RLG202H5 Chapter 69: Love and Fear of God

64 views3 pages

purplemanatee685

19 Jan 2012

School

Department

Course

Professor

For unlimited access to Textbook Notes, a Class+ subscription is required.

Document Summary

Chapter 69: love and fear of god (pages 443-448) In the jewish tradition, the love of god is of central importance. The mishnah quotes deuteronomy to demonstrate that human beings must love god not only for the good that befalls them, but for evil as well. According to the mishnah, the injunction to love god involves being faithful even if this requires the loss of one"s wealth or one"s life. The sifre states that love and fear are incompatible in human relations, but not with regard to the love of god. The sifre also points out that loving god involves convincing others to love god. In rabbinic sources, loving god is seen as living according to his decrees. Medieval jewish thinkers placed stress on mystical love. States that certain statements are believed as true even though they cannot be proved on.

Related Questions

Financial analysis, key concept week 3

A perplexing issue, particularly for many human resource management and marketing professionals, is the absence of a valuation in the traditional financial statements relating to human capital and other internally generated intangible assets, such as brands. Often these value drivers of an organisation form a critical key success factor. Goodwill does appear in many financial statements and this includes intangible assets acquired by another organisation, which are often subject to large impairments losses. However, this raises questions about the sustainability and volatility relating to goodwill valuations. It is against this background that accountants have decided to be cautious in respect of recognising intangible assets in the financial statements.

To prepare for this Key Concept Exercise:

Read the Required Learning Resources forWeek 3.
Consider the controversy of whether human capital should be included in the financial statements.
Consider how human capital could be defined and quantified in financial statements.

In formulating your Key Concept Exercise, consider the following questions:

How do you define human capital?
What is the importance of human capital?
What are the reasons to measure or not measure human capital?

In an approximately 500-word response, address the following issues/questions:

With the rise of the âknowledge economyâ, the traditional valuation of an enterprise as consisting solely of measurable assets, such as buildings, equipment and inventory, is increasingly being questioned. Human capital, although widely recognised as an important component of an enterpriseâs total value, does not appear on a statement of financial position (balance sheet).

Discuss whether or not you believe human capital should be included in the financial statements. Identify how you are defining human capital. What are some of the difficulties that may be encountered in attempting to quantify and record this (these) asset(s)? If recorded, would such values remain constant or be subject to change?

To complete this Key Concept Exercise:

Be sure to read over your Key Concept Exercise before submitting it to your Instructor. Make sure the spelling and grammar are correct and the language, citing and referencing you use when providing your opinion are appropriate for academic writing.

-need 3 Harverd references

chocolategrasshopper504

Please write a 250 word response to the below discussion. Please provide 2 scholarly sources.

The efficient market hypothesis states that share prices reflect all relevant information, and that it is impossible to beat the market or achieve above-average returns on a sustainable basis. There are many critics of this theory, such as behavioral economists, who believe in inherent market inefficiencies. The Efficient Market Hypothesis (EMH) states that securities are very efficient in reflecting the truth about a stock. In other words, when new information is available about a stock, it is incorporated into the price adjustments of the stock quickly enough to reflect the actual state of the market (Malkiel, 2003). EHM debunks the idea that financial analysis and forecasting are useful tools to shop for stocks. In other words, because securities accurately reflect the status of that stock, it is not possible to use financial analysis to find an undervalued stock or predict trends in the market in order to buy low with the future insight to sell high. There are three levels, or degrees, of the efficient market hypothesis: weak, semi-strong, and strong. The weak form assumes that current stock prices reflect all available information, and that past price performance has no relationship with the future. In other words, this form of the hypothesis says that using technical analysis to achieve exceptional returns is impossible. The semi-strong form says that stock prices have factored in all available public information. Because of this, it's impossible to use fundamental analysis to choose stocks that will beat the market's returns. Finally, the strong form of the efficient market hypothesis says that all information, public as well as private, is incorporated into current stock prices. This form of the efficient market hypothesis essentially assumes a perfect market, and isn't plausible when there are insider trading restrictions (VanBergen, 2011). Yes, I believe that financial statement analysis can provide a significant advantage to an investor. The key is that empirical analysis, specifically statistical models aimed at forecasting future trends based on historical data, are simply another tool to be taken in to account. They are not a single source of the definitive answer. But, through the use of high power computing and mathematically rigorous modeling tools, forecasting is a powerful tool to provide additional insight to decision makers to include the financial industry. In support of my position, (Malkiel 2003) reports the findings of several empirical studies which demonstrate positive statistical correlations in short-run return analysis and the successful prediction of up to 40% of variation in long-term return analysis through time-series statistical models, which are able to take into account seasonal fluctuations (Malkiel 2003). One experimental study demonstrated with statistical significance that the Ohlson model provides predictive ability for future stock price movements (Lee, Chen and Tsai, 2014).