InvestX Archives | Page 8 of 28

Q: What Is Spoofing in Trading?

Spoofing is when traders place market orders—either buying or selling securities—and then cancel them before the order is ever fulfilled. In a sense, it’s the practice of initiating fake orders, with no intention of ever seeing them executed.

Oct

2023

What Is Spoofing in Trading?

By Samuel Becker | Growing Wealth, invest, Investing, Terminology | Comments Off

In the financial space, the term “spoofing” refers to an illegal form of stock market and exchange trickery that is often used to change asset prices. Given that the stock markets are a wild place, and everyone is trying to gain an advantage, spoofing is one way in which some traders bend the rules to try and gain an advantage.

Spoofing is also something that traders and investors should be aware of. This tactic is sometimes used to change asset prices — whether stocks, bonds, or cryptocurrencies.

What Is Spoofing?

Spoofing is when traders place market orders — either buying or selling securities — and then cancel them before the order is ever fulfilled. In a sense, it’s the practice of initiating fake orders, with no intention of ever seeing them executed.

Spoofing means that someone or something is effectively spamming the markets with orders, in an attempt to move security prices.

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What’s the Point of Spoofing?

Because stock market prices are determined by supply and demand — for instance, the more demand there is for Stock A, the higher Stock A’s price is likely to go, and vice versa — they can be manipulated to gain an advantage. That’s where spoofing comes in.

By using bots or an algorithm to make a high number of trades and then cancel them before they go through, it’s possible for spoofers to manipulate security prices. For a trader looking to buy or sell a certain security, those valuations may be moved enough to increase the profitability of a trade.

Spamming the markets with orders creates the illusion that demand for a security is either up or down, which is then reflected in the security’s price. Because it would require an awful lot of “spoofed” orders to move valuations, spoofers might rely on an algorithm to place and cancel orders for them, rather than handle it manually. For that reason, spoofing is typically associated with high-frequency trading (HFT).

Is Spoofing Illegal?

If it sounds like spoofing is essentially cheating the system, that’s because it is. In the United States, spoofing is illegal, and is a criminal offense. Spoofing was made illegal as a part of the Dodd-Frank Act, which was signed into law in 2010. Specifically, spoofing is described as a “disruptive practice” in the legislation, straight from the U.S. Commodity Futures Trading Commission (CFTC), which is the independent agency responsible for overseeing and policing spoofing on the markets:

Dodd-Frank section 747 amends section 4c(a) of the CEA to make it unlawful for any person to engage in any trading, practice, or conduct on or subject to the rules of a registered entity that —

(A) violates bids or offers;

(B) demonstrates intentional or reckless disregard for the orderly execution of transactions during the closing period; or

(C) is, is of the character of, or is commonly known to the trade as ‘spoofing’ (bidding or offering with the intent to cancel the bid or offer before execution).

Additionally, there are laws and rules related to spoofing under rules from the Securities and Exchange Commission (SEC), and the Financial Industry Regulatory Authority (FINRA), too.

Example of Spoofing

A hypothetical spoofing scenario isn’t too difficult to dream up. For instance, let’s say Mike, a trader, has 100,000 shares of Firm Y stock, and he wants to sell it. Mike uses an algorithm to place hundreds of “buy” orders for Firm Y shares — an algorithm that will also cancel those orders before they’re executed, so that no money is actually spent.

The influx of orders is read by the market as an increase in demand for Firm Y stock, and the price starts to increase. Mike then sells his 100,000 shares at an inflated price — an artificially inflated price, since Mike effectively manipulated the market to increase his profits.

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Consequences of Spoofing

Because spoofing is a relatively easy way to manipulate markets and potentially increase profits, it’s also a fairly common practice for some traders and firms, despite being against the law. That transgression can cost spoofers if and when they’re caught.

For example, one financial institution was fined nearly $1 billion by the SEC during the fall of 2020 after the company was caught conducting spoofing activity in the precious metals market.

But it’s not just the big players that can be on the receiving end of a smack down by the authorities. During August of 2020, an individual day trader was caught manipulating the markets through spoofing activity — actions that netted the trader roughly $140,000 in profits. The trader was ultimately ordered by the CFTC to pay a fine of more than $200,000.

Despite the cases that make headlines, it’s generally hard to identify and catch spoofers. With so many orders being placed and executed at once (especially with algorithmic or computer aid) it’s difficult to identify fake market orders in real time.

