This page is a compilation of blog sections we have around this keyword. Each header is linked to the original blog. Each link in Italic is a link to another keyword. Since our content corner has now more than 4,500,000 articles, readers were asking for a feature that allows them to read/discover blogs that revolve around certain keywords.

+ Free Help and discounts from FasterCapital!
Become a partner

The keyword january 2021 has 436 sections. Narrow your search by selecting any of the keywords below:

1.Introduction to Price Index[Original Blog]

A price index is a measure of the average level of prices of a basket of goods and services in a given period of time, relative to a base period. Price indices are useful tools for measuring and comparing the changes in prices over time and across regions. They can help us understand how inflation affects the purchasing power of money, how the cost of living varies for different groups of consumers, and how the competitiveness of different economies changes over time. In this section, we will introduce the concept of price index, explain how it is calculated, and discuss some of the advantages and limitations of using price indices.

To construct a price index, we need to follow these steps:

1. Select a basket of goods and services that represents the consumption pattern of a specific group of consumers, such as urban households, rural households, or industrial producers. The basket should include items that are commonly purchased and consumed by the group, and reflect their preferences and tastes. The basket should also be updated periodically to account for changes in consumption patterns over time.

2. Assign weights to each item in the basket, based on their relative importance or share in the total expenditure of the group. The weights can be derived from surveys, national accounts, or other sources of data. The weights should also be updated periodically to account for changes in relative prices and preferences over time.

3. Collect the prices of each item in the basket for the base period and the current period. The base period is a reference point that is used to compare the changes in prices over time. The current period is the period for which we want to measure the price index. The prices should be collected from representative and reliable sources, such as market surveys, official statistics, or online platforms. The prices should also be adjusted for quality changes, taxes, subsidies, and other factors that may affect the comparability of prices over time.

4. Calculate the price index for the current period, relative to the base period, using a formula that aggregates the prices and weights of each item in the basket. There are different formulas that can be used to calculate price indices, such as the Laspeyres index, the Paasche index, the Fisher index, or the Törnqvist index. Each formula has its own advantages and limitations, depending on the purpose and scope of the analysis. The choice of formula may affect the value and interpretation of the price index.

For example, suppose we want to construct a price index for a basket of three items: bread, milk, and eggs. The basket represents the consumption pattern of an average urban household in Country A. The base period is January 2020, and the current period is January 2021. The weights of the items in the basket are 30%, 40%, and 30%, respectively, based on their share in the total expenditure of the household. The prices of the items in the base period and the current period are as follows:

| Item | Price in January 2020 | Price in January 2021 |

| Bread | $2.00 | $2.20 |

| Milk | $3.00 | $3.30 |

| Eggs | $4.00 | $4.40 |

Using the Laspeyres index formula, which uses the base period weights and the current period prices, we can calculate the price index for January 2021 as:

\text{Laspeyres index} = \frac{\sum_{i=1}^n w_i P_i^c}{\sum_{i=1}^n w_i P_i^b} \times 100 = \frac{(0.3 \times 2.20) + (0.4 \times 3.30) + (0.3 \times 4.40)}{(0.3 \times 2.00) + (0.4 \times 3.00) + (0.3 \times 4.00)} \times 100 = 110

This means that the average level of prices of the basket of goods and services in January 2021 is 10% higher than the average level of prices in January 2020. In other words, the inflation rate for the urban household in Country A between January 2020 and January 2021 is 10%.

