Do you ever wonder how much of a return on an investment you would have made if you invested money into a stock or major index? In this post, I’ll show you how you can create a template to calculate those returns in Google Sheets. You can also download the one that I’ve made.
Setting up the inputs
To make a template like this versatile and dynamic, it’s important to create cells for inputs so that the values can easily be updated. One cell should be for the investment amount. Another should be for the index or ticker, and the last option should be for the # of years in the past that you want to look back.
In Google Sheets, if you want to lookup the values for the S&P 500, Nasdaq, or Dow Jones, you’ll need to use the following symbols:
Dow Jones: .DJI
Nasdaq: .IXIC
S&P 500: .INX
There is a period before each symbol. Regular stock symbols, such as GOOG for Alphabet are entered normally without any periods. But for an index, you need to add a period before the symbol. And as you can see from the symbols, they aren’t obvious as the S&P 500 uses INX while for the Nasdaq, it’s IXIC. Rather than entering in these symbols, it may be easier create a lookup list, which you can then use in data validation. For example, I have the list of related values posted in E1:F3
I can then use this lookup so that the user selects Dow Jones, Nasdaq, or S&P 500 and then the corresponding symbol will populate:
To create a drop-down list in Google Sheets, select a cell and click on Data and press Data Validation. From there, you can either manually enter your options, or you can reference a named range. In my example, I’ve referenced a named range called Index, which holds these values.
Next, there’s the field for the # of years you want to look back. This will be used in calculating the stock or index’s previous value. That is the final input that I will use for this template:
Calculating the return
To calculate the return from the investment, we need today’s value and the value from the past. To get the current value is simple and just requires the following formula:
=GOOGLEFINANCE(symbol,”price”)
In my file, I’ve created a named range called symbol which relates to the .INX value in the above screenshot. When no dates are entered, the formula will pull in the latest value for the symbol.
To get the previous value takes a bit more work. The formula will start off the same but I need to adjust the date so that it factors in the number of years I want to go back. To do this, I will use the DATE function and specify the year, month, and date values. Assuming I want the exact same date and only adjust the year, here is how I would adjust the formula:
In this formula, yearsback is the named range relating to the # of years I want to go back. In my example, it is set to 10. By adjusting the year argument in the date function by the number of years I want to go back, that will adjust the year and nothing else. The TODAY function returns the current date and acts as a starting point. For the last argument in the GOOGLEFINANCE function I set the value to 1, since I only want the value from a single day.
The formula will now grab the second row and second column, which relates to the value I want. Now that I have my current previous values, I can calculate the return. For this calculation, I only need to take the current value, divide it by the previous value, and subtract 1:
=currentvalue/previousvalue-1
Here again, I’m using named ranges to easily refer to those values and so it’s easy to see what I’m referencing. The result of this formula is a % change.
Lastly, I need to calculate the value of the investment today. This involves taking the original investment and multiplying it by 1 plus the return. This formula uses named ranges once more:
=originalinvestment*(pctreturn+1)
Here’s what my spreadsheet looks like now when I calculate what a $10,000 investment in the S&P 500 would be worth 10 years ago today:
You can see both the % return as well as the dollar amount of that investment. With the cells highlighted in yellow and a drop-down option, it makes it easy to see the fields that can be adjusted. If you prefer to use this calculation for just stocks, you can do away with the lookup and instead just enter the ticker symbol directly. If you’d like to download my version of the template, you can access a copy of it here.
If you liked this post on How Much Money Would You Have if You Invested in the S&P 500 10, 20, and 30 Years Ago, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow me on Twitter and YouTube. Also, please consider buying me a coffee if you find my website helpful and would like to support it.
A popular investing strategy is dollar-cost averaging. With dollar-cost averaging, people invest a fixed amount of money into an investment on a recurring basis, regardless of whether the price has gone up or down. In this post, I’ll go over how it works, the benefits and disadvantages of dollar-cost averaging, along with a step-by-step guide on how to do it in Excel, using the stock market as an example.
What is dollar-cost averaging?
Dollar-cost averaging is an investment technique that takes the emotional aspect out of investing by spreading purchases over regular intervals, typically on a monthly basis. This means that regardless of market conditions or how you feel about an investment, you invest the same fixed-dollar amount on a recurring basis. When a stock’s price is low, that means you can buy more shares since they are cheaper. And when the price is higher, you buy fewer shares. But the end result is that you’re investing the same amount of money each time.
Why investors might use dollar-cost averaging
Below are the main reasons investors may want to consider using dollar-cost averaging:
Risk Mitigation
Dollar-cost averaging reduces the impact of market volatility on investment returns. By investing consistently over time, investors avoid the risk of investing a lump sum at the market peak and potentially suffering significant losses if the market subsequently declines. If the stock goes up in value, then that means your earlier buy-ins are generating profits and you’re buying into the rally. If the stock is going down, then you’re buying more of it and are averaging down. The benefit here is that as long as the business and investment remains sound, there’s a good chance that the stock will recover from a drop. Buying low could end up setting you up for some great returns.
