Featured faculty: Desmond Tsang
Written by Putro Harnowo

China’s high-speed rail reached a new milestone last year by surpassing 50,000km, making it the world’s longest network of bullet trains. In less than two decades, the lines now connect 97 per cent of Chinese cities with populations exceeding 500,000. This connectivity isn’t just about convenience but also about helping businesses navigate uncertainty with greater confidence.

A new high-speed rail line changes how investors view firms they previously perceived as out of reach. More connectivity also means more oversight, particularly over companies that deliberately sugarcoat their financial reports, which occasionally haunts the market.

Historically, many international giants have fallen for concealing poor performance. Wells Fargo was heavily fined for secretly opening millions of fake accounts to meet sales goals, and Wirecard filed for bankruptcy after its accounting fraud came to light.

“When negative information withheld by management eventually becomes public, they normally see their company stock price suddenly fall or crash,” says Desmond Tsang, an Associate Professor of Real Estate at the School of Hotel and Tourism Management at the Chinese University of Hong Kong (CUHK) Business School.

To ensure due diligence, institutional investors, such as mutual funds, pension funds, and insurance companies, regularly conduct corporate site visits to the firms they invest in, where financial analysts and fund managers meet rank-and-file employees to obtain information that supplements the firm’s financial statements.

“Unlike virtual meetings, corporate site visits allow financial analysts and fund managers to directly observe operations, management practices, and local conditions that can improve information accuracy and quality,” Professor Tsang adds. “This ‘soft information’ often reveals early warning signals of a stock crash and is difficult to capture remotely.”

Firms with less oversight are more likely to conceal their poor performance. Unfortunately, site visits depend heavily on location, so institutional investors typically only come when the benefits outweigh the inconvenience of travelling, leaving remote firms with less scrutiny.

Professor Tsang’s study finds that firms headquartered far from financial hubs, where institutional investors are concentrated, are significantly more prone to stock crashes. His study of Chinese firms also shows that the rapidly expanding high-speed rail network improves corporate site visits, hence lowering crash risks.

“The benefits of site visits are especially pronounced for distant firms, underscoring the role of transportation infrastructure in narrowing information gaps and improving transparency.”

Professor Desmond Tsang

Leaving no stone unturned, only if it’s convenient

Substantial stock ownership gives institutional investors immense influence over corporate governance and the strategic direction of the firms they invest in. The study titled Needed but not there: Firm location, corporate site visits, transportation, and stock price crash risk shows that company managers tend to be more honest with investors about their financial performance during site visits.

Along with Chu Xiaoling at the University of Macau and Lo Kin at the University of British Columbia, Professor Tsang examines the location of more than 1,500 Chinese companies listed on the Shenzhen Stock Exchange and tracks their share prices from 2012 to 2019. The team also collects information on high-speed rail station openings across China and matches it with corporate site visit data during the same period.

The analyses find that although firms with higher risk require more monitoring, the greater geographical distance imposes higher travel costs and considerable hurdles, making institutional investors less likely to visit remote firms in person. Ultimately, fewer corporate site visits are associated with a greater risk of a stock price crash.

“Site visits are not just busywork and particularly crucial for distant firms,” Professor Tsang says. “They cannot be substituted by informal exchanges of soft information between company managers and investors.”

Surprisingly, site visits do not necessarily reduce the risk of stock crashes for firms headquartered near financial centres. Due to their proximity, these firms are already under heightened scrutiny from their stakeholders.

How high-speed rail bridges the information gap

The Shenzhen Stock Exchange requires listed firms to publish a detailed record of each corporate site visit within two trading days, and the study finds significant market reactions around these days. This timely disclosure improves information quality, making stock price movements more closely reflect the company’s actual performance.

However, conducting these essential visits, especially to firms located remotely from the financial centre, often entails high travel costs and logistical challenges. Fortunately, the rapid expansion of China’s high-speed rail eases the burden.

The openings of the high-speed rail stations are found to increase the number of corporate site visits. Stock crash risk for firms connected with new stations decreases significantly following the launch of the high-speed rail network.

As financial analysts and fund managers become more likely to visit, the stocks of firms well-connected to the high-speed railway network are priced more accurately than those of firms that are not connected.

Takeaways for businesses and policymakers

While the study’s empirical setting is in China, Professor Tsang notes that its fundamental mechanisms, including information gap and stock price crash risk, are universal. “The findings should be relevant to emerging and developed markets, where companies don’t always share all the information with investors and transportation systems are visibly improving.”

“The benefits of site visits are especially pronounced for distant firms, underscoring the role of transportation infrastructure in narrowing information gaps and improving transparency,” he adds. “Therefore, policymakers may see value in promoting investor access to remote firms as part of market stability measures.”

For institutional investors, the study proves that physical site visits remain a critical and indispensable channel for exercising robust monitoring. As the inconveniences of site visits can affect stock crash risk, investors should account for travel time when evaluating investment opportunities and weigh other forms of due diligence carefully for firms that are difficult to visit.

For businesses that are inherently remote, such as those in the mining and agriculture sectors, Professor Tsang suggests that proactively offering site visits and transparent reporting can reduce the risk of stock crashes. Enhanced disclosure and hybrid engagement, such as physical visits accompanied by digital tools to check remote facilities, may also help bridge the gap.

The post How transportation mitigates stock crash risks for remote firms first appeared on China Business Knowledge.

Featured faculty: Michael Zhang
Written by Sally Ho

Social media has levelled the playing field of access to financial knowledge, granting institutional and retail investors alike equal access to timely news and sentiment that shape their decisions. Take the collapse of Silicon Valley Bank in 2023, for example. A panic spiralled on social media turned a bank with US$212 billion in assets into bankruptcy in just two days.

Meanwhile, environmental, social and governance (ESG) performance has become one of the most talked-about corporate lingos, not just among consumers but also as a signal in modern investing. Companies are held accountable for their sustainability claims and practices, and failure to do so may put them in the spotlight or, even worse, lawsuits.

Retail investors nowadays increasingly express their views online, influencing other investors’ behaviour and market movements. On social media, a company’s stance on climate change, labour practices, or corporate governance can spark heated discussions. However, little is known about how much retail investors actually value ESG practices among corporates.

“Sustainable investing has accelerated in the past few years, but most discourses focus on how ESG affects firm value or analyst recommendations,” says Michael Zhang, Wei Lun Professor of Business AI at the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School.

“There is a significant gap between the rising importance of ESG in the corporate world and the lack of understanding regarding how retail investors actually process ESG-related information.”

Professor Zhang’s latest study, Attention or sentiment: How social media react to ESG?, aims to address this gap and finds that, when it comes to sustainability, retail investors’ talk and walk don’t always go hand in hand. While retail investors do care about ESG, they may not be able to determine if such practices are financially material in the short term.

Classic dilemma of profit vs. planet

To explore how retail investors react on social media about companies’ ESG performance, Professor Zhang, along with Kalok Chan at City University of Hong Kong, Xu Dapeng of South China University of Technology, and Hong Hong of Tongji University, examines tens of thousands of posts on Seeking Alpha, a popular online community platform for retail stock investors.

With more than 17 million monthly visitors, Seeking Alpha publishes content written by diverse contributors and features comment sections, forums, and groups where users discuss investment strategies. Given these characteristics, this platform has been dubbed social media for retail investors.

The researchers focus on firms in the S&P 500 index, or the top US-listed companies. After including only firms discussed on Seeking Alpha and having ESG scores, the final sample consists of 429 firms.

