Introduction
For over three decades, the asset management industry has sought to establish firms and funds focused on short selling stocks, yet only a handful have achieved long-term success Many of the funds that have since become defunct relied on a narrow strategy of targeting companies they believed were on the verge of bankruptcy for short selling.
In the mid-90s, I invested $10,000 in a research firm that specialized in identifying companies involved in accounting fraud, receiving detailed reports on their fraudulent activities Despite the compelling evidence, the 1995 bull market led to no instances of fraud among the identified firms, with many stocks instead achieving significant gains I ultimately exited my positions, either out of panic or because my put options expired worthless Over the years, the research company flagged around 200 firms, but only three were found to be committing fraud, leaving me and other investors dissatisfied and unwilling to renew our subscriptions.
Short funds have employed various strategies to identify companies at risk of failing, including targeting technologies poised for obsolescence, assessing competitive threats that could undermine a company's viability, and predicting a broader economic collapse in the US that could lead to widespread corporate failures.
Despite the good intentions and strong convictions of those managing short funds, these strategies have largely failed to deliver long-term success While notable cases of fraud, such as Enron and Tyco, have impacted the market, the overall performance of most short funds remains disappointing The challenges of profiting from shorting stocks are evident, especially during economic downturns like those experienced in 2000-2002 and 2008.
This Strategy Guidebook presents a proven quantitative method for shorting stocks, based on consistent behavioral patterns observed since 1995 By analyzing statistical data, we identify that when stocks become excessively overbought in the short term, they typically experience a sharp pullback While few companies go out of business, most stocks pause as profit-taking occurs and speculative investors exit, leading to increased pressure on prices Notably, around 70% of the time, these stocks see lower prices within just a few days following this behavior.
We first identified this behavior in 2003 and started teaching a variation of the strategy in our
Since its inception in 2005, TradingMarkets Swing Trading College has consistently taught timeless trading concepts that remain relevant today Despite the evolving nature of the markets, we take pride in our ability to adapt while maintaining the core principles that have guided our instruction over the years.
2008, the behavior of extremely overbought stocks has not changed And this is where the Alpha is
When engaging in short sales, it's essential to recognize the potential for unlimited losses, despite the use of stop-loss orders, which may lower test results Although some trades may experience significant adverse movements of 50% to 100% before exiting, the long-term test results remain notably positive For those familiar with the risks of options trading, liquid puts can be an effective strategy to manage potential losses, as they allow traders to know their total risk upfront.
To achieve Alpha, you must venture into areas that others avoid, particularly shorting stocks, which many find psychologically challenging Despite the statistical evidence indicating potential advantages, overcoming the fear of shorting popular "story stocks" that have surged to unsustainable levels due to crowd behavior is essential This Guidebook, supported by over a decade of data, will equip you with the knowledge to navigate this strategy effectively.
We are excited to present the latest edition of the Connors Research Strategy Guidebook Series For additional topics from our Strategy Research Series, please click here.
Shorting Mechanics
Many individual investors avoid shorting stocks due to fear of going against market trends or a lack of understanding of the process This section will cover essential basics that you need to know before making your first short sale.
In traditional financial transactions, we typically buy assets like houses, cars, or artwork before selling them However, in the stock market, there's a strategy known as short selling, which allows investors to sell stocks they do not own before purchasing them This unique approach enables traders to profit from declines in stock prices, reversing the conventional buy-first, sell-later model.
In stock transactions, buyers exchange cash for shares from sellers, but short sellers operate differently by borrowing shares instead of owning them Just like buyers can utilize margin accounts to borrow cash from brokers, short sellers can borrow shares from their brokers If a broker has shares available for shorting, they are often marked as Easy to Borrow (ETB) on trading platforms Conversely, stocks classified as Hard to Borrow (HTB) may be unavailable or necessitate contacting a broker's trade desk for access.
When closing a short trade, we cover our position by purchasing the stock, exchanging cash for shares However, these shares are returned to the broker to settle the loan incurred when the short position was initiated.
