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7 Technical Indicators to Build a Trading Toolkit

Written by admin. Posted in Technical Analysis

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Technical indicators are used by traders to gain insight into the supply and demand of securities and market psychology. Together, these indicators form the basis of technical analysis. Metrics, such as trading volume, provide clues as to whether a price move will continue. In this way, indicators can be used to generate buy and sell signals.

Seven of the best indicators for day trading are:

  • On-balance volume (OBV)
  • Accumulation/distribution line
  • Average directional index
  • Aroon oscillator
  • Moving average convergence divergence (MACD)
  • Relative strength index (RSI)
  • Stochastic oscillator

You don’t need to use all of them, rather pick a few that you find helpful in making better trading decisions. Learn more about how these indicators work and how they can help you day trade successfully.

Key Takeaways

  • Technical traders and chartists have a wide variety of indicators, patterns, and oscillators in their toolkit to generate signals.
  • Some of these consider price history, others look at trading volume, and yet others are momentum indicators. Often, these are used in tandem or combination with one another.
  • Here, we look at seven top tools market technicians employ, and that you should become familiar with if you plan to trade based on technical analysis.

Tools of the Trade

The tools of the trade for day traders and technical analysts consist of charting tools that generate signals to buy or sell, or which indicate trends or patterns in the market. Broadly speaking, there are two basic types of technical indicators:

  1. Overlays: Technical indicators that use the same scale as prices are plotted over the top of the prices on a stock chart. Examples include moving averages and Bollinger Bands® or Fibonacci lines.
  2. Oscillators: Rather than being overlaid on a price chart, technical indicators that oscillate between a local minimum and maximum are plotted above or below a price chart. Examples include the stochastic oscillator, MACD, or RSI. It will mainly be these second kind of technical indicators that we consider in this article.

Traders often use several different technical indicators in tandem when analyzing a security. With literally thousands of different options, traders must choose the indicators that work best for them and familiarize themselves with how they work. Traders may also combine technical indicators with more subjective forms of technical analysis, such as looking at chart patterns, to come up with trade ideas. Technical indicators can also be incorporated into automated trading systems given their quantitative nature.

1. On-Balance Volume

First up, use the on-balance volume indicator (OBV) to measure the positive and negative flow of volume in a security over time.

The indicator is a running total of up volume minus down volume. Up volume is how much volume there is on a day when the price rallied. Down volume is the volume on a day when the price falls. Each day volume is added or subtracted from the indicator based on whether the price went higher or lower.

When OBV is rising, it shows that buyers are willing to step in and push the price higher. When OBV is falling, the selling volume is outpacing buying volume, which indicates lower prices. In this way, it acts like a trend confirmation tool. If price and OBV are rising, that helps indicate a continuation of the trend.

Traders who use OBV also watch for divergence. This occurs when the indicator and price are going in different directions. If the price is rising but OBV is falling, that could indicate that the trend is not backed by strong buyers and could soon reverse.

Image by Sabrina Jiang © Investopedia 2020


2. Accumulation/Distribution Line

One of the most commonly used indicators to determine the money flow in and out of a security is the accumulation/distribution line (A/D line).

It is similar to the on-balance volume indicator (OBV), but instead of considering only the closing price of the security for the period, it also takes into account the trading range for the period and where the close is in relation to that range. If a stock finishes near its high, the indicator gives volume more weight than if it closes near the midpoint of its range. The different calculations mean that OBV will work better in some cases and A/D will work better in others.

If the indicator line is trending up, it shows buying interest, since the stock is closing above the halfway point of the range. This helps confirm an uptrend. On the other hand, if A/D is falling, that means the price is finishing in the lower portion of its daily range, and thus volume is considered negative. This helps confirm a downtrend. 

Traders using the A/D line also watch for divergence. If the A/D starts falling while the price is rising, this signals that the trend is in trouble and could reverse. Similarly, if the price is trending lower and A/D starts rising, that could signal higher prices to come.

