Warrants are those financial instruments that is being issued by banks and financial institutions. In case of index warrants, the underlying security is the value of the chosen index. Purchasing an index warrant means taking a bet on how the overall share market will move from the time an index warrant is being purchased till it expires.
Index warrants expires within 3 months from the date it is being purchased.
What is data warehousing? Data warehousing is defined as the method of gathering & handling data from different sources to get meaningful output and insights. Data warehousing is central to the BI system and is built for data analysis and reporting. Source: © nfo40555 | Megapixl.com In simple terms, a data warehouse is a large collection of data utilized by businesses to make investment decisions. What are the characteristics of data warehousing? Data warehouse has supported businesses in making informed decisions efficiently. Some of its key features are highlighted below: The data in a data warehouse is structured for easy access, and there is high-speed query performance. The end users generally look for high speed and faster response time – two features present in data warehousing. Large amount of historical data is used. Data warehouse provides a large amount of data for a particular query. The data load comprises various sources & transformations. What are the benefits of data warehousing? The Companies which used data warehousing for analytics and business intelligence found several advantages. Below are some of them: Better Data: When data sources are linked to a data warehouse, the Company can collect consistent and relevant data from the source. Also, the user would not have to worry about the consistency and accessibility of the data. Thus, it ensures data quality and integrity for sound decision making. Faster decisions: Through data warehousing, it is possible to make quicker decisions as the data available is in a consistent format. It offers analytical power and a comprehensive dataset to base decisions on tough truths. Thus, the people involved in decision making do not have to rely on hunches, incomplete data, and poor quality data. It also reduces the risk of delivering slow and inaccurate data. How does a data warehouse work? A data warehouse is like a central repository where the data comes from various sources. The data streams into the data warehouse from the transactional system and other relational databases. These data could either be structured, semi-structured or unstructured. These data get processed, altered, and consumed in a way that the end-user can gain access to the processed data in the data warehouse via business intelligence (BI) devices, SQL clients and spreadsheets. A data warehouse merges the data that comes from various sources into a complete database. The biggest advantage of this merged data is that the Company can analyze the data more holistically. It also makes the process of data mining smooth. Copyright © 2021 Kalkine Media Pty Ltd. Component of a data warehouse A data warehouse can be divided into four components. These are: Load Manager Load Manager, also known as the front component, does operations related to the mining and loading the data into a data warehouse. Load manager transforms the data for entering into Data warehouse. Warehouse Manager The warehouse manager manages the data within the data warehouse. It analyses data to confirm that the data in the data warehouse is steady. It also conducts operations such as the creation of indexes and views, generation of denormalization and aggregations, modifying and integrating the source data. Query Manager Query Manager is a backend component that does operations concerning the supervision of user queries. End-User access tools End-User access tools comprise data reporting, query tools, application development tools, EIS tools, data mining tools, and OLAP tools. Roles of Data Warehouse Tools and Utilities The tools and utilities in a data warehouse are used for: Data extraction: The data extraction process involves gathering data from heterogeneous sources. Data cleaning: Data cleaning consists of searching for any error in the data. Data transformation: Data transformation process involves changing the data into a data warehouse setup. Data loading: This process involves data sorting, recapping, consolidating, verifying integrity. Refreshing: This process requires revising data sources to the warehouse. Application of data warehouse Data warehouse plays a considerable role across multiple sectors. Some of the sectors it caters to are highlighted below. Aviation sector In the aviation sector, a data warehouse’s role can be seen in crew assignment, route profitability analysis, any promotional activity. Banking Industry In the banking sector, the focus is on risk management, policy reversal, customer data analysis, market trends, government rules and regulations and making financial decision. Through a data warehouse, banks can manage the resources available on the deck effectively. Banks also take the help of a data warehouse to do market research, analyze the products they offer, develop marketing programs. Retail industry Retailers act as an intermediary between the producers and the customers. Hence, these retailers use a data warehouse to maintain the records of both producers as well as the customer to maintain their existence in the market. Data warehouses help track inventory, advertisement promotions, tracking customer buying trends and many more. Healthcare industry In the healthcare industry, a data warehouse is used to predict the outcome of any test and taking relevant action accordingly. Data warehouses help them to generate patient treatment report, offer medical services, track the medicine inventory. Many patients visiting hospital have health insurance. Through a data warehouse, hospitals maintain the list of insurance providers. Investment and insurance sector In the insurance and investment sector, the role of data warehouse becomes important in tracking the data pattern, customer trend and market movement. Services sector In the services sector, a data warehouse is used for maintaining financial records, studying the revenue pattern, customer profiling, resource management and human resource management. Telecom The telecom sector uses a data warehouse in the promotion of its offerings, making sales decision, distribution decision, features to include in case they decide to launch a new product based on the customer requirement. Hospitality The hospitality sector involves hotel and restaurant services, car rental services etc. In this sector, the companies use a data warehouse to study the customer feedback on the various services offered and accordingly design and evaluate their advertising and promotion campaigns.