Different brokers offer varying stocks for borrowing, with highly liquid stocks typically available from most brokers However, less liquid stocks may not be accessible through all brokers If your current broker frequently restricts your ability to borrow shares for short selling, it may be beneficial to consider opening an account with a different broker.
To engage in short selling, you must have a margin account with your brokerage firm, as brokers loan you shares for this purpose It's important to note that short selling is not permitted in accounts like IRAs or 401(k)s that are cash-secured Additionally, similar to margin trading, brokers will charge interest on the borrowed shares.
When purchasing a stock at $100 per share, your maximum risk is limited to the amount spent, as the stock's price cannot fall below zero In contrast, shorting a stock carries potentially unlimited risk since there is no cap on how high the price can rise It's crucial to note that if the stock price moves unfavorably while you're in a short position, your broker will require adequate collateral, such as cash and other securities, to cover your position, similar to the requirements for long positions bought on margin.
Short sellers must pay dividends on borrowed stocks For instance, if I borrow a stock from my broker and short sell it at $50 per share, I am responsible for covering any dividends issued by the company in the interim.
When a company issues a $1/share dividend, the stock price typically drops by the same amount If a broker lends shares to a short seller, the broker still expects to receive the $1 dividend, which is deducted from the short seller's account For instance, if a trader shorts the stock at $50/share and later covers it at $49/share, they effectively gain $1/share, which offsets the dividend payment Thus, while the dividend reduces the stock price, the short seller experiences no net loss; they simply see cash leave their account now instead of realizing their gains later when the short position is closed.
Now that we’ve covered some of the basics around shorting, let’s move on to the rules for the strategy.
Strategy Rules
The ConnorsRSI Short Stock Strategy focuses on identifying stocks that have experienced significant upward movement and reached new short-term highs The approach involves shorting these stocks during additional intraday strength and subsequently waiting for mean reversion to drive prices back down before exiting the position.
This strategy executes trades using a simple three‐step process consisting of Setup, Entry and Exit The rules for each of these steps are detailed below
A Setup occurs when all of the following conditions are true:
1 The stock’s price closes above $5 per share
2 The average volume over the past 21 trading days (approximately one month) is greater than 500,000 shares
3 The stock closes with a ConnorsRSI(3,2,100) value greater than X, where X is 75, 80, 85, 90 or 95
4 The stock’s 100‐day Historical Volatility, or HV(100), is greater than 40
5 The stock’s 10‐day Average Directional Index, or ADX(10), value is greater than 40
6 Today’s High is the highest high in the past N days, where N is 7, 10 or 13
If the previous day was a Setup, then we Enter a trade by:
7 Submitting a limit order to short the stock at a price Y % above yesterday’s close, where Y is 2, 4, 6, 8, or 10
When entering a trade, it is essential to have a predetermined exit strategy, which can include various methods Some trading variations utilize Variable Limits, a concept that will be elaborated on further.
8a The stock closes with a ConnorsRSI value less than 20
8b The stock closes with a ConnorsRSI value less than 30
8c The stock closes with a ConnorsRSI value less than 40
8d The closing price of the stock is less than the 5‐day moving average, or MA(5)
8e The closing price of the stock is lower than the previous day’s close We typically refer to this exit as the First Down Close
Let’s look at each rule in a little more depth, and explain why it’s included in the strategy
Rules 1 & 2 assure that we’re trading liquid stocks which are likely to have shares available to borrow
Rule 3 uses ConnorsRSI to identify a price surge A complete description of ConnorsRSI can be found in the Appendix
Rule 4 focuses on choosing stocks that have demonstrated healthy price volatility in recent months Short-term trading strategies rely on significant price movements to establish trades and achieve profits, making stocks with lower volatility less suitable for this approach.
Rule 5 utilizes the ADX indicator to pinpoint stocks with strong upward trends While ADX itself is non-directional, it confirms the strength of the upward movement indicated by other rules.
