All (116)Personal Introduction (1)AI Summary (8)Project Management (5)Investment Strategy (1)Financial Market Analysis (5)AI Software Engineering (9)AI Learning Methodology (1)AI Interview Design (1)AI Research (8)Content Management (9)Capital Protracted War (18)Cognitive Development (1)Philosophical Reflection (3)Entrepreneurship (1)AI Tools Development (9)Product Development (3)Troubleshooting (2)AI Cost Analysis (1)System Architecture (1)Technical Log (3)Quantitative Finance (6)AI Social Systems (3)Personal Reflection (1)
Signal Trader: Design of the Persistent War Live Trading Module
Capital Protracted War
👤 Fintech developers, quantitative trading strategists, system architects
This article details the design philosophy and implementation specifics of the Signal Trader module in the Persistent War live trading system. As a signal trader, Signal Trader uses Push mode to actively receive signals from the signal side, outputs orders to exchanges, supporting real-time performance and flexibility. Signals are designed with only direction (long 1, short -1, neutral 0) and no intensity, simplifying processing and avoiding overfitting. The stop-loss ratio is determined as the responsibility of the signal side, used for position sizing based on risk, with update frequency lower than the signals themselves. Multi-investor allocation is based on isolation principles, allowing investors to independently subscribe to signals and specify profit-taking ratios and investment amounts, with Signal Trader allocating orders according to VC proportions. The audit system records all actions, facilitating analysis and traceability.
- ✨ Signal Trader uses Push mode to process signals, achieving high real-time performance and flexibility
- ✨ Signals are designed with ternary values (1, -1, 0) and no intensity, simplifying logic and avoiding overfitting
- ✨ Stop-loss ratio is the responsibility of the signal side, used for position sizing based on risk
- ✨ Multi-investor allocation is based on isolation principles, supporting personalized subscriptions and VC proportion distribution
- ✨ The audit system records all actions, providing query interfaces for analysis and traceability
📅 2026-03-12 · 1,122 words · ~5 min read
Signal Trader Interview Summary and Event Sourcing Design Draft
Capital Protracted War
👤 Financial trading system engineers, product managers, auditors, focusing on system design, allocation precision, and auditability.
This document records the Signal Trader design interview around LOGS/71, aiming to converge concepts into implementable system rules. Key contents include: Signal Trader must follow the capital persistence principle, the minimum signal semantics are product_id + direction, nominal value decision authority lies with Signal Trader, multiple signals are executed using netting consolidation, subscription ID serves as the allocation granularity, and the isolation principle must not be violated. Regarding funds and allocation, independent investor buffer pools are established, with VC calculations supporting lazy evaluation. Execution strategy prioritizes market orders, and accounting adopts a dual-track system. Exception handling emphasizes that active system liquidation is not allowed during positions. The audit system employs an event sourcing mechanism, where audit logs are event streams, and state is reconstructed via reducer replay, ensuring traceability, consistency, and replayability. The article also lists the v1 minimum event list and next steps, aiming to advance the system toward provable correctness and enter an auditable, scalable, and production-ready engineering phase.
- ✨ Signal Trader core constraints include position sizing based on loss, signal semantics, nominal value decision authority, etc.
- ✨ Adopts an event sourcing audit system where audit logs are event streams and state is reconstructed via reducer replay.
- ✨ Multi-investor allocation uses subscription ID as the granularity, establishes independent buffer pools, and the isolation principle must not be violated.
📅 2026-03-12 · 770 words · ~4 min read
Trickle Fund
Capital Protracted War
👤 Readers interested in fund design, financial product naming, or investment concepts, particularly those focused on innovative financial models.
This article explores the process of naming the fund, from the initial idea of 'Persistence War Fund' to the final determination as 'Trickle Fund'. The author explains in detail the water-electricity pun meaning of the word 'trickle': the water aspect represents a small but continuous cash flow pattern, while the electricity aspect refers to trickle charging technology, aligning with the fund's design where investors authorize constant cash flow, the fund outputs cash flow after profit-taking, and pre-charged balances earn current returns in a charge-discharge cycle system. The article emphasizes that a good name should be concise, memorable, and withstand explanation, and points out that 'Trickle' in English also has intuitive meanings such as 'trickle-down effect' and 'flowing slowly'.
