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  • Ratio Analysis – Overview, Uses, Formula, Categories of Financial Ratios

    Ratio Analysis – Overview, Uses, Formula, Categories of Financial Ratios

    What is Ratio Analysis?

    Ratio analysis is the numerical method to review the company’s financial soundness through financial ratios. In other words, financial ratio analysis examines important ratios that reveal the company’s assets and liabilities. 

    Stakeholders use financial ratios and evaluations to make crucial judgments about their commitments to a business. Now after understanding the ratio analysis meaning, let’s check out more about the types of ratio analysis, formulas, and uses. 

    Uses of Financial Ratio Analysis

    Comparisons

    Ratio analysis is used, among other things, to assess a company’s position in the marketplace by comparing its financial results to that of other companies in the same sector. 

    It helps businesses assess their unique strengths, weaknesses, and drawbacks by obtaining financial ratios from well-known rivals and comparing them to the Business’s ratios to detect market gaps. The leadership can then make choices intended to strengthen the company’s performance in the market using that information.

    Determination of Market Trends

    Ratio Analysis allows the organization to check for trends in their business performance. Established businesses gather information from financial reports across many time frames. 

    In addition to identifying any unanticipated financial disturbance for a particular reporting period, the trend observed can also be utilized to forecast the trajectory of future profitability.

    Effectiveness of management

    Financial ratio analysis is another tool that a company’s management can use to gauge how well assets and liabilities are managed. 

    Ineffective use of resources like cars, equipment, and buildings leads to high costs that need to be cut. Financial ratios help to assess whether funds are being used too much or too little.

    Types of Ratio Analysis

    Liquidity Ratio

    Using the company’s current assets, its ability to pay down its debt is ascertained by its liquidity ratios. When a business has trouble making ends meet and cannot pay debts, it can turn its assets into cash and use the proceeds to pay off any outstanding debts.

    There are two types of Liquidity Ratios:

    • Current Ratio: The Ratio of a company’s current assets to current liabilities is known as the current Ratio. It determines a company’s capacity to meet its debt commitments over the next 12 months based on its liquidity. A higher current ratio will show that the company can easily pay off its short-term debt commitments. Its formula is:

    Quick Ratio: The quick Ratio, widely known as the acid test ratio, evaluates the company’s capacity to pay off short-term obligations using its most liquid resources. The formula of Quick Ratio is:

    Profitability Ratios

    Profitability ratios evaluate the company’s capacity to turn a profit about the costs that go along with it. A higher profitability ratio than in the last financial reporting period indicates that the company’s financial situation is improving.

    There are four types of Profitability Ratios:

    • Gross Profit Ratio :Gross profit ratio is used to ascertain the company’s operating profits.
    • Net Profit Ratio: After subtracting both cash and non-cash expenses, net profit ratios are computed to assess the Business’s total profitability.
    • Operating Profit Ratio: A company’s stability and capacity to pay off all of its long- and short-term debts are assessed using the operating profit ratio.
    • Return of Capital Employed (ROCE): Return on investment Employed is used to evaluate a business’s profitability about the capital invested in the Business.

    3. Solvency Ratios

    Solvency ratios evaluate a business’s potential for long-term financial success. These ratios compare a firm’s debt levels with its assets, equity, or yearly income.

    There are two types of Solvency Ratios:

    Debt to Equity Ratio: The Ratio between total debt and investor’s equity is known as the debt-equity Ratio. It allows us to determine a company’s leverage. A company should have a debt-to-equity ratio of 2:1.

    Interest Coverage Ratio: The interest coverage ratio is used to assess a company’s future solvency and evaluate how often its revenues would have to increase to pay its interest-related costs.

    4. Turnover ratios

    Turnover ratios evaluate how effectively a company uses its assets and liabilities to create sales and generate profit. It computes the turnover of liabilities, the use of inventories, the use of equipment, and the use of stock. These ratios are crucial because rising Turnover ratios increase a company’s ability to boost profits and revenues.

    There are three Types of Turnover:

    Fixed Assets Turnover Ratio: The effectiveness of a company in using its fixed assets to produce profits is assessed using the fixed assets turnover ratio.

    Inventory Turnover Ratio: The inventory turnover ratio is used to gauge how quickly a business turns its stocks into sales.

    Receivable turnover ratio: The effectiveness of a company in realizing its account receivables is assessed using the receivable turnover ratio.

    5. Earnings Ratios

    The earnings ratio is a tool used to assess a company’s profits for its shareholders.

    There are two types of Earning Ratios: 

    Profit Earning Ratios: Profit Earning ratio is a tool that is used to know the profit earning capacity of the company.

    Earnings per Share: EPS ratio is used to evaluate the earnings of an equity shareholder based on each share.

    Conclusion

    The foundation for financial analysis is laid by ratio analysis. The analysts of financial statements also perform ratio analysis to have a better picture of a company’s finances.

    Financial statements provide data that, unless correctly analyzed, is of limited benefit. To swiftly analyze financial data and derive useful insights, consider using key financial ratios in qualitative analysis.

    It can assist you in discovering information that influences stock prices that, occasionally, even the corporation is unaware of. Moreover, you can also compare your ratios to other companies’ ratios to make improvements and survive in the competitive market. 

    Reference

  • Regression Analysis – Formulas, Explanation, and Examples

    Regression Analysis – Formulas, Explanation, and Examples

    Data modeling and analysis frequently use regression analysis. This statistical approach is used in the fields of finance, investment, and other areas to assess the nature and strength of the connection between two given variables. This blog will walk you through the concept of regression analysis and its applications in real life, including calculations and examples.

    What Is Regression Analysis?

    Regression analysis is the most popular statistical method for determining or estimating the relationship between a dependent variable and one or a group of independent variables. Most survey analysts use regression analysis to comprehend how the given variables are related, which can then be used to forecast the precise result. 

    For example, a paint company wanted to understand the challenges leading to brand marketing. The survey was the most effective way to contact both current and potential clients. A thorough questionnaire was created with the aid of a survey tool for a massive consumer survey. Several questions related to the brand, impact, vision, and culture were effectively asked in the survey. After receiving responses to the survey, regression analysis was used to narrow down the top ten factors responsible for challenges in brand marketing. All the attributes derived (mentioned in the image below) highlighted the challenges in brand marketing.

