Who is controlling TRANSTHERA-B (02617)? Quantitative game behind the four-stage dismantling of 4.5 billion transactions

On September 16th, the Hong Kong stock market witnessed an astonishing extreme market situation. TRANSTHERA-B (02617) experienced a roller-coaster-like trend from skyrocketing to crashing in a single day, with an early surge of nearly 60% in the morning but a sharp decline in the afternoon leading to a rapid expansion of over 58% in losses, with a staggering intraday volatility of close to 124%. By the end of the trading day, its stock price fell to 192 Hong Kong dollars, and its total market value also dropped from the high to 76.204 billion Hong Kong dollars. With a trading volume exceeding 4.5 billion Hong Kong dollars and a turnover rate of 4.13%, there was a precise game dominated by quantitative funds. Extreme volatility exposes liquidity traps From the market data perspective, the performance of China Northwest Transport-B on that day displayed several unusual characteristics. The stock opened at 477.2 Hong Kong dollars, a 15% gap up from the previous day's closing price of 415 Hong Kong dollars, showing a strong bullish sentiment accumulated overnight. After the opening, the stock price continued to soar, reaching a historical high of 679.5 Hong Kong dollars, a nearly 60% increase. It is noteworthy that in response to the abnormal fluctuations in the company's stock price and trading volume in the morning, China Northwest Transport-B issued an announcement during the midday break stating that there had been recent abnormal changes in the trading price and volume. The board of directors confirmed that they were unaware of any reasons that caused such abnormal changes in the stock price and trading volume. However, the good times did not last long, with the stock price shifting dramatically in the afternoon, beginning a freefall and hitting a low of 165 Hong Kong dollars before closing at 192 Hong Kong dollars, marking a 53.73% decline for the day. Such extreme volatility is extremely rare in mature capital markets, and the 123.98% volatility clearly indicates that the market's price discovery mechanism completely failed in a short period of time. What is even more surprising is that despite a trading volume of 45.43 billion Hong Kong dollars, the turnover rate of the stock was only 4.13%. This combination of low turnover rate and high volatility reveals the typical characteristics of quantitative trading - true panic selling and buying only occurring in a small number of shares while most shares remain "locked" with shallow market depth. The market data further reveals the existence of a liquidity trap. The extreme ratio of buy orders in the first ten levels to sell orders in the first ten levels of 90.91% to 9.09% indicates that buy orders are all placed at low positions far from the market price, waiting to "pick up bargains", while there is a lack of proactive buy orders at the current price level. It is important to note that despite the trading volume reaching 45.43 billion Hong Kong dollars, the turnover rate of the stock was only 4.13%. This combination of data reveals the typical characteristics of quantitative trading: true panic selling and buying only occurring in a handful of shares while most shares remain "locked" with shallow market depth. From the perspective of investor structure, China Northwest Transport-B's shareholder groups show a clear polarization: one side consists of strategic investors who are optimistic about the company's fundamentals and hold their shares steady without easily selling them, while the other side consists of short-term traders represented by quantitative funds who engage in high-frequency trading using algorithms. When the latter collectively shifts to selling, due to the former holding onto their shares, there is not enough buying to support the market, leading to a significant decline in stock prices from a few sell orders. Transaction by transaction data provides more details. At 15:59, there were consecutive small trades of 500 shares each (exactly the lot size) at 187.7 Hong Kong dollars. This "one lot at a time" trading pattern is usually when algorithmic trading is testing market liquidity or trying to precisely control the closing price to provide a reference anchor for the next trading day's algorithms. Deconstructing the operation mechanism behind algorithmic gaming The extreme market situation of China Northwest Transport-B perfectly showcases the typical operation path of domestic quantitative institutions borrowing tactics from the US stock market, which can be divided into four stages. In the first stage, liquidity attraction and short selling layout. Quantitative funds first use the high valuation and low liquidity characteristics unique to biotech stocks to slightly raise the stock price through algorithms, attracting trend traders and retail investors chasing the trend. The spike to 679 Hong Kong dollars at the opening is likely to trigger programmed buy orders and stop-loss orders for short selling positions, creating an artificial short-selling market. In the second stage, liquidity withdrawal and flash crash trigger. After the stock price is pushed to an extreme high, the main quantitative funds will instantly withdraw all buy orders providing liquidity, while initiating algorithmic sell orders. Due to the shallow depth of market buy orders, the first sell order will lead to a significant price drop. The lowest point of 165 Hong Kong dollars is likely to have triggered risk control lines in certain quantitative models, causing a chain reaction of programmed sell-offs. In the third stage, shorting shorts and spiraling downward. The rapidly falling stock price triggers a series of risk control stop-loss orders (whether they are institutional programmed risk control or retail stop-loss orders). These stop-loss orders turn into market sell orders, further impacting the market. At the same time, algorithms will accelerate selling based on real-time data (such as a volume ratio of 1.49 showing increased activity), forming a self-reinforcing downward spiral. In the fourth stage, low turnover and position adjustment. When the stock price falls to a low enough position (around 170 Hong Kong dollars), pre-embedded short sellers start covering their positions for profit (buying) and engage in trading with funds trying to "buy low". The quantitative programs also complete a perfect "high sell low buy" cycle. The latest disclosed broker seat data provides a crucial footnote to this crash, revealing the ongoing battle between hidden factions of funds. There were starkly different operations in the two major Hong Kong Stock Connect channels, Shanghai-Hong Kong Stock Connect and Shenzhen-Hong Kong Stock Connect. China Investment (Shanghai-Hong Kong Connect) recorded a net purchase of 497,500 shares, while China Chuangying (Shenzhen-Hong Kong Connect) significantly net sold 801,500 shares. This indicates a huge disparity in valuation judgments among mainland funds. The resolute sell-off from the Shenzhen-Hong Kong Connect funds became an important bearish force of the day. In the net sell-out list, international top investment banks such as Morgan Stanley (-258,000 shares), J.P. Morgan (-41,500 shares), and the Bank of the Netherlands (-90,500 shares) were prominently featured. They usually represent the movements of overseas institutional investors, hedge funds, and quantitative funds, and their unanimous selling actions indicated that professional fund groups chose to cash out at the highs or take short positions during the day. In conclusion, behind the extreme market activities of China Northwest Transport-B, there was a game played predominantly by quantitative funds. The stock's intraday volatility of nearly 124%, a trading volume exceeding 45 billion Hong Kong dollars with a turnover rate of only 4.13% highlighted the gameplay mechanism of algorithmic trading in a shallow market-depth environment: through a series of precise operations such as short squeezing, liquidity extraction, stop-loss triggering, and low-position replenishment, completing a cycle of "high selling and low buying". Investors need to be highly vigilant about the price volatility risks driven by algorithms.