Study On Robecos And Its Investment Strategy Finance Essay - Free Essay Example

Sample details Pages: 9 Words: 2823 Downloads: 6 Date added: 2017/06/26 Category Finance Essay Type Research paper Did you like this example? [Problem definition, relevance and motivation] Robecos investment strategy relies on identifying and exploiting market inefficiencies, which are a result of the predictable patterns in investors behavior. We believe we can outperform the market by locating these inefficiencies. Central in Robecos investment strategy is Robecos proprietary stock-selection model, which is used for decades and was extensively back tested in historical simulations. Don’t waste time! Our writers will create an original "Study On Robecos And Its Investment Strategy Finance Essay" essay for you Create order The outcome of this model is a cross-sectional ranking of stocks based on their expected future returns. In order to generate alpha, Robeco overweights certain high-ranked stocks in comparison to the benchmark weight and underweights certain low-ranked stocks. This ranking process is based on four factors; price momentum, earning revisions, management and value. Management + Value + Earning Revisions + Price Momentum = Stock ranking All these themes consist of multiple variables (e.g. earnings to price ratio (E/P) or book to price ratio (B/P) are variables in Value). These variables determine how attractive the stocks are and they may contain valuable information in predicting stock returns. We equally weight each theme to combine these different themes. [Problem definition] Robecos stock-ranking process focuses on the average effect of earning estimates, regardless of the quality and life of those estimates. We aim to add extra predictive power to the earning estimates b y investigating different aspects: different databases different forms: revisions, predictive surprise, growth level, recommendations different levels: consensus, individual analyst-level, extreme estimates different horizons and life of estimates We try to find out which database is better, which form performs better etc. Well look in more detail to the earning estimates with the goal to add extra predictive power to the currently used earning estimates. The overall question, which we try to answer in this thesis, is: How do we detect whose better and which estimates have better predictive quality. Well examine the predictive power of several candidates (based on the different angles) and well extensively back test these candidates; first we test the single variables and later well test the added value of the new candidates to the existing selection model. [Relevance] Robeco continuously attempt to improve the core stock-selection model, and therefore it is relevant to examine the predictive power of earnings estimates from different angles. We start defining candidates based on estimates at individual analyst-level instead of the consensus earnings estimates. More and more studies focused at the individual analyst level and illustrated the importance of analyst characteristics on the stock-prices. Some candidates based on estimates at individual analyst-level are candidates that focus on past accuracy of earning estimates, the age of the estimates, leader analysts, analyst-true call, and tenure. We also define other candidates that may add extra predictive power to the earning estimates. These candidates are based on the relative earning growth and changes in buy/sell recommendations. Furthermore, we consider different horizons and incorporate data from other financial measures in addition to earnings. [Motivation] A key distinguishing feature of our study from previous literature is that well look at the predictive power of earning estimates from different angles, while most of the previous studies give only an explanation of the abnormal returns of the earning forecasts. Data Well examine different databases with detailed information about earnings estimates: I/B/E/S Detailed database: this database is a good foundation of our research as it offers consensus level and detailed analyst-by analyst earning forecasts. I/B/E/S began collecting earning estimates for U.S. companies around 1976, while the International edition starts in 1987. Factset Estimates database: they also provide consensus and detailed-level earning estimates. They claim their estimates are of higher quality and therefore well examine this database. BETTER DATADESCRIPTION, UNIVERSE, THRESHOLD MARKET CAPITALISATION, COUNTRY, SECTOR ETC Methodology Well define some candidates to improve our current stock-selection model. First, well examine the predictive power of past-accuracy. We try to predict the direction of future estimate revisions. First well define some candidates based on specific analyst characteristics . Currently, Robeco only focuses on the average effect of earning estimates, regardless of the quality of those analysts. Therefore well examine the predictive power of some candidates based on analyst characteristics. Finally, we will examine a relative earnings growth candidate that doesnt rely on analyst characteristics but which has shown predictive power in the literature and which is easy to create given the I/B/E/S dataset. Well construct a top-bottom strategy of each candidate and we will back-test the single variables and the added value of the new candidates to the existing stock-selection model. Candidate list We start