Business Commons^™

How Commonality Persists? (Through Investors' Sentiment And Attention), Chyng Wen Tee, Raja Velu, Zhaoque Zhou

Research Collection Lee Kong Chian School Of Business

Studies on commonality generally attribute the variation in asset returns to the variation in order flows. In this research study, we show that order flows do not predict asset returns, rather their relationship have been static over time. Thus we model both returns and the order flows as endogenous variables, and use investors' sentiment and attention as exogenous factors via a reduced-rank regression. We provide empirical evidence to demonstrate that cross-sectional commonality in attention (sentiment) is linearly (nonlinearly) associated with both returns and order flows at the intraday level, while the sentiment and attention measures themselvesexhibit a nonlinear mutual relationship, …

In Search Of Cryptocurrency Failure, Donglian Ma, Jun Tu, Zhaobo Zhu

Research Collection Lee Kong Chian School Of Business

This paper explores the determinants of cryptocurrency failure and the pricing of crypto failure risk. We document different significant market- and characteristic-based predictors for coin and token failures. The introduction of Bitcoin futures and the outbreak of COVID19 affect the importance of many predictors. Investors require extra return for bearing high failure risk of crypto assets. The return difference across high and low failure risk crypto assets is not explained by the market, size and momentum factors in the cryptocurrency market. Finally, investors benefit from diversifying into high failure risk crypto assets that is little correlated with the stock market.

Legal Risk And Insider Trading, Marcin Kacperczyk, Emiliano Sebastian Pagnotta

Research Collection Lee Kong Chian School Of Business

Do illegal insiders internalize legal risk? We address this question with hand-collected data from 530 SEC (the U.S. Securities and Exchange Commission) investigations. Using two plausibly exogenous shocks to expected penalties, we show that insiders trade less aggressively and earlier and concentrate on tips of greater value when facing a higher risk. The results match the predictions of a model where an insider internalizes the impact of trades on prices and the likelihood of prosecution and anticipates penalties in proportion to trade profits. Our findings lend support to the effectiveness of U.S. regulations' deterrence and the long-standing hypothesis that insider …

Housing Fever In Australia 2020-23: Insights From An Econometric Thermometer, Shuping Shi, Peter C. B. Phillips

Research Collection School Of Economics

Australian housing markets experienced widespread and, in some cases, extraordinary growth in prices between 2020 and 2023. Using recently developed methodology that accounts for fundamental economic drivers, we assess the existence and degree of speculative behaviour, as well as the timing of exuberance and downturns in these markets. Our findings indicate that speculative behaviour was indeed present in six of the eight capital cities at some time over the period studied. The sequence of events in this nation-wide housing bubble began in the Brisbane market and concluded in Melbourne, Canberra, and Hobart following the interest rate rise implemented by the …

Does Abstract Thinking Facilitate Information Processing? Evidence From Financial Analysts, Frank Weikai Li, Rong Wang, Yang Yu, Gloria Yang Yu

Research Collection Lee Kong Chian School Of Business

We study whether abstract thinking – an essential cognitive trait established by psychological and neuroscientific studies – facilitates analysts’ information processing. Exploiting analysts’ questions during earnings calls, we construct an Abstract Thinking Index (ATI) that measures their tendency to involve abstract words, logical reasoning, broader topics, and future outlooks. We find that abstract thinking improves analysts’ forecast accuracy and recommendation informativeness. Consistent with abstract thinking featuring identifying central characteristics and comprehending intangible things, ATI has stronger effects for firms with fundamentals co-moving more with peers and less tangible information. Additional analyses suggest that ATI captures analysts’ cognitive traits rather than …

What Drives The Value Of Financial Analysts’ Advice? The Role Of Earnings And Growth Forecasts, Ohad Kadan, Leonardo Madureira, Rong Wang, Tzachi Zach

Research Collection Lee Kong Chian School Of Business

We offer a parsimonious index at the individual analyst level to measure the extent to which an analyst relies on earnings and long-term growth forecasts in producing her advice. Using this index, we evaluate the contribution of earnings and growth forecasts to the investment value of analysts’ stock recommendations. We find that the fraction of analysts’ advice attributed to forecasts varies considerably across analysts and sectors. The investment value of recommendations is higher for analysts who rely less on their forecasts and more on other sources of information when forming investment advice. Investors recognize the superiority of recommendations from analysts …