“Managers should realise that in the short term, ESG gets you noticed, but financial metrics likely still drive the sentiments.”

Professor Michael Zhang

Given that online attention and sentiment are often drivers of stock market volatility and trading volume, the team categorised the posts into two key responses: social media attention and social media sentiment. Attention refers to how many posts are about a certain company, and sentiment refers to the emotional tone, including optimistic or pessimistic attitudes, towards the company.

After matching and analysing the social media posts with ESG performance scores from Sustainalytics, a global provider of ESG ratings and data, the researchers found that firms with strong ESG scores attract more social media attention. ESG score upgrades are associated with increased social media attention, while downgrades result in decreases in the following months.

However, retail investors on the platform do not necessarily express more positive feelings toward firms with high ESG scores. Investors also do not show more positive sentiment after ESG upgrades or more negative sentiment after downgrades. This suggests a disconnect where sustainability sentiment does not always align with visibility.

Talk is cheap, but vibe speaks volumes

The study further examines the three major components of ESG separately and their individual impact on social media attention and sentiment. The environmental and social components represent the main drivers of increased attention online, while the governance aspect did not have any significant impact.

For online sentiment, social and governance aspects have no significant impact, but surprisingly, the environmental score alone is associated with less favourable sentiment. This finding might seem counterintuitive, but it aligns with a specific stream of financial theory: many retail investors treat environmental efforts as a cost, rather than a clear financial benefit.

“It is likely that retail investors in these online communities often view high environmental commitment as a financial burden,” Professor Zhang says. “From a utilitarian investment perspective, extensive spending on environmental initiatives, like emission cuts or resource reduction, can be seen as an expense that might hurt financial performance.”

Despite being beneficial to wider society, investing in sustainability initiatives can raise questions about short-term profitability and provoke scepticism due to a perceived threat to a company’s bottom line. It appears that retail investors on online forums tend to be driven primarily by financial concerns, rather than environmental causes.

Research implications and future directions

ESG activities may increase visibility among retail investors, but firms shouldn’t assume that higher visibility automatically translates into a positive image, since investor sentiment is driven by profit. “Companies need to manage their expectations regarding the return on their ESG investments when it comes to public perception,” Professor Zhang adds.

“Maintaining ESG standards is crucial for relevance and visibility, even if it doesn’t immediately result in a warmer reception from retail investors. Managers should realise that in the short term, ESG gets you noticed, but financial metrics likely still drive the sentiment.”

For market analysts and regulators, the disconnect between attention and sentiment raises questions about how ESG information is communicated and interpreted. Social media may amplify awareness, but it doesn’t guarantee confidence in sustainability practices or in their financial implications.

Looking ahead, Professor Zhang expects to examine whether the findings hold true for smaller-cap companies, not just S&P 500 firms. “We also plan to explore other digital channels such as X [formerly Twitter], Yahoo! Finance, or Google search to see if the attention and sentiment dynamics might differ on general social media platforms,” he adds.

For now, the key takeaway is clear. In the digital age, seeing isn’t always believing. ESG draws attention, but steering investor sentiment requires more than just doing good.

The post Do retail investors really care about sustainability? first appeared on China Business Knowledge.

Featured faculty: Wu Xian
Written by Putro Harnowo

Against all odds, China managed to rack up record-breaking exports last year with a US$1.2 trillion surplus. It was quite unprecedented, given the US mounting tariffs for months. The tension eventually calmed following the October truce, but a bigger problem is brewing closer to home. The world factory has experienced sustained deflation since 2023.

In contrast to inflation, deflation is a broad decline in the prices of goods and services. While it is not always harmful, deflation may spiral into weak consumer spending, lower business profits, and increased unemployment. The government has committed to stimulating domestic consumption by lowering benchmark interest rates to encourage spending.

“When deflation happens, the government normally wants to boost the economy by lowering the interest rate to raise the inflation rate mildly. However, at some point, the interest rate will hit the floor and cannot be lowered further,” says Wu Xian, Assistant Professor of Finance at the Chinese University of Hong Kong (CUHK) Business School.

To shift away from heavy reliance on traditional interest rate adjustments, the central bank can utilise unconventional monetary policy tools. For instance, the People’s Bank of China, between 2013 and 2014, injected liquidity into the banking system by allowing certain bonds to serve as collateral for commercial banks to borrow. This tool is called collateral-based monetary policy or collateral framework.

“Collateral framework is not unique to China. It has also been adopted widely across the world, for example, the Federal Reserve’s term asset-backed securities loan facility and the European Central Bank’s long-term refinancing operations. However, its impacts were hard to measure,” Professor Wu adds. “There’s a lot of endogeneity in economics, so we couldn’t tell whether the change in markets is due to this policy or other factors, like bond characteristics or the unobservable economic shocks.”

A study by Professor Wu titled Collateral-based monetary policy: evidence from China, in collaboration with Fang Hanming of the University of Pennsylvania and Wang Yongqin of Fudan University, is the first ever to measure the causal positive effects of the collateral framework on the real economy.

Professor Wu and her collaborators find that the collateral framework significantly decreases the bond spread, or the yield gap between a corporate bond and a safer government bond, and provides companies with more capital to invest and pursue other business activities. This tool also has broader and long-term effects. For instance, follow-up studies show that a collateral framework targeting green bonds can stimulate more investments in green initiatives.

Lessons learned from Chinese bonds

China’s central bank provides lending programmes for commercial banks based on loan terms, including the standing lending facility or short-term liquidity operation for immediate cash, the medium-term lending facility with three to 12-month terms, and the pledged supplementary lending with three to five-year term loans to support specific sectors.

To obtain these loans, banks need to put down securities as collateral. Since 2013, the central bank has accepted treasury and local government bonds, as well as AAA-rated corporate bonds, as collateral. This framework was extended in June 2018 to include AA and AA+ rated corporate bonds. While AAA bonds are more secure, an AA rating offers a slightly higher yield for a marginally higher risk profile.

Interestingly, many Chinese bonds are traded on two venues, despite having the same fundamentals. Bonds listed in the interbank market for qualified institutional investors are also available on major exchanges, such as the Shanghai and Shenzhen exchanges, for non-bank financial institutions and retail investors.

Only bonds in the interbank market are eligible as collateral, since the interbank market is regulated by the central bank. Professor Wu and the team use these bonds as the treatment group and the same bonds in the exchange market as the control group. “This allows us to establish a causal relationship between the collateral framework and bond prices, which is not possible in other financial markets.”

The team examines daily bond trading from January to September 2018 and finds that the collateral framework increased the value of eligible bonds. Before the collateral expansion, banks could use the AA and AA+ rated corporate bonds to borrow from other financial institutions in the repo market. The repo market participants don’t lend money based on the full value of the bonds but reduce them by a few per cent.

“Companies can borrow at a lower cost as long as they can issue at least AA or AA+ rated bonds. This allows the central bank to support and ease funding to the real economy.”

Professor Wu Xian

Being included in the collateral framework trims such reduction by three per cent, boosting the collateral value and the prices of these bonds. It reduced the spreads of the newly eligible bonds by 37–53 basis points, equivalently, 10–15 per cent of the average spread in the secondary interbank market, where previously issued bonds are traded among qualified institutional investors.

This effect can further pass through to newly issued bonds in the primary market and allows bond issuers to secure a lower borrowing cost. It reduces the spread of the eligible bonds in the primary market by about 35-56 basis points. This means the bond issuers can borrow at a cheaper rate than before.