Using the Paasche index formula, which uses the current period weights and the current period prices, we can calculate the price index for January 2021 as:

\text{Paasche index} = \frac{\sum_{i=1}^n w_i^c P_i^c}{\sum_{i=1}^n w_i^c P_i^b} \times 100 = \frac{(0.28 \times 2.20) + (0.38 \times 3.30) + (0.34 \times 4.40)}{(0.28 \times 2.00) + (0.38 \times 3.00) + (0.34 \times 4.00)} \times 100 = 109.09

This means that the average level of prices of the basket of goods and services in January 2021 is 9.09% higher than the average level of prices in January 2020, using the current period weights. The current period weights are calculated by dividing the expenditure on each item in the current period by the total expenditure in the current period. For example, the weight of bread in the current period is:

W_{\text{bread}}^c = \frac{P_{\text{bread}}^c Q_{\text{bread}}^c}{\sum_{i=1}^n P_i^c Q_i^c} = \frac{2.20 \times 1}{(2.20 \times 1) + (3.30 \times 1) + (4.40 \times 1)} = 0.28

The Paasche index formula assumes that the quantity of each item in the basket is fixed at the current period level, and does not change with the changes in prices. This may not reflect the actual behavior of consumers, who may adjust their consumption patterns in response to price changes. For example, if the price of bread increases, consumers may buy less bread and more of other items, such as milk or eggs. The Paasche index formula does not capture this substitution effect, and may underestimate the inflation rate.

Using the Fisher index formula, which is the geometric mean of the Laspeyres index and the Paasche index, we can calculate the price index for January 2021 as:

\text{Fisher index} = \sqrt{\text{Laspeyres index} \times \text{Paasche index}} = \sqrt{110 \times 109.09} = 109.54

This means that the average level of prices of the basket of goods and services in January 2021 is 9.54% higher than the average level of prices in January 2020, using the Fisher index. The Fisher index formula is considered to be a more accurate and consistent measure of price changes, as it accounts for both the base period and the current period weights, and avoids the bias of the Laspeyres index and the Paasche index.

Some of the advantages of using price indices are:

- They can help us measure the changes in the purchasing power of money over time. For example, if the price index increases by 10%, this means that the same amount of money can buy 10% less goods and services than before. This implies that the value of money has decreased by 10%.

- They can help us compare the cost of living across different regions or countries. For example, if the price index in Country A is 120, and the price index in Country B is 100, this means that the average level of prices in Country A is 20% higher than the average level of prices in Country B. This implies that the cost of living in Country A is higher than the cost of living in Country B.

- They can help us adjust nominal values for inflation. For example, if the nominal GDP of a country in 2020 is $1,000 billion, and the price index in 2020 is 110, we can calculate the real GDP of the country in 2020 by dividing the nominal GDP by the price index and multiplying by 100. This gives us:

\text{Real GDP in 2020} = \frac{\text{Nominal GDP in 2020}}{ ext{Price index in 2020}} \times 100 = \frac{1,000}{110} \times 100 = 909.09

This means that the real GDP of the country in 2020 is $909.09 billion, which is the value of the output of the country in 2020, measured in constant prices of the base period.

Some of the limitations of using price indices are:

- They may not reflect the actual consumption patterns of different groups of consumers. For example, the basket of goods and services that represents the average urban household may not represent the consumption pattern of a low-income household, a high-income household, or a rural household. Therefore, the price index may not capture the true impact of inflation on different groups of consumers.

- They may not account for the quality changes of goods and services over time. For example, if the quality of a good or service improves over time, but the price remains the same, the price index may not reflect the increase in the value of the good or service.


2.Exploring the Top Performers of 2021[Original Blog]

As the worlds fascination with cryptocurrency grows, so does the number of alternative coins, or altcoins, that are emerging in the market. While Bitcoin remains the most popular cryptocurrency, other digital currencies are gaining traction as well. The rise of altcoins has sparked a new wave of investment opportunities for traders and investors alike. In this section, we will explore the top-performing altcoins of 2021 and unveil the potential behind these digital currencies. We will also discuss the insights from different points of views, including financial experts, cryptocurrency enthusiasts, and traders.

Here are some of the top performers of 2021:

1. Ethereum (ETH) Ethereum is the second-largest cryptocurrency by market cap and has been gaining popularity due to its unique blockchain technology, which allows for the creation of decentralized applications (dApps). Ethereum has seen a surge in value over the past year, increasing by over 700% since January 2021.

