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This paper aims to examine the comovement among green bonds, energy commodities and stock market to determine the advantages of adding green bonds to a diversified portfolio.

Generic 1 Natural Gas and Energy Select SPDR Fund are used as proxies to measure energy commodities, bonds index of S&P Dow Jones and Bloomberg Barclays MSCI are used to represent green bonds and the New York Stock Exchange is considered to measure the stock market. Granger causality test, wavelet analysis and network analysis are applied to daily price for the select markets from August 26, 2014, to March 30, 2021.

Results from the Granger causality test indicate no causality between any pair of variables, while cross wavelet transform and wavelet coherence analysis confirm strong coherence at a high scale during the pandemic, validating comovement among the three asset classes. In addition, network analysis further corroborates this connectedness, implying a strong association of the stock market with the energy commodity market.

This study offers new evidence of the temporal association among the US stock market, energy commodities and green bonds during the COVID-19 crisis. It presents a novel approach that measures and evaluates comovement among the constituent series, simultaneously using both wavelet and network analysis.

The purpose of this study is to examine the impact of a recent innovation in the uranium market, the Global X Uranium Exchange-Traded Fund (URA), on the trading characteristics of constituent and non-constituent stocks.

The authors analyse bid-ask spread measures, relative effective spreads and adverse selection costs to assess changes in information asymmetry among uranium stocks. The authors also study abnormal returns to assess the impact of URA on the market.

Over a three-month period, following the introduction of URA, the authors find uranium stocks display decreased bid-ask spread measures, driven by reductions in information asymmetry. Relative effective spreads decrease by 36% after the introduction of URA, and adverse selection costs decline by 24% over the same period. Uranium stocks experience a significant positive abnormal return of 5.0% the day after the introduction of URA with subsequent price reversals. These suggest that the introduction of URA prompted uninformed traders to rebalance portfolios and migrate to the less information-sensitive Exchange-Traded Fund (ETF), causing temporary deviations in trading characteristics.

The authors demonstrate that the introduction of new financial securities to the market can have a significant impact on the trading characteristics of related equities. As URA is the only ETF in the uranium sector, the authors thereby avoid the influence of multiple ETFs that may have impacted previous studies.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.

The paper aims to investigate differences in non-professional and professional stock investors’ trust in and tendency to follow financial analysts’ buy and sell recommendations.

Online experiment conducted in Sweden in March 2022 comparing non-professional private investors (n = 80), professional investors (n = 33), and master students in finance (n = 28). Information was presented about four company stocks listed on the New York stock exchange. Two stocks were buy-recommended and two stocks sell-recommended by financial analysts. For one stock of each type, the recommendation was presented to participants. Dependent variables were predictions of the stock price after three months, ratings of confidence in the predictions and choices of holding, buying or selling the stock. Ratings were also made of the importance of presented stock-related information as well as trust in analysts’ skill and integrity.

More positive return predictions were made of buy-recommended than sell-recommended stocks. Non-professionals and to some degree finance students tended to trust financial analysts more than professional investors did and they were more influenced by the presentation of the buy recommendations. All groups made too optimistic return predictions, but the professionals were less confident in their predictions, more likely to sell the stocks and lost less on their investments.

A new finding is that non-professional stock investors are more likely than professional stock investors to trust financial analysts and follow their recommendations. It suggests that financial analysts’ recommendations influence non-professional investors to take unmotivated investment risks. Non-professionals in the stock market should hence be advised to exercise more caution in following analysts’ recommendations.

I seek to identify whether cash flow management can affect the performance and risk of the Greek listed companies.

This study examines the relationship of cash flow management with performance and risk, using a sample of 80 non-financial companies listed in the Athens Exchange. The study covers the period 2018–2022, and panel data analysis is applied. Both financial performance and stock return are taken into consideration, while risk concerns the volatility of the companies’ share prices. The various explanatory variables used include the net cash flow, free cash flow, cash conversion cycle days, cash flow from operating activities, cash flow from investing activities, cash flow from financing activities, inventory days, customer days and supplier days.