    Usability of regression analysis

    Numerous practical uses can be made of regression analysis. It is crucial for any machine learning issue involving continuous numbers. Its uses include but are not restricted to the following:

    • Forecasting financial data (like house price estimates or stock prices)
    • Predicting sales and promotions
    • testing vehicles
    • Forecasting and analyzing weather
    • Forecasting time series

    Regression analysis can provide particular information on a relationship between two or more variables and indicate if it is significant. It can estimate the magnitude of an independent factor’s effect on a dependent variable. Regression analysis should be able to tell you what impact changing the value of one variable (like price) will have on the dependent variable (like sales).

    Regression analysis is a statistical tool that businesses may use to test the impact of variables on several scales. They can evaluate the ideal combination of factors to incorporate when creating predictive models, considerably improving forecasting accuracy.

    Finally, regression analysis is the best method for utilizing data modeling to solve regression problems in machine learning. Businesses may forecast each data point’s chances of error by putting the data points on a chart and then drawing the best fit line through them; the farther away from the line the data points are, the greater their error of prediction (this best fit line is also known as a regression line). 

    Examples

    Let’s say a frozen food company wants to relocate its manufacturing facility. Before moving forward, the business wants to examine its revenue generation model and all the potential influences. As a result, the business performs an online survey using a certain questionnaire. The responses from the survey will help analyze the revenue generation model. Accordingly, the company can decide whether to relocate or not and how to proceed with the relocation.

    Consider another example. Suppose a beauty salon manager believes extending the closing time will increase its customers and sales. On the contrary, according to regression analysis, the extra revenue brought on by higher sales won’t be enough to cover the increased operating costs brought on by longer working hours.

    Regression analysis makes it simpler for the business to comprehend the relationships between variables, such as electricity and revenue (here, revenue is the dependent variable), and to interpret survey results. Additionally, knowing how diverse independent variables like price, labor force, and logistics relate to revenue can assist a business in evaluating the influence of various variables on its sales and profitability.

    How To Calculate Regression Analysis?

    Formula For Regression Analysis

    Moreover, regression analysis is usually conducted in spreadsheet programs like MS Excel and Google Sheets as it involves complex calculations.

    Calculation For Regression Analysis — Example

    Let’s say a bank decides to link the interest rate on savings accounts to the repo rate. The bank’s auditor now wants to perform an unbiased study of the decisions made by the bank regarding interest rate changes and whether the Repo rate has changed due to the new changes.

    The bank’s auditor uses the regression method to analyze whether the bank’s rate changed when the Repo rate did.

    With n = 6, we have all the values in the aforementioned table. So, first, determine the regression’s intercept and slope first. The intercept is calculated as follows:

    a = (24.17 x 237.69) – (37.75*152.06) / 6 x 237.69 – (37.75)2 = 4.28

    The slope is calculated as follows:

    b = (6 x 152.06) – (37.75 x 24.17) / 6 x 237.69 – (37.75)2 = (-0.04)

    Now, put the values in the formula to obtain the final figure.

    Hence, the regression line Y = 4.28 – 0.04 x X

    As a result, the slope value indicates a relationship between the repo rate and the bank’s saving account rate. Therefore, it looks like the bank is indeed adhering to the policy of linking its saving rate to the repo rate.

    Financial Takeaways

    Regression analysis is significant since it revolves around data, specifically the numbers and statistics that actually characterize a business. Businesses can essentially crunch the numbers with regression analysis to make better decisions for their organization now and in the future.

    FAQs

    Is regression analysis qualitative or quantitative?

    Regression analysis is a quantitative research method.

    Is regression analysis machine learning?

    Yes, regression analysis is among the most fundamental tools of machine learning used for prediction.

  • Relative Strength Index: Definition, Formula and Calculation.

    Relative Strength Index: Definition, Formula and Calculation.

    Introduction

    People who invest in the stock market always want to see their portfolios grow. But the investing game becomes very tricky without proper knowledge and information about the market. Herbert Spencer’s theory of “survival of the fittest” completely fits in the stock market because if you want to make a profit, it will certainly be someone else’s money. So it’s better to be a warrior in a garden than Gardner in a war.

    In this article, we will discuss the Relative Strength Index, one of the fundamental aspects of technical analysis in the stock market. J. Welles Wilder Jr. built this concept in 1978. Wilder was an American mechanical engineer who was the father of many other technical indicators like ATR, ADX, Parabolic Arc, and RSI.

    Definition

    The Relative Strength Index is a momentum oscillator that measures the speed and change of price movements of the stocks in the stock market. If you see the RSI in the chart, you will find it oscillating between 0-100 in a technical graph, and it will not go below 0 and above 100.

     There are three essential stages in the RSI chart: 

    1. 30
    2. 50 
    3. 70 

    The zone between 0-50 is said to be the bearish zone, and between 50-100, it will be considered the bullish zone. When RSI in the stock market goes beyond 70, it is called overbought, and if it goes below 30, it will be considered oversold.

    These days, conventional traders use a range between 30 to 70, and a new generation of traders are using indicators between 40 to 60. Let’s check now how to calculate the Relative Strength Index with the help of a formula.

    Definition

    RSI= [100/1+RS]

    RS= Average of X days up closes/Average of X days down closes.

    Calculation

    The RSI is calculated during the rise and fall of prices in the stock market. Wilder, the inventor of RSI, used 14 days of RSI, which modern-day stock market traders still use. However, using the 14 days RSI is not binding, and a trader is free to decide the number of days for computing the same. 

    But the interesting thing is that Wilder, in his book Concept of the Technical Trading System, says losses are suggested as positive values, not negative ones.

    Example

    Sreesanth has invested in RBI bank stocks. During the 14-day trading period, the RBI stock generated positive returns on the subsequent 9 days and negative returns on 5 days. Sreesanth decided to calculate the RSI and to calculate RSI, and he had to follow the details given down below:

    1.  Sreesanth will calculate the absolute gain in each of the 9 days. He will add the absolute gain he earned for 5 days on his RBI stock and divide it by 14. It will give the figures of average up closes of the RBI.
    2. Sreesanth will then calculate the total loss in each of the next 5 days on the RBI stock and divide it by 14. It will give the figure of average down closes.
    3. Now, Sreesanth has to divide the average up closes or gains of the RBI by the average down closes or losses to give us the Relative Strength.
    4. The figure is further normalized using the above formula of Relative Strength Index for the RBI stock to ensure that it lies between 0 and 100.