Disciplined Approach
By dollar-cost averaging, investors establish habits that can help them resist the temptation to make impulsive decisions based on short-term market conditions. The investor remains focused on the long term and that can help lead to more rational decisions.
Ease of Implementation
Dollar-cost averaging is simple to execute, whether you’re an experienced investor or a novice one. You don’t need to do any complex analysis and instead just need to do the same thing every month or every period you plan to buy stock. By making the process easy, it makes it easier to adhere to.
Benefits of dollar-cost averaging
There are several advantages to using dollar-cost averaging:
Emotional Discipline
Emotions can often drive investment decisions, leading to irrational actions such as panic selling during market downturns or chasing after hot stocks during bull markets. Dollar-cost averaging can ensure you aren’t being reactive or making emotional decisions, which can lead to losses and risky behavior.
Lower Average Cost
Provided that you’re investing in a quality business that will grow over time, dollar-cost averaging can keep your average cost down. That’s because you’re buying more shares when prices are low, and thus, are able to average down. And if the investment grows over time and its value increases, so do your profits. By making incremental purchases along the way, you don’t need to worry about buying at the peak.
Reduced Timing Risk
Timing the market is notoriously challenging, even for seasoned investors. Dollar-cost averaging mitigates timing risk by spreading investments over time, reducing the impact of market fluctuations on the overall portfolio. Since you’re buying stock at regular intervals, there’s no temptation to time the markets and you get a more balanced investing strategy.
Flexibility and Scalability
Dollar-cost averaging makes it easy for anyone to build up their position in a stock. Whether you can afford to invest $5,000 or $500, you can spread the amount you plan to invest over the course of a full year into 12 monthly payments. Brokerages nowadays offer low or no-cost commissions, making it easy to justify investing even a modest amount; there’s no need to make a big buy-in.
Disadvantages of Dollar-Cost Averaging
These are the biggest drawbacks of using dollar-cost averaging:
Potential Missed Opportunities
The biggest downside of dollar-cost averaging is that if the price of a stock has dropped significantly, you are not investing more than your recurring amount. Even if the stock becomes a steal of a deal, with dollar-cost averaging you could potentially miss out on that opportunity since you aren’t making a big purchase at the time a stock becomes oversold or is trading at a big discount.
Increased Transaction Costs
In the event you aren’t using a low-cost brokerage and where you are incurring transaction fees, you could be incurring high expenses relative to your investment amount. This can be particularly troublesome when you’re making small investment amounts and fees will end up representing a big chunk of your overall investment. In these situations you may either want to increase your recurring investment amount, or simply not deploy dollar-cost averaging.
Diversification Limitations
Dollar-cost averaging is more effective when investing in a few stocks. It wouldn’t be practical or efficient if every month you had to invest the same amount in 10 or more different stocks. It can quickly become a time-consuming process, one that might not be worth sticking to. That’s why when investors talk of dollar-cost averaging, it usually relates to a small number of stocks, or perhaps even just one.
Market Trend Irrelevance
Dollar-cost averaging may not provide good returns in a bear market. When the market keeps going down, buying more simply ends up increasing your losses since you’re investing more during a downtrend. If you are going to use dollar-cost averaging, you need to have confidence in the business you’re investing in and be willing to be patient enough to hang on in the event of a bear market. If you need to sell your investment within a few weeks or months, dollar-cost averaging may not be a suitable strategy for you.
Step-by-Step Guide to Dollar-Cost Averaging
Here are the steps to take if you want to get started with dollar-cost averaging:
1. Set Investment Period
Determine the time interval for your investments. Monthly investments are common, but you can choose any frequency that suits your financial situation.
2. Allocate Investment Amount
Decide on the fixed amount you want to invest during each interval. This can be any amount that fits your budget and investment goals.
3. Choose Investment(s)
Select the asset or assets you want to invest in regularly. This can be individual stocks, exchange-traded funds (ETFs), mutual funds, or any other investment vehicle.
4. Start Investing
Begin investing the fixed amount at the chosen intervals, regardless of the asset’s price. Maintain consistency over the set investment period.
5. Monitor and Adjust
Regularly review your investment strategy and portfolio performance. Adjust the investment amount or asset allocation if your financial situation or investment goals change.
How to Calculate Dollar-Cost Averages in Excel
If you’ve begun dollar-cost averaging and want to know what the average cost of your investment is, you can do this easily in Excel. Create a table with the following headers: Date, Stock Price, Investment, Shares, Cumulative Investment, Cumulative Shares, and Running Average.
The Date relates to when the stock was purchased.
The Stock Price is what the stock price was when it was purchased.
The Investment is the total investment amount. This should be the same amount each period.
The Shares field is the number of shares purchased. This is the Investment total divided by the Stock Price.
The Cumulative Investment field is the sum of the Investment field up until the current date.
The Cumulative Shares field is the same thing, except it calculates the number of shares purchased up until the current date.
