Ebook on stochastics and RSI

Markets are defined by constant price movement and volatility. Regular fluctuations in price can create a lot of noise around an asset, making it difficult to distinguish details about its behavior – including what the price may do next. Fortunately for traders, tools like technical indicators provide a way to analyze patterns and unearth insights that support smart, and hopefully profitable, trading.

Stochastics and the Relative Strength Index (RSI) are two of these technical trading tools. Whether they're used individually or combined into a 'Stochastic RSI,' each offers a different way to gauge price momentum, while presenting overbought or oversold readings and buy or sell signals to a trader. Armed with this information, traders can more confidently attempt to make data-driven, profit-maximizing, and loss-minimizing trades.

Stochastic oscillators and the Relative Strength Index (RSI) are two popular momentum indicators. Each can provide overbought or oversold signals to traders (and can even be combined together). Let's take a look at each.

The stochastic oscillator, developed in the 1950s by George Lane, analyzes price movements to gauge the strength and speed of those movements. Lane compared stochastics to a rocket, explaining that "before [a rocket] can turn down, it must slow down. Momentum always changes direction before price".

This belief is rooted in the idea that an asset's closing price typically trades at the higher end of its daily price range in an upwards-trending market while trading near its daily low during a downturn.

The stochastic oscillator is a momentum-focused indicator prized for its accuracy and clarity. Stochastics gauge an asset's closing price in comparison to a range (measured 0-100) of closing prices over a mutable (though most often 14-day) time period, creating overbought (readings of 80-plus) and oversold (readings of 20 or under) trading signals.

There are two types of momentum with stochastic indicators: 'slow' (indicated in formulas as %K, this is best at gauging wide trading ranges or slower trends) and 'fast' (shown in formulas as %D, this is a moving average of the 'slow' indicator). The crossover of these two values, when graphed, produces transaction signals.

Overbought and oversold readings will generally fall into the greater-than-80, less-than-20 range, respectively. Traders should not misinterpret these signals, however, as guarantees of an impending reversal – stronger trends can mean extended stretches of overbought or oversold behavior, making it pertinent for traders to closely examine the behavior of the stochastic oscillator to gain insight into potential shifts.

The relative strength index (RSI) was developed by J. Welles Wilder Jr. to measure asset momentum using price changes and the speed of those changes. Like stochastics, the RSI is an oscillator that reads between 0 and 100; in this case, the RSI calculation determines the ratio of upward and downward movement using 14 periods of data, then smooths it out so only strong trends approach 0 or 100. Traders traditionally interpret RSI values of 70 or greater as an indicator of an overbought asset, while values 30 or below indicate an asset has been oversold; higher or lower values (like 80 and 20) can be used to minimize the number of bought or sold readings.

Like stochastics, the RSI may also display extended stretches of overbought or oversold behavior during stronger trends. Traders should not mistake the mere appearance of these indicators as signs of an imminent reversal of trajectory.

While RSI and the stochastic oscillator share numerous similarities (and are often used side-by-side for analysis), they maintain some key differences. A foundational assumption of stochastics is that an asset's closing prices generally reflect the direction of its overall trend; the RSI is more concerned with the rate of price movements. This means the RSI is best used for measuring the speed at which a price moves, and typically is more valuable in trending markets. Stochastics function best in up-and-down markets because they are the most effective inconsistent trading ranges.

Stochastics and RSI can also be combined together into one indicator – the stochastic RSI (StochRSI). Stochastics and RSI are price-based indicators, but the stochastic RSI is a stochastic oscillator applied to RSI values, not price data. The resulting indicator is more sensitive to past performance and, in turn, can be used to determine whether a current RSI value is overbought or oversold.

Most institutional investors have access to sophisticated trading tools/software, which can help them identify stochastics and RSI for just about any security. Retail investors, however, often lack access to advantage-creating technology and tools.

Fortunately,Tickeron is innovating to change this dynamic.

Tickeron has created A.I.dvisor - a powerful technical trading tool that harnesses the power of Artificial Intelligence to discover, and deliver, intelligent and backtested trade ideas to retail investors.

A.I.dvisor is programmed to scan thousands of securities, cryptocurrencies, and currencies in the global marketplace, looking for stochastic and RSI trends and indicators for potentially actionable trade ideas. Once A.I.dvisor locates a technical trade idea, it automatically generates news about the security so that investors can take action.

This eBook will show you how.

Identifying trends using stochastics, RSI and other statistics is only part of the equation – of paramount importance is knowing how and when to trade the opportunity.

100% certainty regarding price movement is (unfortunately) impossible. No amount of fundamental and technical data about a trade can truly assure a trader of success.