“Companies can borrow at a lower cost as long as they can issue at least AA or AA+ rated bonds. This allows the central bank to support and ease funding to the real economy,” Professor Wu adds.

Wider effect in the market

After 1 June 2018, issuing new eligible bonds is cheaper in the interbank market than in the exchange market. Firms can take advantage of this policy and choose the best market to issue bonds. Eligible bonds are more likely to be issued in the interbank market than the exchange market.

By the end of 2018, the People’s Bank of China’s lending facilities totalled more than eight trillion Chinese yuan, about 25 per cent of the monetary base.

“Collateral framework is crucial when interest rates are low,” Professor Wu adds. “This way, the central bank can conduct policy expansion by allowing commercial banks to borrow more and lend to other institutions and businesses.”

The 2018 collateral framework also made the People’s Bank of China one of the first central banks to specifically target green bonds. While her study doesn’t explore the impact on green finance, Professor Wu sees that follow-up studies have shown that green firms received more loans because of this framework.

Furthermore, as the interbank and exchange markets coexist with a shared bond structure, Professor Wu plans to understand more deeply whether this arrangement is efficient. Her next study looks into which type of assets should be traded in the decentralised interbank market, which holds 86 to 90 per cent of all Chinese bonds.

“There’s some benefit to keeping both markets, as each has its own strengths,” she adds. “A centralised market is more transparent, but you can find dealers to trade in large quantities in the decentralised exchange markets. How to design these markets is an interesting direction to explore in the future.”

The post How China fine-tunes bond values to spark economy first appeared on China Business Knowledge.

Featured faculty: Jiang Wenxi and Yao Chen
Written by Joanne Madrid

Across major global stock markets, a new habit seems to be taking shape. The trading floor stays calm for hours until the last stretch before closing at 4pm. In a sudden rush, stocks change hands at a remarkable pace, as if all the day’s energy has been saved for 10 final minutes. All signs point back to index funds.

“The rise of index funds has fundamentally altered trading dynamics in the equity markets. Stocks that are heavily owned by index funds show more buying and selling right before the market close,” says Yao Chen, an Associate Professor in the Department of Finance at the Chinese University of Hong Kong (CUHK) Business School.

An index fund is an investment that mirrors the performance of a specific collection of securities or an index. For instance, if the S&P 500, a stock index of the 500 largest US companies, rises by one per cent, the S&P 500 index fund aims to rise by the same amount. To achieve this, the fund actually buys and sells the stocks that make up the index in the same proportions.

By simply mirroring an index rather than outperforming it, index funds generally deliver strong performance, making them popular among investors seeking low-cost portfolios. In the US, index funds accounted for 61 per cent of equity investments last year, mostly managed by two asset giants, BlackRock and Vanguard.

Algorithms continuously monitor an index fund’s portfolio relative to the corresponding index. Meanwhile, fund managers oversee the fund and execute trades once per day, right after the market closes. This timing, as it turns out, has reshaped the trading pattern.

In a study titled How index funds reshape intraday market dynamics, Professor Yao and Professor of Finance Jiang Wenxi, along with their PhD student Wu Siyuan, examine how index funds drive the stock rush near the market close. The study also finds that short sellers are increasingly timing their trades during the rush to camouflage themselves.

Save the best for last?

The stock indices fluctuate throughout the day. However, index funds are valued based on how closely they track their corresponding indices, which are calculated using closing prices of the underlying stocks. Trading closer to the closing price reduces the tracking error or gap between the fund’s return and the index’s return.

“The closer the index fund managers execute their trades to the end of the trading day, the lower their tracking error will be,” says Professor Yao.

Having analysed US equity data from 1993 to 2019, the researchers find that in the last five minutes, not only are more stocks available for trading, but the gaps between the highest bid price and the lowest ask price are also smaller. These indicate a highly liquid market, where trading stocks becomes easy, fast, and cost-effective.

“The closer the index fund managers execute their trades to the end of the trading day, the lower their tracking error will be.”

Professor Yao Chen

More liquidity but less information, just noise

More liquidity does not necessarily make stock prices more informative. During the day, stock prices move in response to economic news, earnings reports, global affairs, or other industry developments.

As the bourse winds down, index funds trade to rebalance their portfolios to match their corresponding index, driven by investor inflows or outflows rather than by real performance. Stocks with higher index fund ownership tend to move with overall market trends, creating noise that can overwhelm information about the actual picture of underlying companies.

“Therefore, if the closing price becomes the main target for most trading, causing a high portion of buying and selling to happen right at the end of the trading day, liquidity may dry up during other trading hours of the day,” Professor Yao adds.

Short sellers go with the flow

The liquidity rush benefits short sellers and informed traders. These traders typically have more genuine information about the stocks and the underlying companies, and try to maximise returns by keeping their transactions discreet to avoid tipping others off. Trading during high liquidity allows them to blend in with the crowd.

“Short sellers bet against the stock and strategically wait until the end of the trading day to trade to coincide with the price reveal from the indices. With this, they can hide their intentions and avoid drastically moving the stock price, allowing them to make more profits,” says Professor Yao.

Despite their smart disguise, collective actions by many short sellers still send a signal. The study finds that a notable increase in short sales right before the market closes is a reliable indicator that the stock price will likely fall further in the subsequent trading days. Eventually, the true information about the company’s performance becomes apparent to the market.

Can regulators entangle the rush hour?

To address the last-minute rush, stock exchanges worldwide have offered closing auctions that allow traders to determine a single closing price for each security. Stock exchanges normally set a cutoff time for placing auction orders, e.g., 3.45pm for the NYSE and 3.50pm for NASDAQ, and the closing prices are announced at 4pm.

Not all trading activity occurs through closing auctions. While the study finds that the volume of securities traded through the auction has grown steadily since 2004, it remains insufficient to slow down the last-minute trading rush. Index fund managers participate largely because closing auctions enable them to trade in large quantities at a precise price, but they rely more on regular trading.

The reasons are not only the high auction fee but also the uncertainty in trading execution. If investment flows change after the cutoff time but before the market actually closes, index fund managers can no longer change the orders and bear the risks of tracking errors.

Finally, although the study focuses on US equities, Professor Yao notes that its implications extend beyond borders, as index funds in other major markets operate in similar ways. “For example, Hong Kong indices are also calculated using closing prices of their underlying stocks,” she adds.

The post What drives last-minute rushes in the stock market? first appeared on China Business Knowledge.

Featured faculty: Wu Jing, George Yang, Johnny Li, and Lisa Wan
Written by Putro Harnowo

The world started 2026 with a complex mix of opportunities and risks. Global productivity and economy have slowed down, but the Organisation for Economic Co-operation and Development expects emerging Asian markets to be resilient.

Following the recent US-China tariff truce, China achieved a record trade surplus exceeding US$1 trillion last year, setting the stage for intriguing developments in 2026. Meanwhile, sustainability backlash dominated 2025, with significant environmental, social, and governance (ESG) investment outflows in the US, leaving the sector trajectory uncertain.

Rapid demographic ageing in Asia and Europe will transform the insurance industry, with developed markets projected to see 35 per cent more individuals aged 65 and older by 2050 compared to 2025. Amid declining birth rates, younger consumers shift their priorities to products and services that provide emotional satisfaction, fueling the “emotional consumption” trend that continues to shape business.

Against these backdrops, we present our 2026 outlook by gathering insights from the Chinese University of Hong Kong (CUHK) Business School faculty. The first outlook highlights the hottest topics in technology, and the second part looks into economic and consumer behaviour that will redefine businesses.

