...Beta-blockers xxxx Collin College HPRS 1310-WW1 April 15, 2012 The first beta-blocker drug approved by the FDA in 1967 was developed by Sir James Black, an accomplishment for which he was awarded the Nobel Prize in Medicine in 1988 (Stapleton, 1997). Sir Black took a different approach to the treatment of angina pectoris—instead of using drugs to increase the amount of oxygen delivered to the heart, Black sought to find a drug that could reduce the amount of oxygen required by the heart. The drugs in this classification are subdivided into two categories: non-selective and selective (cardioselective). Major drugs in the non-selective beta-blocker category include carteolol, nadolol, penbutolol, pindolol, propranolol, sotalol, and timolol. Major drugs in the cardioselective category include acebutolol, atenolol, betaxolol, esmolol, metroprolol, and nebivolol. Some others, including carvedilol and labetalol also have alpha-adrenergic blocking effects, but are outside the scope of this paper. (Vallerand, 2013; Turley, 2010) Beta-blockers are prescribed for the treatment of hypertension, angina pectoris, cardiac arrhythmias, hypertrophic subaortic stenosis, prevention of myocardial infarction, congestive heart failure, migraine headaches, and glaucoma. (Vallerand, 2013; Hodgson & Kizior, 2013) Beta-blockers work to compete with sympathetic neurotransmitters1 for beta1 and beta2 adrenergic receptor sites. Beta1 receptors are found in cardiac muscle, and beta2 receptors...
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...Alzheimer’s disease is a wholesale loss of synapses, contact points via which nerve cells relay signals to one another and a parallel deterioration in brain function, notably in the ability to remember. Amyloid beta (Aβ) denotes peptides of 36–43 amino acids that are crucially involved in Alzheimer's disease as the main component of the amyloid plaques found in the brains of Alzheimer patients. The peptides result from the amyloid precursor protein (APP), which is being cut by certain enzymes to yield Aβ. Study has shown that Beta amyloid begins life as a solitary molecule but tends to bunch up , initially into small clusters that are still soluble and can travel freely in the brain, and finally into the plaques that are hallmarks of Alzheimer’s. The study showed for the first time that in this clustered form, beta-amyloid can bind strongly to a receptor on nerve cells, setting in motion an intercellular process that erodes their synapses with other nerve cells. Further looking into this protein and the information regarding it in various databases, the following was sequence was found out for the Beta amyloid A4 protein in Homo sapien in SWISSPROT. >sp|P05067|A4_HUMAN Amyloid beta A4 protein OS=Homo sapiens GN=APP PE=1 SV=3 MLPGLALLLLAAWTARALEVPTDGNAGLLAEPQIAMFCGRLNMHMNVQNGKWDSDPSGTK TCIDTKEGILQYCQEVYPELQITNVVEANQPVTIQNWCKRGRKQCKTHPHFVIPYRCLVG EFVSDALLVPDKCKFLHQERMDVCETHLHWHTVAKETCSEKSTNLHDYGMLLPCGIDKFR GVEFVCCPLAEESDNVDSADAEEDDSDVWWGGADTDYADGSEDKVVEVAEEEEVAEVEEE E...
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...The above shows the results for the regression that was performed on the individual stocks to be considered – California REIT and Brown Group – with Vanguard 500 Index Trust Fund. From Figure _, the slope of the curve for California REIT vs Vanguard Index was almost a horizontal one and the Beta was 0.147. However from Figure _, the Beta was 1.16 for Brown Group to Vanguard Index which was a much steeper slope as compared to California REIT’s. As Beta measures the volatility relative to the market, which is represented by Vanguard Index 500 Trust, California REIT is much less volatile than the market. However for Brown Group, it is much more volatile than the market as its Beta is more than 1. These results show a different finding from the standard deviations of the individual stocks. From the viewpoint of using standard deviation, California REIT stock was found to be more risky when compared to the Brown Group stock. However this proved to be an unreliable source as the Beta values found gave a different conclusion. If Ms. Wolfe were to base her stock selection solely using the standard deviation method, she might be misled into thinking that the Brown Group stock was a better choice as it was less risky than the California REIT stock. However, by using the regression method, it can be seen that Brown Group stock was much more volatile than the market Index. Depending on Ms. Wolfe’s investment strategy, she might not want to add Brown Group stock to her portfolio as...