- ✨ The fund was ultimately named 'Trickle Fund', replacing the initial idea of 'Persistence War Fund'.
- ✨ The word 'trickle' has a water-electricity pun meaning: water represents small but continuous cash flow, while electricity refers to trickle charging technology, aligning with the fund's charge-discharge cycle design.
- ✨ 'Trickle' in English has rich meanings, including the trickle-down effect and flowing slowly, making the name concise, memorable, and able to withstand explanation.
📅 2026-02-13 · 308 words · ~2 min read
Responses Before the Capital Persistence War Live Trading
Capital Protracted War
👤 Investors and readers interested in high-yield investment strategies, risk management, and Crypto trading
This article is the author's response to doubts before the Capital Persistence War live trading. Regarding the excessively high yield issue, the author explains that high returns stem from taking on predictable high risks and distinguishes between yield calculations based on cash flow versus total assets. Concerning tail risks, the author emphasizes prevention through zero-debt guarantees and exchange liquidation mechanisms, using the Crypto market as an example to illustrate their effectiveness. For article focus, the author acknowledges the fragmented nature of logs and promises to improve readability through AI summaries. The core viewpoint is that the Capital Persistence War strategy pursues high returns, high risks, and high capacity, with key aspects being risk expectation management and technical risk control.
- ✨ High yield rates stem from taking on predictable high risks, with yield calculations based on cash flow rather than total assets
- ✨ Tail risks are prevented through zero-debt guarantees and exchange liquidation mechanisms, validated as effective in the Crypto market
- ✨ The Capital Persistence War strategy aims to balance high returns, high risks, and high capacity
- ✨ Article focus will be improved through AI summaries to facilitate reader follow-ups
📅 2026-02-12 · 1,277 words · ~6 min read
Design Guidelines for Fund Structures in Capital Endurance Strategies
Capital Protracted War
👤 Fund investors, fund managers, financial innovation researchers
This article proposes an innovative fund design model, where investors authorize a fixed cash flow rate (e.g., $1/day) instead of making a lump-sum capital investment. The fund determines position sizes and profit distribution based on this authorized cash flow to ensure fairness. The model eliminates traditional management fees and performance fees, with managers earning profits through relaxed profit-taking multiples to avoid conflicts of interest. Additionally, it removes high-water marks to simplify return processes and plans to integrate with Expert Advisors (EAs) to achieve a closed-loop investment system and enhance capital efficiency.
- ✨ Investors authorize a fixed cash flow rate to determine position sizes and profit distribution
- ✨ Eliminates management fees and performance fees, with managers earning profits through relaxed profit-taking multiples
- ✨ Removes high-water marks to simplify return processes
- ✨ Plans to integrate with Expert Advisors (EAs) for automated management and capital efficiency optimization
📅 2026-02-12 · 815 words · ~4 min read
FMAB Signal Performs Excellently, Ready for Live Trading Deployment
Capital Protracted War
👤 Cryptocurrency traders, quantitative strategy developers, investment analysts
This article reports the excellent performance of the FMAB signal on ETH, with a baseline return of 100% and an increase to 4600%~120000% after anti-Martingale betting, far surpassing other strategies. The author announces plans for live trading, emphasizing the need to prepare capital for a long-term engineering effort. It also notes that the FMA signal performed poorly, causing drawdowns, and reflects on insufficiently scientific position management. Based on test results from February 11, 2026, the article aims to share signal strategy validation and live trading deployment plans.
- ✨ FMAB signal achieved a baseline return of 100% on ETH, increased to 4600%~120000% after anti-Martingale betting
- ✨ Preparing for live trading, requiring capital preparation for a long-term engineering effort
- ✨ FMA signal performed poorly, causing drawdowns, reflecting on insufficiently scientific position management
📅 2026-02-11 · 213 words · ~1 min read
Capital Protracted War: A Strategic Framework for Individual Investors to Transcend Class
Capital Protracted War
👤 Individual investors, especially those seeking to transcend class, interested in programmatic trading and risk control, and new readers.