Rule 6 highlights the significance of an N-day high, indicating that stocks rarely maintain a consistent upward trajectory for long When a stock hits a short-term peak, it typically signals an impending pullback before the price resumes its upward trend.
Rule 7 enables traders to enter positions at the best possible price by identifying overbought stocks The entry strategy takes advantage of an intraday price surge that occurs for a second consecutive day, prompting traders with long positions to lock in profits by selling This selling creates downward pressure on the stock price, which benefits our short position.
Research indicates that stocks trading above their 200-day moving average (MA(200)) are more likely to experience upward price movement, while those below the MA(200) tend to decline By utilizing Variable Limit Entries, investors can capitalize on this trend by placing larger limit orders for stocks that are above their MA(200).
Variable Limit Entries in trading strategies employ a limit percentage that is 1.5 times higher than the standard limit when the stock price exceeds the 200-day moving average (MA(200)) For instance, with a limit percentage (Y) of 4%, a stock closing above the MA(200) on the Setup day would trigger a 6% limit order for trade entry, while a stock below the MA(200) would maintain the 4% limit Conversely, strategies that do not incorporate Variable Limit Entries apply a consistent limit percentage, irrespective of whether the stock closes above or below the MA(200) Examples of both trading approaches will be discussed in the following section.
Rule 8 offers a clear and structured exit strategy, which is rare among trading strategies Backed by over twelve years of historical test results, it provides precise parameters for exiting trades Like other strategy components, we pre-select the exit type and consistently implement this rule in our trading practices.
In our testing, we found that closing all trades at the end of the trading day when the Exit signal is triggered yields effective results However, if this approach isn’t feasible, our research indicates that exiting your positions the following morning typically produces similar outcomes.
A typical trade on a chart using a strategy variation involves ensuring the ConnorsRSI value exceeds 90 and achieving a 10-day high on the Setup day A limit order is set at 6% above the Setup day’s closing price, with no variable limits The exit point is triggered when the ConnorsRSI falls below 30 In this strategy, the parameters are defined as X = 90, N = 10, Y = 6, and the exit method follows Rule 8b.
Chart created in Amibroker Reprinted courtesy of AmiBroker.com
The chart for Zillow Inc (symbol: Z) displays price bars in black alongside the 200-day moving average (MA(200)) in dark green A vertical blue-gray line indicates the selected date, February 14, 2013, which serves as the Setup day The entry day is marked by a red down arrow, while a green up arrow signifies the exit day The middle pane presents additional values related to the stock's performance.
The chart features ConnorsRSI displayed in bright blue, alongside the 100-day historical volatility (HV(100)) represented in purple, and the ADX(10) indicated in bright green In the lower section, daily volume is illustrated as a blue-gray histogram, while the 21-day average volume is shown as a turquoise line We will now verify that all entry and exit conditions have been accurately fulfilled.
Rule 1 requires the stock price to close above $5 on the Setup day The closing price of $42.30 meets this requirement
Rule 2 is satisfied because the 21‐day average volume is over 725,000 shares, which is well above our minimum requirement of 500,000 shares
According to our strategy parameters, Rule 3 stipulates that the ConnorsRSI(3,2,100) must exceed 90 on the Setup day, and it meets this criterion with a recorded value of 90.33 on the chart.
On the Setup day, Rule 4 is met with an HV(100) value of 58.56, exceeding the threshold of 40 Additionally, Rule 5 is satisfied as the ADX(10) value stands at 54.05, which is also above the threshold of 40.
Test Results
While it's impossible to predict the future performance of a trading strategy with certainty, a fully quantified strategy can be assessed through its historical performance This evaluation method is referred to as "back-testing."
To perform a back-test, we begin by choosing a selection of securities, often referred to as a watchlist, to evaluate our strategy In this instance, our watchlist includes both historical and current members of the S&P 500.
To ensure meaningful and informative back-testing results, it is essential to select an appropriate timeframe for analysis In this Guidebook, the back-tests are conducted from January 2001 to April 2013, utilizing the most recent data available at the time of writing.
