SCAN LIBRARY - Rule Definitions & Applications

Price Data

Price

Last Price – This is the most recent price of the most recent trade executed as reported on the tape/time and sales. It is the current price of the stock. Last price can be used as a metric to gauge how it’s trading compared to previous performance. It can be used as filter criteria to find stocks currently trading in a specific price range.

Examples:

XYZ stock is up 2% intra-day based on the Last Price.

Last Price is less than $5

Last Price is greater than 20-day moving average

Bid Price – This price represents how much buyers are willing to pay to purchase shares from sellers. Bidders provide liquidity by displaying their bid prices on the left side of level 1 and level 2 quotes. Retail traders tend to sell their shares on the bid price, thereby taking liquidity and possibly paying a pass-through fee on trades executed through an ECN route. Market sell orders are executed at the inside bid price. Traders trying to purchase shares on the bid can earn a pass-through rebate applied to commissions if their bid price is filled through an ECN route.

Example:

Bid Price > $5

Bid Price < Ask Price by 5% or more

Ask Price – This price represents what sellers are willing to accept for their shares. Also called the Offer Price. This price is located on the right-hand side of the level 1 and level 2 quotes. Retail traders tend to buy their shares on the ask price, especially when using market buy orders. This takes liquidity and can incur ECN pass-through fees tacked on the commission. Traders can earn ECN pass-through rebates by selling their shares on the ask price to provide liquidity. There is no guarantee the limit order will get filled. When certain stocks have a short-sell uptick stipulation/restriction, it requires short sale trades to only occur on the inside ask price.

Example:

Ask  Price > $5

Ask  Price > Bid Price by $0.10 or more

Spread – This is the difference between the inside bid price and the inside ask price. The U.S. equities markets have a standardized penny and nickel increment spreads for stocks, however the spreads will expand and contract throughout the day. Spreads are also a measure of liquidity. Stock with tight spreads of one or two-cents tend to indicate thick liquidity. As spreads get wider, the liquidity also gets thinner as slippage increases. Seasoned traders will try to split the spread by placing limit orders between the inside bid and inside ask. Active traders can scan for stocks with tighters spreads if looking for better liquidity.

Example:

Spread > $0.15

Spread is < $0.01

Range of Day (ROD) – This filter measures the difference between the high and low price of the day. The range is an indication of volatility, whereas a tight range indicates low volatility (contraction) and a wide range indicates higher volatility (expansion).  The relationship between previous RODs can be monitored to indicate contraction or expansion. Contractions often precede expansions illustrated by shrinking RODs prior to a breakout or breakdown and expanding RODs. The same applies inversely as expanding RODs precede contracting RODs.

Examples:

Range of Day > $2

Range of Day > 5-Day Average Daily Range

Volume Weighted Average Price (VWAP) – This popular ratio is calculated by the dollar value of all trades divided by the total number of shares traded since the market open. A moving average type line on an intraday chart displays this indicator, which is often used as a support/resistance level. A rising VWAP tends to indicate an uptrend and a falling VWAP indicates a downtrend. Institutions use VWAP to guage the quality of their transactions and numerous algorithms bet on VWAP reversions when prices extend too far away. VWAP cross signals are popular trade triggers.

Example:

Last Price < VWAP 

Last Price > VWAP by 1% or less

Beta – This ratio is a measure of volatility compared to the S&P 500 index, which represents the general market. A beta of 1 implies that the stock moves proportionately to the market. A beta of 2 implies the stock moves twice as much as the market, meaning a 2% move in the S&P 500 index should result in a 4% move in a stock with a beta of 2. Low beta can be used to scan for stocks moving with the market.

Example:

Beta  > 2

Beta < 2    

Change

Net Change – This is the dollar value difference between the opening price and the closing price for a selected time period. Traders use this scan to find stocks that are trending strongly either up or down. The net change only takes into account the open and close price and ignores high and lows, which gives a clearer picture of the true strength of weakness.

Examples:

5 min net change > $0.50

30 min net change > $2.00

Net Change > 10-Day Average Daily Range

You can use the different time periods to align with your trading timeframes.

