Four a.m. in Shanghai's Lujiazui. Financial‑district lights still glittered, but the light inside Mozi's trading room was deliberately dim. Only data flowing on the three surrounding screens flickered quietly in the dark like a galaxy. He had just completed the final stress‑test of the [Adaptive Dual‑Core Model]; now gazing at the smoothly ascending capital curve on screen, his eyes showed no trace of joy.
This model's birth stemmed from his deep insight into market nature. Markets never exist in a single state; they resemble a patient with multiple personalities: sometimes anxiously jumping repeatedly within narrow ranges—that's the hunting ground of the [Volatility Model]; sometimes like an awakened behemoth, bursting with astonishing power toward one direction—that's where the [Trend Model] excels.
The key problem lies in identification. Like a doctor must accurately diagnose which personality state the patient is in to prescribe appropriately.
Mozi's **market‑state identification algorithm** is such a diagnostic system. It doesn't predict prices; it judges what state the market is in by analyzing data from seven dimensions:
First, **volatility‑structure analysis**. He designed a multi‑time‑scale volatility‑monitoring system, focusing not only on absolute values of historical volatility, but especially on relative relationships between volatilities at different cycles. When short‑term volatility is significantly higher than long‑term and shows sustained amplification, that's often a sign of trend beginning; when volatilities across cycles compress into extremely narrow ranges, the market enters typical choppy state.
Second, **price‑sequence autocorrelation detection**. He introduced an improved Hurst‑exponent calculation model, more sensitively capturing long‑term memory effects in price sequences. In trending markets, this index noticeably leans above 0.5, showing price movement persistence; in choppy markets, it approaches 0.5 or slightly lower, indicating movement closer to random walk.
Third, **technical‑indicator synergy analysis**. He developed an indicator‑consistency scoring system, weighting and scoring ten common technical indicators like RSI, MACD, Bollinger Bands. When these indicators give contradictory signals, the system assigns low scores, indicating chaotic market state; when most indicators resonate, system gives high scores, confirming trend validity.
Fourth, **market‑breadth monitoring**. Though his main battlefield is the gold market, he simultaneously monitors breadth indicators of global major stock indices—advance‑decline ratios, new‑high/new‑low stock counts, etc. These seemingly unrelated data often provide early warning of market‑sentiment shifts.
Fifth, **order‑flow analysis**. Through accessing higher‑level market‑data feeds, his system can analyze large‑order flow direction and strength in real time. Sustained aggressive buying or selling is important evidence for judging trend authenticity.
Sixth, **options‑market sentiment indicator**. He constructed an options‑skew index, measuring market fear and greed by analyzing relative prices of call and put options. This indicator often has leading significance at trend turning points.
Seventh, **macro‑event impact assessment**. He quantifies events like geopolitics, central‑bank meetings, major economic‑data releases, scoring their potential impact intensity and duration on markets.
All these data undergo classification training by a five‑layer neural network, finally outputting three probability values: choppy‑market probability, trending‑market probability, transitional‑market probability. This is the core basis of the **model‑switching logic**.
When choppy‑market probability exceeds 65%, the system automatically switches to [Volatility Model]‑dominant mode. This mode adopts mean‑reversion strategies, operating opposite‑direction when price touches upper/lower volatility‑range bounds; stop‑losses set narrow, pursuing cumulative gains under high win rate.
When trending‑market probability exceeds 60%, the [Trend Model] takes over trading. It establishes positions along trend direction, using trailing stops to protect profits, letting profits run. In this mode, the system tolerates relatively large price retracements to capture main trend waves.
Most complex is the transitional‑market state. When all three probability values fall below critical thresholds, or probability distribution changes rapidly, the system enters "cautious exploration" mode: position limits at one‑third of normal level; both models' signals run but with stricter stop‑loss conditions. The goal now isn't profit but collecting more data on market behavior, preparing for next state switch.
Three months of live‑trading testing proved this fusion model indeed effective. Maximum drawdown reduced from 12% under single models to 6.8%; Sharpe ratio increased from 1.5 to 2.2. More importantly, it successfully avoided several fatal market‑style shifts.
Yet now, Mozi's attention wasn't on those beautiful data.
His gaze drifted occasionally to the side auxiliary screen, showing two unread emails. One from Yue'er, subject "Rethinking Mathematical Determinism"; the other from Xiuxiu, title simple: "Vacuum level breakthrough 10^‑7 Pa."
This reminded him of last night's trans‑ocean video call. Yue'er on screen excitedly explaining her new thoughts on the P/NP problem, blackboard covered with complex mathematical symbols. The way her eyes glowed when speaking reminded him of brightest stars in night sky. And when she occasionally showed worry about proof uncertainty, that mixture of strength and fragility always made him want to cross the screen to comfort her.
