Applied Finance Letters (E-Journal - Auckland Centre for Financial Research)
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149 research outputs found
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EVALUATING STOCK SELECTION IN THE SAAS INDUSTRY: THE EFFECTIVENESS OF THE RULE OF 40
Full text linkThe Rule of 40 is a popular financial guideline used by software-as-a-service (SaaS) industry participants to assess the operational health of the companies. This paper investigates the effectiveness of the Rule of 40 as a stock selection criterion. Our study analyses a sample of 1756 SaaS companies worldwide spanning the period 2003-2022. The findings demonstrate that the Rule of 40 adds value and delivers a moderately high Sharpe ratio as a stock selection tool. A modified rule, the SaaS Investing Rule of 65, is proposed and found to outperform the Rule of 40 in identifying relative winners and losers within the SaaS space. The effectiveness of the rules raises practical implications for investors and analysts. Additionally, we explore the effectiveness of alternative versions of the Rule of 40 using different measures of profitability, as well investigate whether the returns are driven by traditional style factors
COVID-19: PERFORMANCE OF ESG ETFS AND, ESG ETFS VS. THEIR DECLARED INDEXES
Full text linkSince Covid-19 started, it has created nothing but puzzle in the investment field. This paper adds more knowledge to ESG funds by investigating the performance of 96 ESG ETFs during the Covid-19 market stress. My findings show that ESG ETFs outperformed the market during the pandemic, suggesting they were better immune investments than other investment tools. This addresses the controversy that ESG funds are more likely of having actual investment performance value than just being of marketing tools. In addition, this paper examines whether ESG ETFs attempted to track their indexes exactly, and the results indicate that ETF funds did an excellent job on tracking their indexes they followed before Covid-19 and Covid-19 recovery except for during Covid-19 since their indexes were harder to track during the outbreak. This paper also provides discussion on why ESG funds were better immune investment tools. My findings and discussions aim to inform investors and portfolio managers in decision making during this outbreak
CSR SPENDING IN INDIA: EXPLORING THE LINKAGES WITH BUSINESS GROUP AFFILIATION AND PRODUCT PORTFOLIO DIVERSIFICATION
Full text linkThe present study aims to examine the influences of group affiliations status on the CSR spending of a firm and also to test how the group size and interaction of group size and product portfolio diversification influences the CSR spending. The sample of the present study covers 1,513 Indian firms coming under the ambit of CSR reporting, represented through the unbalanced panel data set of 4,459 firm-years from the year 2014 to 2019. The baseline model regresses CSR spending on the group affiliation status and set of controlling variables which are having the impact on CSR spending by using panel least squares regression model. The baseline model is extended to test the impact of group size and interaction of group size and product portfolio diversification on the CSR spending. Industry variations with regard to CSR spending are controlled by introducing industry fixed effects into the regression model. The findings of the study reveal significant positive impact of group affiliation status on CSR spending. The results are also robust to the group size effect and the interaction effect of group size and product portfolio diversification. The findings are supporting stewardship theory and socio—emotional wealth creation view of the group affiliated firm which asserts that group affirms experience variety of stakeholder demands and social issues. Building social reputation through CSR activities will be helpful in handling such situations. The findings also proved that larger group firms with wider product diversification are more encouraged towards CSR spending. This is the first study which tests the impact of group size and also the interaction of group size and product portfolio diversification on CSR spending. The study contributes to the literature on how the ownership style, especially, group affiliation status, influences the social engagement of a fir
MACRO FACTORS IN THE RETURNS ON CRYPTOCURRENCIES
Full text linkThis 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
PRIORITISATION OF FACTORS FOR ARTIFICIAL INTELLIGENCE-BASED TECHNOLOGY ADOPTION BY BANKING CUSTOMERS IN INDIA: EVIDENCE USING THE DEMATEL APPROACH
Full text linkArtificial 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
Full text linkShare 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
THE MARKET VALUE OF DECENTRALISATION
Full text linkA prominent motivation for the use of cryptocurrencies is the system of exchange does not require a central trusted authority. In fact there are a class of decentralised exchanges where participants can exchange cryptocurrencies using a protocol rather than a centralized exchange. This analysis uses the failure of the centralized FTX exchange to estimate the value the market assigns to decentralised versus centralised exchanges. We find the market assigns a significant value to decentralisation
THE JANUARY ANOMALY AND ANOMALIES IN JANUARY
Full text linkPrior research finds that stocks earn significantly higher returns in January compared to other months, with the effect most often attributed to tax-motivated selloffs in December leading to price reversion in January. We examine how patterns in turn-of-the-year performance impact prominent return anomalies. We find that short-term reversals strengthen while momentum changes sign at the turn of the year, and such patterns are more pronounced following years of recession and poor market performance, consistent with tax-loss selling playing a key role. Although additional factors are likely to contribute to the overall effect, no significant change in anomaly performance occurs midyear, casting doubt on window-dressing as a primary driving force
EQUITY PLEDGE, PLEDGOR TYPE AND INVESTMENT EFFICIENCY
Full text linkEquity pledging is susceptible to agency problems and substantial risk, resulting in inefficient corporate investment. We show the negative impact is not just induced by controlling shareholders but also pledged by non-controlling shareholders and actual controllers. Our results add that SOEs with control rights via controlling shareholders or actual controllers can mitigate investment inefficiency problems. We conclude that pledgor type matters and the impact of non-controlling shareholders’ pledges should not be neglected
MEASURING VALUATION UNCERTAINTY: A PCA APPROACH
Full text linkDetermining which companies are more difficult to value is a topic of significant interest in finance. Prior studies have employed many univariate proxies for valuation uncertainty to classify firms into high- and low-valuation uncertainty groups. In this study, I employ principal component analysis (PCA), a dimensionality reduction technique, using 11 valuation uncertainty proxies to extract the valuation uncertainty latent factor contained in the first principal component, which is proposed as a new measure of a firm’s valuation uncertainty, and show that it accurately captures a firm’s valuation uncertainty. I contend that using a PCA-derived valuation uncertainty index offers two benefits. First, integrating multiple valuation uncertainty proxies into a single metric improves our ability to quantify a firm’s valuation uncertainty. Second, it can assist in identifying the proxies that are most useful in measuring a firm’s valuation uncertainty