The Running Average takes the Cumulative Investment and divides it by the Cumulative Shares. Here’s an example of how dollar-cost averaging would have worked if you used to approach with Novavax, beginning in December 2021:
As you can see, with the very first row and very first purchase, the running average is the same as the stock price. But as the stock declines in value over the year, the running average becomes lower.
If you liked this post on How to Do Dollar Cost Averaging in Excel, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow me on Twitter and YouTube. Also, please consider buying me a coffee if you find my website helpful and would like to support it.
In the fast-paced world of investing, identifying trending stocks in Excel can provide a valuable edge for investors seeking profitable opportunities. Fortunately, with the power of Excel’s Power Query and the ability to connect to a website’s API, accessing real-time data and uncovering trending stocks has become more accessible than ever. In this article, I will go through the process of using Power Query to connect to a website’s API and importing in trending stock information.
Why should investors try to identify trending stocks?
As an investor, it is crucial to identify trending and popular stocks for several reasons:
Profit Potential: Trending and popular stocks often have significant profit potential. When a stock is gaining popularity, it usually attracts more investors, leading to increased demand and potentially driving up the stock price. By identifying these stocks early, you can position yourself to benefit from the price appreciation and generate higher returns on your investment.
Liquidity: Popular stocks tend to have higher liquidity, meaning there is a larger pool of buyers and sellers in the market. This liquidity allows you to enter and exit positions more easily, ensuring that you can buy or sell shares without significantly impacting the stock’s price. Investing in liquid stocks provides flexibility and reduces the risk of being unable to execute trades at desired prices.
Market Validation: The popularity of a stock often reflects positive market sentiment and investor confidence. When a company is trending and gaining attention, it may indicate that the market believes in its growth prospects and overall performance. By identifying such stocks, you can align your investment choices with market sentiment and increase the likelihood of investing in companies with strong fundamentals and future growth potential.
InformationAvailability: Popular stocks generally attract more media coverage, research reports, and analyst attention. This increased coverage provides you with a wealth of information and analysis to make more informed investment decisions. You can leverage these resources to understand the company’s financial health, competitive position, industry trends, and other relevant factors that can impact the stock’s performance.
How to get trending stocks in Excel
To get trending stock data into Excel, you should start with finding a good source that you can rely on for trending data. For this example, I’m going to use apewidsom.io, which provides free access to its API using the following url: https://apewisdom.io/api/. Here’s how I’m going to use that to pull in trending data:
Extract the data using Power Query. To get started, I’ll select the Data tab in Excel and click on the From Web option.
Next, there will be a field to enter the URL, this is where I will paste the link that the API references:
After clicking OK, Power Query will launch. When the screen opens up, the following table appears. I click on List to open up another table.
After clicking that, there’s another list of records.
Here, I’ll select the option to convert to table and leave the default settings and click OK. Then, there is another list of records. Clicking on the button with the arrows going in opposite directions will expand them:
After expanding out those records, the table will now looks like a list of stocks and metrics relating to mentions, upvotes, and overall rank popularity:
Now that this has been setup, I will convert this into a Power Query function. To do that, I’ll click on the Advanced Editor button:
In the editor, I will add a line at the top to specify the name of the function. And at the bottom, I will add a line to circle back to it. Lastly, I’ll add a variable for the URL as well, and put that where the link used to be:
Next, with the custom function created, I’m going to go back into Excel and create a list of all the URLs I want to use this function on. In this situation, I’m going to adjust the page number at the end of the URL so that I have pages 1 through 5:
I’ll load this table, called URLtable, into Power Query using the From Table/Range button when selecting data. Next, I’ll select the Add Column tab and select Invoke Custom Function:
Then, I reference the query as well as the URL variable that is to be used:
Then, there will be a field with the results, in table format. Again, this needs to be expanded out:
That will leave a list of stocks starting from page 1 all the way through page 5. You can remove the URL field, which is no longer needed:
If you don’t want to follow through all those steps yourself, you can download the template I’ve created here.
If you liked this post on Get Trending Stocks Into Excel Using Power Query, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow me on Twitter and YouTube. Also, please consider buying me a coffee if you find my website helpful and would like to support it.
Do you have multiple lists in Excel or Google Sheets that you want to combine together? With new functions such as VSTACK and HSTACK, you can do just that. In this post, I’ll show you how you can also filter out duplicates and apply sorting so that your data is organized after consolidating all of your lists.
Combining multiple stock lists into a large one
In this example, I’ll use various stock lists that I want to combine into one large list. On Yahoo Finance, you can find an assortment of different lists to help filter stocks. Below, I’ve pulled the lists of stocks that recently hit new 52-week highs, smart money stocks, medical device and research stocks, and e-commerce stocks:
The advantage of keeping the lists separate is that you can more easily update them. And by using VSTACK, you can combine these lists into a larger one so there’s no worry about having to consolidate them later on.