Image by Sabrina Jiang © Investopedia 2020


3. Average Directional Index

The average directional index (ADX) is a trend indicator used to measure the strength and momentum of a trend. When the ADX is above 40, the trend is considered to have a lot of directional strength, either up or down, depending on the direction the price is moving.

When the ADX indicator is below 20, the trend is considered to be weak or non-trending.

The ADX is the main line on the indicator, usually colored black. There are two additional lines that can be optionally shown. These are DI+ and DI-. These lines are often colored red and green, respectively. All three lines work together to show the direction of the trend as well as the momentum of the trend.

  • ADX above 20 and DI+ above DI-: That’s an uptrend.
  • ADX above 20 and DI- above DI+: That’s a downtrend.
  • ADX below 20 is a weak trend or ranging period, often associated with the DI- and DI+ rapidly crisscrossing each other.

Image by Sabrina Jiang © Investopedia 2020


4. Aroon Indicator

The Aroon oscillator is a technical indicator used to measure whether a security is in a trend, and more specifically if the price is hitting new highs or lows over the calculation period (typically 25).

The indicator can also be used to identify when a new trend is set to begin. The Aroon indicator comprises two lines: an Aroon Up line and an Aroon Down line.

When the Aroon Up crosses above the Aroon Down, that is the first sign of a possible trend change. If the Aroon Up hits 100 and stays relatively close to that level while the Aroon Down stays near zero, that is positive confirmation of an uptrend.

The reverse is also true. If Aroon Down crosses above Aroon Up and stays near 100, this indicates that the downtrend is in force.

Image by Sabrina Jiang © Investopedia 2020


5. MACD

The moving average convergence divergence (MACD) indicator helps traders see the trend direction, as well as the momentum of that trend. It also provides a number of trade signals.

When the MACD is above zero, the price is in an upward phase. If the MACD is below zero, it has entered a bearish period.

The indicator is composed of two lines: the MACD line and a signal line, which moves slower. When MACD crosses below the signal line, it indicates that the price is falling. When the MACD line crosses above the signal line, the price is rising. 

Looking at which side of zero the indicator is on aids in determining which signals to follow. For example, if the indicator is above zero, watch for the MACD to cross above the signal line to buy. If the MACD is below zero, the MACD crossing below the signal line may provide the signal for a possible short trade.

Image by Sabrina Jiang © Investopedia 2020

6. Relative Strength Index

The relative strength index (RSI) has at least three major uses. The indicator moves between zero and 100, plotting recent price gains versus recent price losses. The RSI levels therefore help in gauging momentum and trend strength. 

The most basic use of an RSI is as an overbought and oversold indicator. When RSI moves above 70, the asset is considered overbought and could decline. When the RSI is below 30, the asset is oversold and could rally. However, making this assumption is dangerous; therefore, some traders wait for the indicator to rise above 70 and then drop below before selling, or drop below 30 and then rise back above before buying. 

Divergence is another use of the RSI. When the indicator is moving in a different direction than the price, it shows that the current price trend is weakening and could soon reverse.

A third use for the RSI is support and resistance levels. During uptrends, a stock will often hold above the 30 level and frequently reach 70 or above. When a stock is in a downtrend, the RSI will typically hold below 70 and frequently reach 30 or below.

Image by Sabrina Jiang © Investopedia 2020


7. Stochastic Oscillator

The stochastic oscillator is an indicator that measures the current price relative to the price range over a number of periods. Plotted between zero and 100, the idea is that, when the trend is up, the price should be making new highs. In a downtrend, the price tends to make new lows. The stochastic tracks whether this is happening.

The stochastic moves up and down relatively quickly as it is rare for the price to make continual highs, keeping the stochastic near 100, or continual lows, keeping the stochastic near zero. Therefore, the stochastic is often used as an overbought and oversold indicator. Values above 80 are considered overbought, while levels below 20 are considered oversold.

Consider the overall price trend when using overbought and oversold levels. For example, during an uptrend, when the indicator drops below 20 and rises back above it, that is a possible buy signal. But rallies above 80 are less consequential because we expect to see the indicator to move to 80 and above regularly during an uptrend. During a downtrend, look for the indicator to move above 80 and then drop back below to signal a possible short trade. The 20 level is less significant in a downtrend.