We implement our entry and exit rules on every stock in the watchlist throughout the testing period, meticulously documenting data for each potential trade and consolidating all trade information for a specific strategy variation.
The Average % Profit/Loss, often referred to as the Average Gain per Trade or simply the edge, is a crucial statistic derived from back-tested results It is calculated by summing all percentage gains and losses from trades and dividing that total by the number of trades executed This metric helps traders assess their performance and make informed decisions.
Trade No % Gain or Loss
The Average % P/L would be calculated as:
Average % P/L is the average gain based on invested capital, i.e the amount of money that we actually spent to enter each trade
For short-term trades spanning three to ten days, traders typically aim for an Average % P/L between 0.5% and 2.5% A higher Average % P/L can significantly enhance account growth over time; however, it's crucial to also factor in the Number of Trades metric By utilizing a consistent capital amount for each trade, traders can achieve greater profits from multiple trades with an average gain of 4% per trade, compared to a single trade yielding 10%.
The Winning Percentage, or Win Rate, is a crucial metric that reflects the ratio of profitable trades to the total number of trades executed For instance, in a scenario where 7 out of 10 trades yield positive returns, the Winning Percentage is calculated as 70% (7 divided by 10).
Understanding the significance of Win Rate is crucial, even when Average % P/L appears satisfactory A higher Win Rate typically results in more stable portfolio growth, as losing trades tend to cluster together, leading to drawdowns that can negatively impact your portfolio's value These drawdowns can cause stress and may even tempt traders to exit the market Conversely, a higher Winning Percentage reduces the likelihood of clustered losses, promoting a smoother upward trajectory for your portfolio and minimizing erratic fluctuations.
Let’s turn our attention to the test results for the different variations of the Short Selling Stocks with
ConnorsRSI Strategy First, we’ll sort the test results to show the 20 variations that produced the highest
Average % P/L All variations that generated fewer than 200 trade signals during the 12+ year testing period have been filtered out to avoid skewing the results
Top 20 Variations Based on Average Gain
# Days for Highest High Limit %
Below is an explanation of each column
# Trades is the number of times this variation triggered from January 1, 2001 –April 30, 2013
The average percentage profit or loss (Avg % P/L) represents the overall performance of all trades, factoring in both gains and losses relative to the invested capital Over a testing period of more than 12 years, the top 20 variations have demonstrated positive returns, achieving gains between 5.55% and 9.4%.
The Avg Days Held represents the average duration of trades, measured in days, with a significant range from slightly over 2 days to more than 11 trading days Further discussion on this topic will be provided in a subsequent section.
The win percentage (Win %) represents the proportion of simulated trades that ended profitably, with many of the top 20 variations achieving win rates in the mid-70s This indicates a significant level of successful trades, especially when compared to the average target of 50-60% that many traders strive for.
Entry CRSI is defined by Rule 3 of the strategy, which requires the ConnorsRSI value to exceed the specified entry threshold We conducted tests using ConnorsRSI thresholds of 75, 80, 85, 90, and 95 Unsurprisingly, the higher ConnorsRSI values tend to prevail in the results, although the absence of the 95 threshold raises questions that we will investigate in a subsequent section.
Days for Highest High aligns with Rule 6 of the strategy, showing a trend of higher values in the data This indicates that by adhering to more stringent entry criteria, traders can frequently secure larger gains.
The Limit % is associated with Rule 7 of the strategy, defining the entry price for trades We conducted tests using limit percentages of 2%, 4%, 6%, 8%, and 10% above the closing price of the Setup day.
The use of variable entry limits proved advantageous, as indicated by the prevalence of "Yes" (Y) entries compared to "No" (N) entries Specifically, a "Yes" was recorded when the entry limit was set at 1.5 times the normal for stocks exceeding the 200-day moving average (MA) Conversely, a "No" was noted when the same limit applied irrespective of whether the price was above or below the MA(200) This data suggests that implementing variable entry limits enhances trading outcomes.
