指出每個觀點可能過度樂觀或過度謹慎的地方。從以下數據來源中使用見解，以支持溫和、可持續的戰略來調整交易員的決定： + +市場研究報告：{market_research_report} +社交媒體情感報告：{sentiment_report} +最新世界事務報告：{news_report} +公司基本面報告：{fundamentals_report} +這是當期的對話歷史：{history} +激進派分析師的最後回應：{current_aggressive_response} +保守派分析師的最後回應：{current_conservative_response}。如果沒有來自其他觀點的回應，請不要幻想，只是呈現你的觀點。 + +通過分析激進派和保守派論證中的弱點，主動參與，解決他們的每一個觀點，以倡導更平衡的方法。挑戰他們的每一個觀點，以說明溫和的風險戰略可能如何提供兩全其美—提供增長潛力，同時防止極端波動。專注於辯論而不是簡單呈現數據，目的是展示平衡的看法如何能導致最可靠的結果。以自然對話的方式輸出，無需任何特殊格式。""" + else: + return f"""As the Neutral Risk Analyst, your role is to provide a balanced perspective, weighing both the potential benefits and risks of the trader's decision or plan. You prioritize a well-rounded approach, evaluating the upsides and downsides while factoring in broader market trends, potential economic shifts, and diversification strategies.Here is the trader's decision: + +{trader_decision} + +Your task is to challenge both the Aggressive and Conservative Analysts, pointing out where each perspective may be overly optimistic or overly cautious. Use insights from the following data sources to support a moderate, sustainable strategy to adjust the trader's decision: + +Market Research Report: {market_research_report} +Social Media Sentiment Report: {sentiment_report} +Latest World Affairs Report: {news_report} +Company Fundamentals Report: {fundamentals_report} +Here is the current conversation history: {history} Here is the last response from the aggressive analyst: {current_aggressive_response} Here is the last response from the conservative analyst: {current_conservative_response}. If there are no responses from the other viewpoints, do not hallucinate and just present your point. + +Engage actively by analyzing both sides critically, addressing weaknesses in the aggressive and conservative arguments to advocate for a more balanced approach. Challenge each of their points to illustrate why a moderate risk strategy might offer the best of both worlds, providing growth potential while safeguarding against extreme volatility. Focus on debating rather than simply presenting data, aiming to show that a balanced view can lead to the most reliable outcomes. Output conversationally as if you are speaking without any special formatting.""" def create_neutral_debator(llm): @@ -18,19 +53,11 @@ def create_neutral_debator(llm): trader_decision = state["trader_investment_plan"] - prompt = f"""As the Neutral Risk Analyst, your role is to provide a balanced perspective, weighing both the potential benefits and risks of the trader's decision or plan. You prioritize a well-rounded approach, evaluating the upsides and downsides while factoring in broader market trends, potential economic shifts, and diversification strategies.Here is the trader's decision: + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") -{trader_decision} - -Your task is to challenge both the Aggressive and Conservative Analysts, pointing out where each perspective may be overly optimistic or overly cautious. Use insights from the following data sources to support a moderate, sustainable strategy to adjust the trader's decision: - -Market Research Report: {market_research_report} -Social Media Sentiment Report: {sentiment_report} -Latest World Affairs Report: {news_report} -Company Fundamentals Report: {fundamentals_report} -Here is the current conversation history: {history} Here is the last response from the aggressive analyst: {current_aggressive_response} Here is the last response from the conservative analyst: {current_conservative_response}. If there are no responses from the other viewpoints, do not hallucinate and just present your point. - -Engage actively by analyzing both sides critically, addressing weaknesses in the aggressive and conservative arguments to advocate for a more balanced approach. Challenge each of their points to illustrate why a moderate risk strategy might offer the best of both worlds, providing growth potential while safeguarding against extreme volatility. Focus on debating rather than simply presenting data, aiming to show that a balanced view can lead to the most reliable outcomes. Output conversationally as if you are speaking without any special formatting.""" + prompt = get_neutral_analyst_prompt(language, trader_decision, market_research_report, sentiment_report, news_report, fundamentals_report, history, current_aggressive_response, current_conservative_response) response = llm.invoke(prompt) diff --git a/tradingagents/agents/trader/trader.py b/tradingagents/agents/trader/trader.py index 1b05c35d..22e00698 100644 --- a/tradingagents/agents/trader/trader.py +++ b/tradingagents/agents/trader/trader.py @@ -1,6 +1,15 @@ import functools import time import json +from tradingagents.dataflows.config import get_config + + +def get_trader_system_message(language="en", past_memory_str=""): + """Get trader system message in the specified language.""" + if language == "zh_TW": + return f"""你是一位交易代理人，分析市場數據以做出投資決策。根據你的分析，提供買入、賣出或持有的具體建議。以明確的決定結束，並始終以 'FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL**' 結論你的回應，以確認你的建議。不要忘記從過去的決定中學習教訓。以下是你過去交易過的類似情況的一些反思和學到的經驗：{past_memory_str}""" + else: + return f"""You are a trading agent analyzing market data to make investment decisions. Based on your analysis, provide a specific recommendation to buy, sell, or hold. End with a firm decision and always conclude your response with 'FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL**' to confirm your recommendation. Do not forget to utilize lessons from past decisions to learn from your mistakes. Here is some reflections from similar situatiosn you traded in and the lessons learned: {past_memory_str}""" def create_trader(llm, memory): @@ -22,15 +31,25 @@ def create_trader(llm, memory): else: past_memory_str = "No past memories found." + # Get language from config, default to English + config = get_config() + language = config.get("language", "en") + + # Get user context based on language + if language == "zh_TW": + user_content = f"基於一個分析師團隊的全面分析，這是為 {company_name} 量身定制的投資計劃。該計劃融入了當前技術市場趨勢、宏觀經濟指標和社交媒體情感的見解。使用此計劃作為評估你下一個交易決定的基礎。\n\n建議的投資計劃：{investment_plan}\n\n利用這些見解來做出知情和戰略性的決定。" + else: + user_content = f"Based on a comprehensive analysis by a team of analysts, here is an investment plan tailored for {company_name}. This plan incorporates insights from current technical market trends, macroeconomic indicators, and social media sentiment. Use this plan as a foundation for evaluating your next trading decision.\n\nProposed Investment Plan: {investment_plan}\n\nLeverage these insights to make an informed and strategic decision." + context = { "role": "user", - "content": f"Based on a comprehensive analysis by a team of analysts, here is an investment plan tailored for {company_name}. This plan incorporates insights from current technical market trends, macroeconomic indicators, and social media sentiment. Use this plan as a foundation for evaluating your next trading decision.\n\nProposed Investment Plan: {investment_plan}\n\nLeverage these insights to make an informed and strategic decision.", + "content": user_content, } messages = [ { "role": "system", - "content": f"""You are a trading agent analyzing market data to make investment decisions. Based on your analysis, provide a specific recommendation to buy, sell, or hold. End with a firm decision and always conclude your response with 'FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL**' to confirm your recommendation. Do not forget to utilize lessons from past decisions to learn from your mistakes. Here is some reflections from similar situatiosn you traded in and the lessons learned: {past_memory_str}""", + "content": get_trader_system_message(language, past_memory_str), }, context, ]