The Cost Of Cheap Talk: How Campaign Promises And Default Contributions Affect Donation-Based Crowd Funding Success., Tianci Leon Qiu

Dissertations and Theses Collection (Open Access)

Non-profit organisations (NPOs) find it increasingly harder to engage donors and raise funds from the public. Post-pandemic: the emphasis on tactics to raise funds online through donation-based crowdfunding (DCF) platforms has surged in importance for both NPO survival and continued beneficiary aid. However, unlike equity-based crowdfunding platforms where campaign organisers are obligated to provide investors with tangible returns based on funding milestones, NPOs on DCF platforms do not have to adhere to any funding milestones or are beholden to any tangible obligations towards donors. Consequently, NPOs are greatly incentivised to deploy cheap talk – non-binding, unverifiable messages and claims to …

Seeking Better Sharpe Ratio Via Bayesian Optimization, Peng Liu

Research Collection Lee Kong Chian School Of Business

Developing an excellent quantitative trading strategy to obtain a high Sharpe ratio requires optimizing several parameters at the same time. Example parameters include the window length of a moving average sequence, the choice of trading instruments, and the thresholds used to generate trading signals. Simultaneously optimizing all these parameters to seek a high Sharpe ratio is a daunting and time-consuming task, partly because of the unknown mechanism determining the Sharpe ratio. This article proposes using Bayesian optimization to systematically search for the optimal parameter configuration that leads to a high Sharpe ratio. The author shows that the proposed intelligent search …

Disagreement In Market Index Options, Guilherme Salome, George Tauchen, Jia Li

Research Collection School Of Economics

We generate new evidence on disagreement among traders in the S&P 500 options market from high-frequency intraday price and volume data. Inference on disagreement is based on a model where investors observe public information but agree to disagree on its interpretation; disagreement among investors is captured by the volume–volatility elasticity. For options, there are two natural variables related to disagreement: moneyness and tenor, which we relate to disagreement about the distribution of the market index at different quantiles and times. The estimated volume–volatility elasticity equals unity for options near the money and close to expiration, which is consistent with the …

An Empirical Research On The Financial Distress Risk In The Garden And Construction Industry, Jianlin Guan

Dissertations and Theses Collection (Open Access)

In recent years, the garden and construction industry has faced significant financial distressdue to the downward pressure on the macro economy. This financial distress not onlyposesrisks to the financial stability and management of enterprises but also has far-reachingimpactson society.

This paper utilizes various analytical methods such as case analysis, empirical analysis, andevent analysis to derive the following conclusions:(1)The participation of garden constructionindustry enterprises in public-private partnership (PPP) projects leads to increased financial distress.(2)The higher the debt ratio of the local government where listed gardenandconstruction enterprises are located, the greater the financial distress theyexperience.(3)Enterprises in the garden and construction industry, whose …

Cbdc: Context, Challenges, And Conditions For A Successful Adoption, Charlie Nhuc Hiang Lay

Dissertations and Theses Collection (Open Access)

Central bank digital currencies (CBDC) are the digital version of physical notes and coins. They are the latest milestone in the evolution of money over the centuries due to technological advancements. This digitalisation of physical money primarily serves as a medium of exchange that has a central bank anchor. There are two versions of CBDC, wholesale and retail. This thesis focuses on retail CBDC, which targets the general public and small daily transactions. It discusses the issues and the plausible implementation of a retail CBDC. A CBDC will preserve monetary sovereignty, foster financial stability, and counter private network effects, i.e., …

Consumer Reaction To The Use Of Artificial Intelligence Chatbot On Distribution Of General Insurance In Singapore, Lai Hing Tan

Dissertations and Theses Collection (Open Access)

As technology rapidly permeates all aspects of our lives, it is not unusual to question and even challenge the rationale on why certain industries are slower to adapt to the new digital age. Insurance is a business that is under scrutiny given its traditional ways of selling and legacy challenges. Why is technology investment in insurance companies lagging others? One emerging technological disruption is artificial intelligence (AI). It is the science of designing and building intelligent systems that can complete tasks traditionally performed by humans. AI is expected to fundamentally transform today’s marketplace, for businesses and consumers alike. However, because …