    Now, let’s do it by figure:

    14 days of closing of RBI stock.

    Date
    Closes
    Change
    Gain
    Loss
    Avg. Gain
    Avg. Loss
    RS
    14 day RSI
    11th March
    46.22
    -0.19
    0.19
    0.20
    0.10
    1.97
    66.36
    12th March
    45.64
    -0.58
    0.58
    0.19
    0.14
    1.38
    57.97

    Limitations:

    • RSI is not a reliable indicator for most traders. Sometimes the RSI indicators send ambiguous signals, or we call RSI divergence or misleading signals that can lead the traders to a huge loss.
    • When there is a strong trend in the stock market, RSI is not going above the mark of 100 on the chart, so you cannot measure the market’s momentum during these times. Hence, it is not reliable.
    • There are also incidents with the Traders; when momentum oscillators can move without showcasing any clear trend to the traders, the stock can be overbought or oversold for longer. It might confuse the traders, who cannot make any explicit opinions.

    Conclusion

    RSI indicator is critical whether you are working in the stock market, Forex trading, Future market, or Commodity market. The RSI indicators are prevalent in a few niches of traders. Though like everything, RSI has its pros and cons. But it can benefit you in short-term trading and even in the long term. You have to understand this Indicator very carefully and correctly. 

    So this article tried to give an outlook on the RSI indicators so that you can make decisions not completely based on this single Indicator. Still, RSI, along with other technical indicators, helps you a great deal in your stock market investment.

    Reference

  • Repo Rate & Reverse Repo Rate

    Repo Rate & Reverse Repo Rate

    The repo rate, or repurchase rate, is the primary monetary policy rate at which the Central Bank or Reserve Bank of India (RBI) lends money to banks in the short term and is essentially a measure of credit availability, inflation, and economic growth control. The Indian repo rate is the primary instrument of the RBI’s monetary and credit policy.

    Repo rates are also the most significant rate for ordinary people. Everything from loan interest rates to deposit yields is affected by this important interest rate set by the RBI. Consequently, interest rates on mortgages, auto loans, and other types of loans go up and down depending on the direction of change in the repo rate.

    Repurchase option agreement

    A repurchase option agreement is a forward contract between a commercial bank and a central bank, where the commercial bank agrees to repurchase government bonds at a predetermined rate after the repo period ends.

    Repo period

    This usually happens overnight. However, the term Repo has been introduced by the Reserve Bank of India, which means the interest will be paid in 7 days or 14 days.

    Repo rate by RBI

    The Monetary Policy Committee (MPC) has risen the repo rate by 50 basis points in August 2022 and is now at 5.40%. During the meeting, the MPC decided to leave the reverse repo rate at 3.35%. The bank and marginal standing facility (MSF) rates have also changed and are now 5.15%.

    Repo Rate changes

    Interest rate
    Rate (Percent)
    Repo Rate
    4.9
    Bank Rate
    5.15
    Reverse Repo Rate
    3.35
    Marginal Standing Facility Rate
    5.15

    What is the reverse repo rate?

    In India, the current reverse repo rate is set by the RBI’s Monetary Policy Committee* (MPC), which is headed by the RBI Governor. Decisions are made at bimonthly meetings of the Monetary Policy Committee. The reverse repo rate is at which the RBI borrows money from banks in the short term. It helps RBI to raise funds from banks when needed. In return, the RBI offers them attractive interest rates. Banks also voluntarily reserve surplus funds with central banks because this allows you to earn higher interest rates on your idle surplus funds. 

    The reverse repo rate is the primary monetary policy tool used by the Reserve Bank of India (RBI) to control economic liquidity and inflation. Commercial banks also retain surplus funds received in RBI as they are considered safe. An additional benefit is that the RBI also pays interest, allowing banks to earn interest on their idle funds.

    Reverse repurchase option Agreement

    This is a buying and selling agreement between the Bank and its RBI, in which the Bank commits to resell the government securities such as treasury Bonds to the RBI at a pre-determined interest rate after the reverse repo period.

    Reverse repo period

    Like the repo rate, the reverse repo rate also usually happens overnight, which means the interest will be paid in 7 days or 14 days.

    What changes does the repo rate bring to the economy?

    If the repo rate is low, banks will receive funds from the RBI at a lower interest rate. This allows banks to lower interest rates and make credit more affordable. Low-interest rates are also not attracting savings. In this way, money is injected into the economy, and economic activity is activated. Therefore, the RBI cuts repo rates whenever it wants to stimulate the economy.

    Reverse repo rates, on the contrary, are used during times of high inflation due to excess liquidity in the economy. During this time, the RBI raises the reverse repo rate to allow banks to deposit funds in their RBI to earn higher interest rates. With less money, banks will be unable to lend to consumers. Therefore, the reverse repo rate will be increased to withdraw surplus funds from the market/system. 

    What changes does the repo rate bring to the strength of the Rupee?

    Higher reverse repo rates reduce the money supply in the market as banks entrust surplus funds to the RBI for attractive yields compared to lending to individuals and businesses. It reduces the amount of money in the system, thereby increasing the strength of the Rupee.

    How does the reverse repo rate affect home loans?

    If the RBI raises the reverse repo rate, banks will be able to raise mortgage lending rates because it’s more profitable to invest in low-risk government-backed securities than to lend people money in the form of mortgages. If reverse repo rates go down, so can mortgage rates.

    Main differences between repo rate & reverse repo rate

    Parameters
    Repo rate
    Reverse repo rate
    Controls
    The Repo rate is used to control inflation in the economy
    The reverse repo rate controls the money supply in the economy
    Purpose
    It is used to fulfill the lack of funds
    It is helpful to maintain liquidity in the economy
    Operations
    RBI provides funds to commercial banks against government bonds as collateral
    Commercial banks deposit surplus funds with RBI and receive interest on the deposits
    Borrower’s objective
    A repo rate is used to manage short-term cash shortages.
    Reverse repo rates are used to reduce the money supply of the economy.
    Current rate
    The current repo rate is 5.40%
    The current reverse repo rate is 3.35%
    Charged on
    The repo rate is charged on the repurchase agreement
    It is charged on the reverse repurchase agreement
    Rate
    The repo rate is always higher than the reverse repo rate
    The reverse repo rate is always lower than the repo rate
    Effect of the rate increase
    Higher interest rates will force commercial banks to borrow less from the central bank.
    Encourage commercial banks to send more money to the central bank and earn interest.
    Effect of the rate decrease
    This makes it cheaper for banks to get loans from the RBI.
    This allows banks to make better investments than depositing money in RBI.