And Xiuxiu… his mind pictured visiting her lab last week. Wearing antistatic clothing, she focused intently adjusting vacuum‑pump parameters, fine sweat beading her forehead. When she finally broke through that technical bottleneck, turning to give him a tired yet radiant smile—he felt his heartbeat skip a beat.
These two utterly different emotions resembled the volatile and trending states in his model, coexisting yet so distinct.
For Yue'er, it's intellectual‑level deep attraction. Her every mathematical idea seemed to open a new window before him, letting him see the ultimate beauty of the rational world. Their exchanges often unfold at abstract‑concept level, discussing truth's essence, order's boundaries. This spiritual resonance was something he'd never experienced elsewhere.
For Xiuxiu, it's ideal‑level strong resonance. What she's doing is the best practice of his "using capital to master capital" ideal. Each time he heard her recounting technological‑breakthrough difficulties, each time he saw her resilience under pressure, made him more certain his chosen path was correct. That urge to lend a hand in her journey felt so natural, strong.
What confused him more was these two emotions didn't exclude each other. Like his dual‑core model can simultaneously monitor different market states, his heart seemed able to hold both different‑quality feelings simultaneously. The excitement discussing mathematical philosophy with Yue'er, and the gratification seeing Xiuxiu overcome a technical barrier—both so real, intense.
But this "multi‑state coexistence" of emotions clearly exceeded conventional social‑cognition frames. He knew that in the real world, people expect either‑or choices, not complex probability distributions.
He pulled up the model's historical‑operation log, looking at those clear state‑switch signals, couldn't help a bitter smile. If the emotional world could be so clear—when feelings for A exceed a certain threshold, automatically switch to A‑mode; when B‑feeling index rises, smoothly transition to B‑state.
But reality was these two feelings were like two different‑frequency waves, coexisting in his inner world, intertwining, yet not canceling each other.
What unsettled him more was he found himself starting to anticipate each communication with them. Receiving Yue'er's new email on mathematical thoughts, he'd unconsciously smile; hearing Xiuxiu conquered another technical hurdle, he'd genuinely feel happy. This emotional investment already surpassed his initial expectations.
He recalled last trip to Beijing, deliberately detouring to see Xiuxiu. Standing outside the lab, watching her focused profile—that moment he clearly realized this woman's weight in his heart already far exceeded an ideal companion.
And just the day before, the video call with Yue'er lasted till dawn. When she finally understood a mathematical analogy he proposed, the light of comprehension flashing in her eyes—the joy he felt was so real, deep.
This emotional contradiction was harder to solve than the most complex financial model he'd encountered. In financial markets, he could manage risk through strict discipline and clear rules. But in the emotional world, these tools all failed.
He tried using risk‑management thinking to analyze the situation: worst‑case scenario? possible loss magnitude? any hedging strategies?
But soon he realized this analogy was futile. Emotions aren't asset portfolios; can't be optimized via Sharpe ratios. Each genuine feeling is unique, carries irreplaceable value.
Perhaps the root lay in him trying to use rational frameworks to understand non‑rational emotions. Like he couldn't demand markets behave according to his models, he couldn't demand his own feelings conform to some logical norm.
He shut down the trading system, walked to the floor‑to‑ceiling window. East already paling, morning mist spreading over Huangpu River. This financial world he could decipher with algorithms appeared so clear, orderly in dawn light. Yet his inner emotional world resembled the mist outside—hazy, elusive.
He knew this problem had no perfect solution. Like his dual‑core model must switch between different market states, in the emotional domain he must learn to accept this complexity. Perhaps treating each feeling sincerely while respecting each person's independence and choices was the only way out.
But that meant he must face possible hurt and pain. Whether hurting either of them, or hurting himself—both outcomes he wished to avoid.
He took a deep breath, made a decision: let it follow its natural course. Like his model adjusts automatically based on market state, in the emotional world he needed to stay open and sincere, let time give answers.
This decision couldn't resolve all contradictions, but at least he needn't force himself into either‑or choices. Perhaps in the emotional domain, perfect solutions never existed. Like financial markets always hold uncertainty, the emotional world always accompanies risk and unknown.
He returned to the trading desk, began preparing for the new day's work. On screen, the [Adaptive Dual‑Core Model] stood ready, awaiting market opening. His heart, though still filled with contradiction, no longer tried forcibly simplifying those complex emotions.
Perhaps accepting complexity itself is a kind of maturity. Whether in financial markets, or in the emotional world.