How to Protect Against Spoofing

There are a number of parties that are constantly and consistently trying to gain an edge in the markets, be it through spoofing or other means. For investors, it’s worth keeping that in mind while sticking to an investing strategy that works for you, rather than investing with your emotions or getting caught up in the news cycle.

In a time when a single social media post or errant comment on TV can send stock prices soaring or into the gutter, it’s critical for investors to understand what’s driving market activity.

The Takeaway

Spoofing is meant to gain advantage in the markets, but as such it’s illegal and penalties can be steep. Beyond the spoofers trying to manipulate the market, spoofing has the potential to affect all investors.

If spoofers are manipulating prices for their own gain, that can cause traders and investors to react, not realizing what is going on behind the scenes. While this is more of an issue for active investors or day traders, it’s something to be aware of.

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You may also be interested in:

Market Manipulation: An Overview for Retail Investors

Wash Trading: What Is It and How Does It Work?

What Is a Dark Pool in Trading?

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Oct

2023

Pros & Cons of Using a Moving Average to Buy Stocks

By Kate Ashford | Growing Wealth, Investing, Terminology | Comments Off

The moving average is a tool that can help investors decide whether and when to buy or sell a stock. It presents a smoothed-out picture of where a stock’s price has been in the past and where it’s trending now. Investors may compute moving averages over a variety of time frames, and they are useful to both long-term and short-term investors.

What Is a Moving Average?

A moving average is a metric often used in technical analysis. For a stock, it’s a constantly updated average price.

Unlike trying to track a stock price day-to-day, a moving average smooths price volatility and is an indicator of the current direction a price is headed. A moving average reflects past prices — usually a stock’s closing price — so it’s not a predictor of future direction, just what’s happening now or in the past.

You can compute moving averages using almost any time frame. Common time frames include 20-day, 30-day, 50-day, 100-day and 200-day moving averages.

While a moving average is useful on its own when analyzing different types of investments, it also forms the basis of other types of technical indicators, such as the Moving Average Convergence Divergence (MACD) and the McClellan Oscillator.

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Types of Moving Averages

There are three common types of moving averages that investors might consider when deciding when to buy or sell a stock:

Simple Moving Average:

As the name states, this is the simplest type of moving average. You can calculate the simple moving average by finding the arithmetic mean of a set of data points. For instance, if you had an average daily price for a stock each day for the last 30 days, you would add them all together and divide by the number of days.

The Simple Moving Average (SMA) formula is as follows:

P = Price on a given date

n = The time period

Example: Suppose you were trying to find the simple moving average of a stock price over 10 days.

N = 10 days

Prices (in dollars) = 11, 12, 15, 13, 12, 7, 10, 11, 13, 12

SMA = (11 + 12 + 15 + 13 + 12 + 7 + 10 + 11 + 13 + 12) / 10

SMA = 11.6

Weighted Moving Average

A weighted moving average (WMA) gives more weight to certain price prices. If you overweight recent prices, for example, the measure becomes more responsive to recent price moves and less prone to the lag effect.

Exponential Moving Average:

An exponential moving average is a type of weighted moving average that calculates changes in a price cumulatively, rather than based on previous average. That means that all previous data values impact the EMA, since there is less variation over time.

Why Would an Investor Use a Moving Average?

Using a moving average to analyze a stock can help you filter out the “noise” that comes from random price fluctuations. By looking at the direction of the moving average, you can get a sense of whether the price is generally moving up or generally moving down. If a moving average is moving sideways (neither up nor down), the price is probably sticking within a window and not fluctuating much.

A moving average is sometimes plotted as a line by itself on a price chart to illustrate price trends. And different moving average lines can be used in tandem to spot changes in direction. For instance, an investor might be looking at a faster moving average (one with a shorter period, such as 10 days) versus a slower moving average (one with a longer period, such as 200 days). When these lines cross each other, it’s called a moving-average crossover, and can indicate that the trend is changing or is about to change.

Moving averages can also indicate support or resistance levels. Support levels are a price level where a downward trending line would be predicted to pause, due to demand or buying interest. A resistance level is a price ceiling where an upward trending line would be expected to plateau due to selling interest. Over time, watching moving averages can help investors identify these levels of support and resistance, and use them to make buy/sell decisions.

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Pros of Using a Moving Average

A moving average offers several benefits to investors.

It smooths the data.