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...1) Based on the first three paragraphs of the case, explain Beta Management Company's (BMC) investment strategy. Is it compatible with market efficiency theories? BMC’s Investment Strategy To enhance returns and reduce risks is a general objective of risk-averse investors and shouldn’t be considered an investment strategy proper. BMC follows a market timing investment strategy based on two portfolios: the Vanguard Index and money market (i.e., short-term) instruments. When BMC expects the market to rise, it transfers its assets from the money market to the Index (up to a maximum of 99% of total assets), seeking to obtain capital gains; when BMC expects the market to fall, it transfers back the assets from the Index to the money market instruments (down to a minimum of 50%), so as to avoid capital losses. By setting a floor of 50% on the investment on the Index, BMC endeavours to maintain at all times a return spread so as to “enhance returns”, while seeking to partly capitalize on unpredicted rises (at the cost of losses if the market behaves as predicted). By setting a very high ceiling for the investment in the Index (99%), BMC is willing to take on extra risk to try to fully capitalize on predicted rises. The investment strategy has thus some aggressive elements in it. The objective of “risk reduction” might better accomplished by setting both a lower ceiling and, particularly, a lower floor. Advantages of the Vanguard Index: - Low transaction costs (important in a market...
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...would indicate an underperformance of 1%. The Jensen index, or alpha, bears some relation to the capital asset pricing model, or CAPM. The CAPM equation is used to identify the required return of an investment; it is often used to evaluate realized performance for a diversified portfolio. Because it's assumed that the portfolio being evaluated is a diversified portfolio (meaning that the unsystematic risk has been eliminated), and because a diversified portfolio's main source of risk is market risk (or systematic risk), beta is an appropriate measure of that risk. Alpha is used to determine by how much the realized return of the portfolio varies from the required return, as determined by CAPM. The formula for alpha is expressed as follows: |α = Rp – [Rf + (Rm – Rf) β] | Where: Rp = Realized return of portfolio Rm = Market return Rf = risk-free rate The Jensen index measures risk premiums in terms of beta (β); therefore, it is assumed that the portfolio being evaluated is well diversified. The Jensen index requires using a different risk-free rate for each time interval measured during the specified period. For instance, if you are measuring the fund managers over a five-year period using annual intervals, you must examine the fund's annual returns minus the risk-free assets' returns (i.e. U.S. Treasury bill or...
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...were obtained from the Karachi Stock Exchange Data Portal, which is the primary source of all stock data in the country. Monthly stock returns for each stock are calculated using this data. Monthly market returns were calculated from the broadly-based, capitalization weighted KSE 100 index as the KSE 100 Index was taken as the market portfolio. The three months treasury-bill rate was used as risk-free rate. The data on six-month treasury-bill rates was obtained from the Market Treasury Bills Auction Results from the State Bank of Pakistan data Portal. Methodology- Betas are estimated using the single period, discrete time Market Model (MM) developed by Markowitz (1959) Shape (1963).The MM is expressed as, Rit = αit + βiRmt + εit, -----------------(1) Where Rit is the expected return on an asset “,i”, Rmt is expected return on market portfolio, proxied by the stock market index and βi is the “beta” or the measure of risk or market sensitivity parameter. Rit is measured as the continuously compounded return on the i'th security during time t, while Rmt is the corresponding return on the market. In equation 1, α and β are unknown firm specific parameters assumed to be constant over time,...
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...Numark Beta Driver Release Notes Table of Contents Beta Driver Warning Driver Features Sending Beta Driver Feedback *Important Beta Driver Warning* By installing these Beta drivers for your Numark product, you agree to the following terms and conditions: 1. You acknowledge that this driver is a Beta, non-commercial driver version, and not an official release of the software. 2. You understand that this driver is a pre-release version only, and is still undergoing testing. 3. We advise that this Beta version never be used for live or critical scenarios as functionality cannot be guaranteed. 4. We have endeavored to provide that this Beta version of the software will install and uninstall properly, as well as provide a level of functionality, but we make no guarantee that this software will function or perform as expected. This Beta driver is provided as-is, and the installer accepts all risks. 5. The Beta version will not be supported in any way. 6. There are no warranties under this agreement. 7. In no event shall Numark be liable for any loss of profits, loss of use, or damages pursuant to this agreement. 8. We suggest that anyone experiencing problems with a Beta version driver reinstall a properly certified and supported official driver release. ------------------------------------------------------------------------------------------------------------Driver Features What you should know about Numark’s 3.0 Driver for Mac OS X 10.9 Mavericks Version: 3.0 OS X Compatibility:...