1. New global order with a fragmented yet innovative world

Trade frictions between the US and China have already driven global firms toward diversification, prompting a shift away from reliance on Chinese manufacturing. However, Wu Jing, Professor at the Department of Decisions, Operations, and Technology, explored in his study that complete decoupling remains challenging due to entrenched dependencies.

“Currently, the most prominent strategy is ‘China plus one’ where companies maintain a baseline of production in Chinese Mainland but diversify into other emerging markets,” he says. “Relocating operations to allied or nearby countries appears to mitigate geopolitical risks, but their long-term sustainability is uncertain.”

A notable example of such dependencies is the controls over high-end computing chips by the US, which may not survive without the supply of rare earths from China. This tug-of-war was resolved at a summit of the two world leaders last year, but the truce is seen as a temporary fix, as Singapore’s Prime Minister echoed that the intense competition will continue.

“Companies are increasingly forced to navigate multiple, often conflicting regional supply chains, each governed by its own set of rules. In practice, this often means maintaining dual systems, one aligned with Western standards and another with China, which significantly drives up operational costs as they must build production lines and logistics networks to comply with different regulatory regimes,” Professor Wu adds. “If relations deteriorate further, a bifurcated supply chain system is probable.”

Not only posing a risk to global economies, Professor Wu sees geopolitical fragmentation likely to hamper sustainable supply chains by disrupting the flow of critical materials, driving up costs and creating inefficiencies. However, he believes there would be a silver lining. “Fragmentations may accelerate innovation through competitive investments, as companies facing disruptions would be incentivised to develop innovative solutions and technologies.”

2. Green finance is recalibrating

The US political polarisation, coupled with EU regulatory adjustments amid corporate and governmental pressure, drove much of the ESG backlash last year. Elsewhere, ESG investments face stricter rules: China’s new framework requires listed companies to disclose their decarbonisation plans this year, while firms listed on Hong Kong’s Hang Seng Composite LargeCap Index are mandated to disclose carbon emissions from their suppliers.

These developments underscore resilience, refining the field by weeding out superficial approaches. “Maximising ESG value is not only about disclosing and reporting, but also about what the companies are actually doing,” says George Yang, Professor at the School of Accountancy. “Firms need to be transparent and provide credible and verifiable evidence to stakeholders, especially investors.”

One of the main criticisms is that green investments may obscure the potential earnings. Professor Yang’s recent study finds that prioritising ESG information can make a company’s stock price less accurately reflect future returns, since investors may overlook traditional financial metrics. This finding reveals implications that extend beyond the surface.

“Sensible ESG initiatives are intended to be aligned with corporate strategies and shareholder values, including profit maximisation. However, in the value maximisation of ESG investments, we need to pay attention to a longer time frame than in the traditional approaches,” he adds.

Value maximisation of ESG investments involves incorporating ESG factors to achieve optimal financial performance. As opposed to traditional approaches that typically focus on maximising profits in the short term, ESG investments often take a longer time, even years, to deliver full benefits for shareholders.

Such a gap calls for the need to manage and balance shareholders’ expectations. In this regard, Professor Yang emphasises financial analysts’ crucial role in linking sustainability goals to investor decisions. “Financial analysts should pass investors’ concerns and expectations to the firm and help the firm to improve its actual ESG initiatives.”

3. Insurers’ battle for the ageing population

As the proportion of elderly citizens rises in some parts of the world, the insurers face mounting pressure to manage spiralling claim costs and a wave of soon-to-retire customer base. Johnny Li, Professor at the Department of Finance, observes that only those who master the art of extracting valuable insights from large and intricate big data can survive.

“Insurers aim to accurately categorise individuals with different health profiles into appropriate risk categories and corresponding premiums effectively. Those that fail to leverage data analytics for this purpose will be crowded out of the market,” he says.

To illustrate, Insurer A charges US$100 for all customers, and Insurer B uses predictive analytics, leveraging health history, lifestyle, and medical records, to assess the risk of each policyholder and charges US$50 to healthy customers and US$150 to less healthy ones. Healthy individuals would choose Insurer B, leaving Insurer A with high-risk clients, rising costs, and eventual failure.

“In practice, there are no insurance products that can be called unique,” Professor Li says. “Many insurers are already using predictive analytics, but those that are willing to invest more to have more refined models can put customers into finer categories, and they tend to have a better competitive advantage.”

Professor Li has developed a new method to forecast longevity risk, a financial risk of a person living longer than their savings, for China’s population. The country only saw the insurance industry emerge after 1979, making its population data inconsistent. As a comparison, insurers in Western markets have collected risk data since the 18th century.

He notes that China’s vast territory leads to regional differences in longevity risk, and these trends are likely to diverge further as socioeconomic disparities persist. Therefore, predictive analytics is essential for insurers to thrive. “With limited data available in the Chinese market, factors such as gender, city of residence, and income may be incorporated into a machine-learning-supported model.”

4. Emotional connection is the prime consumer driver

2025 has seen collectable plush monster toys called Labubu taking the world by storm, with teenagers and adults lining up at stores. In Hong Kong, a Japanese character series, Chiikawa, has captured fans’ hearts through themed cafés and pop-up events celebrating its cute and comforting charm.

While AI has integrated itself deeper into our daily lives, human emotions remain utterly irreplaceable and may become more profound in consumer behaviour. For example, a recent report by the AI Security Institute shows that a third of UK adults have turned to AI chatbots for emotional support.

Lisa Wan, Associate Professor in the School of Hotel and Tourism Management, observes modern customers increasingly seeking deep emotional connections and value beyond the product’s functional benefits. “In the case of Labubu or Chiikawa, the appeal lies beyond the toy, but the surprise in the blind box, scarcity from limited editions, and social buzz increase the emotional drive to buy,” she says.

Emotional connection also matters in the tourism industry. Professor Wan’s study highlights how emotional factors, such as thematic storytelling and colour cues, drive customers’ impulsive buying behaviour. Travellers also often form emotional bonds with a destination even before they arrive, sparked by captivating articles, social media, or heartfelt stories shared by friends and loved ones.

Applying an emotional touch may also be useful for Hong Kong, which has seen hotel occupancy rebound, but retail spending and hotel stays are lower than pre-pandemic levels. The city could consider shifting away from mass shopping toward cultural and authentic experiences to foster emotional connection.

“Hong Kong has unique cultural assets, including the mix of East and West, Cantonese heritage, street markets, and festivals,” says Professor Wan. “More attention should be given to how visitors feel connected to the region and the Greater Bay Area. With economic headwinds and more cost-aware consumers, emotional consumption means shifting from luxury for luxury to emotion-driven value, where deep and meaningful experiences matter, even in moderately priced stays.”

Professor Wan elaborates that when customers feel emotionally attached, they become advocates, community members, repeat visitors, and co-creators of value. “Their loyalty goes beyond ‘I like the hotel’ to ‘I feel connected to the brand and destination.’ Loyalty isn’t just about returning customers, but also making them willing to recommend to others.”

The post China Business Knowledge’s 4 market forces in 2026 first appeared on China Business Knowledge.

Featured faculty: Jiang Wenxi and Gao Zhenyu
Written by Putro Harnowo

During an economic downturn, central banks normally launch a stimulus package to boost economic activity by lowering interest rates. Commercial banks as lenders adjust their interest rates based on the benchmark set by the central bank. Reducing interest rates eventually translates into smaller monthly mortgage payments, allowing households to spend more and boost consumption.