The power of statistics, however, can tilt the odds in a trader's favor. Statistics can determine a trader's potential odds of success by backtesting patterns and historical outcomes to make projections about the future. The power of Big Data means investors can analyze more data, more quickly than ever, resulting in data-rich statistics that may improve the odds of success in each trade.

Tickeron's Artificial Intelligence, known as A.I.dvisor, backtests every trade idea to give the user their "Odds of Success" for each potential trade opportunity.

In this eBook, we'll show you how it works.

For Tickeron users, finding news – and potential trade ideas – regarding stochastics and RSI is simple. A.I.dvisor files all stochastics and RSI-related news under #Stochastics ("hashtag stochastics") and #RSI ("hashtag RSI"), so an investor can quickly find the latest trade ideas and technical indicators.

The following chapters will present real examples of A.I.-generated news and trade ideas using stochastics and RSI and will give you a deeper look into what stochastics and RSI are...and how to use them.

Now that we are familiar with the basics of stochastics and the RSI, let's examine how to interpret some common behavioral patterns, then apply the subsequent insight to trading.

Stochastic oscillators are typically charted as two lines: one displaying an asset's actual value, and another showing the asset's three-day simple moving average. Additional lines demarcate boundaries, indicating the ever-important 80 and 20 thresholds that signal overbought or oversold conditions. This simple layout makes it easy for traders to interpret an asset's momentum, look for signals, and make decisions accordingly.

Stochastics are predicated on George Lane's observations that an asset's closing price reflects the upper or lower extreme of its daily price action (for example, if an asset's price is trending downward, its closing price will typically trade at the low end of daily price action), and subsequently, that an asset's price momentum will shift before its actual price follows. As such, traders vigilantly watch stochastic oscillators for intersections and divergences of daily price action and closing price.

The divergence between a stochastic oscillator and its price action is valuable for traders because it may indicate a potential turnaround in behavior. A period of bullish price action broken by a stochastic oscillator indicating a lower high might signal an impending bear run; inversely, divergence from a bear market's price action with a higher low might indicate a positive shift in momentum.

Crossovers are not particularly notable behavior in a vacuum – in fact, they are relatively common. Traders will thus look for additional signs to confirm that a true reversal is occurring.

Support or resistance breaks on a price chart can confirm a bearish or bullish divergence, and on a stochastic oscillator, a break below or above 50 (the midline of the oscillator) can confirm the same. Movement above 50 suggests prices are trading in the higher range for the period in question, while dips below 50 imply the inverse.

In this bullish divergence, the price chart indicates a lower low during February and March; the break above the halfway point comes after. The stochastic oscillator simultaneously shows the asset reach a higher low and move above the lower threshold (20), signaling a potential momentum shift. The slow and fast stochastic measurements cross over at that point and begin to climb above 50 and into the upper half of the stochastic range. The stock's price breaks resistance shortly after, then trades above 50 on the stochastic oscillator until well into May.

The bearish divergence is, essentially, an inverse bullish divergence. The price chart shows progressive climb to a series of higher high prices from late March to early April – the stochastics reveal a matching peak in late March, followed by a series of lower highs. There are multiple crossovers above and below the 80 mark while the price (on the price chart) generally trends higher. Acting on these early signals would not necessarily have resulted in advantageous trades – even a break below the midline on the stochastic oscillator saw bouncebacks before ultimately dropping as anticipated.

The RSI measures both the level and speed of price movements – as positive closing prices rise in value and frequency, the RSI rises; as losses grow steeper and instances pile up, the RSI falls. The RSI may not immediately reverse trajectory when displaying overbought or oversold behavior, so traders impose additional trendlines to better understand when a true divergence may occur.

This example shows how a stock can continue to evolve even as it hits an oversold reading. After reaching an oversold state in July, the stock reached the overbought threshold in September, stayed in flux, then continued upwards. It broke 70 three more times before peaking in December, reached the oversold mark in January, then bottomed out roughly two weeks later.

Interpreting the RSI within context of a trend can help avoid the many false alarms it generates. Establishing a trendline between 70 and 30 – at 50, for example, ala stochastics – can yield more truthful bullish and bearish signals, as can using bullish signals in bullish trends (and vice versa).

Like stochastics, divergences on RSI can be a useful trading signal. Bullish divergences occur when an RSI indicates a higher low as security price reaches a lower low; a bearish divergence takes place when RSI shows a lower high as a security's price trends higher.

The RSI shows lower highs despite climbing price in September and October; price followed the RSI in mid-October. When the price reached new lows in March, the RSI remained above its previous low before following with a strong breakout.

Like stochastics, RSI divergences are not always true signals – assets can remain in trends for extended periods before reaching actual top or bottom, as seen below:

This makes it all the more important to use additional indicators to make advantageous trades. One method touted by Wilder himself is failure swings, which are prized for their independence from divergences and price action.