Image by Sabrina Jiang © Investopedia 2020


Is Technical Analysis Reliable?

Technical analysis is the reading of market sentiment via the use of graph patterns and signals. Various empirical studies have pointed to its effectiveness, but the range of success is varied and its accuracy remains undecided. It is best to use a suite of technical tools and indicators in tandem with other techniques like fundamental analysis to improve reliability.

Which Technical Indicator Can Best Spot Overbought/Oversold Conditions?

The relative strength index (RSI) is among the most popular technical indicators for identifying overbought or oversold stocks. The RSI is bound between 0 and 100. Traditionally, a reading above 70 indicates overbought ad below 30 oversold.

How Many Technical Analysis Tools Are There?

There are several dozen technical analysis tools, including a range of indicators and chart patterns. Market technicians are always creating new tools and refining old ones.

The Bottom Line

The goal of every short-term trader is to determine the direction of a given asset’s momentum and to attempt to profit from it. There have been hundreds of technical indicators and oscillators developed for this specific purpose, and this article has provided a handful that you can start trying out. Use the indicators to develop new strategies or consider incorporating them into your current strategies. To determine which ones to use, try them out in a demo account. Pick the ones you like the most, and leave the rest.

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2012 NBA All-Star Game Full Highlights And Game Recap.

Written by admin. Posted in Blog



) Kobe, KD and the West looked ready to deliver a quick KO.
Kevin Durant knew better.
“With all these great players on the floor, you never know what will happen,” Durant said. “Guys making big shots, and they cut it down to one. We were up 18.”
Just enough, it turned out, to hold off LeBron James and the East in the NBA All-Star game.
A bloodied Bryant scored 27 points, moving past Michael Jordan as the career scoring leader in the game, Durant had 36 in an MVP performance, and the Western Conference won 152-149 on Sunday night.
James and the East cut a 21-point deficit to one in the closing seconds, but weren’t able to move in front. James had 36 points and fellow Heat star Dwyane Wade finished with a triple-double.
“It was fun,” Durant said. “That’s the type of All-Star game you want to see.”
Blake Griffin scored 22 points for the West, which rang up 88 points in the first half, setting an All-Star record. But he won the game with his defense, picking off James’ pass when the East had a chance to tie in the final seconds.
“When I tried to throw it late, that’s what usually happens and it results in a turnover,” James said. “Definitely wish I could have that one back.”
Griffin then hit one free throw with 1.1 seconds left, and Wade was off on a 3-point attempt from the corner. He finished with 24 points, 10 rebounds and 10 assists, joining Jordan and James as the only players with All-Star game triple-doubles.
Bryant was bloodied by a hard foul from Wade and stayed in the game, but left to be evaluated afterward and did not speak to the media.
Durant’s win left Bryant tied for the All-Star record with his four MVP awards. But he got a bigger mark in his 13th All-Star game.
He broke Jordan’s record of 262 points on a dunk with 4:57 left in the third quarter and now has 271 for his career. He passed Oscar Robertson (246 points) and Kareem Abdul-Jabbar (251) earlier in the game.
“That record he got tonight, with KD in the league, I don’t know how long it’s going to last,” Wade said.
It nearly wasn’t enough, as the East’s comeback had the crowd filled with entertainers and athletes chanting for defense – never a part of the All-Star game vocabulary – in the final seconds.
James hit two long 3-pointers in the final period, and the East had a chance when Bryant, with the crowd loudly booing, missed a free throw with 18 seconds left and the West up 151-149.
But New Jersey’s Deron Williams was short on a 3-pointer, and after the East came up with it, James fired a pass into a crowd that Griffin intercepted.
On a colorful night in Orlando, from pregame performer Nicki Minaj’s pink and green hair to the neon sneakers many of the stars wore, Dwight Howard had nine points and 10 rebounds as the game’s host.
The NBA’s first All-Star game in Orlando in 20 years wasn’t close after 2 1/2 quarters. But players always say it gets competitive in the final five minutes, and James was again up for the challenge.
He hiked his scoring average to 25.9 points over his eight All-Star games, and someday he’ll probably take the record Bryant set Sunday.
But he couldn’t quite catch Kobe in the game.
“Being a competitor, no matter All-Star game or not, you don’t want to get blown out,” James said. “Of course not, when you’re going against your peers and you’re going against great players and you’re playing with great players. I just wanted to try to pick it up and see if we could make a run at it, and we did.”
With the 2-year-old Amway Center considered by many the finest arena in the league, the NBA brought its midseason showcase back to Orlando for the first time since the memorable 1992 game, when Magic Johnson was MVP three months after retiring from the league because of the HIV virus.
This one was once in jeopardy of being lost when the lockout lasted into late November. Without a settlement then, All-Star weekend may have been wiped out, as it was in 1999 following a work stoppage.
The party was saved.
James and Howard, wearing bright orange shoes, danced onto the stage for pregame introductions, Howard breaking into an enormous grin when fans gave him a thunderous ovation as the last All-Star introduced. He insists that he and Magic fans still have a love affair despite his trade request, understanding he still loves the city even if not his team, and urged everyone to ignore the trade talk for a weekend and have fun.
“We did it big for our city,” he said in brief pregame remarks to the crowd before the game.
Then Andrew Bynum blocked his first shot attempt.
The speedy Russell Westbrook had the East looking like it was standing still late in the first half, and it was 88-69 at the break.
Howard and Derrick Rose ditched their orange sneakers in the second half – James kept his – and the East quickly got back into it, trimming 12 points off its deficit in less than 6 minutes.