When the US central bank cut its interest rate in September 2024 for the first time since 2020, consumer sentiment soared as they found relief from high loan payments. The same measures were also taken in Chinese Mainland. The People’s Bank of China has adjusted its benchmark interest rate, the loan prime rate (LPR), multiple times from 4.25 per cent in September 2019 to 3.1 per cent in March 2025, to stimulate economic growth.

Oddly, lowering LPR doesn’t seem to help domestic spending much. A new study finds that an interest rate cut doesn’t directly and smoothly translate into more money at the household level. It turns out that many Chinese Mainland households responded to the reduced LPR with mortgage prepayment, or paying off their mortgage early, and cutting their consumption.

“We observe a negative correlation between interest rates and mortgage prepayments in Chinese Mainland,” says Jiang Wenxi, Professor of Finance at the Chinese University of Hong Kong (CUHK) Business School. “In cities where more households prepay their mortgages, essential and non-essential consumption declines in the following months.”

In his latest study, Mortgage prepayments in China and monetary policy transmission, Professor Jiang and his colleague from the same department, Associate Professor Gao Zhenyu, examine what motivates households to prepay their mortgages. Caixin has reported that total mortgage prepayments in 2022 reached 4.7 trillion Chinese yuan (US$700 billion), accounting for 12 per cent of all outstanding mortgage loans, and continued into the first half of 2024.

Professors Jiang and Gao’s study discovers households that prepay their mortgages on average use up more than 70 per cent of their savings and reduce their spending by 2.3 per cent. “This explains why, despite monetary easing efforts since 2019, consumption growth and economic stimulus in Chinese Mainland have been weaker than expected,” says Professor Jiang.

“Households with greater wealth, higher levels of education, and better credit scores are more responsive to the gap between their mortgage rates and LPR, making them more likely to prepay their mortgages.”

Professor Jiang Wenxi

Unique characteristics of Chinese Mainland’s mortgage market

Home loan arrangements vary across markets, but the most common types are adjustable-rate, where the mortgage interest rates fluctuate over time in line with the central bank’s benchmark interest rate, or a fixed-rate mortgage, where the mortgage interest rate stays the same since the loan was taken.

When the central bank lowers interest rates, borrowers with adjustable-rate see lower monthly mortgage payments and more money for spending, making the economic stimulus swiftly affect households. For borrowers with fixed-rate mortgages, they can opt to refinance, which involves replacing the existing mortgage with a new one with better terms.

However, refinancing is prohibited in Chinese Mainland and mortgage rates are mostly adjustable at a very slow pace. Mortgage rate is based on LPR and “local margin” set by the city, which remains fixed throughout the loan term. Local margin varies depending on local rules, but tends to follow the direction of the central bank after a while. Therefore, lower LPR only results in small changes in mortgage rates much later. Researchers called this “mortgage rate rigidity.”

Before 2019, the benchmark interest rate stayed the same for a long time, making the gap between mortgage interest rates and returns on savings relatively small. When LPR was lowered, the rigidity of mortgage rates made the gap with earnings from savings grow more significant, and borrowers started to realise that carrying a mortgage is getting more and more costly.

How interest rate cuts weaken domestic consumption

In the study, Professor Jiang and Professor Gao, as well as Wang Kemin and Ren Haohan from Fudan University, analyse extensive mortgage data obtained from a major state-owned commercial bank in Chinese Mainland. They track borrowers’ payment and consumption behaviour between October 2019 and May 2024 from a randomly selected sample of 100,000 outstanding mortgages.

The researchers find that as the LPR declined, more and more borrowers prepay their mortgages. The prepayment ratio rose to 8.1 per cent by the end of 2021, stalled in 2022 due to the pandemic, and then peaked at 11.5 per cent by early 2023, as shown below. “Borrowers often decided it was best to cut back on both spending and saving so they could pay off their mortgage faster,” says Professor Jiang.

Further analysis shows that consumption of discretionary or non-essential items is particularly affected. “Households with greater wealth, higher levels of education, and better credit scores are more responsive to the gap between their mortgage rates and LPR, making them more likely to prepay their mortgages,” Professor Jiang adds. “The larger the gap between the mortgage interest rate and the LPR, the more likely they are to prepay.”

Designing more effective policy

In August 2023, the People’s Bank of China announced housing credit policies by lowering mortgage interest rates for first-time home buyers and local margin in some cities. The policies expanded the criteria of first-time home buyers, enabling certain borrowers to reset their local margin to a lower rate.

Given the fixed-rate feature of local margin is one of the causes of mortgage rate rigidity, lowering this extra fee helped mortgage rates move closer to the LPR. Around 25 per cent of households in the sample were qualified for this adjustment.

The researchers find that these qualified households were significantly less likely to prepay their mortgage and showed increases in their household consumption. “Policies that directly address mortgage rate rigidity can help monetary policy have a stronger and quicker effect on borrowing and spending decisions, improving how well monetary policy works,” says Professor Jiang.

This finding aligns with the policy initiative introduced in September 2024  by the People’s Bank of China, which aims to further strengthen monetary policy transmission through the household channel. The policy initiative features a new mortgage rate pricing scheme, which allows local margins to adjust to market conditions and shorten the LPR adjustment period from one year to as little as one quarter.

These measures enable the mortgage interest rates to respond more quickly to changes in the benchmark interest rate, reducing rigidities in the mortgage system. “As a result, mortgage prepayment activity has slowed remarkably since September 2024,” Professor Jiang adds.

The post How interest rate cuts could hurt consumer spending first appeared on China Business Knowledge.

Featured faculty: Paul Whelan
Written by Ellis Ng and Putro Harnowo

Foreign exchange or forex is the largest and most liquid financial market in the world, with a daily trading volume of US$9.6 trillion, according to a 2025 survey by the Bank for International Settlements. This number is significantly higher than the stock markets, which are estimated to be around US$700 billion per day.

Forex traders buy and sell currencies to make profits on differences in exchange rates over a global, decentralised market. With low capital requirements and the flexibility to trade anywhere, forex trading may appear easy, but practice suggests otherwise. The forex market is highly volatile and influenced by global politics and economics.

Although various methods have been designed to anticipate price movements and manage risk, forex traders suffering huge losses are not uncommon sights. A notable example is US$900 million lost by world-renowned investor Warren Buffett in 2005, signalling the unpredictable nature of foreign currency investment.

As the most widely traded currency, the US dollar is involved in more than 80 per cent of all forex transactions. Some argue that this domination may change amid intensifying trade and geopolitical tensions, along with US tariffs and protectionist policies that could potentially weaken the greenback’s hegemonic position.

However, Paul Whelan, Associate Professor in the Department of Finance at the Chinese University of Hong Kong (CUHK) Business School, remains cautious about anticipating dramatic changes to established patterns. “It’s too early to know if US tariffs will change the norm. The fundamental driver, consistent global demand for US dollar-denominated assets, remains robust despite shifting geopolitical dynamics.”

Although predicting currency market movements accurately is impossible, Professor Whelan’s recent study reveals a fascinating cycle that also demonstrates the persistent appeal of the US dollar. Every day at precisely 9.55am in Tokyo, 2.15pm in Frankfurt, and 4pm in London, the US dollar strengthens dramatically, only to weaken just afterwards. It’s a systematic pattern researchers have now quantified, revealing daily swings exceeding US$1 billion across global currency markets.

“Rather than market inefficiency, we find the daily swing pattern as a structural feature of the currency market driven by the prevalent demand for US dollars,” Professor Whelan says.