Exit Method is the rule that was used to exit trades in this strategy variation, as described in Rule 8
Next, let’s look at the strategy variations that have historically had the highest frequency of profitable trades or Win Rate
Top 20 Variations Based on Highest Win Rate
# Days for Highest High Limit %
Selecting Strategy Parameters
In earlier sections, we explored various values for strategy parameters like the ConnorsRSI entry threshold (X), N-Day High, entry limit percentage (Y), and exit methods Now, we will address additional factors to contemplate when selecting the variations for your trading strategy.
When considering entry and exit rules in trading, their strictness plays a crucial role in determining how often these conditions are met Strict rules are characterized by their rarity, making them more challenging to achieve, while lenient rules occur more frequently For instance, in oscillators like ConnorsRSI, values near the extremes of 0 and 100 are deemed more stringent and less likely to occur compared to those in the mid-range.
Stricter entry rules lead to fewer trades compared to more lenient rules, but a well-designed strategy often results in higher gains per trade For instance, shorting a slightly overbought stock typically yields a moderate pullback, whereas waiting for the stock to reach extreme overbought levels increases the likelihood of a significant price drop, ultimately enhancing profit potential.
Stricter exit rules have a minimal impact on the number of trades generated by a strategy but can lead to higher average profits This occurs because such rules allow trades to remain open longer, enabling stocks to undergo the mean reversion behavior that the Short Selling Stocks with ConnorsRSI Strategy seeks to capitalize on Consequently, the tradeoff for entry rules involves balancing the frequency of trades with potential gains, while exit rules require weighing shorter trade durations against the possibility of increased profits per trade.
This Guidebook outlines a strategy that compares five variations, all utilizing a consistent timeframe of 10 days for the highest high, a static limit entry of 6%, and an exit method based on ConnorsRSI < 30 The only differing factor among these variations is the ConnorsRSI entry threshold.
The Effect of ConnorsRSI Entry Threshold
# Days for Highest High Limit %
The analysis reveals that the ConnorsRSI Entry Threshold of 75, being the most lenient, resulted in the highest number of trade signals but yielded the lowest average gains per trade Conversely, as the entry rule becomes stricter with a rising ConnorsRSI Entry Threshold, the number of trade signals diminishes, while the average gains per trade increase significantly Notably, the variation with an entry threshold of 95 boasts nearly double the average percentage profit/loss compared to the initial threshold, albeit with less than one-tenth the number of trades executed.
When analyzing stock price movements while keeping all parameters constant except for the Limit %, it's evident that more stocks will see a price increase of 2% or more the following day compared to those that rise by at least 10% This pattern highlights the relationship between limit entry prices and the likelihood of significant price surges.
Variations with Different Limit % Entries
# Days for Highest High Limit %
Stricter entry rules lead to a reduction in the number of trades while increasing the average gains In our analysis of exit strategies, we maintain consistent setup and entry criteria while exploring different exit methods.
Variations with Different Exit Methods
# Days for Highest High Limit %
The five variations produced comparable trade signals, ranging from 1,743 to 1,834 trades, reflecting a minimal variation of approximately ±3% from the average of 1,801 Notably, the lenient exit method, which involves closing positions on the first day the stock price declines, yields an average gain that is only 80% of the gain achieved using the strictest exit method.
The trade duration varies significantly, spanning from 1.75 days to 11.75 days Additionally, a comparison of the second and third lines in the table reveals intriguing insights when utilizing a specific exit method.
When analyzing trading signals generated by ConnorsRSI < 40, it produced 1,825 signals with an average gain of 2.62% over 2.56 days In comparison, using the exit strategy of Close > MA(5) resulted in 1,803 trades with a slightly higher average gain of 2.64%, but with an extended average duration of over 4 days Therefore, if choosing between these two strategies, the first variation is preferable, as it allows for quicker profit-taking, demonstrating that holding trades longer yields minimal additional benefits.
With this knowledge, you can effectively choose strategy parameters that are likely to generate optimal trade signals, maximize average gains, and align with your desired trade duration, enhancing your overall trading strategy.
