Bollinger Bands for Day Trading

Bollinger Bands are a pair of trading bands representing an upper and lower trading range for a particular market price. It is said that a particular security would trade within this trading range under normal circumstances. The Bollinger bands consist of moving averages on either side and are used for decisive entry and exit signals by the traders. The lines are plotted using standard deviation on either side of the moving averages. The volatile nature of the security changes the standard deviation values and thereby changes the width of these bands on either side.

Bollinger Bands can be used as a decisive trading system by investors and traders for all security classes and types. Bollinger Bands can also be used on any time frame. Bollinger bands along with the use of other indicators can be used to make decisive decision. Like when the price is nearing the upper end of the trading band with the help of an indicator like the RSI, traders can go short and when the stock is near the lower end of the trading band traders can use it as a signal to go long.

Key Features of Bollinger Bands

• ·         A move originating at the upper band tends to go all the way to the lower band and vice versa. This is generally the case for most of the securities and therefore is used extensively to enter or exit a particular trade
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• ·         Quick moves tend to happen when the Bollinger bands contract and there is less volatility in price. It is said that when prices are the least volatile, the propensity of a breakout is the highest
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• ·         At breakout, the current trend is generally sustained

Components of the Bollinger Band

• ·         Moving Average: Generally taken as 14 to 20 day moving average
• ·         Upper Band: Generally calculated as 2 standard deviation above the closing prices of the moving average
• ·         Lower Band: 2 standard deviations below the moving average

Buy & Sell Signals

Whenever the stock has hit the lower end of the Bollinger band it is a buy signal and prices generally move back towards the higher end of the trading band once they have crossed over the simple moving average in the middle. A sell signal is generated with the opposite

Rules for Bollinger Band Trading

·         Bollinger Bands are just a relative definition of a high or a low

·         These relative definitions with the use of indicators can be used to enter decisive buy and sell decisions

·         Appropriate indicators can be derived and should be used along with Bollinger Bands. For example: MACD, RSI, OBV (volume indicator) should all be used in conjunction with Bollinger bands

·         Volatility has already been used to calculate the width of the Bollinger Bands and therefore should not be used as a different indicator for buy and sell decisions

·         Use different indicators from different sets. Don’t use two momentum indicators, use one from Momentum and the other from volume if need be

·         Bollinger Bands are used to confirm pure price patterns like different types of Tops and Bottoms

·         Price generally moves within the Bollinger bands so can be up or down depending on the overall trend for long periods of time

·         Closes outside the Bollinger bands can just be a sign of continuation and not a breakout or reversal, so traders really need to use other indicators for confirming the trade entries

·         Bollinger Bands generally have a set default pattern with regards to their makeup and the standard deviation is used to as per the volatility in a particular stock

·         Non Descriptive moving averages should not be used for the creation of Bollinger bands

Understanding Loops and Repeats in R

Decision Trees

Decision Trees

Decision trees are, in general, a non-parametric inductive learning technique, able to produce classifiers for a given problem which can assess new, unseen situations and/or reveal the mechanisms driving a problem. They can be applied to both regression and classification problems.

Decision trees can be easy-to-understand with intuitively clear rules understandable to domain experts

Decision trees offer the ability to track and evaluate every step in the decision-making process. This is because each path through a tree consists of a combination of attributes which work together to distinguish between classes. This simplicity gives useful insights into the inner workings of the method.

Decision trees can handle both nominal and numeric input attributes and are capable of handling data sets that contain misclassified values

Decision trees can easily be programmed for use in real time systems.

They are relatively inexpensive computationally and work well on both large and small data sets

Decision trees are considered to be a non-parametric method. This means that decision trees have no assumptions about the space distribution and on the classifier structure

Validate Data in EXCEL using Validation List

Excel enables you to restrict the values a user can enter in a cell. By restricting values, you ensure that your worksheet entries are valid and that calculations based on them thereby are valid as well. During data entry, a validation list forces anyone using your worksheet to select a value from a drop-down menu rather than typing it and potentially typing the wrong information. In this way, validation lists save time and reduce errors.

To create a validation list, type the values you want to include into adjacent cells in a column or row. You may want to name the range. After you type your values, use the Data Validation dialog box to assign values to your validation list. Then copy and paste your validation list into the appropriate cells by using the Paste Special Validation option. You may want to place your validation list in an out of the way place on your worksheet or on a separate worksheet

Validation lists can consist of numbers, names of regions, employees, products, and so on.

Vamsidhar

www.pacegurus.com

Teaching Statistics

Being able to provide solid evidence-based arguments and critically evaluate claims based on data are important skills that all citizens should have. Hence the study of statistics worldwide at all educational levels is gaining more attention. The study of statistics provides students with tools, ideas and dispositions to react intelligently to information in the world around them. Reflecting this need to improve students’ ability to think statistically, statistical literacy and reasoning are becoming part of the mainstream school and university curricula in many countries. As a consequence, statistics education is becoming a thriving field of research and curricular development.