Dead Cat Bounce Dead Cat bounce is a colloquial phrase which is quite popular in the financial markets. The term was coined a long time ago and generally referred to the peculiar behaviour of the price. The phrase denotes a recovery in the asset’s price, often a sharp one after a prolonged downtrend. Sometimes it is also referred to a short but sharp fall, succeeded by an equally sharp recovery. How does a downtrend continue for a long time? Quite often, some securities in the financial markets depict a very long downtrend which may last from a few months to a few years depending on the severity of the fundamental headwinds. These prolonged downtrends are so strong that no support levels can withhold the downtrend and the prices keep on falling. Every support level gets taken out by excessive selling, which pushes the prices even lower. These lower prices force the long holders to liquidate their positions as no visible halt in the downtrend is noticed. This liquidation from existing buyers further fuels the selling, leading to the continuation of the downtrend. As the price keeps on falling, the buyers do not get enough confidence to buy and consequently keep getting overpowered by selling pressure continues the downtrend. So what is the ideology behind “Dead Cat Bounce”? In due course of a downtrend, the security tends to become oversold for the time being. Oversold is a technical term is used for security which seems to have fallen quite a bit in a specified period. In other words, a security that has been continually sold in a specified period tends to reach a level wherein the sellers are no more interested in selling at further lower rates. This is where the buyers’ step in and try to buy these stocks at low prices, leading to an increase in demand over the supply. This fresh buying tends to push the price up hence resulting in a short upside movement or, in technical parlance a “Bounce”. This point is where the downtrend witnesses a temporary upside momentum which is exactly quoted as a “Dead Cat Bounce”. The ideology is “Even a dead cat will bounce if fallen from a great height.” Likewise, a short bounce is quite expected after a prolonged downtrend which does not change the trend as a bounce does not mean the cat has become alive. Image Source ©Kalkine Group Does it signify a reversal from a downtrend? A Dead Cat bounce is an upside momentum, witnessed after a prolonged downward trend, generally near the oversold price region. But it is to be noted that this price bounce is merely a reaction of the downtrend which is often witnessed in the oversold areas. This does not change the entire trend, and more often than not, the trend continues in the primary direction after the bounce fizzles out. Why is it difficult to trade a Dead Cat Bounce? Most of the time it is difficult to trade a move like a Dead Cat Bounce as the bounce is often very quick and short-lived. The overall trend remains negative, which is in contradictory to the short-term bounce. Also, few investors mistake it for the trend change, which often proves to be a mistake. It generally becomes difficult to estimate some key support areas from where the bounce may occur as the downtrend is quite strong and lacks demand to support the price. However, there are some momentum indicators like RSI (Relative Strength Index), Stochastics oscillator etc. which may help to gauge oversold zones from where the bounce may occur. What are the reasons for a Dead Cat Bounce? There could be many reasons for a Dead Cat Bounce to occur on the charts as the sudden demand may come due to numerous reasons. Some of the reasons are Oversold Price As discussed, due to a prolonged downtrend and continued selling the price often comes to a level wherein the sellers are no more interested in selling at these lower prices and at the same time buyers often find a value proposition. This leads to a spike in demand, which ultimately results in a Dead Cat Bounce. Strong support area There are some levels of support on the price chart that are quite prominent. In other words, there are some regions of support which are quite strong and may remain relevant for years. These support levels are generally hard to break at the first attempt, which results in a bounce or a complete reversal. How to profit from a Dead Cat Bounce There are two different strategies when it comes to trading these kinds of sharp and against the trend moves. They are contradictory to each other, but both are based on proven price behaviour. Short Selling the rally As the primary trend of the underlying is still downward, one thought arises to go short on the bounce. This strategy one to participate in the downtrend but with a much better price. If these rallies are met with a resistance level like a falling trendline, horizontal price resistance etc. then these areas are ideal to sell the bounce in a downtrend. Buying into the rally Another opinion arises, why not to participate in the bounce? This strategy can also be fruitful provided the bounce should be stronger and last for a while, which is not always the case. This essentially calls for a very quick decision making while capitalising on the temporary bounce. Bottomline A Dead Cat Bounce is a prolonged downtrend followed by a short-term bounce. These bounces generally don’t last long, and once they fade, the trend continues towards the south. However, sometimes a bounce may also act as a reversal, but for the added confirmation a trader should also look at other signals of a reversal like bullish divergence at the bottom or a double bottom chart pattern.
