Applied Finance Letters (E-Journal - Auckland Centre for Financial Research)
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    119 research outputs found

    IMPACTS OF RISK PREFERENCE AND SOCIAL INSURANCE ON HOUSEHOLD FINANCIAL MARKET PARTICIPATION IN CHINA: ARE THERE DIFFERENCES BETWEEN URBAN AND RURAL RESIDENTS?

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    This letter examines the impact of risk preference and social insurance on household financial market participation and diversification using the 2017 and 2019 China Household Finance Survey. A multi-value treatment model is used to address the selection bias between risk preference and household financial investment, considering the moderation role of social insurance in between. Overall, our results show that high-risk takers are more likely to participate in the financial market and diversify their portfolios than low risk takers. Focusing on rural and urban differentials, we find marked differences in the impacts of risk preference and social insurance on household financial investment. Having social insurance may widen the difference in investment decisions between high- and low-risk takers in urban areas; the latter group tends not to participate in or diversify when socially insured. In contrast, having social insurance encourages low- and intermediate-risk preferred rural households to participate in the financial market and diversify their financial portfolios. Our work highlights the different consequences of social insurance on investment incentives of the rural and urban households. Whilst the obvious benefits of having social insurance for rural households via risk-sharing, there is undesired consequence of incentive distortion of urban households

    BANK EFFICIENCY AND GOVERNANCE: EVIDENCE FROM JOINT VENTURE AND FOREIGN COMMERCIAL BANKS IN VIETNAM

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    In this paper, we intend to examine the influence of national governance on the bank efficiency of joint venture and foreign commercial banks in Vietnam. Joint venture and foreign commercial banks have been instrumental in introducing new financial products to the Vietnamese market (e.g., mortgage services and medium-term certificates of deposit). At the same time, they have also penetrated the retail market through automobile and housing loans, and international credit card services.  We use the DEA double bootstrap method to develop a bank network function to evaluate bank efficiency. The findings from our random-effects model demonstrate that world governance indicators as proposed by the World Bank independently determine the bank efficiency of the joint venture and foreign commercial banks in Vietnam. There are important implications to be highlighted for policymakers and stakeholders of joint venture and foreign commercial banks and other types of banks in the banking industry elsewhere around the world

    MACRO FACTORS IN THE RETURNS ON CRYPTOCURRENCIES

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    This study investigates the relationship between expected returns on cryptocurrencies and macroeconomic fundamentals. Investors employ a lot of macroeconomic indicators for their investment decision, and hence adopting a few macroeconomic indicators is not sufficient in capturing a change in economic states. Moreover, due to aggregation, macroeconomic indicators are not measured precisely. To overcome these problems, we employ a dynamic factor model and extract common factors from a large number of macroeconomic indicators. We find that the common factors are strongly linked to the cryptocurrency expected returns at a quarterly frequency, while we do not observe this relationship using macroeconomic indicators such as inflation and money supply. This suggests that macroeconomic information matters in a longer term, which contrasts with the previous literature that explores a short-term relationship. The cryptocurrency prices are not determined by macroeconomic fundamentals in a short-term period since speculators impact the prices. However, in a long-term period, the prices are more linked to macroeconomic fundamentals

    EX ANTE PREDICTABILITY OF STOCK RETURNS IN A FRONTIER MARKET

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    This study reports results on the ex ante predictability of stock returns using real-time stock market data in Vietnam, a frontier market, from June 2008 to June 2021. Countries classified as a frontier market are often known for currency manipulation, financial market illiquidity, and political instability. Despite the enormous risk usually posed by these inefficiencies, potential profits are large and achievable for many investors. This study provides evidence on existing a strategy to form out-of-sample long portfolios that generate statistically significant and positive mean monthly returns even in the presence of transaction costs. I also justify the magnitude of these returns by showing that they exceed those of VnIndex and MSCI Vietnam Index. The results reject the hypothesis that the stock prices in Vietnamese market follow random walks, thus oppose the stock market efficiency hypothesis. Evidence found in this study provides a better understanding of informational efficiency in a frontier equity market setting. Specifically, there are several implications on portfolio selection strategies, stock price patterns, and trading behavior bias related to Vietnamese stock market can be drawn from this study

    PRICE CLUSTERING BEHAVIOR IN VIRTUAL REAL ESTATE MARKETS

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    We analyze 21,209 intraday transactions in the virtual real estate market and document significant price clustering at round numbers 0, 00, and 000 as ending digits, consistent with the negotiation hypothesis. The clustering increases with price level and pricing uncertainty proxied by the number of buyers and sellers in the NFT market. Moreover, market venue influences price clustering dynamics. Digits 9, 99, and 999 as ending prices are overrepresented in the sample, consistent with the left digit effects. However, we do not find support for the psychologically feeling right hypothesis or the strategic trading hypothesis