Using Options
In recent years, options trading has experienced significant growth due to tighter spreads, increased liquidity, and the simplified process of trading complex options.
In this section, we will explore how to implement options trading in response to short-term market movements As with all strategies outlined in this Guidebook, there are specific rules to follow when executing an options trade upon the activation of a strategy signal.
Here is what we know based upon the data:
1 The majority of the moves from entry to exit have been held a very short period of time (2‐12 trading days)
2 The average gains per trade have been large – well beyond the normal distribution of prices over that short period of time
3 A high percentage of the moves have been directionally correct
One effective trading strategy, confirmed by professional traders, involves purchasing front month, in-the-money long puts This approach can lead to various outcomes and is noteworthy among different strategies.
Front month, in-the-money long puts are preferred because they closely track the stock's movements This alignment means that when the stock price shifts in the anticipated direction, the potential percentage gains from these options are significantly higher.
2 Buy the front month in‐the money put If you were to normally short 500 shares of the stock, buy 5 puts (every 100 shares should equal one put option contract)
3 Exit the options when the signal triggers an exit on the stock
1 What does in‐the‐money exactly mean here?
When considering options trading, it is advisable to select one to two strike prices that are in the money For instance, if a stock is priced at $48 and the interval between option contracts is $5, investors should consider purchasing either the 50 or 55 puts to optimize their strategy.
2 What does front month mean?
To optimize your trading strategy, focus on options with the nearest monthly expiration, especially when it is eight trading days or fewer from the front month’s expiration date If the closest expiration falls within this timeframe, consider trading the subsequent month’s options instead.
3 What happens if I’m in the position and it expires, yet the signal for the stock is still valid?
In this case, roll to the next month You’re trading the stock signals so you want to have exposure to that signal
4 What about liquidity and spreads?
Liquidity in options trading is not strictly defined, as it can vary among traders Many traders assess liquidity by examining minimum volume and open interest levels.
When evaluating options with active volume, it's essential to examine the spreads For instance, an option trading at a 3.00 bid and 3.30 offer has a 10% spread, making it difficult to achieve profitability In contrast
5 What are the advantages of buying put options instead of shorting the stock?
Assuming the spreads and liquidity are there, the advantages are large:
1 Greater potential ROI on capital invested
When shorting a stock at $50, the potential losses are theoretically unlimited, whereas using options limits your risk to the premium paid For instance, purchasing $55 puts means your maximum loss is confined to the premium, offering a safer alternative with less risk exposure.
One significant advantage of trading options is the increased flexibility it offers For instance, if a stock triggers a short signal at $50 and you purchase $5.50 55 puts, a subsequent drop in the stock price to $46 presents you with various options You can choose to exit your position or roll into the 50 puts, allowing you to recoup most of your investment and potentially turn this into a nearly cost-free trade, especially if you anticipate further declines in stock prices.
Many options books highlight various strategic opportunities, yet professionals advise caution when trading exotic options or strategies beyond simply purchasing puts.
In summary, options present traders with an effective alternative to directly shorting stocks Our strategy is built on a structured approach that focuses on front-month, in-the-money options, utilizing a consistent sizing of one option per 100 shares, and we exit the position when the signal indicates to do so.
The above options strategy, in many experts’ opinion, is the best and most efficient strategy based upon the historical data from these signals.
Additional Thoughts
1 As you have seen throughout this Guidebook, the Short Selling Stocks with ConnorsRSI Strategy has had large quantified edges when applied in a systematic manner
You can explore numerous variations by adjusting the input variables outlined in the rules to tailor the strategy to your needs If you're seeking more trades, consider options with a lower ConnorsRSI entry value or fewer lookback days for the highest high For larger average returns, focus on variations with strict entry criteria, such as a high ConnorsRSI entry value and elevated Limit %, along with longer durations using the ConnorsRSI 20 exit method If your goal is to execute trades quickly, minimizing overnight risk and maximizing capital for other opportunities, look into variations that employ the First Down Close exit method.