“The fundamental driver, consistent global demand for US dollar-denominated assets, remains robust despite shifting geopolitical dynamics.”

Professor Paul Whelan

What causes the billion-dollar daily swing pattern?

In a paper titled Foreign exchange fixings and returns around the clock, Professor Whelan, along with Ingomar Krohn at the Bank of Canada and Philippe Mueller at Warwick Business School, examined 21 years of high-frequency trading data and discovered a daily swing pattern around specific moments known as fixings. Fixings refer to the times when currency exchange rates are officially published, calculated by aggregating bids and offers to establish a reference price for valuing and executing international transactions.

Several key fixings are used worldwide, but the most prominent ones are the Tokyo, Frankfurt and London fixings, which have provided benchmarks for major currencies such as the yen, euro and pound, the top three currencies traded against the US dollar. Banks in Tokyo simultaneously publish their fixing at 9.55am, Frankfurt-headquartered European Central Bank announces its fixing at 2.15pm, and London-based Thomson Reuters updates its WM/Reuters fixing at 4pm, all in local time.

If converted to New York’s Eastern Time Zone (ET), Tokyo fixing happens at 8.55pm, Frankfurt at 8.15am, and London at 11am ET. As shown below, these fixing times are not exactly aligned, creating W-shaped patterns where the US dollar appreciates before the fixings and depreciates immediately afterwards.

Tokyo fixing is especially important as Japan doesn’t apply daylight saving time, a common practice among Northern Hemisphere countries where the clocks are set forward by one hour in spring and back by one hour in autumn, resulting in a change in time difference between Tokyo and other cities in the study throughout the year. From spring through autumn, the W-shaped pattern near the Tokyo fixing shifts by about one hour.

“Japan’s non-observance of daylight savings time serves as a quasi-natural experiment to prove the reversal is really tied to the fixing time,” says Professor Whelan.

What makes the finding striking is its consistency. The analysis of the nine most frequently traded currencies against the US dollar reveals a pervasive and highly statistically significant daily pattern across different time periods, suggesting that this isn’t a temporary market quirk but a fundamental feature of how global currency markets function.

The researchers believe that the pattern is driven by demand for US dollars at around major currency fixing times. Traders and financial institutions that facilitate foreign exchange transactions accumulate US dollars to meet this demand, causing the greenback to appreciate against other currencies. Right after the fixings, the dollars are sold back, leading to a price drop.

These findings highlight important considerations for managing currency risk. For corporations holding international operations, the real-world implications are significant. “Cross-border businesses might take into account timing around fixings to address pricing uncertainty,” says Professor Whelan.

Currency markets don’t always follow the logic

While identifying the daily swing pattern may help mitigate investment risk, it is worth noting that foreign exchange remains volatile due to the significant influence of external factors and trading behaviours. Another study by the researchers, Uncovered interest parity in high frequency, highlights that currency markets are not perfectly rational or predictable.

The researchers explore an investment strategy called a carry trade, which involves borrowing in low-interest-rate currencies, such as the Japanese yen, to invest in assets denominated in higher-interest-rate currencies, like the US dollar. According to the uncovered interest rate parity (UIP) theory, exploiting the interest rate differential shouldn’t yield consistent profits, as currencies with higher interest rates should gradually depreciate to offset the interest gains and maintain market balance.

However, the fact that some traders can still make profits from a carry trade has been perplexing. The researchers sought to determine how and when such an anomaly occurs by analysing foreign exchange market data spanning more than 25 years, focusing on nine of the most heavily traded currencies that account for 75 per cent of global daily average trading volume.

The results show that when major currency markets are closed or less active, mostly at night, the UIP theory tends to hold in diminishing carry trades. However, during daytime at US trading hours, currencies with higher interest rates tend to appreciate instead of depreciate, which contradicts the UIP theory. Most of the profits from carry trades are actually made in short bursts when major economic news comes out, such as the Federal Reserve’s announcements or major economic reports, during trading hours.

“Important economic news, like major reports or announcements, can cause sudden and big changes in currency prices as they show whether the economy is doing well or poorly,” says Professor Whelan. “Holding onto currency investments during these times is risky because prices can jump unexpectedly. To be willing to take this risk, investors need to expect higher returns as compensation for facing these shocks.”

On average, big news days account for only 17 per cent of all trading days in the sample, but contribute to two-thirds of the extra profit beyond normal market fluctuations. However, the probability of losses remains non-negligible, particularly during periods of market turbulence or when currencies behave abnormally.

Currency markets are more nuanced and less predictable compared to other financial markets. While classical theories provide a helpful framework, real-world data reveal consistent patterns of deviations. Market expectations and reactions are vital in understanding currency movements, more crucial than relying on interest rate differentials.

The post What really drives foreign exchange rates? first appeared on China Business Knowledge.

Featured faculty: Desmond Tsang
Written by Putro Harnowo

A couple of years have passed since the pandemic subsided and borders reopened. Commercial real estate markets have shown signs of recovery globally, but the progress appears to be much slower than expected. Oddly, in some parts of the world, the market seems to be losing ground.

Commercial property values in European cities such as Berlin, Frankfurt and Paris have been slashed over the past few years. In the US, the office market in business hubs like New York, San Francisco, Los Angeles and Chicago has seen better days. Hong Kong’s commercial real estate market has also been feeling the pinch, with high vacancy rates in both the office and retail segments.

Desmond Tsang, Associate Professor of Real Estate at the School of Hotel and Tourism Management at the Chinese University of Hong Kong (CUHK) Business School, points out that one of the key reasons is reduced human mobility, referring to fewer people physically visiting or moving around, in commercial real estate. Remote working and digital commerce have become the new normal, but many real estate companies are slow to adapt.

“Reduced mobility is here to stay, and hence, commercial real estate demand would be under pressure, although some sectors or regions would be more affected than others,” he says. “For instance, offices in the US would be more deeply affected since remote working is more prominent there than in some other regions like Hong Kong or Singapore.”

His latest study, Human mobility and commercial real estate: Evidence from REIT operating performance, documents how changes in human mobility have become a permanent fixture. Along with Erkan Yönder of Concordia University and his PhD student, Halil Özgür, Professor Tsang found that for office properties, a one per cent decline in human mobility leads to a 1.9 per cent drop in rental revenue, driven by a sudden drop in demand for office space. As the supply cannot adjust quickly, higher vacancies occur.

For retail properties, a one per cent decrease in human mobility increases operating expenses by 2.1 per cent. This is because shopping centres and malls feature common areas like hallways, restrooms, seating areas, courtyards, and the like that require continuous maintenance and enhancement, where operating expenses are fixed regardless of the number of visitors. The shift in shopper behaviour drives retail owners to invest in additional features, promotional events and other campaigns to draw customers back.

The study urges the public and private sectors to monitor and consider human mobility factors when evaluating property performance. At the same time, property owners should develop strategies to respond to the structural shifts or consider repurposing spaces to accommodate such changes.

“The outlook is not all bad, as we may see some conversions from office to residential and some flight-to-quality phenomenon, in which high-end, amenity-rich buildings will fare much better,” Professor Tsang says. “Many brick-and-mortar department stores may face declining sales and the same goes for lower-tier shopping centres and districts, but there could still be value for some new retail concepts, such as experiential retail and food delivery hubs.”

“Reduced mobility is here to stay, and hence, commercial real estate demand would be under pressure, although some sectors or regions would be more affected than others.”