The empirical results provide evidence of a positive relationship between financial performance and net cash flow and free cash flow. In addition, operating cash flow is positively related to financial performance. The opposite is the case for investing and financing cash flow. Finally, some evidence of a negative relationship between financial performance and inventory and customer days is provided too. On the other hand, stock return and risk are not related to the cash flow management variables at all.

To the best of my knowledge, this is one of the few studies to examine the relationship of cash flow management with performance and risk, using data from the Greek stock market. The results can form an effective selection tool for investors seeking Greek companies with the highest financial performance potential, which may reward them with higher dividends.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

This paper aims to add further evidence to adoption criteria for “revolutionary” business techniques.

Adoption criteria for business techniques with a high degree of novelty have been developed earlier. The case of exchange-traded funds supports the earlier findings. The methodology applied is explicative.

The analysis supports findings that an effective response to a problem, the availability of a controllable procedure, the means to apply the procedure easily and the hardware jointly explain adopting “revolutionary” business techniques.

The results of case studies, in general, do not permit induction. More research might identify additional adoption criteria or falsify the presently obtained results. Therefore, further research is invited.

Managers seeking or being introduced to new techniques in business administration might use the criteria outlined here for their evaluation.

The author believes this paper corroborates earlier findings on adopting “revolutionary” business techniques that draw on theoretically developed technologies.

The objective of this chapter is to analyse the performance of the UiPath (PATH) company on the New York Stock Exchange, in the context of the war between Russia and Ukraine, and to predict the closing price of the PATH stock using autoregressive integrated moving average with (ARIMAX) and without (ARIMA) exogenous variable methods and autoregressive neural networks (NNAR, NNARX).

UiPath has gained a significant reputation in the IT market and has become a point of interest in recent years. However, the current context is marked by an event of international impact, the war between Russia and Ukraine. In this context, this analysis will consider performance from two perspectives: forecasts of the closing price and forecasts of the closing price with an exogenous variable, namely the war between Russia and Ukraine.

In the analysis that follows, we will address a forecast of the stock closing price using ARIMA, ARIMAX, NNAR and NNARX, as well as analysis of changing points and structural breaks of the series.

The changing points in the mean and variance but also the breaks in the structure justify the course of the closing price. From the information extracted in the analysis, it can be concluded that market sentiment is currently pessimistic due to the downward trend in the price. Both the public and the shareholders are disappointed with the performance of PATH stock and are waiting for the next change point that will change the trend of the series.

This paper investigates the role of economic disagreement in the cross-sectional pricing of individual stocks. Economic disagreement is quantified with ex ante measures of cross-sectional dispersion in economic forecasts from the Survey of Professional Forecasters (SPF), determining the degree of disagreement among professional forecasters over changes in economic fundamentals.

The authors introduce a broad index of economic disagreement based on the innovations in the cross-sectional dispersion of economic forecasts for output, inflation and unemployment so that the index is a shock measure that captures different aspects of disagreement over economic fundamentals and also reflects unexpected news or surprise about the state of the aggregate economy. After building the broad index of economic disagreement, the authors test out-of-sample performance of the index in predicting the cross-sectional variation in future stock returns.

Univariate portfolio analyses indicate that decile portfolios that are long in stocks with the lowest disagreement beta and short in stocks with the highest disagreement beta yield a risk-adjusted annual return of 7.2%. The results remain robust after controlling for well-known pricing effects. The results are consistent with a preference-based explanation that ambiguity-averse investors demand extra compensation to hold stocks with high disagreement risk and the investors are willing to pay high prices for stocks with large hedging benefits. The results also support the mispricing hypothesis that the high disagreement beta provides an indirect way to measure dispersed opinion and overpricing.

Most literature measures disagreement about individual stocks with the standard deviation of earnings forecasts made by financial analysts and examines the cross-sectional relation between this measure and individual stock returns. Unlike prior studies, the authors focus on disagreement about the economy instead of disagreement about earnings growth. The authors' argument is that disagreement about the economy is a major factor that would explain disagreement about stock fundamentals. The authors find that disagreement in economic forecasts does indeed have a significant impact on the cross-sectional pricing of individual stocks.