Based on the lists above, this is the formula that I use to combine them all together, using VSTACK:
=VSTACK(A2:A31,B2:B10,C2:C31,D2:D20)
Since I don’t want to include the headers, I start from row 2. You’ll notice that I’ve hardcoded the ranges here. One way to make this more dynamic would be to use a COUNTIF or COUNTA function for the individual lists, and then use the INDIRECT function to limit the scope of the list. Another option involves converting the lists into tables. That way, you only have to list the table column and you don’t have to worry about the ranges. The one caveat here is that if you have lists that have different lengths, you’ll want to make each list its own table. Otherwise, Excel will automatically fill in the gaps with blank values:
While the data looks correct, if I were to use the VSTACK formula for these different table columns, I would get a consolidated list that involves many zero values. To keep it cleaner, it’s easier to just separate them into their own tables, and then reference them afterwards.
To reference these columns, my formula becomes much simpler:
=VSTACK(Table1[Recent 52-Week High],Table2[Smart Money Stocks],Table3[Medical Device and Research Stocks],Table4[E-commerce])
The advantage of doing it this way is that now I don’t have to worry about hardcoding the ranges, and thus, it’s easier to update.
Whichever method you prefer, the end result should look like a consolidated list:
Removing duplicates and sorting the list
In some of these lists, there is some overlap. AMZN and META are two stocks that show up twice. This means that my consolidated list will include those values multiple times. To get around this, I can embed the formula within the UNIQUE function:
=UNIQUE(VSTACK(A2:A31,B2:B10,C2:C31,D2:D20))
If you also want to sort your list, then you can add the SORT function as well:
If you have the same lists but instead have them going horizontally, then you can use the HSTACK function. It works the same way as the VSTACK but as the H suggests, it will require horizontal arrays. Here are the same list of stocks as in the first example, this time transposed so that they go horizontally:
In this case, the formula for HSTACK would be as follows:
=HSTACK(B1:AE1,B2:J2,B3:AE3,B4:T4)
You can apply the same steps as for the VSTACK to eliminate duplicates and to sort the results.
These formulas work the same in Google Sheets as in Excel
Whether you’re working in Google Sheets or Excel, these formulas will be the same. The VSTACK, HSTACK, SORT, and UNIQUE functions are all available on the latest version of Excel and on Google Sheets. There is no need to change any of the formulas besides just adjusting for any difference in ranges. The formulas themselves work in the same ways, making it easy to transfer data between Google Sheets and Excel and to replicate these formulas wherever makes sense for you.
If you liked this post on How to Use VSTACK and HSTACK in Excel and Google Sheets to Consolidate Lists, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow me on Twitter and YouTube. Also, please consider buying me a coffee if you find my website helpful and would like to support it.
The Relative Strength Index (RSI) is a popular trading indcator that investors use for trading purposes. In this article, I’ll go over details as to what RSI is, why it’s useful, and how to calculate it in Excel.
RSI is a bounded oscillator that fluctuates between 0 and 100, providing insights to investors as to whether a stock is overbought or oversold. It compares the magnitude of recent price gains relative to recent price losses over a specified period of time, typically 14 days, and generates a value that indicates the potential for a price reversal or continuation.
The higher the losses are relative to the gains, the lower the RSI value becomes. And the opposite is also true, with the RSI value rising when a stock has been accumulating more gains than losses. Generally, an RSI value above 70 indicates an overbought condition, suggesting a potential price correction or reversal to the downside. Conversely, an RSI value below 30 indicates an oversold condition, implying a potential price bounce or reversal to the upside. Traders often use these overbought and oversold levels to identify possible entry or exit points in the market.
Why RSI Is a Useful Indicator for Traders
It’s important to note that the RSI is just one tool among many in technical analysis, and it should be used in conjunction with other indicators and analysis methods to make well-informed trading decisions. However, here are 4 reasons traders might find it useful:
1. Finding overbought and oversold levels
RSI can help investors identify buying and selling opportunities. When a stock is deeply oversold and the business is still in good shape but perhaps is down due to a bad quarter, it could be a sign to buy the beaten-down stock. In essence, it can help find market overreactions. At the same time, it can spot a stock that perhaps has become too hot when its RSI level is over 70 or 80, and that perhaps it has risen too much and too quickly.
It’s useful to also look at a stock’s historical RSI levels to gauge what kind of an opportunity it is. If it frequently dips in and out of oversold/overbought territory, it could simply be that the stock is volatile. But if it is rare for the stock to become oversold/overbought, then it could make for a good opportunity to buy or sell the stock depending on what the indicator says.
2. Measuring momentum and confirming a trend
The RSI provides insights into the strength and momentum of a price trend. When the RSI is rising and stays above 50, it indicates that buying pressure is dominant and the price trend may continue. Conversely, when the RSI is falling and stays below 50, it suggests that selling pressure is dominant and the price trend may continue downward. This information can help investors confirm the strength of a trend and make informed decisions about entering or exiting positions.