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...would I hold a zero beta stock in my portfolio? Some Background In class we wondered why you would hold a zero beta stock, that is a stock that has the same expected return as the risk free rate yet has its return is uncertain, but the risk free return is certain. The only way you would in fact hold such a stock is if it gave you something the risk free return did not give you. I said this was because this stock provided diversification, and this example illustrates this point. Before I work the example, there is something you should think about. If the CAPM is true, the only stocks that are held are those in the market portfolio, so by holding a zero beta stock I am also saying it is part of the market portfolio. The Example Assume the CAPM holds with a riskless asset and the market porfolio contains a zero beta stock. Since everybody holds the market, this means that everybody willing chooses to hold a zero beta stock. What I want to know is why people just don’t drop this stock out of their portfolios and replace it with the risk free security. What would happen to the expected return of my portfolio if I took the 5% of my wealth out of the zero beta stock and put it in the risk free asset instead? Nothing, since the from the CAPM equation we know that the expected return of the zero beta stock must be the same as the expected return of the riskless asset. What would happen to the standard deviation of my portfolio if I replace the zero beta asset with the riskless...
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...WRITTEN ANALYSIS OF THE CASE BETA COMPANY SYNOPSIS Beta Company produces two Product A and B and standard costs of each product were predetermined by management. During November actual production for Product A was 4,200 units while Product B was 3,600 units. For material X, 39,000 pounds were purchased at $14.40 and for material Y, 11,000 pounds were purchased at $9.70. Variance analysis for actual cost versus standard cost should be prepared for the said month to be able to measure results of operations, which may be the basis in making a decision on whether to maintain the present performance if the result is satisfactory, or take the necessary corrective action if material differences are reported. OBJECTIVES To be able to compute variances of actual costs against standard cost of November Production of products A and B of Beta Company and to be able to analyze results and assess performance of departments specifically that of Purchasing and Production. PROBLEM 1. Calculate the material price and usage variances for the month. 2. Calculate the labor rate and efficiency variances for the month. 3. How would your answers to Question 1 and 2 change if you had been told that November’s planned production activity was 4,000 units of A and 4,000 units of B? 4. How would your answers to Question 1 and 2 change if you had been told that November’s sales were 4,000 units of A and 3,500 units of B? CONSIDERATIONS/FACTS: Pre-determined standard cost Material...
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...Discuss beta and its importance. Also, what type of investor would invest in a high beta stock and a low beta stock? Also, in your textbook, review the Real World case, focusing on "Beta, Beta, Who's Got the Beta?" on page 348. Is beta a useful tool? Why were the beta estimates discussed in the reading different? Beta is very important as it would be critical to make decisions on which stocks should be traded in certain market conditions. A trader would want to be in a high beta stock in robust condition and looking at low beta stocks in a low volume or bear type market. Advantages of beta would include: ease of calculation, simplicity of the application, finding the correct trading utensils. Disadvantages of beta would include: based on historical, data,difficult to gauge future returns, would not work with newly issued stocks. It would make sense for a short term trader to invest in high beta stocks as there would likely be high risk and high returns. Conversely it would make sense for a long term investor to invest in low beta stocks as it would allow for low risk and steady returns. In my situation with the exception of a few situations I would focus on low beta stocks. The beta values discussed in reading are different largely do to the the sample length used by the firms doing the calculations. “There are a few lessons to be learned from all of this. First not all betas are created equal. Some are computed using weekly returns and some using daily returns(Ross,2011)...
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...Thoughts on Smart Beta Chao Liu May 22 2014 The two articles in FT introduce the recent popular investment strategy: smart beta. Smart beta concept is growing popularity across the world because it has allegedly been providing investors risk-adjust excess return. Some consider smart beta approach as a strategy lies between traditional active management in which the fund managers actively pick stocks for their portfolios, and the passive management in which the investor simply replicate the market index. One way to create smart beta portfolios is to substitute the market cap weighting method with an alternative weighting, and the other more popular way is to track certain stocks or certain parts of the market using certain risk factors. These certain risk factors have been recognized to provide risk premium in academia. For example, we have learned in this semester that there are many return anomalies existed in past several decades such as small cap stock, value stock and momentum effect. Those factors are not new to investors, so investors can decide whether take these factors into consideration when forming their investment portfolios. The central questions to ask are: What sources of returns are accounted for smart beta strategies? Can smart beta strategies offer consistent higher risk-adjusted return over time? From the perspective of efficient market theory, any excess return over a market index is due to higher risk bearing. As we can learn from the two FT articles...