    PRIORITISATION OF FACTORS FOR ARTIFICIAL INTELLIGENCE-BASED TECHNOLOGY ADOPTION BY BANKING CUSTOMERS IN INDIA: EVIDENCE USING THE DEMATEL APPROACH

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    Artificial Intelligence (AI) is a concept of recent origin and is accepted for banking activities such as customer service, detection of fraudulent activities, and suspicious transactions. For the successful implementation of AI in the Indian context, a deep understanding is required in terms of its need and importance compared to the traditional banking system. To date, this outlook of AI has been less focused by industry practitioners and experts for the smooth flow of operational procedures in banks for developing countries, for example, India. This study aims to unearth factors and establish a relationship among the identified factors through the decision-making trial and evaluation laboratory (DEMATEL) approach to categorize the factors and frame the cause-and-effect relationships. Fifteen factors are identified through a literature review of existing studies, and ten experts were solicited to express their outlook on this subject. The result indicated that 'Transparency of information,' 'Perceived security of AI-based technology,' 'Social influence on customer,' 'Government regulation of AI in banks,' 'Awareness level of AI,' 'Efficiency of AI system,' 'Technical requirement,' and 'Cost of AI-based technology' were causative factors that support customer acceptance and penetration of AI in banks. The study presents a unique approach to customer acceptability towards AI in banks in developing countries using the DEMATEL technique. This study also discusses the possible area for the adaption of AI in Indian banks. The findings will support policymakers and practitioners in executing AI-based technologies in the banking sector in emerging nations

    PAYOUT POLICY DURING MARKET-WIDE FINANCIAL CONSTRAINTS: EVIDENCE FROM THE COVID-19 DOWNTURN

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    Share repurchases are perceived as a flexible payout mechanism as it distributes free cash flow while mitigating the risk of underinvestment. It may be simpler to stop or trim share repurchases than dividend payments. We test the flexibility hypothesis of share repurchases using the Covid-19 economic crisis as a natural experiment where firms encounter a sudden cash-flow uncertainty. We employ a balanced panel of S&P 1500 firms from the period 2014 to 2021. Our results are consistent with the view that share repurchases offer more flexibility than dividends. Firms are likely to reduce share repurchases when they are cash constrained but still maintain dividend payouts. However, firms are also likely to trim dividends if the financial constraints persist

    COUNTRY-SPECIFIC INVESTOR ATTENTION AND ADR MISPRICING

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    This paper examines the effect of country-specific investor attention on ADR mispricing. Investor attention is measured by the amount of traffic a country’s Wikipedia profile page receives. A two-stage least squares (2SLS) regression is employed to examine the relationship between investor attention and ADR mispricing, but also to mitigate endogeneity between the two variables of interest. We use the FIFA World Ranking (country soccer ranking) and the number of UNESCO heritage sites as instruments for investor attention; given the unlikelihood that either of those variables can be caused by ADR mispricing. Our results show that lower levels of investor attention lead to higher ADR mispricing, therefore leading to a greater divergence of the law of one price for the sample of ADRs.  The results are robust across various model specifications and to well-known determinants of mispricing such as turnover, stock prices, exchange rates, and market capitalization

    STUDENT LOANS: LESSONS FROM BORROWERS

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    The study presents the results and the analysis of a survey of recent student loan borrowers. The fields of study that result in the highest disbalance between the amount borrowed and the generated earnings are identified. Additionally, the survey results shed light on the post-graduation spending behavior of the borrowers. The results indicate that the present student loan crisis may, at least in part, be caused by the selection of the major area of study and by the post-graduation personal consumption overadjustment of individuals from several (less financially lucrative) fields of study

    PRODUCTIVITY UNCERTAINTY AND STOCK PRICE CRASH RISK

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    This study examines the impact of productivity uncertainty on stock price crash risk. Empirical results show that higher productivity uncertainty contributes to higher stock price crash risk. This effect holds firmly after addressing potential endogeneity and the performing of robustness tests. Moreover, the positive impact of productivity uncertainty on stock price crash risk is more pronounced for firms with weak market competition and less independent boards. The findings of this study are meaningful as they offer a risk-based explanation for stock price crash risk which is based on the presumption of investors’ behaviors

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    Applied Finance Letters (E-Journal - Auckland Centre for Financial Research) is based in New Zealand
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