3. Identifying divergence patterns
Another valuable aspect of the RSI is its ability to identify divergence patterns. Divergence occurs when the direction of the RSI differs from the direction of the price. Bullish divergence happens when the price makes lower lows while the RSI makes higher lows, indicating a potential trend reversal to the upside. On the other hand, bearish divergence occurs when the price makes higher highs while the RSI makes lower highs, suggesting a potential trend reversal to the downside. Investors can use these divergence patterns as early warning signals of potential trend shifts and adjust their investment strategies accordingly.
4. Confirmation with other indicators
The RSI can be used in conjunction with other technical indicators to confirm signals and strengthen investment decisions. For example, if a stock shows overbought conditions based on the RSI, investors may look for additional indicators such as bearish candlestick patterns or negative volume divergences to support their decision to sell or take profits.
Other technical indicators investors can use alongside RSI
Investors often use many different indicators to make investment decisions. Here are a few commonly used indicators that can be used in conjunction with the RSI:
1. Moving Averages
Moving averages are trend-following indicators that smooth out price fluctuations over a specific period. The most commonly used moving averages are the simple moving average (SMA) and the exponential moving average (EMA). Investors often use moving averages in combination with the RSI to identify trend direction and potential support or resistance levels.
2. MACD (Moving Average Convergence Divergence)
The MACD is another trend-following momentum indicator that consists of two lines, the MACD line and the signal line. It helps identify potential buy and sell signals by measuring the relationship between two moving averages. Traders often look for convergence or divergence between the MACD and the RSI to confirm potential trend reversals or continuations.
3. Bollinger Bands
Bollinger Bands consist of a centerline (typically a moving average) and two bands that are plotted above and below it. These bands represent volatility levels. When the price reaches the upper band, it suggests that the asset is overbought, while reaching the lower band suggests oversold conditions. Combining Bollinger Bands with the RSI can provide additional insights into potential price reversals or breakouts.
4. Stochastic Oscillator
The Stochastic Oscillator is a momentum indicator that compares the closing price of an asset to its price range over a specific period. It consists of two lines, %K and %D, which oscillate between 0 and 100. Traders often look for oversold or overbought conditions on the Stochastic Oscillator in conjunction with the RSI to confirm potential trading signals.
5. Volume indicators
Volume indicators, such as On-Balance Volume (OBV) or Volume Weighted Average Price (VWAP), provide insights into the buying and selling pressure behind price movements. By analyzing volume alongside the RSI, investors can assess the strength and validity of potential price trends or reversals.
6. Fibonacci retracements
Fibonacci retracements are based on the mathematical relationships found in the Fibonacci sequence. They are used to identify potential support and resistance levels. Combining Fibonacci retracements with the RSI can help investors identify areas where a price correction or reversal may occur.
These are just a few examples of indicators that investors can use alongside the RSI. The choice of indicators depends on the investor’s trading strategy, timeframes, and personal preferences. It’s important to test and evaluate different combinations of indicators to find a system that works well for individual investment goals and risk tolerance.
Why you shouldn’t buy a stock just because the RSI is low
Buying a stock solely based on a low RSI level is not a recommended approach for several reasons:
1. It lacks context
The RSI is just one indicator and provides a snapshot of the stock’s recent price performance relative to its own historical price movements. It doesn’t take into account other fundamental factors or external market conditions that may impact the stock’s future prospects. For example, a stock may have a very low RSI because investors are selling it off due to liquidity issues or problems that may significantly impact the investing thesis behind a stock. Therefore, solely relying on the RSI without considering other relevant information may lead to an incomplete assessment of the stock’s potential.
2. False signals
The RSI is a bounded oscillator that fluctuates between 0 and 100. While an RSI below 30 may indicate an oversold condition, it doesn’t guarantee an immediate rebound or a profitable buying opportunity. Stocks can remain oversold for extended periods, and the RSI alone may not accurately predict the timing or magnitude of a price reversal. It’s essential to consider other technical and fundamental indicators to validate the potential opportunity.
3. Downtrends and value traps
A low RSI reading can sometimes be an indication of a stock in a prolonged downtrend. Just because a stock is oversold does not mean it will necessarily recover or provide substantial returns. There may be fundamental reasons behind the stock’s decline, such as poor financial performance, unfavorable industry conditions, or negative news. Investing solely based on a low RSI without understanding the underlying reasons for the low reading can lead to falling into a “value trap” not unlike how investors may buy a stock simply because its price-to-earnings multiple is low.
4. Confirmation bias
Relying solely on the RSI to make investment decisions may lead to confirmation bias, where investors seek information that supports their preconceived notions. It’s crucial to consider a broader range of indicators, conduct thorough research, and evaluate multiple factors to make well-informed investment decisions.
5. False oversold signals in strong downtrends
In strong downtrends, a stock can remain oversold for an extended period as selling pressure continues. Attempting to catch a falling knife solely based on a low RSI reading can result in further losses if the stock continues its downward trajectory. It’s important to assess the overall trend, market conditions, and other technical and fundamental factors to increase the probability of making successful investment decisions.