    Conclusion

    The main difference between repo rate and reverse repo rate is that in the case of repo, in the case of reverse repo, the central bank injects liquidity into the economy by lending to commercial banks at more favorable interest rates. But banks absorb liquidity from the economy by raising interest rates.

  • The Meaning and Calculation of Return on Assets

    The Meaning and Calculation of Return on Assets

    We all have made investments in assets once in our lifetime, may it be gold or electronics. And once we made those investments, we would have also expected some return from them. 

    This return would be an increase in value, efficiency, or end-of-the-day happiness received through using the asset. But this is in our day-to-day lives. 

    So, what about the companies and industries that invest in assets?

    The industry term for the return received through the investment in assets is known as Return on Assets. In this blog, we’ll dive into Return on Assets and in detail understand different topics like the formula to calculate ROA, differences between ROA and ROE (Return on Equity), and much more.

    ROA is a financial ratio that reveals how profitable a company is, based on total assets. We can also know how efficiently a company utilizes its assets to generate profit through its ROA.  

    ROA – Key Points

    • ROA is a financial metric to analyze a company’s ability to use assets and generate profit.
    • Higher the ROA measure, the better the performance of a company.
    • Net income divided by the total assets of a company gives its ROA.
    • It is best to compare the ROA of a company in one industry to the ROA of another in the same industry as the metrics used to value the assets will remain the same.
    • It is said that ROA factors in the debt of a company, but ROE doesn’t.

    ROA as a comparative measure

    Efficiency is a core metric for analyzing the performance of any business. Comparing profits to revenue may give out the performances of companies, but comparing profits to assets used by the companies gives out the practicality of that company’s existence. 

    For any public company, ROA can differ substantially, and it can be dependent on the industry in which it operates. When using ROA as a comparative measure, it’s important to ensure the comparative figures are from the same industry. 

    ROA ratio provides the investors with a view of how effectively a company converts its investments on assets to net income. A company is said to be able to earn more income through its investments when the ROA ratio is high.

    Calculation of ROA

    ROA of a company is calculated by using the total assets in the company to divide the net income. It can be expressed as Net Income/Total Assets.

    For example, two companies, A and B, invest in assets like plant and machinery, equipment, and more in the automobile industry. A’s investment sums up to $1500, and B’s investment comes to $13500. End of the year, the net income earned by both companies is $180 and $150, respectively.

    ROA of the companies using the return on assets ratio formula:

    A = 180/1600 = 11%

    B = 1100/13500 = 8%

    We can say that B has a more valuable business through the return on total assets formula. Still, A has an efficient business because it’s not just about earning profit but also about a company’s long-term existence.

    Effective ROA Ratio

    Once we calculate the return on assets ratio, how do we know where the company stands in terms of efficiency?

    Industry experts say the ROA ratio of a company above 5% is considered good, and a ratio above 20% is considered excellent. But this is in general terms. When looking at ROA percentage, investors should also consider the company’s industry, market, customer base, and other factors that affect investment decisions in a company’s assets.

    ROA as a Financial Ratio

    A higher ROA may indicate a company is generating more profit against the total assets. On the contrary, a lower ROA means lower profits against the total assets. 

    Companies with higher ROAs tend to experience greater profits, while those with declining ROAs may struggle financially due to poor investment decisions. 

    As ROA also considers a company’s debt, a higher ROA in one year may say low debt, and a lower ROA in the next year may mean the company’s debt has increased.  

    Investing Decisions and ROA

    ROA is considered one of the very useful financial ratios to analyze a company’s performance. Investors can use the return of assets interpretation to find stock opportunities because the ROA shows a company’s efficiency in using its assets to generate profits. 

    Comparing the ROAs of two companies can give the investor an idea of who will sustain longer in the advancing market.

    Though ROA is considered a vital metric to compare companies, investors should also consider various other factors that affect a company’s performance. ROA alone may not give the perfect analysis of a company’s performance.

    Different industries and their average ROA

    Industry
    Average ROA
    Healthcare
    7.97%
    Transporation
    6.91%
    Consulting Services
    51.43%
    Retail
    7.20%
    Grocery Stores
    33.50%
    Tobacco
    15.89%

    ROA vs. ROE

    Though ROE measures a company’s efficiency in utilizing its resources, a major difference between ROA and ROE is how a company’s debt affects the ratios.

    ROA considers total assets, including the Capital of the company. This Capital figure would include any debt the company borrows. So ROA factor provides a view of how leveraged a company is.

    ROE, on the other hand, considers a company’s equity, which excludes any liability. Thus, the company’s debt is out of the scene.

    For any company, debt plays a major role. To analyze a company’s efficiency, we have to consider its debt and how well it can manage the debt with the net income, it has earned.

    Issues with using ROA as an industry measure

    A major setback in using ROA as an industry measure to compare companies is that the ROA ratio cannot be used across industries. 

    The ratio is more or less very specific to one industry, and we cannot compare a company’s ROA in one industry to that of another company in another industry. 

    The reason for this is those different companies have different asset bases. For example, the asset base of the clothing industry is different from that of the automobile industry. Sometimes recording the assets in the company’s books at historical costs rather than market value may lead to inaccurate analysis.  

    The Bottomline

    ROA becomes an important financial metric for analyzing the efficiency and performance of a company in any industry. Though it illustrates a company’s net income as a percentage of total assets, it is not the only appropriate metric. 

    All investors should look at the overall picture when they compare different companies.

  • Strength, Weakness, Opportunity, and Threat (SWOT) Analysis

    Strength, Weakness, Opportunity, and Threat (SWOT) Analysis

    Making informed decisions for a company’s growth and survival requires evaluating its competitive position. A SWOT analysis framework is used to assess a company’s competitive situation and create a strategic plan. You will learn about the theories and applications of the SWOT analysis in this blog.

    What Is A SWOT Analysis?

    Using SWOT analysis, an organization can determine its strengths, weaknesses, opportunities, and threats to project planning or competitive business environments. Situational analysis or situational evaluation are other names for it.

    In other words, SWOT analysis evaluates a company’s performance, rivalry, risk, and potential and specific areas inside a company, like a product line or division, an industry, or another organization.