2. Binance Coin (BNB) Binance Coin is the native token of the Binance exchange, which is the largest cryptocurrency exchange by trading volume. Binance Coin has seen significant growth over the past year, with its value increasing by over 1,000% since January 2021.

3. Cardano (ADA) Cardano is a third-generation cryptocurrency that aims to solve some of the scalability and sustainability issues that are present in other digital currencies. Cardano has seen a surge in value over the past year, increasing by over 1,500% since January 2021.

4. Dogecoin (DOGE) Dogecoin was created as a joke in 2013 but has recently gained popularity due to endorsements from celebrities such as Elon Musk. Despite its initial purpose, Dogecoin has seen a surge in value over the past year, increasing by over 6,000% since January 2021.

These top-performing altcoins have shown incredible potential for growth and have become a promising investment opportunity for traders and investors. With the rise of altcoins, the cryptocurrency market is becoming more diverse, and it is important to stay informed about the potential opportunities and risks associated with investing in digital currencies.


3.Real-life Examples of Breakout Pullback Trades[Original Blog]

Breakout pullback trades are a popular trading strategy that can help traders maximize their gains. This strategy involves identifying a breakout in a stock's price and then waiting for a pullback to enter the trade. The pullback provides an opportunity to enter the trade at a lower price, which can increase the potential for profits. In this section, we will explore real-life examples of breakout pullback trades and how they can be executed successfully.

1. Apple Inc.

Apple Inc. (AAPL) is a well-known technology company that has experienced significant price movements over the years. In September 2020, the stock experienced a breakout when it surpassed its previous all-time high of $137.98. This breakout signaled a potential uptrend, and traders who identified this breakout could have entered the trade at a lower price during the subsequent pullback. The pullback occurred in October 2020, when the stock dropped to $115.98, providing traders with a buying opportunity. The stock has since continued to climb, reaching a new all-time high of $156.69 in January 2021.

2. Amazon.com Inc.

Amazon.com Inc. (AMZN) is another well-known company that has experienced significant price movements. In February 2020, the stock experienced a breakout when it surpassed its previous all-time high of $2,170.22. The subsequent pullback occurred in March 2020, when the stock dropped to $1,626.03. Traders who identified this breakout could have entered the trade at a lower price during the pullback, which would have resulted in significant gains. The stock has since continued to climb, reaching a new all-time high of $3,552.25 in September 2020.

3. Tesla Inc.

Tesla Inc. (TSLA) is a popular electric vehicle company that has experienced significant price movements in recent years. In February 2020, the stock experienced a breakout when it surpassed its previous all-time high of $968.99. The subsequent pullback occurred in March 2020, when the stock dropped to $361.22. Traders who identified this breakout could have entered the trade during the pullback, which would have resulted in significant gains. The stock has since continued to climb, reaching a new all-time high of $900.40 in January 2021.

4. General Electric Company

General Electric Company (GE) is a multinational conglomerate that has experienced significant price movements in recent years. In November 2019, the stock experienced a breakout when it surpassed its previous all-time high of $13.26. The subsequent pullback occurred in March 2020, when the stock dropped to $5.48. Traders who identified this breakout could have entered the trade during the pullback, which would have resulted in significant gains. The stock has since continued to climb, reaching a high of $14.42 in January 2021.

5. Coca-Cola Co.

Coca-Cola Co. (KO) is a well-known beverage company that has experienced significant price movements over the years. In February 2020, the stock experienced a breakout when it surpassed its previous all-time high of $60.13. The subsequent pullback occurred in March 2020, when the stock dropped to $36.27. Traders who identified this breakout could have entered the trade during the pullback, which would have resulted in significant gains. The stock has since continued to climb, reaching a high of $55.68 in January 2021.

Breakout pullback trades can be an effective trading strategy for maximizing gains. By identifying breakouts and waiting for pullbacks, traders can enter trades at lower prices, increasing their potential for profits. The real-life examples provided above illustrate how this strategy can be executed successfully. However, it is important to conduct thorough research and analysis before entering any trade to minimize risk and maximize gains.