While the RSI can be a useful tool to identify potential opportunities, it should be considered as part of a comprehensive analysis that incorporates other indicators, fundamental analysis, and market conditions. By taking a holistic approach to investment decision-making, investors can make more well-rounded and informed choices.
How do you calculate RSI?
Here are the steps to take when determining how to calculate RSI:
1. Determine the timeframe
Traders usually use a 14-day timeframe for calculating the RSI, but it can be adjusted to suit different trading strategies and timeframes.
2. Calculate the average gain and average loss
The RSI compares the average gains and average losses over the chosen timeframe. To calculate the average gain, sum up all the positive price changes (gains) over the period and divide them by the number of periods. Similarly, calculate the average loss by summing up all the negative price changes (losses) and divide that by the number of periods.
3. Calculate the relative strength (RS)
The relative strength is the ratio of the average gain to the average loss. RS = Average Gain / Average Loss.
4. Calculate the RSI
The RSI is derived from the relative strength and is calculated using the formula: RSI = 100 – (100 / (1 + RS)).
Calculating RSI in Excel
Using the STOCKHISTORY function in Excel, you can easily download a stock’s historical prices. In this example, I’ve downloaded Amazon’s stock price between the period Jan 1, 2021 and Dec 25, 2022.
The next step is to calculate the gains and losses for each day. This just involves looking at the current closing price and the previous. If the price went down, the difference goes into the loss column. If it’s a gain, it goes into the gain column. Here’s an example of the formula for the gain column:
=IF(B7>B6,B7-B6,0)
Here’s a look at what the sheet looks like with the formulas filled in for the gain and loss columns:
Next up, I need to calculate the average gains and average losses. I’ll do this for the past 14 trading days. For the first value, I just need to calculate a simple average:
=AVERAGE(C7:C20)
For subsequent cells, however, I’ll use an exponential average. That way, I’ll apply more weighting to the the most recent calculation:
=((E20*13)+C21)/14
Next, I will calculate the RS Value. To do this, I take the average gain and divide it by the average loss:
=E20/F20
Lastly, that leaves the RSI calculation, which contains the following formula:
=100-(100/(1+G20))
With all the fields filled in, this is what the spreadsheet looks like:
If you want to follow along with the file that I’ve created, you can download it from here. You can also watch the corresponding YouTube video that goes along with this tutorial:
If you liked this post on How to Calculate the Relative Strength Index (RSI) in Excel, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow me on Twitter and YouTube. Also, please consider buying me a coffee if you find my website helpful and would like to support it.
Bollinger Bands are used in technical analysis to help calculate and measure volatility. There are three bands that are included in chart: a moving average, and a lower and upper band. Normally, the upper and lower band are set to be within two standard deviations of the moving average. The standard deviation helps measure volatility and determines the width of the bands. As volatility increases, the band widens, and the opposite happens when volatility decreases.
The Bollinger Bands are often used by traders to identify opportunities for when to buy or sell a stock. If a stock price gets closer to the upper band, then it is considered to be overbought, and hence, this can be a time to sell. If, on the other hand, it is approaching the lower band, then it is oversold, and it may be an opportune time to buy. A similar tool that traders may also use is the Relative Strength Index, as that too tracks momentum and helps traders identify when a stock is overbought and oversold.
Why should you use Bollinger Bands?
Traders may use Bollinger Bands for a variety of reasons:
To identify buying and selling opportunities, such as when a stock is overbought or oversold. However, it’s important not to be overly reliant on a single indicator and it’s a good idea to also review other tools in conducting technical analysis to help confirm your trading decision.
Bollinger Bands can help gauge volatility. When the volatility is high, there is an opportunity for traders to take advantage of a large spread. With a large spread, there are more opportunities to buy low and sell high than there are when volatility is low and price is trading within just a narrow range.
Traders may also use Bollinger Bands to spot trends in the market as the bands will slope in a similar direction to price. This can help potentially identify buying and selling opportunities based on the stock’s trajectory.
How to create and chart Bollinger Bands
The process for creating a chart to show Bollinger Bands in Excel and Google Sheets is similar — the main difference is in how to pull in the stock price. The steps below go over the steps specific to Google Sheets:
Start with downloading the stock prices. In my example, I have downloaded the stock price for Meta Platforms going back to 2020. This was done using the GOOGLEFINANCE function in Google Sheets, and the formula is as follows: =GOOGLEFINANCE(“meta”,”price”,”1/1/2020″,today())
Calculate the 20-day moving average from the closing prices. This is done using the AVERAGE function. Assuming the closing prices start from cell B4, the formula would be as follows: =AVERAGE(B4:B23). Copy the formula down to all the cells.
Calculate the standard deviation using the STDEV function. This is also based on the last 20 closing prices and is copied down to the bottom of the data set. This is the formula to calculate the standard deviation based on this example: =STDEV(B4:B23).