Filters Available:

5 Min Net Change

10 Min Net Change

20 Min Net Change

30 Min Net Change

Net Change From Open – This is the dollar value difference between the last price (current price) and the day’s open price. It is a measure of the net intra-day performance of the underlying stock. Traders use this to find stocks that are showing the largest price gains or losses on the day.

Example:

Net change from open  > 10%

% Change – This is the percentage value difference between the last price and the closing price of the previous time period.  Traders use this scan to find stocks that are trending strongly either up or down. The % change only takes into account the open and close price to give a clearer picture of the strength or weakness of the stock.

Examples:

5 min % change > 2%

% Change > 10%

You can use the different time periods to align with your trading timeframes.

Filters Available:

5 Min Net % Change

10 Min Net % Change

20 Min Net % Change

30 Min Net % Change

% Change From Open – This is the percentage value difference between the last price (current price) and the day’s open price. It is a measure of the net intra-day performance of the underlying stock. Traders use this to find stocks that are showing the largest percentage gains or losses on the day.

Example:

% change from open  > 5

Highs

Day High – This filter triggers when the last price is at the highest price of the day. Traders use day high as a filter to find strong stocks to consider buying into the uptrend or shorting in anticipation of a reversion or reversal.

Example:

Last Price < Day High by 1% or less

Today’s Close < Day High by 1% or Less

You can apply different time periods to gauge the significance of the new high.

Filters Available:

5-Day High

10-Day High

20-Day High

40-Day High

26-Week High

52-Week High

Yesterday’s High – This filter triggers when the last price hits yesterday’s highest price. Traders use yesterday’s high to find stocks that may either form a double top reversal or a breakout pattern. Stocks that breakout through yesterday’s high can trigger short covering rally to spur a new uptrend. Yesterday’s high tends to start off as a resistance level, which can turn into a new support level after a breakout.

Example:

Last Price > Yesterday’s High

Yesterday’s High > 20-Day High

Lows

Day Low – This filter triggers when the last price is at the lowest price of the day. Traders use day low as a filter to find weak stocks to consider short selling into the downtrend or buying in anticipation reversal bottom.

Example:

Last Price < Day Low by 1% or less

Today’s Close < Day Low by 1% or Less

Day Low > 10-Day Low

You can apply different time periods to gauge the significance of the new low. The longer the time period of the low, the closer the stock may be to a bottom.

Filters Available:

5-Day Low

10-Day Low

20-Day Low

40-Day Low

26-Week Low

52-Week Low

Yesterday’s Low – This filter triggers when the last price hits yesterday’s lowest price. Traders use yesterday’s low to find stocks that may either form a double bottom reversal or a breakdown pattern. Stocks that breakdown through yesterday’s low can trigger more stop-losses and panic selling. Yesterday’s low tends to start off as a support level, which can turn into a new resistance level after a breakdown.

Example:

Last Price < Yesterday’s Low

Yesterday’s Low > 5-Day Low

Range

Day (Daily) Range – This measures the dollar value difference between the lowest price and highest price of the day. Traders use intraday day range as a measurement of volatility. Stocks trading in a smaller day range represent low volatility and price consolidation. Stocks trading in a large day range tend to represent trending stocks and price expansion.

Example:

5-Day Average Daily Range > $2

Day Range > 10-Day Average Daily Range

You can also select the average daily range for specific periods of time to determine if the volatility and pricing is suitable for your trading style.

Filters Available:

2-Day Avg. Daily Range

5-Day Avg. Daily Range

10-Day Avg. Daily Range

15-Day Avg. Daily Range

20-Day Avg. Daily Range

30-Day Avg. Daily Range

60-Day Avg. Daily Range

Yesterday’s Range – This measures the dollar value difference between yesterday’s lowest price and highest price. Traders use yesterday’s range to find stocks forming an “inside” day indicating price compression, which usually precedes a price expansion in the form of a breakout or breakdown. Stocks trading above or below yesterday’s range can indicate early price expansion in the form of a breakout or breakdown.

