RSI Trade Settings Explained + 4 Unique Trading Strategies
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Predicting SARS-Cov-2 Infection Trend Using Technical Analysis Indicators
medRxiv preprint doi: https://doi.org/10.1101/2020.05.13.20100784; this version posted May 20, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Predicting SARS-CoV-2 infection trend using technical analysis indicators Marino Paroli and Maria Isabella Sirinian Department of Clinical, Anesthesiologic and Cardiovascular Sciences, Sapienza University of Rome, Italy ABSTRACT COVID-19 pandemic is a global emergency caused by SARS-CoV-2 infection. Without efficacious drugs or vaccines, mass quarantine has been the main strategy adopted by governments to contain the virus spread. This has led to a significant reduction in the number of infected people and deaths and to a diminished pressure over the health care system. However, an economic depression is following due to the forced absence of worker from their job and to the closure of many productive activities. For these reasons, governments are lessening progressively the mass quarantine measures to avoid an economic catastrophe. Nevertheless, the reopening of firms and commercial activities might lead to a resurgence of infection. In the worst-case scenario, this might impose the return to strict lockdown measures. Epidemiological models are therefore necessary to forecast possible new infection outbreaks and to inform government to promptly adopt new containment measures. In this context, we tested here if technical analysis methods commonly used in the financial market might provide early signal of change in the direction of SARS-Cov-2 infection trend in Italy, a country which has been strongly hit by the pandemic. -
Stock Chart Pattern Recognition with Deep Learning
Stock Chart Pattern recognition with Deep Learning Marc Velay and Fabrice Daniel Artificial Intelligence Department of Lusis, Paris, France [email protected] http://www.lusis.fr June 2018 ABSTRACT the number of patterns recognized implies having a human examining candlestick charts in order to deduce signal char- This study evaluates the performances of CNN and LSTM acteristics before implementing the detection using condi- for recognizing common charts patterns in a stock historical tions specific to that pattern. Adding different parameters data. It presents two common patterns, the method used to to modulate ratios allows us to tweak the patterns’ charac- build the training set, the neural networks architectures and teristics. This technique does not have any generalization the accuracies obtained. potential. If the pattern is slightly outside of the defined Keywords: Deep Learning, CNN, LSTM, Pattern recogni- bounds, it will not be detected, even if a human would have tion, Technical Analysis classified it otherwise. Another solution is DTW3 which consists in computing 1 INTRODUCTION the distance between two time series. DTW allows us to Patterns are recurring sequences found in OHLC1 candle- recognize a pattern that could vary in size and length. To stick charts which traders have historically used as buy and use this algorithm, we must use reference time series, which sell signals. Several studies, notably by Bulkowski2, have have to be selected by a human. The references must gener- found some correlation between patterns and future trends, alize well when compared with signals similar to the pattern although to a limited extent. The correlations were found to in order to capture the whole range. -
Relative Strength Index for Developing Effective Trading Strategies in Constructing Optimal Portfolio
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 19 (2017) pp. 8926-8936 © Research India Publications. http://www.ripublication.com Relative Strength Index for Developing Effective Trading Strategies in Constructing Optimal Portfolio Dr. Bhargavi. R Associate Professor, School of Computer Science and Software Engineering, VIT University, Chennai, Vandaloor Kelambakkam Road, Chennai, Tamilnadu, India. Orcid Id: 0000-0001-8319-6851 Dr. Srinivas Gumparthi Professor, SSN School of Management, Old Mahabalipuram Road, Kalavakkam, Chennai, Tamilnadu, India. Orcid Id: 0000-0003-0428-2765 Anith.R Student, SSN School of Management, Old Mahabalipuram Road, Kalavakkam, Chennai, Tamilnadu, India. Abstract Keywords: RSI, Trading, Strategies innovation policy, innovative capacity, innovation strategy, competitive Today’s investors’ dilemma is choosing the right stock for advantage, road transport enterprise, benchmarking. investment at right time. There are many technical analysis tools which help choose investors pick the right stock, of which RSI is one of the tools in understand whether stocks are INTRODUCTION overpriced or under priced. Despite its popularity and powerfulness, RSI has been very rarely used by Indian Relative Strength Index investors. One of the important reasons for it is lack of Investment in stock market is common scenario for making knowledge regarding how to use it. So, it is essential to show, capital gains. One of the major concerns of today’s investors how RSI can be used effectively to select shares and hence is regarding choosing the right securities for investment, construct portfolio. Also, it is essential to check the because selection of inappropriate securities may lead to effectiveness and validity of RSI in the context of Indian stock losses being suffered by the investor. -
Forecasting Direction of Exchange Rate Fluctuations with Two Dimensional Patterns and Currency Strength