Day-to-day price swings can be confusing to track, and make it difficult to determine a stock’s direction. A moving average smooths out volatility, giving you a better look at how a stock is trending.

It’s a simple gauge.

As an analytical tool, a simple moving average is easy to interpret. If a stock’s current price is higher than an upward trending moving average line, the stock is headed up in the short-term. If a stock’s price is lower than a downward trending moving average line, the stock is headed down in the short-term.

Easy to calculate.

A moving average is a relatively easy metric, so the average investor can calculate it on their own.

Cons of Using a Moving Average

It’s important to keep the drawbacks of moving averages in mind when using them to determine whether to buy shares of a company.

They’re not predictive.

As with all investments, past performance is not an indicator of future performance, so a moving average — no matter which type you use — can’t tell you what a stock will do next.

There’s a lag.

The longer the period your moving average covers, the greater your lag — meaning how responsive your moving average is to price changes. A 10-day exponential moving average, for instance, will react quickly to price turns, while a 200-day moving average is more sluggish and slower to react to changes.

There’s trouble with price turbulence.

If prices are trending in one direction or another, a moving average may be a helpful metric. But if prices are choppy or volatile, the moving average becomes less useful, since it will swing along with the price. Allowing for a lengthier time frame may resolve this issue, but it can still occur.

Simple moving averages weigh all prices equally. This can be a disadvantage if a stock’s price has taken a significant but recent shift.

Weighted moving averages may send false signals.

Since WMAs put more weight on more recent data, they’re faster to react to price swings, which can occasionally be misleading.

The Takeaway

Moving averages are just one metric you can use to evaluate a stock. They can help quiet the noise of price fluctuations and show you what a stock is doing over time. That said, in some environments or with specific price patterns, moving averages may lag or send a misleading signal.

With that in mind, knowing what a moving average is can be helpful when learning how to size-up potential investments. It’s critical to consider the pros and cons, of course, but moving averages can be another tool in an investor’s tool chest.

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Sep

2023

What Happened During Tulip Mania?

By Ashley Kilroy | Growing Wealth, invest, Investing | Comments Off

One of the most famous instances of an asset bubble was the “Tulip Mania” that erupted in Holland during the 17th century. It was the first recorded major financial bubble, during which demand for tulips exploded, and prices for the flowers followed suit.

This led some investors to speculatively purchase tulips, resulting in losses when prices fell back down. Despite Tulip Mania occurring centuries ago, it can still be used as a history lesson for current traders and investors.

What Was Tulip Mania?

Tulip Mania was a speculative frenzy that erupted in Holland during the 17th century. The Dutch were newly independent of Spain and building themselves into prosperous traders. The mid-1600s was a period of wealth for them, as they benefited from rare imports brought through the Dutch East India Company.

Interest in exotic items was at an all-time high, and collectors became fascinated with not just tulips, but “broken” tulips. These tulips came from bulbs and grew into striped or multicolored patterns. As demand grew, more companies began selling bulbs.

The most famous tales about Tulip Mania sound like something out of a book. People of all walks of life bought the flowers in a frenzy at sometimes extremely high prices. They hoped for significant returns and to escape their social classes, but they met financial disaster. Those investors fell into ruin when the tulip bubble burst in 1637 – similar to the dotcom bubble in more recent times – and some of the stories even detail tragic endings; people losing everything and drowning themselves in the canals. All because a tulip-incited mass hysteria that created a financial crisis.

But, is it really true?

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What Really Happened During Tulip Mania?

The “mania” in the story of Tulip Mania comes from an 1841 account by a Scottish author named Charles MacKay. His Memoirs of Extraordinary Popular Delusions and the Madness of Crowds detailed a “tulipomania” where people poured years of salaries into the speculative tulip trade. From farmers, to nobles, to chimney-sweeps, he documented every class buying in. Then, the memoir described mayhem following the market collapse in 1637. Ultimately, MacKay created a dramatic tale that was more fiction than fact.

There was a Dutch tulip bulb market during the Dutch Golden Age. However, traders were limited to buyers with the finances to invest in luxury items. Typically, this group included merchants, artisans, and the upper class.

Additionally, the price increase was not consistent. Between December 1636 and February 1637, some highly sought-after bulbs experienced a price spike. Some of the most expensive went for 5,000 guilders, which equaled the value of a nice home in 1637. Or, there is evidence that the highest bid totaled out to 5,200 guilders. That matched 20 times the yearly salary of a skilled worker. But these prices were the exception, not the rule.

