Joint Optimization Decision of Online Retailers’ Pricing and Live-Streaming Effort in the Postepidemic Era

The isolation requirements of the coronavirus epidemic and the intuitive display advantages of live-streaming have led to an increasing number of retailers shifting to social live-streaming platforms and e-commerce live-streaming platforms to promote and sell their products in real time. However, the provision of live-streaming services will also incur high live-streaming effort costs. In this paper, we develop two decision models for retailers to sell goods through a single online shop and both online shop and live-streaming room; we also present the optimal decisions of pricing and live-streaming efforts. Furthermore, we identify the profitability conditions for retailers to determine when to provide live-streaming services. In addition, we examine the impact of the provision of live-streaming services on the optimal price and live-streaming effort. We obtain three findings. First, there is a unique optimal decision on the price and live-streaming effort under certain conditions. Second, when the effect coefficient of the live-streaming room reaches a certain threshold, there are enough customers who enter the live-streaming room to watch and buy and it is profitable for retailers to provide live-streaming service. Finally, the optimal price and live-streaming effort increase with the increase in average return loss, the effect coefficient of live-streaming effort, and the extra return rate and decrease with the increase in the proportion of customers who choose to buy in the online shop and the price discount coefficient in the live-streaming room.

How to Determine the Cost of Capital for a Commercial Forestry

This paper focuses on designing a methodological workflow to fill a knowledge gap for determining the cost of capital for commercial forestry projects. Upon reviewing the literature, a method to determine the cost of capital for profit-oriented forestry seems to be lacking. Accordingly, we selected and analyzed 42 companies that do businesses worldwide, are present on the stock exchange, and possess or lease forest land. Based on their business activities (growing forest, sawmilling, final production, paper production), these companies are classified into four subgroups. An algorithm has been devised using the concept of risk diversification and the capital asset pricing model for three groups of investors and four forestry subgroups. In doing so, the real risk-free rate (0.43%) is set as the difference between an average return on 10-year US government bonds (2.59% nominal) and the 10-year average US inflation rate (2.16%). The measure of forestry systematic risk (beta coefficient) varies between 0.83 and 1.41, while the equity (stock exchange market) risk premium is set to 6%. Unsystematic risk is determined using a process of mapping which takes into account all risk elements marked as relevant for the forestry sector. This approach provides results that reveal the cost of capital varying between 5.41% and 16.55% based on the current level of an investor's portfolio diversification and the risk characteristics of the forestry subgroup. Finally, the forestry companies meeting the investor's expectations are noted as preferable investment opportunities.

Sukuk Performance Using Comparison of Return and Risk Through Calculation of Market Price and Fair Price

Sukuk investors’ important information used by investors of Sukuk (proof or claim of ownership on assets) is the market price of the Sukuk issued by the IDX and the fair price of the Sukuk issued by the Indonesian Securities Price Appraiser (PHEI). This is a signal or initial information for investors in considering the decision to invest in Sukuk. The measured performance returns as measured by Holding Period Yield (HPY), Yield To Maturity (YTM), and Sharpe Index, while Risk of Sukuk is measured based on its standard deviation. Corporate Sukuk are classified into financial and non-financial sectors and have short, medium, and long maturities. Comparative analysis is conducted using an Independent Sample t-test and ANOVA. The results showed that the average Sukuk return was calculated at a higher market price than the fair price. Sukuk return results in a pattern of movement that tends to be inversely proportional to the market price or fair price of the Sukuk, while the risk of Sukuk based on price issuing institutions had a movement pattern that tends to be in the same direction as the price. Furthermore, corporate Sukuk in the non-financial sector had a higher average return but was more susceptible to risk than the financial sector. Corporate Sukuk with long maturities had a higher average yield and risk exposure than medium and short-term Sukuk. Hypothesis testing showed a significant difference between the market price and the fair price of corporate Sukuk.

Profit Calculation in a late 14th century sole proprietorship, the case of Francesco DATINI

This paper examines the Profit on merchandise accounts (a forerunner of the income statement) in a sole proprietorship in Pisa that officially operated between 1386 and 1392, but took several months to finally end its activities, which it did in 1393. The Profit on merchandise account was where the balance on each goods account was transferred when all the items recorded in it were sold. The principal contribution of this paper is the identification of a unique approach to medieval product costing that ensured indirect expenses on merchandise were recovered from customers when sales took place, while earning an average return of over 10 percent on those costs. It also highlights the problems encountered when working with archival material that has deteriorated over time; and presents a research method that reconstructs missing data using the trail to original entries and contra entries recorded in double entry.

Impact of Budget on Indian Share Market

This paper seeks to study the impact of budget on share market. The method of study was descriptive research. To study the impact is measured in average return by using the event window of Pre-Budget and Post-Budget of 30 Days and the data has been collected for the 18thDecember 2020 to 1stFebruary 2021 &2ndFebruary 2021 to 16thMarch 2021 (excluding Saturday, Sunday and Festival) and the statistical tools used are T-Test Paired, two sample for means on return are calculated by using the formula. The most probably there is not impact on budget on share market because at the same time there is other factors are also present in the market. The implication of this paper is that the investor should not only consider one factor and one event window because there is other factor present with affect the share price at the same time and by using the more than one event window. so, investor come to know a which period they will get a more returns so investor should use either one factor and multiple event window or take multiple factor and one event window. It gives more clear and accurate result. Company Name & Return Pre-Budget Budget-Day Post-Budget XYZ X1 X X2 Here we have taken the 10 companies return of pre-budget and post- budget. On the basis of this we will further analyse that investor should invest in which companies.