Professor Desmond Tsang

How mobility affects real estate performance

In the study, the researchers utilised Google mobility data that tracks the movement of US citizens to help mitigate the pandemic’s impact from 2020 until the tech giant terminated it in October 2022. They then matched data from Google with local points of interest from an open-source platform, OpenStreetMap, during the same timeline to observe actual changes in human mobility.

Mobility was observed to decline significantly from the second quarter of 2020, when authorities issued stay-at-home orders and closed public facilities, and then further eased by 2022, following the widespread availability of vaccines. Interestingly, despite the social restriction no longer in place, people were still 4.6 per cent less mobile in 2022 compared to before the pandemic. The analyses revealed a persistent decline in mobility due to structural shifts in how people live, work and shop.

To identify local factors behind such a change, the team collected demographic data from the US Census Bureau and then applied a machine learning approach, extending analyses through 2023. Locations with a higher proportion of residents holding a bachelor’s degree or higher were found to experience a greater reduction in mobility. The researchers argue that individuals with higher level of education are more likely to be able to work remotely during and after the pandemic.

To measure the impact of human mobility on commercial real estate, the researchers examined US real estate investment trusts (REITs) data from S&P Global Market Intelligence from 2019 to 2023. REITs own and operate numerous commercial real estate properties and are also publicly traded on stock exchanges, requiring their financial reports to be detailed and transparent.

Their analyses demonstrated that human mobility has a significant impact on REITs’ earnings, with considerable effects on office and retail properties both during and after the pandemic. For both types of properties, a one per cent drop in mobility lowers REITs’ net operating income by 2.8 per cent during the pandemic and by 1.8 per cent post-pandemic.

Hong Kong commercial real estate landscape

Although the study was conducted using US data, Professor Tsang believes that other developed markets are seeing similar trends of decline in human mobility, including Hong Kong. “There are many different reasons for mobility changes in different regions, making reduced mobility remain in many parts of the world in 2025,” he says. “For the US, it goes back to work-from-home and flexible work models. For Hong Kong, decreased mobility in some central areas stems from the travel flows between Hong Kong and mainland China after the pandemic.”

Mainland Chinese visitors have always been the largest group of tourists in Hong Kong, but their numbers have yet to return to pre-pandemic levels, according to the city’s tourism board. On the other hand, an increasing number of Hong Kong residents prefer to spend weekends and holidays in mainland China due to more affordable options, which affects the city’s commercial real estate rent.

As Hong Kong landlords and retailers battle against shifting consumer habits and a wave of store closures, Professor Tsang suggests businesses must devise plans to reduce operating costs while sustaining revenue and enhancing their brand reputation. “Focusing on new and innovative ways of shopping and retail is a possible strategy,” he adds.

For instance, he suggests encouraging more mixed-use developments by integrating living, working and leisure spaces with a 24/7 urban ecology rather than traditional retail, or adopting holistic district renewal instead of revitalising isolated building projects.

The study with US data found that mobility dropped significantly near commercial areas, restaurants, banks and schools due to pandemic restrictions and lasting changes, such as remote work. Areas near warehouses, industrial buildings and farms saw smaller declines, as these places often depend on physical presence and were less impacted by remote work trends. To extend the findings in the Hong Kong market, more data are needed to measure the magnitude of mobility’s impact accurately.

“Some companies track cell phone data for the Hong Kong market and this can be put to good use to understand travel patterns and office utilisation in different areas,” he adds. “It would be interesting to see whether mobility patterns in commercial hubs that are more remote would be different from those in downtown areas. This relates to the importance of location in human mobility and commercial real estate performance, which, in essence, we examine as a novel mechanism for mobility change.”

The post What is left of empty offices and retail shops? first appeared on China Business Knowledge.

Featured faculty: Cen Ling and Jo Chanik
Written by Putro Harnowo

“Data is the new oil,” according to British mathematician Clive Humby in 2006. Many have rushed to get their hands on data since then, and none are more eager to turn numbers into profits than financial institutions. Just like oil, crude data needs to be extracted and refined, which brings the dawn of new alchemists called data scientists.

A data scientist uses a blend of skills in statistics, computer science and domain knowledge to draw meaningful insights from abundant data available. The fast-growing demand for this profession outpaces the growth of talent supply, and financial institutions found themselves competing not only among themselves but also against tech companies to attract the best data savants.

“Financial institutions have significantly increased their recruitment of data scientists in the past two decades,” says Jo Chanik, Assistant Professor in the Department of Finance at the Chinese University of Hong Kong (CUHK) Business School. “Institutional investors strategically adjust portfolio allocation and recruitment decisions to maximise the benefits generated by their data scientists.”

Along with Associate Professor Cen Ling from the same department, Professor Jo observes a clear pattern of the surge of data scientists on Wall Street. The number rose from 11,799 in 2008 and slightly dipped after the subprime crisis, but since then, it has quadrupled to reach 57,050 data scientists in 2021, with the top three employers by numbers being big names like Morgan Stanley, Credit Suisse and Goldman Sachs. Some firms recruit more than others, leading to variations in the concentration of data scientists.

However, the study finds that if a small group of investors has significantly more data and analysis on certain stocks, powered by employing more data scientists, they can uncover additional information unknown to others. Having exclusive information will make these investors trade less aggressively and frequently, which can slow down the rate at which useful information is reflected in the stock price.

“Competition among data scientists speeds up the production and trade of private information, but the concentration of data scientists covering a stock reduces its price informativeness in the capital markets,” Professor Jo adds.

“Competition among data scientists speeds up the production and trade of private information, but the concentration of data scientists covering a stock reduces its price informativeness in the capital markets.”

Professor Jo Chanik

Are data scientists the modern Midas?

As explained in a paper titled, Data scientists on Wall Street, Professor Jo and Professor Cen, as well as Han Bing of the University of Toronto and Han Yanru of Stevens Institute of Technology, collected detailed resumes from the Revelio Lab, which gathers career history data from various sources, including LinkedIn and Indeed.

They then merged the dataset with data from Refinitiv and Thomson Reuters Global Ownership to link with the actual stock holdings. Data scientist roles were further identified with a US-based occupations classification system called the ONET code, resulting in 326,627 unique data scientists employed by 3,126 institutional investors from 2008 to 2021.

Data scientists were mainly classified into three groups: data collectors for those gathering and organising data, data analytics for those evaluating data for making business decisions, and data maintenance refers to storing and protecting data with proper hardware. Data analytics has the most substantial impact on trading profitability, implying that data analysis provides the most direct and valuable insights for investment decisions.

Institutional investors with more data scientists also achieve higher profits. Each additional data scientist hired leads to a 0.004 percentage point increase per quarter in “abnormal” profits, which refer to returns earned that exceed predictions by standard asset pricing models. One extra data scientist translates to a 13 per cent increase in the average trading profitability.

“Data scientists assist financial institutions in earning abnormal profits by collecting, maintaining, and analysing large datasets, particularly alternative data, to identify mispriced assets,” says Professor Jo.

“Their insights allow institutions to make profitable trading decisions, with data analysts having the strongest impact on generating investment returns.”

Unequal access creates unequal outcomes

As multiple institutional investors can hold the same stock, the researchers then focus on the concentration of data scientists. To illustrate, stock A is held by 10 investors, with one having ten data scientists and the rest having none. The same number of investors holding stock B, each owning one data scientist. While the total number of data scientists is the same, stock A has a higher data scientist concentration than stock B.