This article systematically elaborates on the 'Capital Protracted War' investment strategic framework proposed by zccz14 in 2026. Drawing wisdom from Mao Zedong's 'On Protracted War' and combining it with the anti-Martingale capital management strategy, it proposes the core proposition: 'Use losses you can afford to gamble for returns you 'cannot afford'.' Through four principles—controllable losses, advantage accumulation, pressing the advantage, and clear objectives—it refutes theories of inevitable individual failure, all-in for quick riches, and steady development. It aims to achieve exponential growth of personal capital, ultimately allowing investors to 'exit the market after victory.' The article details its mathematical formalization framework, key concept extensions (such as the 'power generation/consumption' framework), experimental validation systems (including synthetic data and real data validation with BTC and ETH), and looks forward to future directions like community-based trading. As of February 2026, the theory has completed experimental validation and is preparing to enter live trading.
- ✨ Core proposition: Use controllable losses to pursue high returns, achieve exponential growth, and ultimately exit the market.
- ✨ Four principles: Controllable losses, advantage accumulation, pressing the advantage, and clear objectives.
- ✨ Mathematical framework: Based on risk control lines, dual-account systems, and anti-Martingale position calculations.
- ✨ Experimental validation: Shows strategy effectiveness in synthetic data and real BTC/ETH data.
- ✨ Key concepts: Such as the 'power generation/consumption' framework, position sizing based on losses, and essential differences from the Martingale strategy.
📅 2026-02-11 · 4,494 words · ~20 min read
Performance Analysis of Anti-Martingale Betting Strategy in BTC Trading
Capital Protracted War
👤 Quantitative traders, cryptocurrency investors, strategy developers, financial data analysts
This article analyzes the application effectiveness of the Anti-Martingale betting strategy in BTC trading. By importing BTC data for testing, it was found that benchmark signals performed poorly on 5m data, while the trend-following dual moving average strategy performed excellently on 15m, 30m, and 1h data. The Anti-Martingale betting strategy performed outstandingly on BTC 1h data, achieving a return rate of 9994.17%, far exceeding the benchmark strategy's 18.94%, with a smoother net value curve. The article points out the existence of favorable trend clustering phenomena, and the Anti-Martingale strategy can effectively utilize this characteristic to enhance returns. Meanwhile, through an extreme parameter case (1024x TP), it emphasizes the importance of signal strategy quality. Finally, it proposes future research directions based on the three-body dynamics hypothesis to design gating mechanisms.
- ✨ The Anti-Martingale betting strategy achieved a return rate of 9994.17% on BTC 1h data, significantly outperforming the benchmark strategy.
- ✨ Favorable trend clustering phenomena exist, and the Anti-Martingale strategy can effectively utilize this characteristic to enhance overall returns.
- ✨ Signal strategy quality has a decisive impact on the effectiveness of the Anti-Martingale betting strategy; extreme parameters may lead to net value resetting to zero.
- ✨ Future optimizations could involve designing gating mechanisms based on the three-body dynamics hypothesis to improve the periodic performance of trend-following strategies.
📅 2026-02-10 · 498 words · ~3 min read
Sand Table Capital Persistence War Experimental Framework Released
Capital Protracted War
👤 Developers, analysts, and decision-makers interested in capital operations, strategic decision-making, experimental frameworks, or npm package development
This article documents the author's release of the capital persistence war experimental framework on February 4, 2026. Named Sand Table, with package name sandt, it has been published on the npm platform. The author explains that the naming inspiration comes from sand table wargaming, emphasizing that the framework aims to simulate capital operations and strategic decision-making, conducting experiments from micro samples to macro market levels and generating reports to aid decision-making. The author also discusses reasons for the package name choice, including conciseness, command-line convenience, and potential extended meanings (such as delta time or Strategy & Tactics), hoping the project avoids being purely theoretical and serves practical purposes.