Liquidity Constraints, Consumption, And Debt Repayment: Evidence From Macroprudential Policy In Turkey, Sumit Agarwal, Muris Hadzic, Changcheng Song, Yildirim Yildiray

Research Collection Lee Kong Chian School Of Business

Using account-level credit card data from a large Turkish bank, we study the impact of a unique credit card policy that increases minimum payment on consumption and debt repayment. We show that the policy reduces credit card spending and debt, boosts existing debt repayment, and reduces credit card delinquency. The credit card debt of affected consumers falls on average by 50% two years into the policy’s implementation. An increase in minimum payment has a stronger effect than does a decrease of a similar magnitude. We build a benchmark life cycle model with soft liquidity constraint to explain the reduction in …

Hedging Cryptos With Bitcoin Futures, Francis Liu, Natalie Packham, Meng-Jou Lu, Wolfgang Karl Haerdle

Sim Kee Boon Institute for Financial Economics

The introduction of derivatives on Bitcoin enables investors to hedge risk exposures in cryptocurrencies. Because of volatility swings and jumps in cryptocurrency prices, the traditional variance-based approach to obtain hedge ratios may not be suitable for hedgers. In this work, we consider two extensions of the traditional approach: first, different dependence structures are modelled by different copulae, such as the Gaussian, Student-t, Normal Inverse Gaussian and Archimedean copulae; second, different risk measures, such as value-at-risk, expected shortfall and spectral risk measures are employed to find the optimal hedge ratio. Extensive out-of-sample tests using the data from the time …

Exchange-Traded Funds And Real Investment, Constantinos Antoniou, Frank Weikai Li, Xuewen Liu, Avanidhar Subrahmanyam, Chengzhu Sun

Research Collection Lee Kong Chian School Of Business

We investigate the link between exchange-traded funds and real investment. Cross-sectionally, higher ETF ownership is associated with an increased sensitivity of real investment to Tobin's q and a heightened ability of stock returns to forecast future earnings. Inclusion of stocks in industry ETFs enhances investment-q sensitivity and implies greater incorporation of earnings information into prices prior to public releases. Greater nonmarket ETF ownership leads to increased (reduced) reliance of real investment on own (peers') stock prices. Overall, the evidence is consistent with ETFs positively affecting real investment efficiency via greater flows of information.

Assessing The Odds Of A Us Recession, Thomas Lam, David Fernandez

Sim Kee Boon Institute for Financial Economics

In this commentary, SMU Sim Kee Boon Institute for Financial Economics (SKBI) Principal Researcher Thomas Lam and SKBI Director SMU Professor of Finance (Practice) Dave Fernandez offer their perspectives on the current multifaceted and highly charged US recession debate. While America is currently not in a downturn, the near-term odds of one have edged up, according to models based on key monthly and weekly indicators.

Impact Of Geographical Diversification And Limited Attention On Private Equity Fund Returns, Victor Ong

Research Collection Lee Kong Chian School Of Business

This article analyzes the effect of geographical diversification on global private equity (PE) fund returns. We find that there is a negative correlation between geographical diversification and PE fund returns. To establish the causality between geographical diversification and PE fund returns, we employ an instrumental variable analysis where the instrument used is the stock market capitalization of the host country where the PE fund is based. Our results apply to Net IRR, TVPI and DPI as dependent variables used to proxy for PE fund returns in the main regression model. A one standard deviation increase in geographical diversification results in …

The Financialization Of Cryptocurrencies, Lei Huang, Tse-Chun Lin, Fangzhou Lu, Jian Sun

Research Collection Lee Kong Chian School Of Business

We show that change in Grayscale Bitcoin Trust premium is the single most significant predictor of Bitcoin daily return. This sentiment measure is similar to the closed-end fund discount measure as in Baker and Wurgler (2006), but more likely to reflect the excess demand from traditional investors than from blockchain specialists. Although there is a substantial variation in Bitcoin price quotes worldwide, this Grayscale premium and discount predict Bitcoin daily return for the most liquid Bitcoin exchanges. Using K-means clustering and LDA analysis, we find that this predictability is especially significant when there is a large variation in bullish and …