Failure swings are marked by a series of reversals – in a bullish instance, an asset starts in an oversold zone, begins climbing, turns down, then bounces back up, achieving a low higher than its oversold level; in its bearish counterpart, the asset begins in overbought territory, pulls back, rebounds, then exceeds its previous low without crossing back into overbought territory. These movements signal to a trader that momentum may be increasing or slowing, respectively, and they should act accordingly.

In this bullish failure swing, the RSI dips beneath the oversold mark (30), rebounds, returns towards the line, then breaks out past its previous high.

In the above bearish example, the asset climbs above the overbought mark (70), drops, climbs towards 70 without exceeding it, then moves lower than its previous low.

Standard RSI uses a 0 to 100 range, but a renowned trader and writer Constance Brown argues that span might not be the most accurate way to frame an RSI. In her book Technical Analysis for the Trading Professional, Brown posits that oscillators do not actually range between 0 and 100. Instead, Brown distinguishes different parameters for bull and bear market ranges for RSI.

While ranges vary based on a variety of factors (like trend strength or RSI parameters), Brown argues that 40 and 90 (with 40 and 50 acting as support zones) are the most common parameters for a bull market RSI. She recommends trading during the pullbacks into the 40-50 zone – instances where risk is low, but upside is high.

Brown identifies 10 and 60 to be the most common range in a bear market, with the 50 to 60 marks functioning as support. In this 14-day RSI of a bear market for the US Dollar Index, the asset rarely exceeded 50 (and never 60) until a strong breakout at the tail end of the year.

The true breakout in December was validated by its ability to break the 50-60 resistance zone.

Stochastic RSI (StochRSI) was developed by Tushar S. Chande and Stanley Kroll to be a more sensitive indicator than its two namesakes. Increased sensitivity and speed means it produces more signals than its counterparts, which traders can use to seize trade opportunities that might otherwise be missed.

StochRSI uses 80 and 20 for overbought and oversold readings, respectively, rather than 70 and 30. The standard centerline of 50 is still in effect, and can be used for identifying uptrends (above 50) and downtrends (below 50).

StochRSI is more volatile than standard RSI, leading to more buy and sell signals (and opportunities for profit). The primary difference between the two when charted is speed of movement from overbought to oversold signals. That's why traders will use other tools in conjunction with stochastic RSI, like moving averages, to smooth out readings.

Key to trading with StochRSI is timely trend identification – traders who seek out oversold conditions in uptrends and overbought conditions in downtrends can profit accordingly when momentum shifts.

This chart shows an asset in an uptrend as the 10-day simple moving average exceeds the 60- day SMA. Traders would look to identify oversold conditions for this asset, in search of an eventual bounce. The StochRSI identified four separate oversold instances during the time period in question; the asset reversed course after each. In this instance, the centerline acted as the threshold for a true upturn – the trader could have leveraged the three instances the mark was exceeded into profitable trades.

The downside to plentiful signals is less true confirmation of trends. StochRSI is prone to volatility regardless of parameters – even a short-term SMA can only smooth readings so much. In this case, an asset received bearish signals from the StochRSI, but did not immediately enter an extended downturn. In fact, the asset was healthily up a few days later:

The 5-day SMA on the 20-day StochRSI did not exceed 50, however, despite the rising price, and the momentum never confirmed the upwards trajectory. Slowing momentum created an exhaustion gap as the asset dipped beneath the support line for an extended downturn. This rampant volatility means traders should always use Stochastic RSI with complementary indicators and deploy it carefully. It is a useful, if imperfect, tool when used with caution.

Tickeron's Artificial Intelligence, known as A.I.dvisor, is programmed to scan the stock, ETF, cryptocurrency, and FOREX markets in search of technical trading patterns. Once it discovers a pattern or a trend, it delivers the chart to subscribers in the form of "News," which includes trade ideas and a trader's odds of success.

In this chapter, we take a look at how you can navigate Tickeron's News Feed to find timely trade ideas, specifically for the Stochastics and RSI technical indicators.

When you visit Tickeron's homepage, you can immediately find news and trade ideas in the News Feed. The first step is to select what types of securities you're interested in, using the 'Filters.' In the image below, we've selected Stocks, ETFs, and Mutual Funds.

As you can see from a quick glance, there are a lot of options an investor has right from the home page, from checking market summaries to finding Tickeron A.I.'s best trade ideas. Since this chapter is about finding patterns and trade ideas for Stochastics and RSI, the first place to click is where all the technical trading news is collected: # TechnicalAnalysis (see red arrow below).

After clicking on # TechnicalAnalysis, the next page you'll see will show the latest news for all types of patterns and indicators. In the example below, you can see that A.I.dvisor made a correct call about SMPL rising to a target price within a Cup-and-Handle bullish pattern, for a solid +22.21% gain.