- ✨ Document date is noon on February 4, 2026
- ✨ Released the Sand Table capital persistence war experimental framework
- ✨ Package name is sandt, published on the npm platform
- ✨ Naming inspiration comes from sand table wargaming
- ✨ Framework is used to simulate capital operations and strategic decision-making
📅 2026-02-04 · 220 words · ~1 min read
AI-Assisted Capital Persistence Experiments and Community-Based Subjective Trading
Capital Protracted War
👤 Quantitative traders, AI application researchers, investment strategy developers, professionals interested in combining subjective and quantitative approaches
Based on experimental experiences from February 3, 2026, this article discusses AI's role in improving efficiency in capital persistence experiments, emphasizing that redesigning experiments can systematically evaluate signal strategies and betting strategies. The author argues that subjective trading should be limited to signal strategy design, avoiding interference with betting strategies to overcome irrational decision-making in human fund management. To address potential issues where humans might peek at betting accounts, a community-based trading model is proposed: multiple subjective traders provide signal strategies, a consolidated betting account is managed by programs, and profits are distributed based on contributions, balancing fairness and efficiency to encourage better signal strategy design and control risks.
- ✨ AI enhances the efficiency of capital persistence experiments, achieving a qualitative leap
- ✨ Redesigning experiments systematically evaluates signal strategies and betting strategies
- ✨ Subjective trading should only apply to signal strategies, avoiding interference with betting strategies
- ✨ Human fund management suffers from irrational decision-making, requiring programmatic execution
- ✨ Community-based trading prevents subjective traders from adjusting strategies based on betting accounts
📅 2026-02-03 · 883 words · ~4 min read
Capital Persistence War Experiment Design
Capital Protracted War
👤 Quantitative trading researchers, algorithmic trading developers, financial engineering professionals, and traders interested in fund management and risk control strategies.
This article elaborates on a quantitative trading experiment design named 'Capital Persistence War,' with the core concept of using a benchmark account (always trading with 1 unit position) to guide the fund management of a betting account. The betting account employs the Anti-Martingale strategy to dynamically adjust positions, with key elements including time scale t, unrealized/realized profit and loss, risk control line (RiskLine), venture capital (VC), benchmark stop-loss amount (StopLoss), and position size calculation. The document also defines trigger conditions and handling procedures for profit-taking and stop-loss events, emphasizing maximizing venture capital utilization efficiency under risk control conditions and establishing an observation period mechanism. Overall, it aims to build a systematic trading framework to optimize fund management and risk control.
- ✨ Dynamic fund management design based on benchmark accounts and the Anti-Martingale strategy
- ✨ Achieving strict risk control through risk control line and venture capital (VC)
- ✨ Calculating aggressive positions based on benchmark stop-loss amount (StopLoss) to maximize capital efficiency
- ✨ Defining trigger conditions and state reset rules for profit-taking and stop-loss events
- ✨ Establishing an observation period mechanism to pause trading when parameters are zero
📅 2026-02-02 · 874 words · ~4 min read
Three-Layer Structure and Experimental Design Reconstruction of Backtesting Systems
Capital Protracted War
👤 Quantitative investment researchers, backtesting system developers, investment strategy analysts
This paper proposes reconstructing the backtesting system into a three-layer structure: market sequences as investment objects, signal strategies as responses, and betting strategies as investment subjects. The author suggests splitting each experiment into combinations of these three components and emphasizes the need for a thorough revision of experimental design and evaluation systems. The new evaluation focus shifts from peak expectations to the frequency and distribution characteristics of profit-taking events, particularly the average time interval of profit-taking events given M_T, to provide more meaningful investment guidance.
- ✨ The backtesting system should be reconstructed into a three-layer structure of market sequences, signal strategies, and betting strategies
- ✨ Market sequences are investment objects, which can be generated from synthetic or historical data
- ✨ Signal strategies are responses to market sequences, producing buy/sell signals
- ✨ Betting strategies determine capital allocation and risk management, reflecting investment subject preferences
- ✨ Experimental design requires evaluating each signal strategy under all market sequences and betting strategies
📅 2026-02-01 · 571 words · ~3 min read
Experience with OpenClaw and Opus Models, and Capital Endurance Battle Experiment
Capital Protracted War
👤 Tech enthusiasts interested in AI tool deployment and model comparisons, as well as researchers or investors focused on quantitative trading strategies.