Example:

Day Range > Yesterday’s Range

Yesterday’s Range > $3

Open

Today’s Open – This filter is based on the first trade of the day, which establishes the line in the sand where performance is measured for the rest of the day, excluding price gaps. Net change is based on the different between today’s open price and last price. The open price can also serve as a support or resistance level

Example:

Last Price > Today’s Open

Today’s Open > Yesterday’s Close by 10% or More

You can also select the open price for different days.

Filters Available:

Open 2 Days Ago

Open 3 Days Ago

Open 4 Days Ago

Yesterday’s Open – This filter is based on yesterday’s opening price and can serve as a support or resistance level. Stocks trading above yesterday’s open price indicate price strength as yesterday’s open acts as a support level. Stocks trading trading below yesterday’s open indicate weakness as yesterday’s open acts like a price resistance. Stocks trading above yesterday’s open indicate strength as yesterday’s open price acts like a support.

Last Price > Yesterday’s Open

Yesterday’s Open > Yesterday’s Close

Close

Today’s Close – This is the price of last trade of the day, which establishes the line in the sand where performance is measured after hours and the next day. After hours price gaps are based on today’s close.

Example:

Today’s Close > Yesterday’s Close

Today’s Close > $10

Today’s Close < Day High by 1% or less

Today’s Close > VWAP

Today’s Close > 50-Day Simple Moving Average by 1% or less

You can also select the Close for different days.

Filters Available:

Close 2 Days Ago

Close 3 Days Ago

Close 4 Days Ago

Yesterday’s Close – This filter is based on yesterday’s last trade price. Pre-market price gaps are based on yesterday’s close. Intraday performance is also measured against the net gain or loss from yesterday’s close price. Stocks trading above yesterday’s close indicate price strength as yesterday’s close acts as a support level. Stocks trading trading below yesterday’s close indicate weakness, as yesterday’s close can be a price resistance.

Example:

Yesterday’s Close > Yesterday’s Open

Today’s Open > Yesterday’s Close

Last Price > Yesterday’s Close

Liquidity

Share Volume

Day’s Share Volume – This is the total number of shares traded intraday since the market open at 9:30 am EST. Share volume cumulatively counts every share that changes hands throughout the day. This means if you buy 100 shares and sell back the same 100 shares, it counts as 200 shares of volume for the day. The day’s share volume can be a measure of liquidity and interest in the underlying shares. Heavy volume implies high liquidity and interest, whereas light volume implies thinner liquidity and interest.

Example:

Day’s Share Volume > 2 million

Day’s Share Volume > 5-Day Avg. Volume  by 100% or more

While a single day’s share volume doesn’t provide much information, using the average daily volume in the context of a pre-selected range of days can better help to measure when volume is abnormal.

Filters Available:

2-Day Avg. Volume

5-Day Avg. Volume

10-Day Avg. Volume

15-Day Avg. Volume

20-Day Avg. Volume

30-Day Avg. Volume

60-Day Avg. Volume

Yesterday’s Share Volume – This is the total number of shares traded the prior day. It can be used as a reference point to scan for stocks trading abnormally heavy volume. Breakouts and breakdowns that are accompanied with higher than normal volume tend to have more stability and liquidity.

Example:

Day’s Share Volume > Yesterday’s Share Volume by 300%

Yesterday’s Share Volume > 30-Day Average Share Volume

Yesterday’s Share Volume > 5 Million

Trading Size Volume – This is used to filter trades by volume size. It can be used to spot block trades, which is a sign of institutional activity. A series of large block trades can signal institutional buying and selling, which in turn triggers more participants and liquidity.

Example:

Tradin Size Volume > 50,000   

Dollar Volume

Day’s $ Volume – This is the total dollar value of all the shares traded since the open.  This value can be used as a gauge of liquidity. Larger $ volume tends to imply larger liquidity and vice versa.  

Example:

Day’s $ Volume > $100 million

Day’s $ Volume > Yesterday’s $ Volume

Yesterday’s $ Volume – This is the total dollar value of all the shares traded the prior day.  This value can be used as a measuring unit to filter exceptional $ volume, which may represent a breakout or breakdown.