    Components of the SWOT analysis

    Strengths include aspects like a strong brand, a devoted client base, a strong balance sheet, innovative technology, etc., that indicate what an organization excels at and what sets it apart from the competition. For instance, a hedge fund might have created a proprietary trading method that outperforms the market. The next step is for it to decide how to use the results to draw in more investors.

    An organization’s weaknesses prevent it from operating at its highest potential. A bad brand, higher-than-average turnover, high levels of debt, an inadequate supply chain, or a lack of cash are examples of areas where the company needs to improve to stay competitive.

    Opportunities are advantageous outside variables that might provide a company with a competitive edge. If a nation lowers its tariffs, a car manufacturer may export its vehicles into a new market, boosting sales and market share.

    Threats are elements that could potentially hurt an organization. For instance, a corporation that produces wheat is at risk from a drought since it could ruin or diminish crop yield. Other frequent threats include growing material costs, heightened competition, a shortage of labor, etc.

    What Are The Applications of SWOT Analysis?

    Making Use of Advantages

    You must match your strengths to the opportunities if you want to benefit from market advances. If you have high-quality items and a prospective new consumer nearby, you must allocate resources to this business to take advantage of it. Give your top salespeople, for instance, the task of signing up for this new company.

    Getting Rid of Weaknesses

    You must remedy the issue or stop the weak activity to address vulnerabilities found in a SWOT analysis. For instance, you can’t stop a weak sales strategy, but you can train your salespeople and offer them more resources. Salespeople will be inspired to use the available customer information for their sales calls if you invest in CRM software and make it accessible to them on mobile devices.

    Lessen Threats

    Threats identified by a SWOT analysis must be dealt with in one of three ways: by strengthening the business to counter the danger, by ceasing the threatened activity, or by deciding the threat is inconsequential and taking no action.

    SWOT Analysis of A Company

    Strengths
    Weaknesses
    Return on Investment: Infosys executes new projects with a fair amount of success and generates solid earnings from its current operations.

    Comprehensive Business Solutions: Infosys delivers end-to-end business services in IT, software, business consulting, and business process management.

    Strategic Alliances: To improve its services and business solutions, Infosys has teamed up with significant technological and business companies.

    Low Salary Expenses: The majority of Infosys’ 119 development centres are situated in India, which offers the business high-calibre technical expertise at a much-reduced price.

    Brand Value: Infosys has a credit grade of CRISIL AAA / Stable / CRISIL A1+ and is ranked as the 602nd largest public business in the world, as per the Forbes Global 2000 ranking (rated by CRISIL).
    Putting More of an Emphasis on Product Segments: Infosys has begun to put more emphasis on its platform and product business, but the services segment still accounts for about 94% of its revenue.

    Emerging Markets: Rapid technological advancements are largely to blame for the explosive growth of emerging markets. Infosys is losing out on development opportunities as it doesn’t offer services for the majority of new economies.

    Restricted Market: The majority of the company’s sales are made in North America and Europe. Thus, the business is susceptible to volatility and unequal growth.

    Significant Attrition Rate: Many employees quit Infosys in search of higher-paying positions, more rewarding career possibilities, and study opportunities.
    Opportunities
    Threats
    Cloud Computing: As Cloud Computing has transformed the fundamentals of how we compute, there is a growing demand for cloud-based solutions..

    Acquisition: Investing in tech firms is one strategy to advance technology. Infosys recognised the potential and made significant investments in early-stage technology firms..

    Emphasis on Emerging Markets: Infosys needs to concentrate on developing nations with potential for future growth in the demand for IT services and consulting services..
    Global Market Volatility: As a result of the unstable global financial markets, Infosys is subject to unstable global macroeconomic indices..

    US immigration restrictions: US laws could change, which would affect Infosys’ business and that of other nations that rely heavily on the US market..

    Increasing wages: India’s rising wages are putting pressure on Infosys and other Indian IT companies, which already enjoy a significant competitive edge that lowers labour costs..

    More competition: Competition is escalating exponentially; Infosys is in the same industry as major consulting and technology companies like SAP, Oracle, Salesforce, Wipro, and Capgemini.

    Final Words

    A business can employ a SWOT analysis for general business strategy meetings or meetings focused on a particular department, such as marketing, production, or sales. By doing this, you may decide on a general strategy after conducting a SWOT analysis and observe how it will affect the segments below.

    SWOT is a great planning technique, but with a few drawbacks. Not all of the points within the categories are given the same priority. Also, SWOT does not take into consideration the variations in weight. Thus, it should not be used in isolation. 

    FAQs

    Is SWOT analysis internal or external?

    A SWOT analysis is both internal and external. Internal factors mean strengths and weaknesses, whereas external factors are threats and opportunities.

    Does SWOT analysis have limitations?

    Yes, a SWOT analysis has a few limitations. Namely, it neither prioritizes issues nor provides solutions or alternative decisions. Moreover, it can generate many ideas but not help you select the best.

    What are the benefits of SWOT analysis?

    By addressing weaknesses, thwarting threats, seizing opportunities, leveraging strengths, and developing corporate goals and methods for accomplishing them, a SWOT analysis can help you better understand your company.

    Is SWOT analysis qualitative or quantitative?

    The traditional SWOT analysis is based on qualitative analysis and does not have a way to quantitatively assess the weight or intensity of the SWOT components.

  • What is T distribution?

    What is T distribution?

    The T distribution sometimes referred to as the Student t-distribution, is a probability distribution that is applied in smaller samples with an unknown population variance to estimate population parameters.

    The T distribution is a kind of probability distribution with a bell-shaped pattern resembling the normal distribution but with thicker tails. This distribution will be utilised in place of the normal distribution when the sample size is small. T distributions have broader tails than normal distributions because they are more likely to contain extreme values.

     

     

    What does it mean?

    Typically, the sampling distribution of a statistic tends to follow a normal distribution for large sample sizes. As a result, calculating a z-score (the statistic linked to normal distribution) is simple as long as the population’s standard deviation is known. This helps statisticians to assess probabilities using the sample mean through the normal distribution. But, when the sample size is small, the population’s standard deviation is frequently unknown. In this case, statisticians utilise the distribution of the t statistic. The t distribution, in essence, enables statisticians to do statistical studies on smaller data sets that would otherwise be impossible to analyse using the normal distribution.