This article documents the author's experience using the OpenClaw AI tool on January 31, 2026, including the process of deploying it on an Alibaba Cloud ECS server and connecting it to a Feishu robot. The author notes that OpenClaw is more suitable for local deployment, as cloud servers are costly and functionality is limited by tool installations like browsers. The article compares the performance of MiniMax M2.1 and Opus models, concluding that Opus is significantly better for programming tasks. The author used OpenCode+Opus to complete the code for the Capital Endurance Battle experiment, open-sourced it on GitHub, and shared preliminary findings: in a GBM high-volatility market model, a mean reversion strategy combined with anti-Martingale money management can achieve exponential capital growth under transaction costs, while a trend-following strategy cannot, highlighting the advantage of high-win-rate strategies. The author states that further validation is needed and invites attention to the open-source project.
- ✨ The OpenClaw AI tool can be deployed on a cloud server and connected to a Feishu robot, but it's more suitable for use on a local idle machine.
- ✨ Cloud servers are expensive, and OpenClaw's functionality is limited by tool installations such as browsers.
- ✨ OpenClaw equipped with MiniMax M2.1 performed poorly, and the author considers this model weak.
- ✨ The Opus model is significantly more effective than MiniMax M2.1 for programming tasks and is praised as the SOTA model for coding.
- ✨ The author used their GitHub Copilot Opus quota to complete the Capital Endurance Battle experiment code and open-sourced it.
📅 2026-01-31 · 385 words · ~2 min read
Capital Endurance War: Reiteration and Discussion of Investment Philosophy
Capital Protracted War
👤 Individual investors, fund managers, professionals interested in exponential growth investment strategies
Based on discussions from a business seminar on January 29, 2026, this article first reviews the losses of the Midas strategy on HYPE tokens, analyzing market characteristics and strategy limitations. The core section reiterates the investment philosophy of Capital Endurance War, proposing a clear distinction between positive cash flow (power generation) and negative cash flow (power consumption) investment intentions, emphasizing the importance of matching tools with purposes. The article critiques the linear thinking of traditional investments that pursue stable annualized returns, advocating for achieving exponential capital growth through continuous cash inflows and dynamic position management under clear risk control lines. Finally, the article addresses common questions, clarifies the differences between Capital Endurance War and strategies like Martingale or fixed-ratio investing, and notes that its core is goal-oriented rather than tied to specific strategies.
- ✨ Midas strategy losses stem from small-cap token characteristics and regression strategy limitations
- ✨ Investments should distinguish between positive cash flow (power generation) and negative cash flow (power consumption) intentions
- ✨ Tool design should focus on a single purpose, allowing investors to freely combine generators and consumers
- ✨ Traditional investments pursue stable annualized returns, while Capital Endurance War aims for exponential growth
- ✨ The Capital Endurance War framework includes clear risk boundaries, continuous cash inflows, dynamic position management, and redefined victory conditions
📅 2026-01-30 · 2,958 words · ~14 min read
The Nature, Types, and Risk Analysis of Leverage
Capital Protracted War
👤 Investors, financial professionals, individuals interested in leverage and risk management
Starting from the objective existence of leverage, this article points out that leverage is ubiquitous and does not disappear due to subjective will, with risks lying in control rather than leverage itself. The article equates leverage with volatility in mathematical essence, suggesting leverage can be reduced to volatility. It distinguishes in detail between on-exchange leverage (e.g., margin trading) and off-exchange leverage (e.g., borrowing, funds), noting that on-exchange leverage has no interest cost but is limited, while off-exchange leverage is flexible but incurs interest or profit costs. It specifically analyzes the essence of fund leverage, achieving high leverage through performance fees, and provides a leverage-adjusted volatility formula. Finally, it emphasizes that individuals can obtain leverage through strategies like pyramiding, suggesting that future funds may serve more as psychological comfort than actual leverage tools.
