An underinvestment problem refers to a situation in which a company, or its stockholders, decides not to invest in low-risk investments that would deliver safe cash flow for the advantage of shareholders of the company's debt. The company, instead, chooses to invest in high-risk assets that leave the bondholder exposed to high risk without a promise of a higher return.
What is Data Mining? Data mining is a process that facilitates the extraction of relevant information from a vast dataset. The process helps to discover a new, accurate and useful pattern in the data to derive helpful pattern in data and relevant information from the dataset for organization or individual who requires it. Key Features of data mining include: Based on the trend and behaviour analysis, data mining helps to predict pattern automatically. Predicts the possible outcome. Helps to create decision-oriented information. Focuses on large datasets and databases for analysis. Clustering based on findings and a visually documented group of facts that were earlier hidden. How does data mining work? The first step of the data mining process includes the collection of data and loading it into the data warehouse. In the next step, the data is stored and managed on cloud or in-house servers. Business analyst, data miners, IT professionals or the management team then extracts these data from the sources and accordingly access and determine the way they want to organize the data. The application software performs data sorting based on user’s result. In the last step, the user presents the data in the presentable format, which could be in the form of a graph or table. Image Source: © Kalkine Group 2020 What is the process of data mining? Multiple processes are involved in the implementation of data mining before mining happens. These processes include: Business Research: Before we begin the process of data mining, we must have a complete understanding of the business problem, business objectives, the resources available plus the existing scenario to meet these requirements. Having a fair knowledge of these topics would help to create a detailed data mining plan that meets the goals set up by the business. Data Quality Checks: Once we have all the data collected, we must check the data so that there are no blockages in the data integration process. The quality assurance helps to detect any core irregularities in the data like missing data interpolation. Data Cleaning: A vital process, data cleaning costumes a considerable amount of time in the selection, formatting, and anonymization of data. Data Transformation: Once data cleaning completes, the next process involves data transformation. It comprises of five stages comprising, data smoothing, data summary, data generalization, data normalization and data attribute construction. Data Modelling: In this process, several mathematical models are implemented in the dataset. What are the techniques of data mining? Association: Association (or the relation technique) is the most used data mining technique. In this technique, the transaction and the relationship between the items are used to discover a pattern. Association is used for market basket analysis which is done to identify all those products which customer buy together. An example of this is a department store, where we find those goods close to each other, which the customers generally buy together, like bread, butter, jam, eggs. Clustering: Clustering technique involves the creation of a meaningful object with common characteristics. An example of this is the placement of books in the library in a way that a similar category of books is there on the same shelf. Classification: As the name suggests, the classification technique helps the user to classify and variable in the dataset into pre-defined groups and classes. It uses linear programming, statistics, decision tree and artificial neural networks. Through the classification technique, we can develop software that can be modelled so that data can be classified into different classes. Prediction: Prediction techniques help to identify the dependent and the independent variables. Based on the past sales data, a business can use this technique to identify how the business would do in the future. It can help the user to determine whether the business would make a profit or not. Sequential Pattern: In this technique, the transaction data is used and though this data, the user identifies similar trends, pattern, and events over a period. An example is the historical sales data which a department store pulls out to identify the items in the store which customer purchases together at different times of the year. Applications of data mining Data mining techniques find their applications across a broad range of industries. Some of the applications are listed below: Healthcare Education Customer Relationship Management Manufacturing Market Basket Analysis Finance and Banking Insurance Fraud Detection Monitoring Pattern Classification Data Mining Tools Data mining aims to find out the hidden, valid and all possible patterns in a large dataset. In this process, there are several tools available in the market that helps in data mining. Below is a list of ten of the most widely used data mining tools: SAS Data mining Teradata R-Programing Board Dundas Inetsoft H3O Qlik RapidMiner Oracle BI