with describing a candidate list of potential factors that may help i n predicting stock returns. Because we first define these candidates we reduce data mining. Candidates based on analyst characteristics There are several candidates which well examine based on analyst characteristics. Candidate 1: Past Accuracy We start with simply look at the predictive power of past accuracy. For each analyst on each stock we measure the analysts historical accuracy, using the same measure as in Brown(2001). Brown(2001) shows that for distinguishing more accurate from less accurate earnings forecasts a simple model of past accuracy performs as well as a more complex model based on 5 analyst characteristics. Past accuracy (PAt) is defined as the individual analysts forecast error that year (FEt) minus the mean of the forecast errors of all analysts following the company that year () scaled by the mean of the forecast errors of all analysts following the company that year (): The forecast error is defined as the absolute value of the difference bet ween the actual annual earnings (A0t) and the last forecast made by the analyst for that year (LA1t). FE = |A0t|- |LA1t| We have to examine the database and the distribution of the estimates. Then we can decide which weighting scheme to use. We put more weight on analysts with more accurate estimates in the past. We can also order the estimates and take the median of the ordered set of past accuracy. Candidate 2: Forecast Age Recent estimates are more important than stale estimates. We use the same variable as used in Brown(2001). The forecast age (AGEt) is defined as the number of calendar days between the analysts last annual forecast and the fiscal year-end minus the average forecast age of all analysts following the company that year. We should give more weight to the analysts with the most recent estimate. Again we first have to examine the database and the distribution of the estimates, before we can decide which weighting scheme to use. Candidate 3: Lead Ana lyst The timeliness of analysts forecasts can be used as a proxy for unobservable skills in collecting information as leader analyst should be able to release earning forecasts before competing analysts. Cooper et al (2001) uses a Leader-Follower-Ratio (LFR). This ratio measures to which extent the analyst is a leader. Well also use this ratio to rank the stocks which are followed by these leader analysts. The Leader-Follower-Ratio is the cumulative time that a forecast revision leads to the cumulative time that a forecast revision follows: With and Where ti,1 and ti,0 is the length of time that a certain forecast revision leads or follows a given forecast revision respectively. If the LFR is higher than 1, the analyst is a leader. Cooper et al (2001) shows that forecast revisions by lead analysts are positively correlated with recent changes in stock prices. This may indicate that lead analysts have predictive power and therefore we will examine this candidate. We would expect to observe excess stock returns as investors respond to the release of revised forecasts by follower analysts. Well only focus on these lead analysts. Again, we first examine the database. Now we define variables that are based on conflict of interest. If we know the incentives for analysts to make biased earning forecasts, we can generate an abnormal return by identifying these biases. Candidate 4: Analyst true call In the research report of J.P. Morgan (2009) they focus not only on analyst forecasts that strongly deviating from the consensus but from what they call Analyst true Calls. The earnings forecasts of these analysts are already away from consensus but they move them even further away from the consensus. More weight should be given to these analyst forecasts, as these analysts are very confidential about their forecasts because they even move further away from the consensus. We use the same method as described in the research report of J.P. Morgan (2009 ): First we should find the highest en lowest earnings forecasts for the next fiscal year stock by stock. We focus on the analysts who are already away from consensus. Starting with these analysts, we filter these analysts to include only the stocks where the highest earnings forecast have been further increased. Or the lowest earnings forecasts have been further decreased (over the previous month). Thus, we focus on the analysts who make a forecast revision even further away from consensus. In the third step we create two universes: positive Analyst true calls (the highest earnings forecast is further increased) negative Analyst true calls (the lowest earnings forecast is further decreased) Rank the stocks in the two universes. We buy the stocks in the top of the positive universe and sell the stocks in the bottom of the negative universe. Disadvantage of this test: This methodology is a very strong approach. An analyst will not move further up or down every mo nth. We should test this discreteness. In the research report of J.P. Morgan (2009) they do not repeat this procedure every month. We can make this strategy more robust : Find x% of the earning forecasts in the bottom quintile and x% in the highest quintile. After a revision, we select the estimates which moved further away from consensus. Select from the estimates found in step i, x% of these estimates which are again in the bottom quintile or highest quintile. In the third step we create