The EAFE index-maintained by MSCI is a market-capitalisation weighted market performance index, which tracks the performance of the stock market across the developed markets outside the United States and Canada.
What is Earnings Per Share? EPS is the per share profit by a business in a given period. While analysing a business financially, it serves as one of the basic tools. EPS is calculated by dividing profits by total shares outstanding for a given period. EPS is reported on the profit and loss statement of an enterprise and works as a denominator for beloved price-to-earnings ratio (P/E ratio), used not just by novice investors but also fund managers. A business is required to generate sustainable earnings in its life cycle, and earnings or profits are essentially among major intend of a promotor. To know more about P/E ratio read: Understanding Price-Earnings Ratio But reported earnings of a business will likely differ from actual cash earnings because devising profits mandate broader accounting standards and principles to provide a fair picture of an enterprise. EPS, therefore, becomes imperative for investors, market participants and other users of information. EPS estimates are circulated by sell-side analysts to market participants. Financial Modelling is applied to arrive at the EPS estimates of future financial years, semi-annual periods or quarterly, depending on the reporting adopted by the firm. Analyst estimates are then collected by market data providers like Reuters, Bloomberg, IRESS to provide a consensus view of analysts on the business and its financials, including revenue, operating expense, earnings before interest and tax, profit after tax, EPS. Market estimates enable participants to evaluate the expectations of sell-side analysts from a particular company, sector or even index. Analyst estimates also indicate the divergence between an individual’s expectations and collective expectations of analysts that are tracking the company. An individual can, therefore, determine whether the stock of the company is undervalued or overpriced by the market against hi one’s fair value estimates that are based on the expectations from the company. More on EPS read: What Do We Mean By Earnings Per Share (EPS)? How to calculate EPS? Although general formula considers total shares outstanding in the denominator, it is preferred to use weighted average shares outstanding over a period because companies issue new shares, buyback or cancel shares. Net Income is the profit reported by a business after incurring income tax. It is also called as Net Profit After Tax. Dividends on Preferred Shares are paid to preferential shareholders because they have first right over the income of a business, but preferred shares don’t have voting rights like common shareholders or ordinary shareholders. Weighted Average Shares Outstanding is calculated after incorporating changes in number of shares during a period, and using weighted average shares outstanding provides a fair financial position of a company. Basic V/S Diluted EPS Diluted EPS is calculated after adding the weighted average number of shares that would be issued after the conversion of dilutive shares to weighted average shares outstanding. Dilutions can include share rights, performance rights, convertible bonds etc. Whereas Basic EPS is calculated by taking weighted average shares outstanding that incorporate changes to number of shares outstanding such as buyback, new issues etc. What is Adjusted-EPS? In a financial period, firms may incur one-time expenses or transactions that are not usual in the normal course of business. The objective of adjusted EPS is to arrive at a fair picture of the business, especially for financial forecasting. Extraordinary items are excluding from EPS to arrive at adjusted EPS figure. These items can include gain on sale of assets, loss on sale of assets, merger costs, capital raising costs, integration expenses etc. What is Normalised EPS? Normalised EPS is calculated to arrive at an EPS figure, which embeds the fluctuations in income due to business cycles or industry cycles. It also includes adjustments made for calculation of adjusted EPS such as one-time gains or losses. Normalised EPS is a useful measure for companies that are sensitive to economic cycles or changes in the business environment. By smoothening out the fluctuations, it provides a fair picture of the business. If a company has reported high normalised earnings over periods, it is considered that the company is less sensitive to changes in business cycles because of its stable revenues and income during the periods. EPS and Price-to-earnings ratio Calculation of price-to-earnings ratio requires EPS as denominator and price of the stock as numerator. EPS therefore becomes a very important financial metric for investors. EPS and price data also allows participants to compare the historical trends of the P/E ratio with the current market scenario and P/E ratio of the stock. How can increase grow EPS? Businesses can increase EPS by focusing on increasing their revenue, by improving operational efficiencies either by deploying technology to reduce cost, or negotiate better prices with vendors, operate in tax efficient manner, etc. Businesses can also improve EPS by undertaking corporate action such as buying back of shares. Read: Pros and cons of buybacks – Story of 5 Popular Stocks including Aurizon Good read: Every Doubt You Have On Earnings Per Share- Explained Right Here!