What is Day Trading? Day trading is popular among a section of market participants. It is a type of speculation wherein trades are squared-off before the market close in the same day. An individual or a group is engaged in buying and selling of securities for a short period for profits, the trades could be active for seconds, minutes or hours. One can engage in day trading of many securities in the market. Anyone who has sufficient capital to fund the purchase can engage in day trading. For a class of people, day trading is a full-time job. Day traders are agnostic to the long-term implications of the security and motive is to benefit from the price changes on either side and make profit out of the asset price fluctuations within a day. They bet on price movements of the security and are not averse to take short positions to benefit from the fall in price. Day trading is not only popular among individuals or retail traders but institutional traders as well, therefore the price movements are large sometimes depending on the magnitude of information flow and accessibility. Everyone wants to make money faster, and many are inclined to speculate in markets, but it comes with considerable risk and potential loss of capital. People engaged in day trading also incur losses, and oftentimes outcomes are disheartening. Day trading is a risky activity, similar to sports betting and gambling, and it could become addictive just like gambling and sports betting. Since the motive is to earn profits, the profits realised from day trading also tempt people to continue speculating. People spend considerable time and efforts to make the most out of day trading. They have to continuously absorb and incorporate information flow, which has become increasingly accessible driven by new-age communications systems like Twitter, Facebook, forums etc. But not only information flows have been favourable, day traders are now equipped with best in class infrastructure to execute trades even on compact devices like mobile phones. The accessibility to markets is at a paramount level and gone are days of phone call trading and lack of information flows. What are the essentials for Day Trading? Basic knowledge of markets With lack of basic knowledge of markets, day trading may yield unacceptable outcomes. It becomes imperative for people to know what’s on the stake. Prospective day traders should know about capital markets, and the securities traded in capital markets like bonds, equity and derivatives. Buying shares and expecting a return from the price movements are on the to-do list for many. However, it is important to know about and risks and potential returns from speculating in capital markets. After getting some basic knowledge about markets and securities, aspiring day traders should know how to analyse market prices of securities through fundamental analysis and technical analysis. Although day traders don’t practice fundamental analysis extensively, they spend considerable time to apply technical analysis, to formulate a entry and exit strategy. Device and internet connection Trading is now possible on mobile applications as well as computer applications or websites. An aspiring day trader will likely begin with mobile phone given the accessibility, and laptops/computers are useful as scale grows larger and complex. Internet connection is prerequisite to practising day trading, and it is favourable to have a fast internet connection to avoid glitches and potential problems. These perquisites are now available with large sections of societies. Broker and trading platform A broker will facilitate a market for potential trades. The security brokerage industry has also seen a profound shift as technology has driven cost lower while competition is ramping up across jurisdictions. Large retail brokerages have moved towards zero commission trading in the U.S., and the same is seen being the trend across other geographies as well. The entry of discount and online brokerages has perhaps given wings to the retail market participants as well as the retail market for security brokers. Robinhood has grown immensely popular in the United States, but there are many firms like Robinhood in other jurisdictions. Each country has some firms with business model on same lines as Robinhood. Brokers now offer high-quality mobile applications and web services to clients, and trading security has never been so accessible. They also provide access to the global market along with a range of securities, including commodity derivatives, currency derivatives, CFDs, options, futures, bond futures etc. Real-time market information flow On public sources, market price information is at times not live due technical shortcomings, which will not work appropriately, especially for day traders. Brokers not only provide platform and market but several other services, including margin lending, real-time data, research. Day traders closely track prices of securities and overall information flow to incorporate developments in bidding, and real-time data provides accurate prices throughout market hours. Information flow largely relates to the news around the company, industry or economy. Day traders now have far better sources of information than the conventional sources, and sometimes these sources could be exclusive to a group. What are the risks of day trading? Most of the aspiring day traders end up losing money, given the lack of experience and knowledge. They should rather only bet on capital that they are comfortable to loose, in short, they should avoid risk of ruin. Day trading is sort of pure-play speculation and application of knowledge, information flow, laced with good trading system is paramount. The only concern of day traders is movement in price, which contradicts from investments. Day traders try to time and ride the momentum in the price and exit the trade before momentum turns otherwise, which can happen frequently. It consumes considerable time and induces stress on the individuals given the nature of security prices, which can move north and south abruptly throughout the day, hours, minutes and seconds. Day traders should have enough capital to trade in cash instead of margin. Day trading on margin or borrowed money is extremely risky and has the potential to make a person insolvent, especially in cases of extreme risk-taking. The leverage associated with borrowed money magnifies profits as well as losses. Aspiring day traders should equip themselves with adequate knowledge, competency and sound risk management process. Although fast money is dear to most, it is better to know what is at stake before jumping into markets with excitement.