- ✨ Leverage is objectively existing and ubiquitous, with risks stemming from control rather than leverage itself
- ✨ Leverage and volatility are consistent in mathematical essence and can be reduced to each other
- ✨ On-exchange leverage is achieved through exchange tools, typically with no interest cost
- ✨ Off-exchange leverage is obtained through borrowing or funds, incurring interest or profit costs
- ✨ Funds achieve high off-exchange leverage through performance fees, combined with on-exchange leverage to amplify volatility
📅 2026-01-24 · 816 words · ~4 min read
Capital Endurance War: Strategic Practice Guide for Individual Investors
Capital Protracted War
👤 Individual investors, people interested in investment strategies and practices, AI tool users
This article is a practical guide on the Capital Endurance War strategy, where the author abandons academic packaging and advocates for plain language explanation. The core idea is that the fundamental purpose of Capital Endurance War is to allow individual investors to leave the market after victory, not to pursue stable profits. The article discusses the difference between this strategy and lotteries, pointing out that the market is a game of strategy rather than a pure probability game; it addresses whether the strategy would still be profitable if everyone adopted it, emphasizing that differences in underlying strategies can avoid crowding; and mentions counterarguments to collective action problems. The author also plans to validate the strategy through backtesting and shares interactions with the AI tool OpenCode, deciding to build an adversarial generative Agents framework.
- ✨ The fundamental purpose of Capital Endurance War is to allow individual investors to leave the market after victory, not to pursue stable profits.
- ✨ The market is a game of strategy disguised as a probability game, where investors can increase their win rate through strategies.
- ✨ Capital Endurance War does not assume a uniform underlying strategy; differences can avoid collective action problems and crowding effects.
- ✨ Plans to validate the strategy through backtesting, focusing on T_S performance and failure thresholds.
- ✨ The author interacted with the AI tool OpenCode and decided to build an adversarial generative Agents framework.
📅 2026-01-21 · 846 words · ~4 min read
Capital Protracted War: A Strategy for Individual Investors to Transcend Social Classes
Capital Protracted War
👤 Individual investors seeking leapfrog wealth growth, especially those dissatisfied with traditional investment methods and willing to embrace new strategies.
This article critiques three mainstream investment views: the inevitability of individual failure, the all-in gamble for quick riches, and steady development theory. It proposes 'Capital Protracted War' as a fourth approach for individual investors to transcend social classes. The core idea is to use minimal acceptable risk to pursue victory-level high returns, achieving leapfrog wealth growth by controlling loss rates, accumulating advantages through programmatic trading, and adding positions with floating profits to press the advantage. The article emphasizes the need for stable cash flow, using programmatic trading to avoid emotional decisions, and accepting the possibility of failure, with the ultimate goal of achieving exponential wealth growth under controllable losses.
- ✨ Using controllable losses to pursue extremely high returns is key to transcending social classes
- ✨ Refutes three erroneous views: the inevitability of individual failure, the all-in gamble for quick riches, and steady development theory
- ✨ Must prepare stable cash flow to control maximum loss rates
- ✨ Use programmatic trading to avoid emotional decisions and accumulate advantages
- ✨ Immediately add positions with floating profits when profitable to press the advantage
📅 2026-01-17 · 5,429 words · ~24 min read
Work Log: Reflections and Practice on the Floating Profit Pyramid Strategy
Capital Protracted War
👤 Traders and investors interested in capital management and trading strategies, as well as individuals focused on work logs and AI applications.
This article is a work log documenting the author's daily work and reflections while under the weather. The core content revolves around the 'floating profit pyramid' capital management strategy: the author draws wisdom from reading 'On Protracted War' to plan related articles; recalls that the strategy's inception stemmed from thoughts on futures trading stories years ago, and recently systematized it when pondering how to earn 20 million in a year; further validates its potential through a case shared by Mage (an All-in strategy from $12 to $100,000 using floating profits). The author believes that implementing the floating profit pyramid during periods of volatility clustering in market trading may achieve rapid capital growth. The log also mentions writing purposes including recording work insights, preparing for AI training, and future project planning, and thanks team support for enabling focused thinking.
- ✨ Floating profit pyramid is a promising capital management strategy, originating from the author's thoughts years ago and now systematized.
- ✨ Effectiveness of the strategy is supported by historical cases (e.g., 'On Protracted War') and real-world examples (e.g., All-in strategy from $12 to $100,000).
- ✨ The author believes that floating profit pyramid may achieve rapid capital growth during periods of market volatility clustering.
- ✨ The work log serves to record reflections, prepare for AI training, and plan future projects.
- ✨ Team support enables the author to focus on strategy research and macro planning.
📅 2026-01-17 · 488 words · ~3 min read