Real life Examples of Breakout Pullback Trades - Breakout pullbacks: Maximizing Gains with Breakout Pullbacks

Real life Examples of Breakout Pullback Trades - Breakout pullbacks: Maximizing Gains with Breakout Pullbacks


4.Gauging Risk Appetite through Market Volatility[Original Blog]

One of the ways to measure the risk appetite of investors is to look at the market volatility, which reflects the degree of uncertainty and fluctuations in the prices of financial assets. Market volatility can be influenced by various factors, such as economic news, geopolitical events, natural disasters, and investor sentiment. In general, higher volatility indicates lower risk appetite, as investors demand higher returns for holding risky assets, and lower volatility indicates higher risk appetite, as investors are more willing to take on risk for lower returns. In this section, we will explore how market volatility can be used to gauge the risk appetite of investors, and what are some of the indicators and tools that can help us do so. We will also discuss some of the challenges and limitations of using market volatility as a measure of risk appetite.

Some of the points that we will cover in this section are:

1. How to measure market volatility? There are different ways to measure the volatility of a market, such as using historical data, implied volatility, or model-based estimates. Historical volatility is calculated based on the past returns of an asset or a market index, and reflects the realized variability of prices over a given period of time. Implied volatility is derived from the prices of options contracts, and reflects the market's expectation of future volatility over the life of the option. Model-based estimates are based on statistical or econometric models that try to capture the dynamics of volatility and its determinants, such as volatility clustering, mean-reversion, and leverage effects. Each of these methods has its own advantages and disadvantages, and they may not always agree with each other. For example, implied volatility may be higher or lower than historical volatility, depending on the market sentiment and the demand and supply of options.

2. What are some of the indicators of market volatility? There are various indicators that can be used to monitor the volatility of different markets, such as equities, bonds, currencies, and commodities. Some of the most widely used indicators are:

- The VIX index: The VIX index, also known as the fear index, is a measure of the implied volatility of the S&P 500 index options, and reflects the market's expectation of the 30-day volatility of the US stock market. The VIX index is calculated by the chicago Board Options exchange (CBOE), and is based on a weighted average of the prices of near-term and next-term put and call options on the S&P 500 index. The VIX index is often used as a proxy for the overall market volatility and risk appetite, as it tends to rise when the market is fearful and fall when the market is confident. A high VIX index indicates low risk appetite, and a low VIX index indicates high risk appetite. For example, the VIX index spiked to over 80 in March 2020, during the peak of the COVID-19 pandemic, indicating extreme fear and uncertainty in the market, and then gradually declined to below 20 in January 2021, as the market recovered and became more optimistic.

- The MOVE index: The MOVE index, also known as the Merrill Lynch Option Volatility Estimate index, is a measure of the implied volatility of the US Treasury options, and reflects the market's expectation of the future volatility of the US bond market. The MOVE index is calculated by Bank of America Merrill Lynch, and is based on a weighted average of the prices of options on 2-year, 5-year, 10-year, and 30-year Treasury securities. The MOVE index is often used as a proxy for the interest rate volatility and risk appetite, as it tends to rise when the market expects large fluctuations in the interest rates and fall when the market expects stable interest rates. A high MOVE index indicates low risk appetite, and a low MOVE index indicates high risk appetite. For example, the MOVE index surged to over 160 in March 2020, during the onset of the COVID-19 crisis, indicating high uncertainty and volatility in the bond market, and then dropped to below 50 in January 2021, as the market stabilized and the Federal Reserve maintained its accommodative monetary policy.

- The CVIX index: The CVIX index, also known as the CBOE/CME FX Euro Volatility Index, is a measure of the implied volatility of the eur/USD currency pair options, and reflects the market's expectation of the 30-day volatility of the exchange rate between the euro and the US dollar. The CVIX index is calculated by the CBOE and the CME Group, and is based on a weighted average of the prices of near-term and next-term put and call options on the eur/USD currency pair. The CVIX index is often used as a proxy for the currency volatility and risk appetite, as it tends to rise when the market anticipates large movements in the exchange rate and fall when the market anticipates stable exchange rate. A high CVIX index indicates low risk appetite, and a low CVIX index indicates high risk appetite. For example, the CVIX index reached over 15 in March 2020, during the height of the COVID-19 turmoil, indicating high volatility and risk aversion in the currency market, and then declined to below 6 in January 2021, as the market calmed down and the euro appreciated against the dollar.