Example:

Yesterday’s $ Volume > $5 Million

2-day Avg. $ Volume – This is the average $ value for all the volume traded during a specified 2-day time period.

Example:

$ Volume >  2-Day Avg. $ Volume by 100% or more

# of Trades

Day’s # of Trades– This is the total number of individual trades executed since the open.  Larger # of trades reflects heavy activity, interest and liquidity in the underlying stock.

You can filter by a daily average number of trades to determine if trading activity is rising or falling. It can also be used as a unit to measure spikes in trading activity, which often precede breakouts and breakdowns as more participants are engaged with the stock.

Example:

# of Trades  > 5-Day Avg. # of Trades by 150%

# of Trades > 1000

Filters Available:

2-Day Avg. # of Trades

5-Day Avg. # of Trades

10-Day Avg. # of Trades

15-Day Avg. # of Trades

20-Day Avg. # of Trades

30-Day Avg. # of Trades

60-Day Avg. # of Trades

Yesterday’s # of Trades– This is the total number of individual trades executed during the prior trading day.  Larger # of trades reflects heavy activity, interest and liquidity in the underlying stock.  It can also be used as a unit to measure spikes in today’s trading activity.

Filters Available:

Yesterday’s # of Trades > 2000

Yesterday’s # of Trades  < # of Trades

Fundamentals

Financials

Revenue – This total gross sales for the underlying company, also known as the top line. Revenue is reported quarterly on the10-K filing. It is a measure of top line growth. Revenues are segmented annually, quarterly, consecutively and year-over-year (YOY). YOY revenue refers to the same quarter for the prior year.

Example:

Revenue > $50 Million

Gross Profit– This is profit resulting from gross revenues minus the cost of goods sold, which includes labor and supplies. The difference between revenue and gross profit is referred to as gross margin, sales profit and gross income. Gross profit can be used as a percentage to measure the efficiency of operations. It appears on the income statement.  Gross profit can be used as an indicator to find profitable (or unprofitable) companies.

Example:

Gross Profit  > $1 Million

Gross Profit < Revenue by 50% or less

EBITDA– This is Earnings Before Interest Taxes Depreciation and Amortization (EBITDA), used to measure operating performance free of taxes, financing and accounting factors.  It’s used to measure the organic operating performance of a company.

Example:

EBITDA  > $5 Million

Cash– This the total cash available in the company as reported on the income statement. Cash is a liquid asset that immediately adds to valuation. You can scan for companies that have large amounts of cash or companies that may be close to bankruptcy.

Examples:

Cash > $50 Million

Cash < $100,000

Debt– This is a monetary obligation owed by the company on loans, mortgages, debentures, credit facilities or bond offerings. Debt is considered a liability. Long-term debt represents monies owed that exceed a 12-month period. Companies with large debt are susceptible to cash flow problems down the road. Debt is used in many financial ratios to measure financial health.

Example:

Debt  > Cash

Debt > $10 Million

Trailing P/E– This is a financial metric that is calculated by dividing the share price by the prior 12 month earnings-per-share (EPS) to derive the price-earnings (P/E) ratio.  P/E is used as a comparative measure of valuation against peers, industry and benchmarks indicies.

Example:

Trailing P/E < 21

Forward P/E– This is a financial metric that is calculated by dividing the share price by the forward projected earnings-per-share (EPS) to derive the price-earnings (P/E) ratio. The forward EPS is gathered from the forward guidance from the company or the consensus analyst estimates.  Forward P/E is an estimate, whereas trailing P/E is actual since it’s based on achieved results.

Examples:

Forward P/E < 17

Forward P/E < Trailing P/E

Share Structure

Market Capitalization – This represents the total market value of a publicly traded company, calculatted by multiplying the last price (of the stock) by the total number of outstanding shares. Market Cap is used to classify the size of the underlying company ranging from mega-cap ($200 billion or more), large-cap ($10 billion to $200 billion), mid-cap ($2 billion to $10 billion), small-cap ($300 million to $2 billion), micro-cap ($50 million to $2 billion) and nano-cap (under $50 million). Risk is proportionate to the market-cap. Mega-caps are viewed as less risky due to the huge liquidity and heavy insitutional ownership that tends to stabilize price while nano-caps are the most risky and illiquid. 