two universes: positive Analyst true calls negative Analyst true calls Rank the stocks in the two universes. We buy the stocks in the top of the positive universe and sell the stocks in the bottom of the negative universe. The second approach is more suitable for ranking, because not all analysts revise their earnings forecasts each month. Candidate 5: Tenure Brown(2009) shows that a strategy by buying a portfolio of firms that are followed by low-tenure analysts and selling a value-weighted portfolio of firms that are followed by high-tenure analysts earn abnormal returns. We use almost the same definition for tenure as in Brown(2009), but well use months instead of years. TENi,t = the number of months since the analyst first makes an estimate of year-ahead earnings in the I/B/E/S database. Well follow the approach as defined in Brown(2009). We rank all stocks of the firm in the analyst forecast sample based on the median value of analyst tenure. Consider a set of k ordered tenure variables of a set of analysts at a certain point in time t for stock i: TEN1,i,tTEN2,I,t.. TENk,i,t. where The median of this ordered dataset is equal to: MEDIANi,t [TENk,i,t] = ( + )/2 Where is the largest integer not greater than x, and is the smallest integer greater than x. Stocks that are followed by high-tenure analysts are in the top portfolio and stocks which are followed by low-tenure analyst are in the bottom portfolio. We can use this can didate in addition to our current earnings revisions strategy. Candidate 6: Star analyst Fang and Yasuda(2008) show that recommendation changes of star analyst are profitable. We will examine the predictive power of earning forecasts of these star analysts. We use this candidate in addition to the current earnings revisions strategy Fang and Yasuda(2008) measures analysts reputation as the All-American title that is granted by the Institutional Investor magazine. This magazine published rankings throughout the year and has been the greatest source of survey-based rankings which identifies the top analysts. They cover equity markets in Asia, Europe, Japan, Latin America, Russia and the U.S.  [1]  An analyst remains his star status for 12 months after the publication in the Institutional Investor magazine. AA elections occur in October of every year. We should match the names of the AA analysts from the Institutional Investor listings with I/B/E/S dataset. I NEED ADDITIONAL INFORMATION ABOUT THE AVAILABILITY OF THESE RANKINGS. DO I NEED TO BE A MEMBER BEFORE I HAVE ACCES TO THIS MAGAZINE? Other candidates Candidate 7: Relative earnings growth According to Da and Warachika (2009), stocks with optimistic and pessimistic long-term analyst forecasts relative to the short-term implied growth have negative and positive risk-adjusted returns, respectively. We need the earnings in the previous year (A0t), earnings forecasts for the current fiscal year (A1t) and long-term growth forecasts (LTGt) from the I/B/E/S Detailed Database. We use the same definition of implied short-term growth as in Da and Warachika (2009). The implied short-term growth (ISTGt) is defined as: The difference LTGt ISTGt is appropriate to measure the relative optimism or relative pessimism of analysts at portfolio level. Da and Warachika (2009) conduct the analysis on an earnings-per-share basis, which is also available in the I/B/E/S Detailed Database. In the paper they explain that for some firms the earnings forecasts for the current fiscal year is near zero. Therefore, they construc t a Slope variable as the difference between the rankings of LTG and ISTG. Well use the same approach. We can rank the stocks according to the Slope variable into deciles from 1 to 10 in descending order. We should buy stocks in the top and sell stocks in the bottom. Candidate 8: Changes in buy/sell recommendations Jegadeesh and Titman(2004) and Jha et al(2003) show that the change in analyst buy/sell recommendations provide a meaningful signal as they confirm the earning revisions. In Jegadeesh and Titman (2004) they examine the relation between analyst recommendations and other concurrently available public information. They find that quarterly change in consensus recommendations is a robust return predictor that appears to contain information orthogonal on this range of other predictive variables. Therefore, well use the changes in buy/sell recommendations as signals for further stock performance. Combining previous candidates to create an accurate estimate and investiga te multiple horizons, incorporate data from other financial measures in addition to earnings and use the change in buy/sell recommendation, It is reported in the research paper of Starmine(2007) that a small group of analysts usually lead the peer group and release forecast of higher quality. By following the earnings revisions of these analysts we can improve the outperformance based on consensus. They try to measure the analysts historical accuracy to better predict the direction of future estimates of earning revisions. This model put more weight on the most accurate and most recent estimates. They investigate multiple horizons, incorporate data from other financial measures in addition to earnings and they use the changes in buy/sell recommendations. We can use the basis idea of this model. How can we measure earnings accuracy? We can use past accuracy, the timeliness of the estimate (tenure) and how extreme the estimate is (Analyst-true-call). We first have to test the predictive power of the single candidates and test the accuracy of these variables. OTHER IDEAS? If we have a measure for the accuracy of analyst forecasts, we can calculate an weighted-average estimate which is better than the consensus estimate. Because we identify the individual analysts that are more likely to be accurate in the future, we can get an estimate better than the consensus. We should also look at the age of the earnings estimate. Starmine(2007) exclude analysts with stale forecasts from their analysis. We first have to examine the dataset, we can do the same, or we use a certain weighting scheme (for example exponential). If we have the estimate which is better than the consensus estimate, we can add other aspects to this estimate, as is done in Starmine(2007). We combine the Predicted Surprises (percent difference between this weighted average estimate and the consensus) and consensus changes on EPS, EBITA and Revenue for the current fiscal quarter, curren t fiscal year and next fiscal year. Then we can combine the revisions component score with the recommendation revisions component. Here you can see a screenshot of a video on the StarMine website: Back test We will first test the predictive power of a single candidate, by using the back-test. The basic idea of the back test is to sort the universes into deciles based on the candidate characteristics. Analyze results We select the most promising factors for inclusion in the current stock-selection model. Time Schedule Task Mar. Apr. May Jun. Jul. Aug. Literature review, description methodology X X Download data data check X X Test predictive power of single variables x X Test the added value of the new candidates to the existing selection model X X Further improvements X X Writing thesis X X X

Attention Deficit Hyperactive Disorder ( Adhd ) - 754 Words

Goodman and Scott (1997) suggest that ‘childhood hyperactivity is a high level of behaviour that is often characterised by lack of control rather than the volume of behaviour.’ However, Booton, Cooper, Easton Harper (2012) argue that children with hyperactivity are unable to sit still, have poor concentration and impulsive behaviour. I agree with Booton, Cooper, Easton Harper (2012) because these are the challenging characteristics that appear in children who are hyperactive. In contrast to Goodman and Scott (1997), I believe hyperactivity does not necessarily occur due to lack of control. There may be high volumes of hyperactivity that can be controlled through behaviour management strategies (BMS) such as positive reinforcement,†¦show more content†¦Their definition includes the symptoms of hyperactivity and ADHD but the distinction between the two has not been identified. The distinction between ADHD and hyperactivity is that, ADHD is a neurological develop mental disorder which is required to be diagnosed Lauth et al (2006). Whereas hyperactivity is the regular pattern of inattention, impulsiveness and over activity McLaughlin (2004) by which diagnosis is not obligatory. Roger (2003) argues that teachers should develop a personal plan for hyperactive behaviour (HB) which focuses on academic survival skills and is centred in a supportive one-to-one programme emphasising positive role play. I believe this (BMS) may not work on all students, for example, children in Early Years Foundation Stage (EYFS) (2008). In EYFS (2008) teaching is often done through play, where the child learns through games and physical activity. At this stage of their education, they are learning through positive role play. In contrast to Roger (2003), children in EYFS do not require academic survival skills as they have not been academically prepared for the future. Moreover, Leaman (2009) suggests that teachers should encourage children to take responsibility of their actions by setting up a reward system to motivate children. Bowen, Jensen Clark (2004) argue that contingent verbal praise should be associated with the delivery of any tangible or token reinforcer, then as

Pressure Injury Identification And Prevention In Emergency Department

Question: Discuss about the Pressure Injury Identification And Prevention In Emergency Department. Answer: Project topic Pressure injury identification and prevention: Pressure injury are commonly called as pressure sores. Pressure sores are the regions on the skin that get damaged due to constant friction or pressure in emergency departments. Pressure sores develop in persons who lack mobility like the older patients, patients who are confined to chair, also the bed ridden patients in the emergency departments. The other names of the pressure sores are pressure ulcers, bed sores and decubitus ulcers (Cushing and Phillips 2013). The regions of the skin that has bones underneath, like the elbows, heels, back of head, tailbone are the major areas of the patient that get affected in the emergency department. These regions do not receive the adequate amount of blood flow, that is why such regions develop the sores or injuries. There are several ways to identify pressure injuries in an emergency department. The skin that gets affected by pressure shows discoloration usually in blue, purple color, skin loss from the affected area develop a patch of dead cells. Prevention of the pressure injury in an emergency department is the prime motive of my work. Hence, devising a plan includes the identification of the