- The OVX index: The OVX index, also known as the CBOE crude Oil etf Volatility Index, is a measure of the implied volatility of the USO oil fund options, and reflects the market's expectation of the 30-day volatility of the crude oil prices. The OVX index is calculated by the CBOE, and is based on a weighted average of the prices of near-term and next-term put and call options on the USO oil fund, which tracks the performance of the West Texas Intermediate (WTI) crude oil. The OVX index is often used as a proxy for the commodity volatility and risk appetite, as it tends to rise when the market expects large swings in the oil prices and fall when the market expects stable oil prices. A high OVX index indicates low risk appetite, and a low OVX index indicates high risk appetite. For example, the OVX index soared to over 300 in April 2020, during the unprecedented collapse of the oil prices, indicating extreme volatility and panic in the oil market, and then dropped to below 40 in January 2021, as the oil prices recovered and the market became more balanced.

3. How to use market volatility to gauge risk appetite? Market volatility can be used to gauge the risk appetite of investors by comparing the volatility of different markets, or by comparing the volatility of a market with its historical average or range. For example, one can compare the VIX index with the MOVE index, or the CVIX index with the OVX index, to see which market is more volatile and which market is more attractive for investors. Alternatively, one can compare the current level of the VIX index with its long-term average of around 20, or its historical range of 10 to 80, to see if the market is more fearful or more confident than usual. However, using market volatility to gauge risk appetite is not a straightforward or foolproof method, as there are some challenges and limitations that need to be considered, such as:

- The relationship between volatility and risk appetite is not linear or stable: The relationship between volatility and risk appetite is not always linear or stable, as different levels of volatility may have different implications for the market sentiment and behavior. For instance, a moderate increase in volatility may indicate a healthy correction or a diversification opportunity, while a sharp spike in volatility may indicate a panic or a crisis. Similarly, a moderate decrease in volatility may indicate a calm or a complacency, while a sharp drop in volatility may indicate a euphoria or a bubble. Therefore, one needs to take into account the magnitude and the direction of the change in volatility, as well as the context and the cause of the change, when using volatility to gauge risk appetite.

- The volatility of a market may not reflect the true risk of the market: The volatility of a market may not always reflect the true risk of the market, as there may be some factors that distort or mask the volatility of the market. For example, the volatility of a market may be artificially suppressed or inflated by the intervention or the manipulation of the authorities or the market participants, such as the central banks, the regulators, the hedge funds, or the speculators. Alternatively, the volatility of a market may be temporarily reduced or increased by the liquidity or the illiquidity of the market, such as the availability or the scarcity of the buyers or the sellers, or the ease or the difficulty of the trading or the hedging. Therefore, one needs to be aware of the potential biases or noises that may affect the volatility of the market, and adjust the volatility measure accordingly, when using volatility to gauge risk appetite.

- The volatility of a market may not capture the full spectrum of the market risk: The volatility of a market may not always capture the full spectrum of the market risk, as there may be some aspects or dimensions of the market risk that are not reflected or incorporated in the volatility measure. For example, the volatility of a market may not account for the tail risk or the extreme risk of the market, such as the occurrence or the impact of the rare or the unforeseen events, or the black swans or the grey rhinos. Alternatively, the volatility of a market may not consider the correlation or the contagion risk of the market, such as the interdependence or the spillover of the risk across different markets, or the systemic or the domino effect of the risk. Therefore, one needs to supplement the volatility measure with other indicators or tools that can capture the other aspects or dimensions of the market risk, when using volatility to gauge risk appetite.

Market volatility can be a useful and powerful tool to gauge the risk appetite of

OSZAR »