That leaves the final part of the story: the fallout.

Tulip Mania Bubble Burst

Tulip Mania is the classic and most well-known historical example of a financial bubble.

Traders bought into the bulbs with the intent to resell and earn a profit. However, the flowers’ held no inherent value. Their status as a luxury item determined their prices and pushed demand. In fact, demand grew so high that professional traders began bidding on the product on the Stock Exchange of Amsterdam. People even used margined derivative contracts to increase the number of tulips they could buy despite their financial limits.

But before spring even hit, the bubble burst. The mania fell away after the tulips lost their value when the supply of tulips increased due to warmer weather. With so many of the crops, bulb traders realized the product wasn’t as rare as they thought. An auction in Haarlem in February of 1637 seemed to solidify the thought when the auctioneers failed to sell any bulbs.

When the prices dropped, traders had to sell their holdings for a lower value. However, this led to a few broken relationships and lost reputations, not any tragic deaths.

So, there was no morbid end when the Tulip Mania bubble burst. MacKay reported that Holland’s national economy fell apart due to the volatile market crash, but those claims appear exaggerated. The bubble only impacted those who were involved in the Tulip trade, and most investors were in an easily salvageable position. They financially recovered relatively quickly. On the other hand, growers did struggle to replace the lost buyers when certain contracts fell through.

What Tulip Mania Reveals About Financial Markets

While the story is more straightforward than MacKay made many believe, it is still a valuable moment in economic history. It became a parable that explains the nature of bubbles and the crashes that occurred throughout the history of the stock market.

Part of its value as a lesson stems from its moment in time. Multiple bubbles followed Tulip Mania, including the railroad mania bubble during the 1840s, where commentators encouraged investors to buy into U.K. railway stocks or in the early 2000s when Americans began speculating in residential housing before that bubble burst.

The dynamics behind each of these events is similar to the dynamics of the tulip bubble. Speculators drive up the price of an asset beyond its intrinsic value until the bubble eventually busts and those who bought at the top of the market end up losing money in the market downturn.

The Takeaway

Tulip Mania is perhaps the penultimate example of a market bubble, which still resonates today, even though it occurred in Holland centuries ago. Bubbles can also occur in the pricing of individual securities, sectors, or the broader stock market, eventually leading to a crash in prices.

A stock market crash is an alarming time that can send many investors into a panic. They see the drop and move immediately to selling. However, panic selling in the face of market volatility can have disastrous effects on a portfolio. Either you sell when the market is struggling and earn lower returns as a result, or you miss out on the market rebound.

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Sep

2023

What Is Quadruple Witching?

By Matthew Zeitlin | Financial Independence, Growing Wealth, invest, Investing | Comments Off

Quadruple witching refers to the simultaneous expiration of four popular investment contracts, creating wild market conditions. Given its name, it may just be the spookiest day of the year for investors – sorry, Halloween! Quadruple witching day occurs on the third Friday in March, June, September, and December.

The last hour of those trading days is known as the “quadruple witching hour”, when many derivatives contracts expire, often creating volatility in the markets. That’s because there may be higher market volume on those days as traders either close out or roll over their positions.

What is Quadruple Witching Day?

Quadruple witching, or quad witching, is trader’s terminology for the four dates on the calendar when four kinds of options contracts expire: stock options, stock index futures, index options, and stock futures.

Each of the contracts has expiration dates that will match up each quarter, which is why quadruple witching, or quad witching, happens in the third, sixth, ninth and twelfth month of the year respectively. The expiration for these contracts happen at the same time in the day — the afternoon.

While events like quadruple witching may not impact how and when you invest (especially if you’re investing for the long term), they are a good reminder of the investment risks that any investing strategy or approach brings.

How much attention individual investors pay to witching day may depend on their investing philosophy and their time horizon. Since quad witching can result in short-term volatility, many passive investors may ignore them entirely. On the other hand, active investors who try to time the market and get in and out of trades quickly in the most advantageous manner, may use them to inform their strategy and consider buying or selling witching hour stocks.

Contracts Involved in Quad Witching

To understand quadruple witching, you have to first understand the different options contracts involved. Stock index futures, stock index options, single stock futures and single stock options are all derivatives, meaning their value corresponds to the value or change in value of an underlying asset. The underlying assets are either stock market indexes, like the S&P 500, or individual company stocks.