What are ETFs? ETFs are similar to funds where pooled money of investors is managed by a fund manager, who runs the ETF. These funds invest in equity, debt, commodity or any other asset class, depending on its offering. Good read: Mastering the Basics of Investing in ETFs Price of the ETF is based on a value of net assets in the fund and is subject to change each trading day consistent with underlying changes in the value of net assets. Since ETFs are traded in markets just like shares, the quoted price of an ETF either reflects a discount to its NAV or a premium to its NAV. Investors have flocked to ETFs because of low-cost proposition and opportunity to take exposure in a specific pool of assets, which are professionally managed by an investment team with the investment manager. Some ETFs are also used as a proxy to define sentiment in an underlying sector, commodity or index since ETFs are actively traded in market hours, incorporating the latest information in prices. Fund management businesses have continued launching new and innovative ETFs, which have seen great demand over the past. Read: Gold ETFs register massive capital influx; while PDI, GPP, ERM, AME, RED Under Investors’ Lens Large and popular ETFs have also defied liquidity problems because of large scale investor participation. But it remains a problem with lesser-known ETFs with small market participation. ETFs also pay distributions to the holders that are either derived through interest income, dividend income or capital gain. Active and Passive ETFs With ETFs markets growing strongly as ever, there remains a divide between active fund managers and passive fund managers. Passive investment strategies have grown immensely popular among market participants over time. This strategy is cost effective. Many seasoned investors such as Warren Buffett, John C Bogle- founder of the Vanguard Group have endorsed passive ETFs. Active ETFs do not track a benchmark, and performance is not tracked to any given index. These funds are based on countries, sectors, market capitalisation, asset classes, etc., and active investment management allows a manager to beat the returns delivered by broader markets or indices. If you look at the great investors like Warren Buffet, Philip Fisher or Peter Lynch, they have set themselves as a preamble for active investors, and their record of delivering sustainable returns over the long term continues to attract investors to active alleys of markets. Since Passive ETFs are designed to match returns of respective benchmarks, there is no scope of delivering outperformance no guarantee that fund will not underperform the benchmark. However, the expenses charged to investors are relatively lower compared to Active ETFs. Passive ETFs are cheaper than Active ETFs because the use of resources is limited in the former. Since they are designed to match the benchmark and its underlying securities, trading in Passive ETFs is mostly automated running on algorithms, and stock picking is not required, thereby no research. Read: ETFs: Investors Up the Ante and ETFs Run the Show for Long-Term Returns ETFs based on asset classes and style Sector ETFs: These are the most common type of ETFs in market. Sector ETFs track specific sectors like Information Technology, Consumer Staples, Consumer Discretionary, Metal & Mining. These are similar to index funds but are actively traded in stock exchanges. Equity ETFs: Equity ETFs may include equity-focused Sector ETFs. As the name suggests equity, these funds invest in stocks independently or are benchmarked to a specific index. Perhaps, Equity ETFs are the most common ETFs. Fixed Income ETFs: These funds invest in fixed income instruments and pay distributions out of the interest earned on bonds. Further Fixed Income ETFs can be separated as investment-grade ETFs, high-yield ETFs, Government bond ETFs. Commodity ETFs: Commodity ETFs invest in physical commodities like precious metal, agricultural goods, natural resource. These funds include products like Gold ETFs, Oil ETFs, Grain ETFs, Silver ETFs. Good read: Investing in Commodity ETFs Short ETFs: Also known as inverse ETFs, these funds are designed to benefit when the benchmark is falling. Short ETFs hold short positions in the benchmark index futures or constituents of the index to benefit from fall in value or prices. To know more about short selling read: Minting Money While the Asset Price Tanks; Enter the World of Short Selling Leveraged ETFs: Leveraged ETFs use derivatives to amplify the returns and risks of a fund. These are also called geared ETFs. Leveraged ETFs may also hold equity or bonds along with the derivatives to amplify the net asset value movement of funds. Do read: All You Need to Know About Exchange Traded Funds Why investors prefer ETFs? Passive investment vehicles continue to appear compelling to a large investor base, and there are numerous reasons driving the demand for passive investment vehicles. Low-cost and no minimum investment: ETFs have lower expenses compared to traditional mutual funds, and most of the funds have no minimum investment criteria. As a result, the market for ETFs has grown strong, due to its reach to investors with limited capital. Must read: Mutual Funds vs. ETFs: Which Are Better? Exposure to specific asset classes: Investors with large portfolio also use ETFs to enter to into specific asset classes like Gold ETF or Commodity ETF, but not limited to sector ETFs, theme-based active ETFs like technology, mobility, e-commerce etc. Portfolio diversification: ETFs provide investors with an opportunity to diversify a portfolio of concentrated stocks by including exposure to specific sectors, indices, and commodities. More importantly, the diversification is available at a low-cost investment, which further drives the need for ETFs in a portfolio. Accessibility: It is perhaps the most compelling value ETFs provide to investors. Since ETFs are available on stock exchanges like shares, investor participation remains strong, and some popular ETFs boast high liquidity levels. Read: Confused on How to Invest in ETFs? We Have Some Tips! Further read: 6 Reasons to look at ETFs