Calculate the Upper Band. Do this by multiplying the standard deviation by 2, and adding that to the 20-day moving average. Assuming the 20-day moving average is in cell C23 and the standard deviation is in cell D23, this is what the formula would look like: =C23+D23*2
Calculate the Lower Band. For this, multiply the standard deviation by -2, and add that to the 20-day moving average. Based on the above assumptions, the formula would be as follows: =C23+D23*-2
Once all those formulas are entered, your data set should look something like this:
Next, create a line chart to show the values on a graph. Then apply any formatting (e.g. dotted lines, colors, etc) and you should have a visual that looks like this:
If you liked this post on How to Create and Chart Bollinger Bands in Google Sheets and Excel, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow us on Twitter and YouTube.
If you’re looking to buy stocks, a one of the more common ratios you’ll likely consider in your analysis is the price-to-earnings, or P/E multiple. You can look at either the trailing P/E or the forward P/E. Below, I’ll look at what the difference between those multiples is, how to calculate each one, and how you can use them to determine a company’s expected growth rate.
What is the difference between the trailing P/E and the forward P/E?
The P/E ratio looks at the stock price in relation to earnings per share. If it’s a trailing earnings multiple, then that means you’re looking at the company’s earnings over the trailing twelve months, or ttm. A forward earnings multiple is based on analyst expectations and what the company’s earnings will be over the next year.
If a company had a worse year than normal or analysts are expecting lots of growth in the year ahead, the forward P/E will be lower than the trailing P/E. If, on the other hand, the company performed exceptionally well and perhaps benefitted from one-time gains, then its trailing P/E may look better (i.e. lower) than its forward P/E if analysts don’t expect a significant change in the business over the next year.
The smaller the gap between the trailing P/E and the forward P/E, the more consistent the earnings numbers are and the less of a change analysts are expecting from the previous year. If, however, the gap is significant, that could be an opportunity for investors because if a stock has a high trailing P/E multiple (due to an abnormally bad year), it can be missed on stock screeners if people are searching for stocks with low P/E multiples.
You can think of a forward P/E as what the company’s earnings will be in a normal or typical year whereas the trailing P/E is one that may have been distorted for a number of reasons.
How to calculate the trailing and forward P/E ratios
Here are the steps you can take to calculate the trailing P/E multiple:
Add the company’s net income over the past four quarters. This is its income over the trailing twelve months.
Take that total and divide it by the averaged diluted shares outstanding over the course of the year. Unless there’s a significant variation over the course of the past year, you can often just use the shares outstanding as of the most recent quarter. The result of this calculation will give you diluted earnings per share, or EPS.
Get the current share price and divide it by EPS. This will be your trailing P/E multiple.
Here’s how I did the above calculations for Tesla’s stock in Excel, based on data as of Jan. 16, 2023 that was pulled from Yahoo Finance:
For the forward P/E multiple, the calculation is more straightforward since it is based on analyst expectations. Here are the steps to calculated the forward P/E multiple:
Obtain the average analyst earnings per share estimate for the next year.
Take the current share price and divide it by that estimate.
If you go to Yahoo Finance and go under the Analysis tab, you will see a series of analyst expectations for earnings for the new year:
Since I’m looking for the full year, I’ll take the average estimate for ‘Next Year (2023)’ which is an EPS of $4.79. By taking the share price of $122.40 and dividing by this figure, I arrive at a forward P/E of 25.55. This tells me that analysts are expecting Tesla to have a better year in 2023 as its forecasted EPS of $4.79 is higher than the $3.23 it has reported over the past four quarters.
You can use earnings multiples to estimate the earnings growth analysts are forecasting
This year, analysts are projecting that the company’s EPS will be $4.79, which is 48% higher than the $3.23 it reported over the past four quarters. However, you can estimate how much growth analysts are expecting from the business without having to dive into the EPS numbers.
Since the numerator, price, in the P/E multiples remains constant, the only change is the earnings, the denominator. You can do the same earnings growth calculation by taking the trailing P/E and dividing it by the forward P/E, and then subtracting 1 from that value:
If the forward P/E is lower than the trailing P/E, that tells you that analysts are expecting that the company’s earnings are expected to decline in the coming year.
If you liked this post on How to Calculate Trailing P/E vs Forward P/E in Excel, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow us on Twitter and YouTube.
If you’ve ever looked up historical stock prices on Yahoo Finance, you know that there is both a closing price and an adjusted closing price. Sometimes the values are the same, but sometimes there’s a difference In this post, I’ll cover why that happens, and how you can calculate the difference yourself.
What is the difference between the two prices?
The adjusted closing price in Yahoo Finance factors in the impact of dividend payments. For stocks that pay dividends, the further back you go, the greater the difference there will be between the close and the adjusted closing price. With the closing price, you’ll just see the raw change in price, whereas the adjusted closing price will also factor in the dividend, and that can give you a better view of how the stock’s total returns have been over time, not just from the increase in share price. And thus, the longer of a duration you’re looking at and the more dividend income along the way, that creates more of a gap between the close and adjusted close.
For stocks that don’t pay dividends, there will be no difference between these two values.