Options contracts give holders the right, but not the obligation, to buy or sell a stock at a certain price at a future date. Futures contracts are contracts to purchase shares of a given stock at a certain price in the future.

For indices, futures and options are contracts on the value of an equity index. Investors often use these either to hedge or make outright speculations on the moves of an index. All four derivatives are complex investments that involve risks when playing the market, and they’re more often used by professional traders and institutional traders than retail investors.

How Does Quadruple Witching Affect the Market?

Quadruple witching days are those four days of the year when these types of contracts all expire, those who bought contracts and choose to exercise them will receive their stock or cash, or they make additional transactions to take advantage of arbitrage opportunities.

This can lead to more buying and selling of shares than is typical for a given day or, especially a given hour. Increased volume can mean more volatility in the markets and the possibility of large swings during the day.

One reason these days can cause hiccups in the markets is that while certain positions expire, investors may want to extend them. This means they have to “roll” the bet in order to keep it active, potentially forcing other players in the market to buy or sell, especially if the market is already volatile or choppy.

For trades that involve the transfer or automatic buying of stock, like options trades on individual shares, the quadruple witching date can mean automatic buying up of shares to fulfill the options contracts, leading to spikes even if there is no “fundamental” reason for them.

Overall, volumes in options trades can go up on quadruple witching days, which can sometimes have knock-on effects on the price of the underlying assets involved in options contracts.

The Takeaway

Quadruple witching day occurs on the third Friday in March, June, September, and December. The last hour of those trading days is known as the “quadruple witching hour”, when many derivatives contracts expire, often creating volatility in the markets. That’s because there may be higher market volume on those days as traders either close out or roll over their positions.

Quadruple witching offers an opportunity to understand how market mechanics can affect actual prices, but it may not impact the strategy for most long-term investors. More experienced investors and traders may find profitable opportunities, however, as the markets enter a period of volatility.

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Sep

2023

How Time-Weighted Rate of Return Measures Your Investment Gains

By Samuel Becker | Growing Wealth, invest, Investing | Comments Off

One of the most important and most common methods investors use to measure their returns is the time weighted rate of return formula. That’s because the time-weighted rate of return measures a compound rate of growth.

The time-weighted rate of return incorporates the impact of transactions such as portfolios rebalancing, contributions, and withdrawals. That leaves investors with a clearer picture of their portfolio’s overall performance.

What Is the Time-Weighted Rate of Return?

Starting with the basics, a return on investment (ROI) is a measure of how much money investments earn, or how much they’ve grown in value. Returns can be positive or negative (if a stock loses value following its purchase, for example). But obviously, investors make decisions with the goal of earning positive returns.

A rate of return, then, is a measure of the pace at which investments are accruing value, expressed as a percentage. The higher the rate of return, the better. Essentially, it’s a measure of a portfolio’s or investment’s performance over time. Rates of return can be calculated for certain time periods, such as a month or a year, and can be helpful when comparing different types of investments.

But investment portfolios are rarely static. Many investors make contributions or withdrawals to their portfolios on a regular basis. Many people contribute to their 401(k) with each paycheck, for example, or rebalance when market moves throw their asset allocation out of whack.

During these transactions, investors are buying and selling investments at different prices and times based on their investing strategy. That can make it more difficult and complicated to calculate a portfolio’s overall rate of return.

That’s where the time-weighted rate of return formula becomes useful. In short, the time-weighted rate of return formula takes into account a portfolio’s cash flows, and bakes in their effect on the portfolio’s overall returns. That gives investors a better, more accurate assessment of their portfolio’s performance.

That’s why the time-weighted rate of return calculation is, for many in the financial industry, the standard formula for gauging performance, over both the short- and the long-term.

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The Time-Weighted Rate of Return Formula

The time-weighted rate of return formula can look intimidating for even seasoned investors, but it’s an important step in building and maintaining an investment portfolio. But like many other financial formulas, once the variables are identified, it’s a matter of plug-and-play to run through the calculation.

First, let’s take a look at the basic portfolio return calculation:

Basic portfolio return = (Current value of portfolio – initial value of portfolio) ÷ initial value

While this formula provides a value, it assumes that an investor made one investment and simply left their money in-place to grow. But again, investors tend to make numerous investments over several time periods, limiting this calculation’s ability to tell an investor much about their strategy’s effectiveness.

That’s where the time-weighted rate of return comes in. In essence, the time-weighted formula calculates returns for a number of different time periods — usually additional purchases, withdrawals, or sales of the investment.