    Smaller values of the degrees of freedom parameter of the T distribution result in larger tails, whereas higher values cause the T distribution to resemble a typical standard distribution with “0” as the mean and “1” as the standard deviation. The mean sample, m, and standard sample deviation, d, will differ from M and D due to the sample’s randomness when a sample of n observations is selected from a population with a normally distributed mean, M, and standard deviation, D.

    Formula to Calculate Student’s T Distribution

    Here’s the T distribution formula 

    t = (x̄ – μ) / (s/√n)

    Where,

    x̄ is the sample mean

    μ is the population mean

    s is the standard deviation

    n is the sample size 

    So, we see that the required data are necessary to calculate the T distribution. 

    One requires the population mean, which is the population’s average. One needs the sample mean to determine whether the population mean is authentic and whether the sample picked will represent the same statement. To normalise the value, the t distribution formula subtracts the sample mean from the population mean, divides the result by the standard deviation, and multiplies the result by the square root of the sample size.

    The value can go awry, and we won’t be able to calculate probability because the student’s t distribution has restrictions on how it can arrive at a number and is therefore only relevant for smaller sample sizes. Additionally, one needs to get that value from the student’s t distribution table to calculate probability after arriving at a score.

    Example of T distribution

    Let us consider an example of T distribution where the different variables are provided for consideration. 

    Here, the population mean is 310, 50 is the standard deviation, 16 is the sample size, and 290 is the sample mean 

    We can easily calculate the t-distribution from these values. 

    Value of t = (Sample Mean – Population Mean)/( standard deviation /√Sample size)

    = (290 – 310) / (50 / √16)

    = -1.60

    T-distribution’s significance in finance

    In finance, when we believe an asset return can be viewed as a random variable, we utilise probability distributions to create images that depict our opinion of an asset return’s sensitivity.

    Because it has a little “fatter tail” than the normal distribution, the student’s T distribution is likewise very well-liked. When our sample size is limited, we often use the student’s T. (i.e. less than 30). The left tail in finance stands for the losses. Therefore, we dare underestimate the likelihood of a significant loss if the sample size is limited. We can use the student’s T’s bigger tail in this situation. However, it so happens that the fat tail of this distribution is frequently insufficiently fat.  

    What is the t-distribution table?

    The proportions associated with z-scores are determined using the t-distribution table. This table is used to calculate the ratio for t-statistics. The critical values of the t distribution are displayed in the t-distribution table. The likelihood of t deriving values from a particular value is displayed in the t-distribution table. The area of the t-curve between the ordinates of the t-distribution, the given value, and infinity is the obtained probability.

    Only three values are required to use the t-distribution table:

    • The degrees of freedom of the t-test
    • The number of tails of the t-test, whether one-tailed or two-tailed)
    • The alpha level of the t-test (common choices are 0.01, 0.05, and 0.10)

    T distribution vs normal distribution

    When a normal population distribution is assumed, normal distributions are employed. The normal distribution and the T distribution are similar, but the T distribution has fatter tails. However, both presuppose a population with a normal distribution. The kurtosis of T distributions is larger than that of normal distributions. Kurtosis is a way to figure out how skewed distribution is. With a T distribution as opposed to a normal distribution, there is a higher chance of finding values quite distant from the mean.

    When testing the value of the population mean for any given population, both of the distributions are used. The Z test is used when the standard deviation of the population is known, while the T distribution is used when the parameter of the population is unknown.

    Also, the T distribution is usually used when the number of people in the sample is small (less than 30), while the Z distribution is used when the number of people in the sample is large (more than 30).

    Conclusion

    T distribution is a probability distribution used in various statistical tests for two reasons. One is to test whether observed results are different from what would be expected under the null hypothesis, and the other is to test whether two sets of measurements are drawn from the same parent population, often referred to as paired testing.

  • Terminal Value: Definition, Formula, Calculation

    Terminal Value: Definition, Formula, Calculation

    Suppose your friend has invested in a company’s stocks, made a handsome profit through it, and you also got inspired and motivated by his success in stocks. Therefore, you also decided to invest in the same firm’s stock for a long time without knowing about the company. You made a profit for a few months, and you thought everything was on track, but after a few months, you started to face setbacks in your stock investment and lost a significant portion of it. Now, most chances would be that you will never invest in stocks in the future.

    The learning is that earning profits in the stock market will be difficult for you without having technical knowledge and the company’s long-term growth potential and vision. To make this easier for you, this brief guide will reflect on the importance and usage of the term Terminal Value in understanding the long-term growth potential of a corporate and the consequent profits derived thereof. 

    Terminal Value Meaning

    Forecasting has been a basic human instinct from the beginning of human civilization, but it gets murkier as time progresses. It holds even in the financial world as well, mainly when estimating the company’s future cash flows.

    So, Terminal Value is the value of an asset, business, or project beyond the forecasted period, when the future cash flows can be estimated. The Terminal Value here assumes that business will grow at a set growth rate forever after the forecasted period and often comprises a large percentage of the total assessed value. The Terminal Value is also known as the”continuing value” or “horizon value.”

    Now let’s check out how to calculate the Terminal Value with the help of a formula.

    Terminal Value Formula & Calculation

    Formula:

    Terminal Value is mathematically represented as:-

    Terminal Value= (FCF*(1+g))/d-g

    FCF=Forecasted Cash Flow

    d= discount rate

    g= terminal growth value.

    Calculation:

    Now let’s check out the following step-by-step process to calculate the Terminal Value:

    There are three ways to calculate the Terminal Value of the company. The first two assume that the company will remain on a going concern basis while estimating TV. But the third approach assumes that a large corporation will take over the firm. Let’s look at this detail one by one.

    1- Perpetuity Growth Model

    This method is also known as the Gordon Growth Method. This method assumes that the company’s growth will continue (at a stable growth rate), and the return on capital will be more than the cost of capital. In this method, we discount the Free cash flow to the firm beyond the projected years to find the terminal value.

    The formula to calculate the Terminal Value through Perpetuity Growth Model is:

    Terminal Value= FCFF5*(1+growth rate)/(WACC-growth rate).

    2- Exit Multiple Method.

    An exit multiple calculates the Terminal Value in discounted cash flow formula to value a business. This method can determine the value of the business at the end of the project. The assumption is based on the existing public market valuation of comparable companies. Moreover, the most common multiple used in this method is EV/EBITDA or EV/EBIT.