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Artificial Intelligence: What It Is and How It Is Used

Written by admin. Posted in A, Financial Terms Dictionary

Artificial Intelligence: What It Is and How It Is Used

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What Is Artificial Intelligence (AI)?

Artificial intelligence (AI) refers to the simulation of human intelligence by software-coded heuristics. Nowadays this code is prevalent in everything from cloud-based, enterprise applications to consumer apps and even embedded firmware.

The year 2022 brought AI into the mainstream through widespread familiarity with applications of Generative Pre-Training Transformer. The most popular application is OpenAI’s ChatGPT. The widespread fascination with ChatGPT made it synonymous with AI in the minds of most consumers. However, it represents only a small portion of the ways that AI technology is being used today.

The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal. A subset of artificial intelligence is machine learning (ML), which refers to the concept that computer programs can automatically learn from and adapt to new data without being assisted by humans. Deep learning techniques enable this automatic learning through the absorption of huge amounts of unstructured data such as text, images, or video.

Key Takeaways

  • Artificial intelligence (AI) refers to the simulation or approximation of human intelligence in machines.
  • The goals of artificial intelligence include computer-enhanced learning, reasoning, and perception.
  • AI is being used today across different industries from finance to healthcare.
  • Weak AI tends to be simple and single-task oriented, while strong AI carries on tasks that are more complex and human-like.
  • Some critics fear that the extensive use of advanced AI can have a negative effect on society.

Understanding Artificial Intelligence (AI)

When most people hear the term artificial intelligence, the first thing they usually think of is robots. That’s because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth.

Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include mimicking human cognitive activity. Researchers and developers in the field are making surprisingly rapid strides in mimicking activities such as learning, reasoning, and perception, to the extent that these can be concretely defined. Some believe that innovators may soon be able to develop systems that exceed the capacity of humans to learn or reason out any subject. But others remain skeptical because all cognitive activity is laced with value judgments that are subject to human experience.

As technology advances, previous benchmarks that defined artificial intelligence become outdated. For example, machines that calculate basic functions or recognize text through optical character recognition are no longer considered to embody artificial intelligence, since this function is now taken for granted as an inherent computer function.

AI is continuously evolving to benefit many different industries. Machines are wired using a cross-disciplinary approach based on mathematics, computer science, linguistics, psychology, and more.

Algorithms often play a very important part in the structure of artificial intelligence, where simple algorithms are used in simple applications, while more complex ones help frame strong artificial intelligence.