pressure injuries and its effective prevention. The plan in involves everyday skin care, change in diet plans, providing support devices, and changing lying or sitting posture in an emergency department (Ausili et al. 2013). Project idea justification (Mini) Pressure injuries are common in old patients who are either bed ridden or confined to wheel chair in the emergency departments. Such patients or the old people that are affected by the pressure injuries are incapable of taking their own care. That is why knowledge of identifying and prevention of the pressure injuries need to be developed among the nurses so that pressure injuries in the emergency departments can be identified well before they develop (Bogie, Powell and Ho 2012). Pressure injury has certain complication that if left untreated can lead several worsening medical conditions in the emergency departments. Implications like cancer due to squamous cell carcinoma, joint and bone infections, pus collection in the dead cells, inflammation of the tissues, and even sepsis can develop within the patients that are affected by the pressure injuries in emergency departments. According to Bulfone et al. (2012), the patients in the emergency department often experience pressure injuri es because patients lie on the for longer periods without changing sides. Hence, there are chances where they might develop pressure injuries on the elbow and back. Question that may arise The major risk factor that can arise in this project are the malnutrition, obesity, blood circulation disorders, smoking, paralysis and immobilization. Hence, failure to deal with these situation or occurrences in the emergency department can lead to increased incidence of pressure injuries and can be fatal for the patients. References Ausili, E., Paolucci, V., Triarico, S., Maestrini, C., Murolo, D., Focarelli, B. and Rendeli, C.L.A.U.D.I.A., 2013. Treatment of pressure sores in spina bifida patients with calcium alginate and foam dressings.Eur Rev Med Pharmacol Sci,17(12), pp.1642-7. Bogie, K., Powell, H.L. and Ho, C.H., 2012. New concepts in the prevention of pressure sores.Handb Clin Neurol,109, pp.235-246. Bulfone, G., Marzoli, I., Quattrin, R., Fabbro, C. and Palese, A., 2012. A longitudinal study of the incidence of pressure sores and the associated risks and strategies adopted in Italian operating theatres.Journal of perioperative practice,22(2), pp.50-56. Cushing, C.A. and Phillips, L.G., 2013. Evidence-based medicine: pressure sores.Plastic and reconstructive surgery,132(6), pp.1720-1732.

John Keats La Belle Dame Sans Merci Analysis Essay Example For Students

John Keats La Belle Dame Sans Merci Analysis Essay John Keats ?La Belle Dame Sans Merci?SPeech is where you make speeches. â€Å"La Belle Dame sans Merci† In â€Å"La Belle Dame sans Merci,† John Keats’ stresses the idea that beauty is only skin deep and also lies in the eye of the beholder. Through the use of two speakers, Keats’ is able to portray his theme by means of a story. As the poem begins, the reader meets the first speaker. As we read on, we come to find out that this is a passer-by. We also find out the state of the other speaker, â€Å"wretched Wight.† Sounds so full of life. We also find out the setting. â€Å"The sedge is wither’d from the lake, /And no birds sing.† Again, the reader sees the lack of life in the setting. As the first speaker continues, he starts to interrogate the other man. â€Å"†¦what can ail thee†¦?† He describes the man as â€Å"a lily on thy brow, with anguish moist and fever dew.† This translated more than likely indicates that the man is sad. He has also lost the color in his cheeks by stating, â€Å"on thy cheek a fading rose.† Now, it is time for the other speaker to respond. His first remark is the route of his problem†¦Ã¢â‚¬ I met a lady.† Wow, cut, print, we have ourselves the beginning of the majority of problems men face. He has met a woman. He then starts to describe her as if in a trance â€Å"Full beautiful, a faery’s child. † The woman is made out to be a goddess. He furthers his description with â€Å"Her hair was long, her foot was light, /And her eyes were wild.† Through stating her attributes in past tense, the second speaker is relaying that she is no longer there. Now the second speaker (for the sake of understanding, we shall call him Sark), Sark is describing what they did together. â€Å" set her on pacing steed.† And she sat like a true lady and they were merry. She took him into â€Å"her elfin grot† and the laid together. She â€Å"look’d at as she did love him. † By this saying, it can be presumed that she did not really love him, but only acted like it because of the gifts he was bestowing upon her. As he fell asleep, Sark had a dream. He dreamt that â€Å" saw pale kings, and princes too, /Pale warriors, death-pale were they all.† These men can be presumed as others who had fallen for this woman and had come to the same misery as him. Sark wakes up and finds himself alone â€Å"On the cold hillside.† He then continues to explain that is why the passer-by found him where he is, where â€Å"the sedge is wither’d from the lake, /And no bird sings.† This is a true story of falling in love with the beauty and not the person. The man fell for her like a rock in water. He gave up everything for her and she left him. But in retrospect, when the title of the poem is translated, it turns out she is the â€Å"beautiful woman without pity.† Speech and Communcations