    This method assumes that a market with multiple bases is a fair way to value a business. Here, the firm’s value is obtained by multiplying financial metrics such as EBITDA or EBIT by a factor obtained from comparable companies. An appropriate range of multiples can be generated by looking at the recent acquisition in the market.

    The multiple obtained here is then multiplied by the project EBIT or EBITDA in year N (the final year of the projected period) to give future value at the end of year n. The company’s terminal value or the future value is then discounted back using the company’s Weighted average cost of capital. 

    The value obtained here is then added to the Present value of FCC to determine the implied enterprise value. For the cyclical businesses where the business fluctuates along with the variation in the economy, here we use average EBIT or EBITDA.

    Terminal Value= EBITDAn * Exit Multiple.    

    3- No Growth Perpetuity Method:

    The method used in industries with a lot of competition and opportunities to make excess returns tend to be zero. In the No Growth Perpetuity Method formula, the growth rate equals zero, meaning the investment return will equal the cost of capital.

    Terminal Value Formula= FCFF6*WACC

    Example:

    Now, let’s understand the concept through the example of Adani Group. The Group wants to estimate the value of one of its subsidiaries, Adani Power. Its financial team has decided to use the Perpetuity growth method to estimate the future value of the subsidiary. The economic team put the growth rate at 3% in perpetuity per annum, and free cash flow was estimated to be Rs. 150,000,000 at the end of the forecasted fifth year. The WACC or discount rate is 10%.

    From the data given above, we can identify the following:

    Terminal Value= unknown

    Forecasted free cash flow= Rs. 150,000,000

    Growth rate=3%

    Discount rate 10%

    Now we can substitute the value by using a formula.

    Terminal Value= (FCF*(1+g))/d-g

    TV= 150,000,000(1+(3/100))/10/100-3/100

    Terminal Value= Rs. 58,200,000

    Limitations:

    • The perpetuity growth model assumes the discount rate and growth rate, and even the slightest inaccuracy in these rates can lead to improper results. Also, these rates change yearly, and this model does not take care of these aspects.
    • The growth rate can be higher than the discount rate or weighted average cost of capital for some time. In these circumstances, the Terminal Value calculation gives negative or wrong results. Also, companies can show a negative free cash flow; hence the data can go wrong with the perpetuity growth model.
    • In the Exit Multiple Method, the multiples change with time. Hence, choosing a correct multiple becomes a challenge here.

    Conclusion:

    Despite all its flaws and limitations, Terminal Value is still an easy and straightforward way to check the company’s future forecast. The Terminal Value is very important in discounted cash flow of the company as it accounts for a considerable 60-80% of the total valuation. So here, you should pay special attention to the growth and discount rates.



  • What is venture capital & how does it function?

    What is venture capital & how does it function?

    Venture capital is a type of private equity & a type of financing that investors invest in start-up firms & small enterprises that are supposed to have continuing development & expansion possibilities. 

    Although venture capital emphasizes monetarily, it is also provided in other categories, such as supervisory and technical expertise. Venture capital does not necessarily appear in the company’s initial stages but can be utilized at different phases when the company evolves.

    Venture capital has become the most used form of funding over the years. Sources such as venture capital funds, investors, financial entities, and investment banks play a key role in providing venture capital. In venture capital funding, most of the company’s ownership is created and sold to investors through individual limited partnerships that venture capital firms establish.

    Features of venture capital

    Risk factor

    Venture capital requires funding by individuals into new ventures that are in the initial stage of the company, and that, of course, is very uncertain to succeed in the future company goals and objectives. The return on investment depends entirely on the company’s failure or success. 

    Lack of liquidity

    Investors cannot withdraw venture capital investments in the short run. They are essentially long-run investments either in the form of convertible securities or loans.

    Long term Investments

    Venture capital is meant for long-term monetary relations, which assists companies in their growth and expansion in the initial stages of the business. It is initiated by buying equity capital that offers returns in the long term. It’s not recommended for entities who are interested in getting profits in a short span of time. 

    Financing new companies

    It involves funding finances for start-up companies which are difficult in their early stages. Various investors easily attract companies with a unique purpose or great potential for higher returns.

    Funding venture capital

    Pre-Seed Stage

    Pre-seed stage capital is when capital is provided to an entrepreneur to help them develop an idea.

    Seed-stage

    Seed stage capital is when capital is provided to help an entrepreneur (or potential entrepreneur) develop their idea into an early-stage product. This is a small amount that a businessperson obtains for the purpose of being qualified for start-up credit.

    Early-stage

    Early-stage capital is when capital supports product development, marketing, commercial manufacturing, and sales. This stage promotes commercial manufacturing, sales & development, and product development.

    Later-stage

    Later stage capital is when capital is the venture capital provided after the business generates revenues but before an Initial Public Offering (IPO). Major expansions, product improvements, huge marketing campaigns, and M & A require this type of capital.

    Parameters
    Angel Investors
    Venture capital
    Private Equity
    Investment Plan
    They are more flexible in whom they invest because they are investing their personal money. By exiting an IPO or merger & acquisition deal, angel investors expect a return on investments.
    A fund theory & fiduciary responsibility are involved in venture capitalists’ LPs. Thus, there is less flexibility in how they invest. Like Angel investors, VCs expect ROI through exiting an IPO or M&A deal.
    Private equity can change the business- they can buy the company, expand its operations & then exit the firm through reselling the same, mostly for profit.
    Company Stage
    They are the early investors in a start-up company (pre-seed & seed). They fund even less or even no customers at all.
    VCs are prime investors in companies whose technology or product is functioning and who have a few or more customers. They support you to evolve your company to the next level.
    They Invest in recognized and established companies. Their role comes after raising funds from venture capital. They help companies struggling with their operational incompetence.
    Investors
    They are wealthy & attributed individuals investing their personal money in various start-up companies
    General partners are investors who work for VCs & invest in other Limited Partner’s funds which could be sovereign wealth funds, well-off family trusts, pensions funds, etc.
    They invest directly in an established private company. Unlike VCs & Angel investors, they don’t usually fund startup companies.
    Risk Degree
    They stand a chance of higher risk since they invest in startups with no customers or products or technology.
    VCs invest in companies that have already passed the pre-seed or seed stage. Thus, they have lower risks of loss than angel investors.
    They have both the lowest returns on investments and risk since they only aid established companies on the operational front. They have the flexibility to sell the company for a profit.