Defining Macroeconomics Macroeconomics is a branch of Economics that evaluates the functioning of an economy as a whole. It studies the performance and behaviour of key economic indicators such as economy’s output of goods and service, exchange rates, the growth of output, the rate of unemployment and inflation, and balance of payments. Macroeconomics emphasises on the policies and economic behaviour that influence consumption and investment, exchange rates, trade balance, money flow, fiscal and monetary policy, interest rates, national debt, and factors influencing wages and prices. The scope of the subject goes beyond microeconomic topics like the behaviour of individuals, firms, markets, and households. History of Macroeconomics Macroeconomics originated with John Maynard Keynes post the great depression when the classical economist failed to explain the great economic fallout. Classical economics mostly comprised theories that studied pricing, distribution, and supply & demand. In 1936, John Maynard Keynes published – The General Theory of Employment, Interest and Money – effectively changing the perception of how macroeconomic problems should be addressed. The theories of Keynes shifted to focus on aggregate demand from the aggregate supply. Keynes said: ‘In the long run, we are all dead’. This statement was made to dismiss the notion that the economy would be in full employment in the long run. Later the theories developed by Keynes formed the basis for Keynesian economics, which gained popularity over other schools of thoughts including Neoclassical economics. Neoclassical economics emerged in the 1900s. It introduced imperfect competition models, which included marginal revenue curves, indifference curves. The theories in neoclassical economics argued about the efficient allocation of limited productive resource. Neoclassical economists explain consumption, production, pricing of goods and services through supply and demand. Some assumptions of this thought were an individual’s motive is to maximise utility as companies seek to maximise profits. Individuals make rational choices and act independently on perfect information. Over the years, many new schools of thought in Macroeconomics have found footing in the economics world. These include monetarist theories, new classical economics, new Keynesian economics, and supply-side macroeconomics. Difference between Macroeconomics and Microeconomics Major topics in Macroeconomics National income and output The estimation of national income includes the value of goods and services produced by a country in a financial year domestically and internationally. National income essentially means the value of total output generated by an economy in a year. National income can also be referred as national expenditure, national output or national dividend. Financial systems Understanding financial systems is an important concept in macroeconomics. A financial market is a market for financial securities and commodities, including bonds, shares, precious metal, agriculture goods. It is important for an economy to have markets where buyers and sellers can exchange goods. A financial market helps in the allocation of resources. Financial markets facilitate savings mobilisation, i.e. financial intermediaries channelise funds from savers to borrowers. Investment remains on the agenda for policymakers to promote growth, and financial markets facilitate funds by allowing individuals to invest in bonds and stocks, which are issued by institutions seeking funds for investments. Business cycles A Business cycle or an economic cycle refers to fluctuations in production, trade or economic activities. The upward and downward movement generally indicates the fluctuations in gross domestic product. A business cycle has four different phases: expansion, peak, contraction, and trough. An expansion in an economy is when economic growth, employment, prices are rising. The peak is achieved when the economy is producing maximum output, inflation is visible, and employment levels are running high. After a peak, the economy enters into contraction, which leads to a fall in employment, depleting economic activity, and stabilisation in prices. At trough, the economy is at the bottom of the cycle, and the next phase of expansion starts after the trough. Interest rates Macroeconomics also deals with interest rates in the economy. Interest rate policy of an economy is formulated and maintained by the central bank. A central bank manages the money supply in the economy. The intervention by the central bank to propel economic growth is called monetary policy. The monetary policy of an economy seeks to maintain employment and inflation in the economy. The motive of the monetary policy is to achieve full employment and maintain stable prices.