Statistics is vigorously gaining importance and recognition in today’s society thanks to the boom created by the buzz words Big Data and Analytics. Statistics is a central tool in moving science, economics, politics, schools, and universities forward. Quantitative information is omnipresent in media and in the everyday lives of citizens worldwide. Data are increasingly used to add credibility to advertisements, arguments, or personal and professional advice. Therefore, there is a growing public and policy consensus that being able to provide reliable and persuasive evidence-based arguments and critically evaluate data-based inferences are crucial skills that all citizens of the twenty-first century should have. All students consequently must become statistically literate and be able to reason statistically even at an informal level as part of their compulsory and lifelong education

Despite the increasing awareness of the importance of statistical literacy, statistics has been viewed by many students as difficult and unpleasant to learn. Many university instructors find statistics and research methods courses equally frustrating and unrewarding to teach. In schools, mathematics teachers often view statistics as a marginal strand in the mathematics curriculum and therefore minimize or ignore its teaching. Students equate statistics with mathematics and expect the focus to be on numbers, computations, formulas, and one right answer. They are uncomfortable with the messiness of data, the different possible interpretations based on different assumptions, and the extensive use of writing and communication skills. The dissatisfaction with students’ ability to think and reason statistically, even after formally studying statistics at the undergraduate and graduate level should lead to a re-examination of the field of statistics education

Many students still leave their course perceiving statistics as a set of tools and techniques that are soon forgotten. Even current methods of teaching continue to focus on the development of skills and have neglected to instill in their courses experiences that develop the ability to think statistically

There is a need for data driven, innovative approaches in teaching statistics keeping in mind the objective of statistics in the real world. This subject should be comfortable even to a students who fears mathematics because this subject is all about working with relationships and the use of technology simplifies the process further. All the statistics and business analytics courses designed by www.pacegurus.com keep in mind a student with very little knowledge of statistics, but has the attitude to learn, decipher from the data and make meaningful conclusions needed for the aspects of life. 

Bottom Line: Statistics is much much bigger than just a few calculations. It helps you in every walk of life. Don’t compare it with Maths and develop fear and allergy towards it. Start enjoying it……

Vamsidhar

www.pacegurus.com

Intermediate Statistics using SPSS - Workshop

Intermediate Statistics using SPSS - Workshop

www.pacegurus.com announces a 2-Day workshop on "Understanding Credit Derivatives" for the Corporate, Business Schools, any other learning institutions. Even individuals can get enrolled for one-one learning of the subject. The program would be conducted by VAMSIDHAR AMBATIPUDI at your campus. The detailed syllabus for the same can be found at

http://www.pacegurus.com/Intermediate-Statistics-SPSS.html

For further details do contact us at +91-9848012123. Request you to share the information with your friends and colleagues and do recommend PACEgurus for Finance, Investment, Actuaries, Risk Management, Statistics and Business Analytics trainings for your organization.

Integrating Strategy and Analytics

Integrating Strategy and Analytics

“The vast majority of strategic initiatives never succeed.”

“Organizations fail not because they have the wrong strategy but because they do not execute the strategy properly.”

Statements like these have been repeated so often they have become conventional wisdom. An entire industry of management consultants exists to help companies define the right strategy so that they won’t fail. Yet failure, or at least muddling through, is still much, much more common than outright success. Through analysis you can determine where execution works well and where it does not. With that information you can evaluate the solutions, determine which one(s) to implement

Organizations are complex places. Cognitively, people have a hard time focusing on too many things at once. A primary vehicle for reduced complexity is standard business processes. Unfortunately, simplification and standard processes are not enough. You have to recognize and manage the organizational complexity for successful strategy execution. The challenge for frontline and middle managers is how to deal with the competing strategic and operational objectives

Most analytics conducted today by the business and by HR are incomplete and cannot solve strategy execution problems on their own. You need a full causal model to diagnose the entire system and to understand what really drives behavior and performance. You need to know what drives performance in your organization to get strategy execution right. The problem with organizational analytics today is that they tell an incomplete story. Enterprise analytics and human capital analytics are conducted along parallel and separate tracks. Both attempt to determine why performance happens, yet each on its own can tell only part of the story. Without the complete story, we don’t really know the best ways to improve strategy execution and organizational effectiveness.

When you understand the link to the larger system, you can properly diagnose the root causes of behavior and motivation. It’s also the surest way to find changes to solve the problems instead of temporary solutions that only paper over the root causes

VAMSIDHAR AMBATIPUDI
www.pacegurus.com