Applications of Artificial Intelligence

The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries. AI is being tested and used in the healthcare industry for suggesting drug dosages, identifying treatments, and for aiding in surgical procedures in the operating room.

Other examples of machines with artificial intelligence include computers that play chess and self-driving cars. Each of these machines must weigh the consequences of any action they take, as each action will impact the end result. In chess, the end result is winning the game. For self-driving cars, the computer system must account for all external data and compute it to act in a way that prevents a collision.

Artificial intelligence also has applications in the financial industry, where it is used to detect and flag activity in banking and finance such as unusual debit card usage and large account deposits—all of which help a bank’s fraud department. Applications for AI are also being used to help streamline and make trading easier. This is done by making supply, demand, and pricing of securities easier to estimate.

Types of Artificial Intelligence

Artificial intelligence can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon’s Alexa and Apple’s Siri. You ask the assistant a question, and it answers it for you.

Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.

Special Considerations

Since its beginning, artificial intelligence has come under scrutiny from scientists and the public alike. One common theme is the idea that machines will become so highly developed that humans will not be able to keep up and they will take off on their own, redesigning themselves at an exponential rate.

Another is that machines can hack into people’s privacy and even be weaponized. Other arguments debate the ethics of artificial intelligence and whether intelligent systems such as robots should be treated with the same rights as humans.

Self-driving cars have been fairly controversial as their machines tend to be designed for the lowest possible risk and the least casualties. If presented with a scenario of colliding with one person or another at the same time, these cars would calculate the option that would cause the least amount of damage.

Another contentious issue many people have with artificial intelligence is how it may affect human employment. With many industries looking to automate certain jobs through the use of intelligent machinery, there is a concern that people would be pushed out of the workforce. Self-driving cars may remove the need for taxis and car-share programs, while manufacturers may easily replace human labor with machines, making people’s skills obsolete.

The first artificial intelligence is thought to be a checkers-playing computer built by Oxford University (UK) computer scientists in 1951.

What Are the 4 Types of AI?

Artificial intelligence can be categorized into one of four types.

  • Reactive AI uses algorithms to optimize outputs based on a set of inputs. Chess-playing AIs, for example, are reactive systems that optimize the best strategy to win the game. Reactive AI tends to be fairly static, unable to learn or adapt to novel situations. Thus, it will produce the same output given identical inputs.
  • Limited memory AI can adapt to past experience or update itself based on new observations or data. Often, the amount of updating is limited (hence the name), and the length of memory is relatively short. Autonomous vehicles, for example, can “read the road” and adapt to novel situations, even “learning” from past experience.
  • Theory-of-mind AI are fully-adaptive and have an extensive ability to learn and retain past experiences. These types of AI include advanced chat-bots that could pass the Turing Test, fooling a person into believing the AI was a human being. While advanced and impressive, these AI are not self-aware.
  • Self-aware AI, as the name suggests, become sentient and aware of their own existence. Still in the realm of science fiction, some experts believe that an AI will never become conscious or “alive”.

How Is AI Used Today?

AI is used extensively across a range of applications today, with varying levels of sophistication. Recommendation algorithms that suggest what you might like next are popular AI implementations, as are chatbots that appear on websites or in the form of smart speakers (e.g., Alexa or Siri). AI is used to make predictions in terms of weather and financial forecasting, to streamline production processes, and to cut down on various forms of redundant cognitive labor (e.g., tax accounting or editing). AI is also used to play games, operate autonomous vehicles, process language, and more.

OpenAI released its ChatGPT tool late in 2022. It rapidly gained in popularity with millions of users being added each month in 2023. ChatGPT is considered a Weak AI, but it’s not strictly reactive and can respond creatively to a wide variety of topics.

How Is AI Used in Healthcare?

In healthcare settings, AI is used to assist in diagnostics. AI is very good at identifying small anomalies in scans and can better triangulate diagnoses from a patient’s symptoms and vitals. AI is also used to classify patients, maintain and track medical records, and deal with health insurance claims. Future innovations are thought to include AI-assisted robotic surgery, virtual nurses or doctors, and collaborative clinical judgment.

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