    Pros & cons of venture capital

    Advantages

    • Large capital can be raised.
    • Managerial & technical expertise are offered.
    • Support is provided to manage the risk involved.
    • Great exposure to learn and grow.
    • Future raising funds is possible
    • Venture capitalists are mostly reliable
    • They help with hiring the best resources to build a team

    555Startup companies usually fail to provide security as collateral. Though, VC doesn’t require any security to provide any funds.

    Disadvantages

    VC is a type of equity capital that is higher in costs than debt-equity.

    • Since the large chunk of the company is sold, the ownership is reduced.
    • A traditional reporting structure is required.
    • Obtaining investors is time intensive and can lead to diverting from the business.
    • Underachievers can lose their business.
    • Leverage negotiations are occasional.
    • The business is anticipated to grow speedily.
    • The performance schedule plays a key role when it comes to releasing funds.

    Examples of venture capital

    Google

    Most popular, GV (Google Ventures) invests in various industries, including hardware, software, biotech, health care, customer care, & clean tech. They are among the highest funding investors who are up to millions of dollars throughout the different stages of a company and its need for funds.

    Salesforce

    Based in San Francisco- California, Salesforce was established in 2009 and is a corporate venture arm of Salesforce.com. They invest in cloud-based & tech companies.

  • Weighted Mean Formula – Calculation with Examples

    Weighted Mean Formula – Calculation with Examples

    An extensive collection of numbers is represented by a single number in a simple average. But if items in the collection have different levels of importance associated with them, it might not be an accurate portrayal of an average.

    In this situation, a weighted average is more accurate than a simple average. This is because each data point’s value is multiplied by the allotted weight in a weighted average before being added together and divided by the total number of data points. Thus, a weighted average can increase the accuracy of the data.

    What Is a Weighted Mean?

    Most frequently, a weighted average is calculated to balance the frequency of the values in a data set. For instance, a survey may have enough responses from all age groups to be deemed statistically valid, but the 18–34 age group may receive the least amount of responses compared to the proportion of the population that they make up. The survey team may factor in the data from respondents who are 18 to 34 years old to ensure that their opinions are well represented.

    Values in a data set, however, may be weighted for factors other than frequency of occurrence. The mark for skill might be given more weight than the other grades, for instance, if students in a dancing class are graded on their ability, attendance, and politeness

    Uses of a Weighted Mean

    Weighted means are useful in a wide variety of scenarios in our daily life. Some of the common uses are as follows:

    The weighted mean is used by students to determine their percentage grade in a course. In this scenario, the student must multiply the weighted average of all course assessments (such as assignments, exams, projects, etc.) by the corresponding grade that was earned in each category.

    It is employed in descriptive statistical analysis, such as the computation of index numbers. For instance, the weighted average approach is used to calculate stock market indices like the Nifty or BSE Sensex. It can also be used in physics to determine an object’s centre of mass and moment of inertia.

    Business owners can also benefit from comparing the average costs of items bought from various suppliers, where the weight indicates the quantity of goods purchased. It provides a clearer picture of their spending.

    A customer’s decision to purchase a product or not is influenced by the product’s quality, understanding of the product, price, and service provided by the franchise. Each criterion is given a weight by the customer, who then determines the weighted average. This will enable him to choose the goods more wisely.

    The interviewer evaluates a candidate’s personality, work talents, educational background, and teamwork ability to hire them for a position. Different weights (importance levels) are assigned based on the profile before the ultimate choice is decided.

    What Is the Formula for Weighted Mean?

    The formula to calculate the weighted mean is as follows:

     

    Here, W denotes the weighted average, n denotes the number of terms to be averaged, wi denotes the weights applied to x values, and xi denotes the data values to be averaged.

    Calculating weighted mean using formula

    A trader purchases 20,000 units of a product at ₹1 each, 15,000 at ₹2 each and 10,000 at ₹3 each. We calculate the following using the units as the weight and the overall quantity of units as the total of all weights:

    [1(20,000) + 2(15,000) + 3(10,000)] / (20,000 + 15,000 + 10,000) = (20,000 + 30,000 + 30,000) / (20,000 + 15,000 + 10,000) = 80,000 / 45,000 = 1.78

    This equals a weighted average cost of ₹1.78 per unit.

    Calculating weighted mean through excel

    1. Add a column to your spreadsheet that contains the weight for each data point after entering your data.

       

    1. Type =SUMPRODUCT(X:X,X:X)/SUM(X:X) and enter the values.

    1. Click enter to obtain your results.

       

    How to Calculate Weighted Mean?

    Suppose a firm conducts a survey of 4 shops to determine the average electricity usage in each shop per day in percentage. The first shop has one AC, which uses electricity for 40% of the day; the second shop has two ACs, which use electricity for 50% of the day; the third shop has three ACs, which use electricity for 60% of the day, and the fourth shop has four ACs, which use electricity for 70% of the day. Calculate the mean electricity usage of ACs per shop for each day.

    Solution: The weighted arithmetic mean can be calculated using the steps listed below. 

    Number of ACs in the shop (xi)
    Usage percentage in a day (wi)
    1
    40
    2
    50
    3
    60
    4
    70

    Step 1: First, assign a weight to each value in the dataset.

    x1 = 1, w1 = 40

    x2 = 2, w2 = 50

    x3 = 3, w3 = 60

    x4 = 4, w4 = 70

    Step 2: Calculate the numerator of the weighted mean formula.

    To calculate it, multiply each sample by its weight and then add the products to obtain the final value

    = 1 x 40 + 2 x 50 + 3 x 60 + 4 x 70

    = 40 + 100 + 180 + 280

    = 600

    Step 3: Then, calculate the denominator of the weighted mean formula by adding their weights.

    = 40 + 50 + 60 + 70

    = 220

    Step 4: At last, divide the numerator by the denominator.

    = 600/220

    = 2.7273

    Hence, the mean electricity usage is 2.7273.

    Note: An outlier in the data can readily change the weighted mean. We cannot rely on the weighted mean if our data set contains extremely high or extremely low values.

    Key Takeaway

    The weighted average considers the relative frequency or relevance of particular variables in a data set.

    Sometimes a weighted average is more precise than a basic average.

    Each data point’s value is multiplied by the allotted weight in a weighted average before being added together and divided by the total number of data points. Because of this, a weighted average can increase the accuracy of the data.

    Investors in stocks use a weighted average to keep track of the cost basis of the shares they have acquired over time.