Examples:

Market Cap < $50 Million

Market Cap > $500 Million

Shares Outstanding – This represents the total number of stock shares that have been issued by the company including restricted shares. Shares outstanding is a component of many financial metrics to determine valuation like market capitalization and performance like earnings per share.

Example:

Shares Outstanding  > 1 billion

Share Float – This represents the total number of shares that are available to trade. Restricted stock is unregistered shares held by insiders and affiliates that must vest and meet obligations before becoming free trading shares. The share float is the true measure of supply in the open market. Heavy floats provide more liquidity and price stability. Thin floats can be very volatile as liquidity is thin, which makes it susceptible to large price moves, spread slippage and short-squeezes.

Example:

Float  < 2 million

Float < Share Outstanding by 70% or more

% Held By Insiders – This is the percentage of outstanding shares owned by insiders of the company and beneficial owners who own 10% or more of the voting shares. Value investors tend to favor companies with a high percentage of insider ownership believing insiders were look out for their best interest and improve shareholder value as well.  

Example:

% Held By Insiders  > 70%

% Held By Insiders  > % Held By Institutions 

% Held By Institutions – This is the percentage of outstanding shares owned by insitutions. High institutional ownership tends to provide more stability and liquidity since institutions tends to be long-term holders.

Example:

% Held By Institutions  > 80%

% Held By Institutions  > % Held By Insiders 

Short Interest

Shares Short – This represents the total number of shares that have been sold short. These shares are borrowed from the total outstanding shares.  A high number of short shares can be construed as bearish sentiment for the underlying stock.

Example:

Shares Short  > 10 million

Short % of Float – This represents the percentage of the float that has been sold short.  All stocks have shares short as market makers and specialists regularly borrow shares to meet demand. High short percentage of float indicates bearish sentiment, assuming the short-sellers know something that the public doesn’t. When short percentage of float grows higher than 25%, the probability of a short squeeze rises.  

Examples:

Short % of Float  > 25%

Short Prior Month – This represents the percentage of the float that has been sold short.  All stocks have shares short as market makers and specialists regularly borrow shares to meet demand. High short interest is considered bearish, assuming the short-sellers know something that the public doesn’t. When short float grows higher than 25%, the probability of a short squeeze rises.  

Shares Short > Shares Short Prior Month

Short Prior Month > 10 Million Shares

% Change Month Over Month (MOM) – This represents the rise or fall of short interest over the prior month. Falling short interest is considered bullish and rising short interest is considered bearish.

Example:

Short Float % Change Month Over Month> 10

Days To Cover – This is the theoretical numbers of days needed to completely cover all short sales in a stock. The total shares short divided by the average daily volume calculate days to cover. It’s often used to gauge the potential magnitude of a short-squeeze, with more days to cover equating to larger magnitude and duration of the squeeze.

Example:

Days To Cover > 20

Indicators

Accumulation Distribution Line – This volume-based indicator measures the cumulative money flow in and out of a stock. It can be used to confirm a price trend when overlayed on a price chart. A rising ADL indicates an uptrend while a falling ADI indicates a downtrend. This indicator can be enhanced when combined with other price indicators and momentum indicators. 

Examples:

Accumulation Distribution Line < Last Price

Accumulation Distribution Line > 50-period moving average

Accumulation/Distribution Oscillator – This is the oscillator version of the Accumulation Distribution Lines (ADL) place on a separate chart, using zero as the base line. The accumulation/distribution oscillator (ADO) always reverts back to the zero line. When ADO rises through the zero line, it confirms an uptrend. When ADO falls through the zero line, it confirms a downtrend. Traders can play price reversal trades on ADO reversions back to the zero line and breakout/breakdowns when it crosses the zero line.

Examples:

Accumulation/Distribution Oscillator > 0

Accumulation/Distribution Oscillator < 0

Average Directional Index (ADX) – This oscillator is used to measure the strength of a price trend. ADX is non-directional, meaning it doesn’t show the direction of the trend. Instead, ADX confirms a strong trend when it rises above 20. The higher the ADX value goes, the stronger the trend. ADX under 20 signifies lack of trend.  