It then “weights” each time period (assigns them all roughly equal importance, regardless of how much was invested or withdrawn during a given period). Then, the performance of each period is included in the formula to get an overall rate of return for a specified period.

Calculating the time-weighted rate of return over the course of a year, for instance, would include the performance from each individual month. And, yes, that’s a lot of math. Computers and software programs can help, but it’s also doable the old-fashioned way.

This is what the time-weighted rate of return formula looks like:

Time-weighted return = [(1 + RTP1)(1 + RTP2)(1 + RTPn)] – 1

There are variables needed to calculate the equation:

n = Number of time periods, or months
RTP = Return for time period (month) = (End value – initial value + cash flow) ÷ (initial value + cash flow)
RTPn = Return for the time period “n”, depending on how many time periods there are

Let’s break it down again, and assume we’re trying to calculate the time-weighted return over three months. That would involve calculating the return for each individual month, three in all. Then, multiplying those returns together — “weighting” them — to arrive at an overall, time-weighted return.

How to Calculate Time-Weighted Rate of Return

To run through an example, assume we want to calculate a three-month, time-weighted return. An investor invests $100 in their portfolio on January 31. On February 15, the portfolio has a value of $102, and the investor makes an additional deposit of $5. At the end of the three-month period on April 30, the portfolio contains $115.

For this calculation, we wouldn’t think of our time periods as merely months. Instead, the time periods would be split in two — one for when a new deposit was made. So, there was the initial $100 deposit that would constitute a time period that ends on February 15. Then a second time period, when the $5 deposit was made, which constitutes a second time period.

With this information, we can make the calculation. That includes calculating the return for each time period during our three-month stretch. So, for time period one, the basic formula looks like this:

Return for time period = (End value – initial value + cash flow) ÷ (initial value + cash flow)

Now, we plug in our variables and calculate. Remember, there was no additional cash flow during this first period, so that won’t be included in this first calculation.

Time period 1:
($102 – $100) ÷ $100 = 0.02, or 2%

Then, do the same to calculate time period two’s return:

Time period 2:
[$115 – ($102 + $5)] ÷ ($102 + $5) = 0.074, or 7.4%

Now, take the returns from these two time periods and use them in the time-weighted rate of return formula:

Time-weighted return = [(1 + RTP1)(1 + RTP2)(1 + RTPn) – 1

With the variables — remember to properly use percentages!

TWR = [(1 + 0.02) x (1 + 0.074)] – 1 = 0.95, or 9.5%

So, the time-weighted return over this three-month stretch (which included two time periods for our calculation), is 9.5%. If we had simply done a basic return calculation, we’d reach a different number:

Basic portfolio return = (Current value of portfolio – initial value of portfolio) ÷ initial value
$115 – $100 ÷ $100 = 0.15, or 15%

That 15% figure is too high, because it doesn’t account for cash flow. In this case, that was a $5 deposit made in mid-February. The basic return formula folds that into the overall return figure. The time-weighted calculation gives us a more accurate return percentage, and one that accounts for that mid-February deposit.

Other calculations

While the time-weighted rate of return is an important measurement, it’s not the only way to look at a portfolio’s returns. Some investors may also choose to evaluate a portfolio or investment based on its money-weighted rate of return. That calculation is similar to the time-weighted rate of return because it incorporates inflows and outflows, but it does not break the overall investment period into smaller intervals.

Another common measure is the compound annual growth rate, (CAGR), which measures an investment’s annual growth rate over time and does not include the impact of inflows and outflows.

The Takeaway

Having an accurate, timely view of a portfolio’s performance is critical for understanding current investments, planning future investments, and considering changes to your asset allocation. While other rate of return calculations can be useful, it’s important to understand their limitations.

The time-weighted rate of return formula is helpful because it takes into account the numerous inflows and outflows of money over various time periods. Armed with that insight, investors can adjust their strategy to try to increase their rate of return. That may mean reallocating or rebalancing their portfolio to include more aggressive investments or less risky securities.

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Example of Spoofing

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The Takeaway

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Weighted Moving Average

Exponential Moving Average:

Why Would an Investor Use a Moving Average?

Pros of Using a Moving Average

It smooths the data.

It’s a simple gauge.

Easy to calculate.

Cons of Using a Moving Average

They’re not predictive.

There’s a lag.

There’s trouble with price turbulence.

Weighted moving averages may send false signals.

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