3 What about stops (and we include the answer to this in all our Strategy Guidebooks)?
We have published research on stops in other publications including in our book Short ‐ Term Trading
Research over the past two decades indicates that using stops in trading can diminish performance and often lead to significant losses While it may seem beneficial to exit a position when a stock declines, frequent stop hits can accumulate substantial losses that few trading strategies can recover from.
For many traders, the use of stop-loss orders is essential, as it helps them manage risk and make difficult trading decisions with greater confidence However, whether to implement stops is ultimately a personal choice, and both approaches have their merits It's important to note that applying stops may reduce the potential edges in short-term trading strategies Successful traders can be found in both categories, highlighting that there is no one-size-fits-all approach in trading.
When testing trading strategies, it's essential to consider slippage and commissions, even though limit prices minimize slippage concerns Ensure you trade at the lowest possible costs, as many firms now offer trading for less than 1 cent per share If you're an active trader, take the time to compare brokerage options, as online firms are eager to attract your business.
Thank you for exploring this segment of the Connors Research Trading Strategy Series For any inquiries regarding this strategy, please don't hesitate to reach out to us at info@connorsresearch.com.
Since the mid-1990s, Larry Connors and Connors Research have been dedicated to developing and testing quantified trading strategies, evaluating numerous technical indicators to determine their effectiveness in predicting price movements As a result of this extensive research, they have created their own indicator, ConnorsRSI, which will be detailed in this chapter along with its calculation methods.
ConnorsRSI is a composite momentum indicator that combines three components, two of which are based on the Relative Strength Index (RSI) calculations created by Welles Wilder in the 1970s The third component assesses the most recent price change on a scale from 0 to 100 Together, these elements create an oscillator that fluctuates between 0 and 100, signaling whether a security is overbought (high values) or oversold (low values).
Before calculating ConnorsRSI, it's important to understand Wilder's RSI, a widely-used momentum oscillator that assesses the strength of a stock's gains versus its losses over a specified look-back period Wilder recommended a 14-period look-back as optimal, commonly referred to as RSI(14) The following formula calculates the RSI(14) based on a series of price changes.
To calculate the Relative Strength Index (RSI) for a different number of periods (N), simply substitute 14 in the formula with N and replace 13 with N-1 The RSI will always yield a value between 0 and 100, regardless of the period selected Traders commonly utilize RSI(14) to identify overbought conditions when the value exceeds 70, and oversold conditions when it falls below 30.
Research indicates that shorter look-back periods enhance the effectiveness of the Relative Strength Index (RSI) in predicting short-term price movements Strategies employing RSI(2) have been extensively published, alongside those utilizing RSI(3) and RSI(4) Adjusting the period length influences the RSI levels that signify overbought and oversold conditions; specifically, an RSI(2) value below 10 typically indicates an oversold condition, whereas a value above 90 serves as a reliable marker for an overbought condition.
ConnorsRSI is a powerful indicator that integrates three key components, each of which has demonstrated significant predictive ability according to our research.
Price momentum can be effectively assessed using the Relative Strength Index (RSI), which identifies overbought and oversold conditions in the market The ConnorsRSI specifically utilizes a 3-period RSI calculation based on the daily closing prices of a security, denoted as RSI(Close,3).
The duration of an up or down trend in a security's closing price can significantly impact future price movements When a security closes lower than the previous day, it is considered to have "closed down," and consecutive days of such closures create a "streak." Our research indicates that longer down streaks often lead to a more substantial price bounce upon mean reversion, while extended up streaks tend to result in more significant downward movements when the stock reverts to its mean Thus, the duration of these streaks serves as an effective overbought/oversold indicator.
Theoretically, the duration of a streak can be limitless, yet practical limits based on historical data suggest that streaks rarely exceed 20 days, whether upward or downward However, this observation does not align with the typical values of oscillators, which usually range between 0 and 100.
To effectively analyze streaks, we will represent an up streak with positive numbers and a down streak with negative numbers, allowing for a clear distinction in the count of days.
Day Closing Price Streak Duration