Examples:

Average Directional Index > 20   

Average Directional Index < 20   

Average True Range – This is a volatility measurement indicator. High volatility stocks are reflected by higher average true range (ATR) above 20. Lower volatility stocks are reflected by lower ATR under 20. Traders can use ATR crossovers through 20 for potential triggers.

Examples:

Average True Range > 20   

Averafe True Range < 20   

Bollinger Bands – This indicator measures both volatility and price range by using a combination of a 20 period moving average (Middle Bollinger Band) and two envelopes (Upper and Lower Bollinger Bands) set at a 2 standard deviation away.  The upper Bollinger Band envelope is the nominal top range of price action, while the lower Bollinger Band envelope is the nominal bottom of the range. Prices tend to revert off the Bollinger Bands back to the middle Bollinger Band, which acts as the trend line. Each of these Bollinger Bands are inflection points where price will deflect or pierce through towards the next Bollinger Band.

Examples:

Last Price > Upper Bollinger Band

Last Price <  Middle Bollinger Band

Last Price > Lower Bollinger Band

Upper Bollinger Band > Lower Bollinger Band by 20% or more

Balance of Power – This is another indicator that tracks the activity between buyers and sellers using the zero line. Generally, when balance of power is above the zero line, it indicates systemic buying and when balance of power falls under the zero line, it indicattes system selling. Traders use this indicator in combination with other indicators to spot price reversal triggers and trend pullbcaks at the zero line tests. 

Examples:

Balance of Power > 0

Balance of Power < 0   

Commodity Channel Index – This is a momentum oscillator that identifies overbought and oversold conditions and their inflection points to use as buy and sell triggers.  The Commodity Channel Index (CCI) is plotted on a chart with a zero line, 100 band and – 100 band. Stocks become overbought when CCI rises through the 100 band and sell triggers form when CCI falls back down through the 100 band. Stocks are oversold when CCI falls below the – 100 band and trigger buy signals when it rises back  up through the –100 band.

Examples:

Commodity Channel Index < 100 by 2% or less

Commodity Channel Index > –100

Commodity Channel Index > –100

Exponential Moving Average – This indicator acts as a support and resistance level and trend line. Unlike a simple moving average, the exponential moving average places more weight on the most recent prices, which is why it’s also known as a weighted moving average. Traders use the exponential moving average (EMA) to indicate trend direction using crossovers for entry and exit triggers.

Example:

Last Price > 50-Period Exponential Moving Average

You can use a combination of two Exponential Moving Average lines for crossover signals to identify new trends.

Examples:

20-Day Exponential Moving Average crossover above the 50-Day Exponential Moving Average

50-Day Exponential Moving Average crossover below the 200-Day Exponential Moving Average

Moving Average Convergence Divergence (MACD) – This indicator measures momentum using two exponential moving average oscillators on a 0.5, zero line and -.05 scale chart. The lead exponential moving average is the MACD line and the laddard exponential moving average is the Signal Line. The MACD indicates overbought conditions above the 0.5 that trigger a sell signal when both oscillators cross back down under 0.5. The MACD indicates oversold conditions below the -0.5 that trigger a buy signal when MACD oscillators cross back up through 0.5.

Examples:

Moving Average Convergence Divergence < 0.5

Moving Average Convergence Divergence > -0.5

MACD Histogram – This is the histogram version of the moving average convergence divergence indicator using a bar chart instead of oscillation liness on the same 0.5, zero line and –0.5 scale.  Focus is placed on the zero line cross to indicate a trend reversal.

Examples:

MACD Histogram > 0

MACD Histogram < 0

MACD histogram can be used in unison with the MACD oscillators to pinpoint “safer” entries that correlate with the oscillator crossovers at 0.5 and – 0.5 lines with the additional confirmation of the histogram rise or fall at the zero line.