On the left hand side of the page, you will find the menu of technical indicators to choose from, and that's where you can find the #Stochastic and #RSI indicators. In this case, we'll click on #RSI.

As you can see in the image below, A.I.dvisor will automatically generate the latest RSI news and will even deliver the Tickeron user trade ideas based on what it finds. On the left-hand side, you're also welcome to add additional criteria for the A.I. to look for, such as searching for only bullish RSI news.

In the image below, you can see that Milacron Holdings' (MCRN) RSI Indicator left the oversold zone, indicating that it could be headed for an upswing. You'll also notice that A.I.dvisor has statistics available on this indicator, but that the data is locked (see red circles below).

The good news is, all you have to do to discover the backtested statistics and the A.I.-calculated odds of success is to sign up for a FREE account on Tickeron.com!

Now that you know how to navigate your way to RSI Indicator news and trade ideas, let's take a look at how investors and traders can use the indicators for actionable trade ideas and actions.

As we mentioned in the previous chapter, RSI measures a security's price momentum on a scale from 0 to 100. When a security's RSI rises above the 70 level, traders see it as indicating the security is heading into overbought territory, and they'll look for sell signals. Conversely, when a security's RSI dips below 30, that's a sign that the security may be oversold. Traders respond accordingly.

In the chart above, Tickeron's A.I. discovered that TimkenSteel Corp's stock, TMST, rose up to an overbought level but then dipped back below 70 -- signaling that the selling could intensify as trader's rush to exit an overbought security. When a trader sees this A.I.dvisor-generated news, they may take it as a signal to sell TMST or perhaps explore put options on the stock.

The A.I.dvisor goes a step further, by backtesting other cases when TMST's RSI left the overbought zone. In 17 cases when that happened, 13 of them resulted in TMST's price falling -- indicating a successful prediction. Based on this data, A.I.dvisor projects that the odds of success for the current trading opportunity are 76%.

In this example, the RSI indicator approached the 30 level as shares of Hawaiian Holdings (HA) were being sold off -- indicating that selling momentum was progressively increasing. Once HA hit the 30 level (yellow dot on the chart), traders may be alerted to the idea that shares were oversold.

The A.I.dvisor found this crossover and created an alert when shares left the oversold zone -- meaning traders may have an opportunity to scoop up shares with the assumption that a price recovery could be coming. You can see how HA left the oversold zone back in late December, which also (looking at the chart) indicated an upswing ahead. Traders who see this A.I.dvisor signal might consider buying shares of HA or exploring call options on the stock.

A.I.dvisor goes a step further to provide the trader more data -- it backtests previous cases when HA's RSI Indicator left the oversold zone, finding 17 previous instances. A.I.dvisor determined that in 11 of those cases, the trading outcome was successful (the price increased). A.I. pegs the odds of success on this trade at 65%.

Now that you know how the Stochastic Oscillator works, you can take a look at the above chart and observe the trade idea established by A.I.dvisor. In this example, A.I.dvisor found that Toyota Motor's Stochastic Oscillator left the oversold zone on April 6 (see the orange dot), which may indicate that the stock's downtrend may be poised to reverse.

For traders, this could be an indication that it could be a good time to pick up shares of Toyota to try and capture the upside, or perhaps explore call options in an effort to profit if the share price does indeed rise.

As with the RSI news, A.I.dvisor goes a step further and backtests previous cases when Toyota's Stochastic Oscillator left the oversold zone, finding 67 previous instances. A.I.dvisor determined that in 54 of those cases, the trading outcome was successful (the price increased). In this instance, the A.I.dvisor pegs the trader's odds of success at 81%.

For investors and traders interested in seeing current #RSI and #Stochastics trade opportunities, and for those who want to learn more about A.I.-generated trade ideas, visiting Tickeron.com is the easiest way to get started.

For those interested in learning more about RSI and Stochastics as technical indicators, including how they were developed and how they're calculated, continue reading! The next chapters will give you everything you need to know about RSI, Stochastics, trade signals, and trade strategies.

Stochastics and RSI can bring clarity to the inherently chaotic behavior of markets. Their ability to accurately measure momentum provides traders with myriad overbought, oversold, and buy-sell signals that, when used in proper context, can confirm trends and influence profitable trading. Their widespread use is a testament to their efficacy, and no trader should lack a general knowledge of their use.

Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has a long track record as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years in the development of his proprietary trading and quantitative algorithms (now Tickeron's A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors with an easy-to-use interface.

The A.I. identifies patterns by their key geometrical elements, formed by changing stock prices when plotted on a chart. The A.I. does not take into consideration stock fundamentals, expert recommendations, market conditions, and so forth. Trading in stocks and other securities involves the risk of loss.

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