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...Calculating and Interpreting Beta Introduction: In 1990, William Sharpe won a Nobel Prize in Economics for his work in developing the Capital Asset Pricing Model (CAPM). Traditionally the CAPM has been the basis for calculating the required return to the shareholder. This figure in turn has been used to calculate the economic value of the stock and the Weighted Average Cost of Capital (WACC) for capital budgeting. In recent years, the CAPM has been attacked as an incomplete model for explaining market pricing behavior, but academics and practitioners cannot agree on a good replacement. And so the CAPM remains an important model in practical investment and financial management decision making. Calculating Beta: The most important component in calculating the required return to shareholder (from the CAPM) is the company’s beta. The CAPM can be succinctly stated as: k s k RF k M k RF s k RF Market Risk Premium s [1] The original model was conceived of theoretically, and was expected to be forward looking. Careful reading of Sharpe’s original work show that the market assesses systematic risk looking at expected future covariance of the company’s returns with that of the overall market. It is assumed that these covariances are unbiased and efficient estimates of the observed relationships ex post facto. Traditionally the CAPM relationship is estimated using simple regression on historical outcomes, where ks is the y variable, and kM-kRF (or...
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...PAWEL BILINSKI AND DANIELLE LYSSIMACHOU b1 The Risk Interpretation of the CAPM’s Beta: Evidence from a New Research Method This study tests the validity of using the CAPM beta as a risk control in cross-sectional accounting and finance research. We recognize that high risk stocks should experience either very good or very bad returns more frequently compared to low risk stocks, i.e. high risk stocks should cluster in the tails of the cross-sectional return distribution. Building on this intuition, we test the risk interpretation of the CAPM’s beta by examining if high beta stocks are more likely than low beta stocks to experience either very high or very low returns. Our empirical results indicate that beta is a strong predictor of large positive and large negative returns, which confirms that beta is a valid empirical risk measure and that researchers should use beta as a risk control in empirical tests. Further, we show that because the relation between beta and returns is U-shaped, i.e. high betas predict both very high and very low returns, linear cross-sectional regression models, e.g. Fama-MacBeth regressions, will fail on average to reject the null hypothesis that beta does not capture risk. This result explains why previous studies find no significant cross-sectional relation between beta and returns. Key words: Market beta; New research method; Empirical accounting and finance research. PAWEL BILINSKI (pawel.bilinski.1@city.ac.uk) and DANIELLE LYSSIMACHOU...
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...Beta (finance) From Wikipedia, the free encyclopedia Jump to: navigation, search In finance, the Beta (β) of a stock or portfolio is a number describing the volatility of an asset in relation to the volatility of the benchmark that said asset is being compared to. This benchmark is generally the overall financial market and is often estimated via the use of representative indices, such as the S&P 500.[1] An asset has a Beta of zero if its returns change independently of changes in the market's returns. A positive beta means that the asset's returns generally follow the market's returns, in the sense that they both tend to be above their respective averages together, or both tend to be below their respective averages together. A negative beta means that the asset's returns generally move opposite the market's returns: one will tend to be above its average when the other is below its average.[2] It measures the part of the asset's statistical variance that cannot be removed by the diversification provided by the portfolio of many risky assets, because of the correlation of its returns with the returns of the other assets that are in the portfolio. Beta can be estimated for individual companies using regression analysis against a stock market index. Contents[hide] * 1 Definition * 1.1 Security market line * 2 Choice of benchmark * 3 Investing * 4 Academic theory * 5 Multiple beta model * 6 Estimation of beta * 7 Extreme and interesting cases * 8 Criticism...
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...of Beta What is beta and how can we use it to analyze a stock. Before I analyze my quantitative data from my excel I’m going to discuss Beta in general. For my discussion of beta I will be using 3 examples of stocks that each have a different beta. Apple (AAPL) with a beta of .93, fluctuates close to the overall market. Walmart (WMT) has a beta of .3 which will be the lowest of the group. The last stock I will be analyzing for my discussion of beta is SanDisk Corp. (SNDK) with 2.21. What is beta, what does it tell you about the stock? The number supposedly represents risk. There are some drawbacks with the number that I will discuss later on. Beta means how volatile are these stocks and how sensitive they are compared to the market. Do they move with the market, do they move less than the market low volatility ( B<1), or do they move more than the market high volatility (B>1). When talking about the market I will be using the S&P 500 for the United States. The technique that I have used in quantifying Beta is regression analysis. Even though this paper will be discussing beta in application of stocks it can also be applied to portfolios. The market just a convention has a beta of one. When a stock for example apple rises and falls its stock fluctuations are close to the amount of fluctuations of the market. Low beta stocks such as Walmart will decline by .30 of a percent if the market declines by one percent. On the other hand if we had Sandisk with the beta being...
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