Example:

MACD > –0.5 and MACD Histogram > 0

MACD Signal Line  – This is lagging MACD exponential moving average oscillator. The buy or sell trigger is signaled when the lead oscillator forms a crossover through the laggard (Signal Line) oscillator. The strength of the crossover will depend on the proxmity of the trigger on the scale.

Examples:

MACD Signal Line > 1

MACD Signal Line < 0

Money Flow Index (MFI) – This oscillator illustrates buying and selling pressure utilizing price and volume data on a 20 and 80 band/line trigger scale. Similar to the stochastic, the Money Flow Index (MFI) uses a single oscillator to monitor overbought conditions above the 80 band and oversold conditions below the 20 band. Buy signals trigger when MFI crosses up through the 20 band and sell signals trigger when MFI cross down below the 80 band.

Examples:

MFI < 80 by 2% or less

MFI > 20 by 2% or Less

MFI > 80

MFI < 20

Rate of Change (ROC) – This is a single line oscillator that measures the velocity of price momentum on a zero line scale. Rate of Change (ROC) places the same weighting between current and past values. ROC above zero tends to be bullish and vice versa under the zero line being bearish. Overbought conditions tend to form above 30 Oversold conditions form under – 30.

Examples:

ROC > 0

ROC < 0

Relative Strength Index (RSI) – This is a single line momentum oscillator that measures the velocity of price movement on a 0 to 100 line/band scale with triggers on the 30 and 70 bands. RSI under 30 is oversold as a buy trigger forms when it crosses back up through the 30 band. RSI above 70 is overbought and sell trigger forms when RSI falls back under 70 band. RSI can be combined with other price indicators to time precision entries.

Examples:

RSI > 70

RSI < 30

RSI > 30 by 2% or Less

Parabolic Stop and Reverse (PSAR) – This trend indicator provides a rolling trailing stop line that triggers when price crosses through it.  The reverse trade triggers when the PSAR starts to plot again as a support. The accelertion factor known as STEP can be configured with higher plots to increase sensitivity, which gives earlier signals but are prone to more choppiness and wiggles. PSAR is most effective when stocks are uptrending or downtrending. 

Examples:

Last Price > PSAR

Last Price < PSAR

Last Price < PSAR by 2% or Less

Simple Moving Average – This building block price indicator takes the aggregate average of a specified time period and plots dynamically to create a moving average line, which illustrates trend and acts as a support or resistance. Using two simple moving averages like a 5-period and 15-period gives a cleared visual of the trend along with trend channel, with the crossovers as trend reversal triggers.

Examples:

5-period Moving Average > 15-period moving average

50-period Moving Average < 200-period moving average by 1% or Less

Last Price > 10-Day Simple Moving Average

Stochastic – This is a momentum oscillator that gauges overbought and oversold conditions on a 0 to 100 scale with signal triggers at the 20 and 80 bands. It is comprised of two oscillators, a lead and laggard. The lead stochastic is %K and laggard stochastic is %D, which is a 3-period moving average of  %K. Due to the jerkiness factor, a smoother version of both the %K and %D were created by further smoothing both out with a 3-period simple moving average (SMA) to create the %K slow and %D slow, lead and laggards. The default setting on most platforms is %K of 14, %D of 3 with a 3-period SMA smoothing. The smoothing factor can be adjusted with a longer period simple moving average to create clearer separation between the lead and laggard oscillators, like the commonly used 5-period moving average.

Prices become overbought when stochastic rise above the 80 band and trigger a sell signal when the stochastic oscillators crosses back under the 80 band. Prices are oversold when the stochastic falls below 20 band, and trigger a buy signal when the stochastic cross back up through the 20 band.

Examples:

Stochastic < 80

Stochastic > 20

TRIX – This is a price oscillator using the zero base line scale. TRIX above 0.00 indicate an uptrend and TRIX below 0.00 indicate a downtrend. TRIX divergence buy signals triggers when stock prices hit new lows, while TRIX is rising on the 0.00 line crossover. TRIX divergence sell signals trigger when stocks prices hit new highs, while TRIX is falling on the 0.00 line crossover 

Examples:

TRIX > 0

TRIX < 0