How to calculate the difference
A difference between the two prices in Apple’s stock history doesn’t show up until the last time it issued a dividend, on Nov. 4. Technically the company didn’t pay the dividend on that day, but that was the date of record for the dividend, and so investors who owned the stock at that date were eligible for the dividend. The actual payment took place later, on Nov. 10.
To factor in for this difference, we need to take the amount of the dividend ($0.23) and divide it by the stock’s price immediately before this date. On Nov. 3, the stock price closed at $138.88. Taking $0.23 and dividing it by the stock price returns a value of 0.001656. If we take 1 minus that amount, that equals 0.99834389. That’s what the closing price needs to be multiplied by to arrive at the adjusted close. Here’s how it looks in the spreadsheet:
That ‘dividend impact’ factor will be applied to every value before the dividend. And when doing that, you arrive at the adjusted closing price. However, that’s not the end of this because if we go to the next dividend in August, the values are off again:
The issue here is that we need to factor in another dividend payment. It’s another payment of $0.23 and this time the stock price was $165.81. The discount factor is now 0.99861287. However, this needs to be multiplied by the first discount factor as well, in order to ensure we are adjusting for both dividend payments. And so the correct factor is 0.996959:
You would need to continue to make these adjustments the further back in time you go, and each time, taking into account all the dividend payments in-between today and the date of the stock price on that day. This is why over time, the difference gets larger.
If you liked this post on How to Calculate Yahoo Finance’s Adjusted Closing Price, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow us on Twitter and YouTube.
***UPDATE: There is a newer version of this template available here****
For a limited time, I have a free stock trading template that is available for you to download in Excel. If you buy and sell stocks often, this is a template that will help you easily enter in your trades and track your performance.
How to use the template
There are three main buttons on this template that you will need to use, all of which are located within the ribbon, under the Trading Journal group:
The Enter Transaction button will allow you to post and trades you make. Clicking on it will show the following pop up:
At the very top there is a Date Picker button which will allow you to select the date of the transaction, rather than manually entering it. Here is an overview of the other fields;
Ticker: this is simply the name of the stock you are buying.
Action: indicate whether you are buying, selling, or adding to an existing position.
Strategy: select your strategy for this transaction. If you want to add or remove available strategies, click on the Update Strategies button.
Shares this is the number of shares you are buying or selling.
Price: this is the price per share for the transaction.
Fees: the amount of any fees you have incurred on the transaction.
Once all this is entered, click on the button to Post Transaction and the details of the transaction will be posted to the Log sheet and an entry will be opened up on the Transactions tab. The Transactions tab will show you a summary of your positions, including any profits and losses, and whether they are open or closed.
There is a Settings tab where you can manually adjust strategies. You can also specify different holding categories should you want to track that (e.g. what constitutes a short, medium, or long holding period).
Once you’ve entered some transactions, you can head over to the Summary tab which will give you a visual breakdown of your investments. To be sure the data is updated correctly, click on the Refresh button in the ribbon button (not the default refresh option in Excel).
You can use slicers in the report to filter by different dates, strategies, and holding periods.
If you like this Stock Trading and Tracking Template, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow us on Twitter and YouTube.
Warren Buffett fans like to track the billionaire investor’s moves, and a good way to do that is through Berkshire Hathaway’s 13f filings. His company reports its holdings every quarter, showing where there were changes in its positions. By looking at multiple filings, investors can track the changes from one period to another. With this free template, you can do that quickly and easily all on your own. All you have to do is specify the specific filings that you want to compare to one another.
How the template works
This template uses PowerQuery to grab the data from the 13f filings. It will then compare the two to find the changes in share count.
There are only two inputs you need for the template, both are on the Current.Holdings tab. You’ll need to paste the URL for the current 13f filing and the previous one (or whichever filings you want to compare against one another). It can sometimes be a bit tricky to get exactly what you’re after. Here’s how you can find the 13f filings for Berkshire Hathaway to use in this template:
Do a search for 13f so that you can see just the 13f filings on that page:
4. Find the reporting period you want and click on the Filing button — don’t click on the actual description next to it.
5. When you open up the link, you should see multiple files you can open. Select the information table that is in html format:
When you open the file, you should see the holdings in a table format:
If this is what you see, then the link you’ve downloaded will work. Note, on older 13f filings (e.g. 2013 and older), the format is in a text file and they won’t work with this template.
6. Copy the link and enter it into one of the fields on this template, either for the new filing or the old one.
7. Once you’ve filled in both the new and old links, then go to the Data tab in Excel and click on Refresh All. This will update the queries that the template relies on, and calculate the changes.
Now the different sheets will update:
Current.Holdings: this will show you the current holdings as per the New13f file
Change.In.Holdings: this will show you the change between the two filings. The change will be reflected in total shares and as a % of change in shares.
Old.Holdings: this will show the number of shares held per the Old13f file.
If you like the Berkshire Hathaway 13f Template, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow us on Twitter and YouTube.