Impact of COVID-19 on the Stock Market by Industrial Sector in Chile: An Adverse Overreaction

This paper studies the reaction of share prices in the Chilean securities market at the sectoral level to the arrival of COVID-19 in the country. The following question is answered: Did the Chilean market act efficiently before the arrival of COVID-19? To answer this question, an event study using a 10-day investment return window was applied to the industrial sectors that make up the IPSA (Selective Stock Price Index). To obtain the abnormal returns (AR) and cumulative abnormal returns (CAR) for the event window, three models were used: (1) adjusted average return, (2) adjusted market return, and (3) the market model. The results of the study show an overreaction to market losses, except in the utilities industry, causing greater losses after the event, which shows that information is slow to be incorporated in the previous stage and suggests that the prices of the assets do not reflect all the information available in the market. A significant finding is that the Chilean stock market responded inefficiently in the face of the arrival of the pandemic. This information is useful for investors in the formation of portfolios and/or investment strategies with a view to the long term.

The Month-of-the-Year Effect in the European, American, Australian and Asian Markets

This paper examines the existence of the month-of-the-year effects in four different continents, namely Europe, Asia, America, and Oceania. Nine indexes were analyzed in order to verify differences between monthly returns from January 1990 to December 2013, followed by an examination of the January effect, Halloween effect, and the October effect, testing for statistical significance using an OLS linear regression in order to verify whether those effects offer consistent opportunities for investors. Investors with globally diversified portfolios benefit from the Halloween effect, with a 1.2% average monthly excess return in winter and spring, while the pre-dotcom-bubble period had a better performance than the post-dotcom-bubble period. In the global post-dotcom-bubble period, there is statistical evidence for 1.60% and 1% lower average monthly returns in January (the January effect) and in months other than October (the October effect), respectively, contradicting the literature. The dotcom bubble seems to be responsible for the January effect differing from what might otherwise have been expected in the later period. There is no consistent and clear impact on continental incidence. The Halloween effect is revealed to be a fruitful strategy in the FTSE, DAX, Dow Jones, BOVESPA, and N225 indexes taken one-by-one. The January effect excess average return was only statistically significative for the pre-dotcom-bubble period for globally diversified portfolios. This paper contributes to a wider global and comparable view upon month-of-the-year effect.

Modelling the seismic potential of the Indo-Burman megathrust

The Indo-Burman arc is the boundary between the India and Burma plates, north of the Sumatra–Andaman subduction zone. The existence of active subduction in the Indo-Burman arc is a debatable issue because the Indian plate converges very obliquely beneath the Burma plate. Recent GPS measurements in Bangladesh, Myanmar, and northeast India indicate 13–17 mm/y of plate convergence along a shallow dipping megathrust while most of the strike-slip motion occurs on several steep faults, consistent with patterns of strain partitioning at subduction zones. A short period of instrumentally recorded seismicity and sparse historical records are insufficient to assess the possibility of great earthquakes at the Indo-Burman megathrust. Using the advantage of the Block-and-Fault Dynamics model allowing simultaneous simulation of slow tectonic motions and earthquakes, we test the hypothesis whether the India-Burma detachment is locked and able to produce great earthquakes, or it slips aseismically? We have shown that the model of locked detachment is preferred because it more adequately reproduces observed tectonic velocities. The integral characteristics of synthetic seismicity, the earthquake size distribution, and the rate of seismic activity are consistent with those derived from observations. Our results suggest that the megathrust is locked and can generate great M8+ earthquakes. The estimated average return period of great events exceeds one thousand years. Earthquakes of this size pose a great threat to NE India, Bangladesh and Myanmar, the most densely populated areas of the world.

Four Global Catastrophic Risks – A Personal View

Global catastrophic risks (GCRs) affect a larger than hemispheric area and produce death tolls of many millions and/or economic losses greater than several trillion USD. Here I explore the biophysical, social-economic, demographic and cultural strands of four global catastrophic risks – sea level rise, a VEI 7 eruption, a pandemic, and a geomagnetic storm – one human-exacerbated at the least, one geological, one biological in large part, and one from space. Durations of these biophysical events range from a day or two to more than 100 years and the hazards associated range from none to numerous. Each of the risks has an average return period of no more than a few hundred years and lie within a range where many regulators ordinarily demand efforts in the case of less extreme events at enhancing resilience. Losses produced by GCRs and other natural hazards are usually assessed in terms of human mortality or dollars but many less tangible losses are at least as significant. Despite the varying durations, biophysical characteristics, and the wide array of potential consequences, the aftermath at global (and at more granular scales) can be summarised by one of four potential futures. While this assessment considers the present and the near future (the Anthropocene), much of this appraisal applies also to global catastrophic risks in the Early Holocene.

THE EFFECT OF RAMADAN MONTH ON STOCK RETURN AND VOLATILITY OF A SHARIA-BASED INDEX

This study aims to examine the effect of a religious-related calendar anomaly, namely Ramadan, on stock return and volatility of a Sharia-based index in Indonesia. This study used the GARCH (p,q) method and linear regression to examine the effect of Ramadan on stock returns and volatility, with Ramadan as a dummy variable. This study results show that Ramadan month has a significant positive effect on stock returns, or it can be said that an anomaly occurs during Ramadan month. Meanwhile, volatility during Ramadan month is negative and not significant. This study also exercised a T-test to support the GARCH regression (p,q) and linear regression results. The t-test results show that the average return during Ramadan is higher than in other months. Meanwhile, the average volatility during Ramadan is lower than in other months.