In stock A, the investor with more data scientists has an analytical edge as it has more resources focusing on one stock. In stock B, each investor has similar resources, making the race to extract and leverage information more intense, eventually diminishing the informational advantage.

When a handful of investors with higher data scientist concentration strategically tilt their asset allocation to a smaller set of stocks, they enjoy an “information monopoly,” where the generated insights are concentrated within a few. Such a privilege is not for sharing.

“It’s not the number but the concentration of data scientists that reduces price informativeness. When data scientists are concentrated among a few institutional investors, these investors gain an information monopoly and have less incentive to trade on their information quickly,” says Professor Jo. “These investors trade cautiously to protect their advantage, delaying the incorporation of information into stock prices and limiting its spread across the market.”

Investors who hire more data scientists are found to hold more concentrated portfolios. A one standard deviation increase in data scientist concentration leads to an 11 per cent decrease in price informativeness. “This concentration creates a situation where valuable insights remain with a small group of investors rather than being reflected in stock prices, leading to less efficient price formation.”

Race to build the best data army

While institutional investors compete to be one step ahead of others, hiring more and more data scientists has become the new battleground. Investors finding themselves lagging behind their peers will react by increasing their recruitment efforts, especially for data analytics roles.

Financial institutions that frequently trade stocks, cover a broader range of industries, and have larger assets are more likely to expand their data teams, as evidenced by hedge funds employing more data scientists than pension funds and banks. These investors are strategically monitoring and responding to their competitors’ hiring activities, rather than blindly following general trends. Data scientists who worked for competitors are also sought after, leading to a tense catch-up in the talent race.

The number of data personnel recruited positively correlates with the number of data-science related undergraduate programmes at local universities, suggesting that the supply in the labour market affects financial institutions’ employment.

“Data science roles in financial markets will likely continue growing rapidly, with increasing specialisation and strategic importance,” Professor Jo adds. “As the competition intensifies among financial institutions and against tech companies, we may see wider wage premiums for data talent, more sophisticated analytical techniques, and potentially regulatory responses addressing the efficiency costs of concentrated information advantages.”

Although the study used data on American institutional investors, he believes the findings would likely be relevant to emerging markets like China. “The competition for data talent and the value of information advantages are universal market dynamics. However, regulatory differences, varying levels of market efficiency, and potential differences in data availability might affect the magnitude of these effects in emerging markets.”

The post The irresistible rise of financial data scientists first appeared on China Business Knowledge.

Featured faculty: Johnny Li, Chan Wai-sum and Zhu Xiaobai
Written by Putro Harnowo

Just like every dark cloud has a silver lining, insurers are proficient at managing risks and turning them into opportunities. As ageing population has become a pressing issue around the globe, the booming demand for insurance and annuities presents considerable potential.

China, one of the fastest-ageing countries, is expected to see its personal insurance market expand from four trillion Chinese yuan (US$553 billion) in 2021 to between 6.6 and 12.6 trillion Chinese yuan by 2035, according to the Boston Consulting Group 2024 report. Its pension insurance market share is expected to soar from one to 20 per cent, and health insurance is projected to grow from 27 to more than 35 per cent.

The Chinese government has also encouraged commercial insurance, basic pension, annuity, and wealth management funds to participate in listed companies’ private placements as strategic investors. Such a move is a part of a broader strategy to attract long-term capital and enhance the stability of the country’s financial markets.

While a sense of optimism seems to fill the air, there lies a fundamental challenge that could defy expectations. “Mortality data in China is collected through diverse sources and methodologies, resulting in inconsistency,” says Johnny Li, Professor at the Department of Finance at the Chinese University of Hong Kong (CUHK) Business School.

Mortality rate is a fundamental component determining population size and age structure, in addition to fertility and migration rates. Compared to other demographic measures that inform broader societal trends, mortality forecasting has more direct financial and actuarial consequences as it allows insurers and pension funds to price life insurance products, annuities, and pensions appropriately and to maintain sufficient reserves.

Accurate mortality projection is clearly the need of the hour, yet only a handful of attempts have been made to build reliable models. Therefore, Professor Li and his colleagues at the School, Emeritus Professor Chan Wai-Sum and Assistant Professor Zhu Xiaobai, as well as Kenneth Zhou at the University of Waterloo and Felix Chan Wai-Hon at the University of Hong Kong, developed A Bayesian approach to developing a stochastic mortality model for China.

“Bayesian is a technical term, a distinguished approach that we can incorporate as much information as possible and overcome data challenges from different sources,” Professor Li says. “Insurance and financial sectors need a model like this, given the data challenges facing them.”

“For actuaries and insurers, the life expectancy projection is not the only important variable, but the uncertainty surrounding the projection is probably even more important. With the Bayesian approach, we can generate measures of uncertainty.”

Professor Johnny Li

Three criteria for a robust mortality model

As explained in the paper, China’s age and gender-specific mortality data before 1981 are absent, while the data from 1981 to 2014 are either partially or completely missing. The data for 1981, 1989, 2000 and 2010 were obtained from nationwide censuses, but the rest were acquired from surveys of a fraction of the national population, making it arduous to forecast demographic trends accurately.

Many other countries may have similar data issues. However, Professor Li notes that the problem in China is unique due to its significant population size. A reliable mortality model is compulsory to drive more innovative pension policies and healthier ageing strategies, crucial for the current demographic shifts.

For a mortality model to be robust, he underscores three essential criteria. The first criterion is to incorporate as much data as possible so that the model can use any available information. The second criterion is appropriate provision of uncertainty, since the model should consider not only the best estimate but also a range of possible deviations or uncertainty around the estimate.

Uncertainty here refers to the degree of variability produced by the model, quantifying how much the projected mortality rates might deviate from expectations due to various sources and limited data. “For actuaries and insurers, the life expectancy projection is not the only important variable, but the uncertainty surrounding the projection is probably even more important,” he adds. “With the Bayesian approach, we can generate measures of uncertainty.”

The third criterion is parsimonious and biologically reasonable. As the model is basically an approximation of reality, parsimonious refers to a realistic model that captures the necessary details but not overly complicated. Biologically reasonable means the mortality model should produce sensible results, for instance, the mortality rates for the elderly should be higher than those of much younger people.

Wider applications in the markets

Since the initial study proposes a mortality model for the nationwide population, Professor Li and his colleagues at CUHK have developed an enhanced version for different parts of China.

In practice, this enhanced model has been utilised by insurance companies to establish continuing care retirement communities (CCRCs) in Shanghai, Beijing, Guangzhou, Xiamen, and more. CCRC is a residential community providing healthcare, security, social activities, meals, housekeeping, and wellness programmes for the elderly. This concept has been around for more than a century in Europe and the US, and has found its way to China in recent years.

“Our model now includes the extension of geographical specificities that can be used to predict the demands of CCRCs in different cities across China and also to estimate how long people will spend their time in those communities,” Professor Li adds.

Professor Li argues that the enhanced mortality model is also very useful for reinsurance purposes. Insurers that have sold a considerable number of annuity and other insurance products normally share their risks by purchasing insurance policies from reinsurers. Reinsurance companies naturally have larger risk pools than primary insurance companies. Professor Li’s model can be used, for instance, by a reinsurer with portfolios in Shanghai and China’s Greater Bay Area, to leverage diversification opportunities.

Professor Li is currently refining his model to incorporate more factors that may drive life expectancy, such as smoking prevalence, lifestyle and living conditions. This work is expected to improve forecast accuracy.

The post Refining longevity risks for China’s ageing population first appeared on China Business Knowledge.