FORECASTING DIRECTION OF EXCHANGE RATE FLUCTUATIONS WITH TWO DIMENSIONAL PATTERNS AND CURRENCY STRENGTH A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY BY MUSTAFA ONUR ÖZORHAN IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PILOSOPHY IN COMPUTER ENGINEERING MAY 2017 Approval of the thesis: FORECASTING DIRECTION OF EXCHANGE RATE FLUCTUATIONS WITH TWO DIMENSIONAL PATTERNS AND CURRENCY STRENGTH submitted by MUSTAFA ONUR ÖZORHAN in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Engineering Department, Middle East Technical University by, Prof. Dr. Gülbin Dural Ünver _______________ Dean, Graduate School of Natural and Applied Sciences Prof. Dr. Adnan Yazıcı _______________ Head of Department, Computer Engineering Prof. Dr. İsmail Hakkı Toroslu _______________ Supervisor, Computer Engineering Department, METU Examining Committee Members: Prof. Dr. Tolga Can _______________ Computer Engineering Department, METU Prof. Dr. İsmail Hakkı Toroslu _______________ Computer Engineering Department, METU Assoc. Prof. Dr. Cem İyigün _______________ Industrial Engineering Department, METU Assoc. Prof. Dr. Tansel Özyer _______________ Computer Engineering Department, TOBB University of Economics and Technology Assist. Prof. Dr. Murat Özbayoğlu _______________ Computer Engineering Department, TOBB University of Economics and Technology Date: ___24.05.2017___ I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work. Name, Last name: MUSTAFA ONUR ÖZORHAN Signature: iv ABSTRACT FORECASTING DIRECTION OF EXCHANGE RATE FLUCTUATIONS WITH TWO DIMENSIONAL PATTERNS AND CURRENCY STRENGTH Özorhan, Mustafa Onur Ph.D., Department of Computer Engineering Supervisor: Prof. -
Relative Strength Index (RSI) Application in Identifying Trading Movements of Selected IT Sector Companies in India 1P
IJMBS VOL . 7, Iss UE 1, JAN - MARCH 2017 ISSN : 2230-9519 (Online) | ISSN : 2231-2463 (Print) Relative Strength Index (RSI) Application in Identifying Trading Movements of Selected IT Sector Companies in India 1P. Selvam, 2L. Rakesh 1Business Studies, Sree Sastha Institute of Engineering & Technology, Chennai, India 2Senior Business Analyst, The Royal Bank of Scotland, Chennai, India Abstract The other variation of computing RSI: The stock market has been an integral part of the economy of any RSI = 100 X (1/(D/D+U) RSI – 100 ((100/U) /( 1+U/D)) country. The stock market plays a pivotal role in the growth of the Where, industry and commerce of the country that would subsequently D = an average of downward price change affect the economy of the country to a great extent. In the recent U = an average of upward price change past, share market investment has become one of the predominant As mentioned early, RSI usually makes fluctuation between 0 investment avenues for investors. Hence, investors wishing to make to 100. RSI peaks are an indication of overbought levels and an investment in share market are required to be conversant with suggest price tops, while RSI troughs are an indication of oversold share market trading practices, price fluctuations and appropriate levels and share price bottoms. Two horizontal lines are normally time for buying and selling securities. This article is proposed to drawn at 30 (indicating an oversold area) and 70 (indicating an apply the momentum oscillator by the name “Relative Strength overbought area). These two RSI lines can be adjusted depending Index – (RSI)” for figuring out an overbought and oversold on the market environment. -
Point and Figure Relative Strength Signals
February 2016 Point and Figure Relative Strength Signals JOHN LEWIS / CMT, Dorsey, Wright & Associates Relative Strength, also known as momentum, has been proven to be one of the premier investment factors in use today. Numerous studies by both academics and investment ABOUT US professionals have demonstrated that winning securities continue to outperform. This phenomenon has been found Dorsey, Wright & Associates, a Nasdaq Company, is a in equity markets all over the globe as well as commodity registered investment advisory firm based in Richmond, markets and in asset allocation strategies. Momentum works Virginia. Since 1987, Dorsey Wright has been a leading well within and across markets. advisor to financial professionals on Wall Street and investment managers worldwide. Relative Strength strategies focus on purchasing securities that have already demonstrated the ability to outperform Dorsey Wright offers comprehensive investment research a broad market benchmark or the other securities in the and analysis through their Global Technical Research Platform investment universe. As a result, a momentum strategy and provides research, modeling and indexes that apply requires investors to purchase securities that have already Dorsey Wright’s expertise in Relative Strength to various appreciated quite a bit in price. financial products including exchange-traded funds, mutual funds, UITs, structured products, and separately managed There are many different ways to calculate and quantify accounts. Dorsey Wright’s expertise is technical analysis. The momentum. This is similar to a value strategy. There are Company uses Point and Figure Charting, Relative Strength many different metrics that can be used to determine a Analysis, and numerous other tools to analyze market data security’s value. -
Moving Average Convergence Divergence (MACD)
Understanding Technical Analysis : Moving Average Convergence Divergence (MACD) Apart from candlestick chart pattern indicators, traders or analysts often use the Hi 74.57 Moving Average Convergence Divergence (MACD) and Relative Strength Index Potential supply (RSI) in technical analysis of financial security. Like the candlestickdisruption chart indicators, due to MACD is also used to identify any trend pattern movement. attacks on two oil Brent tankers near Iran What is MACD? WTI Momentum • MACD is a momentum oscillator indicator WTI Oscillator which is used to identify trend formation Lo 2,237.40 (24 Mar 2020) • MACD shows a relationship betweenLo 18,591.93 two (24 Mar 2020) Moving moving averages of a financial instrument. • It combines price points of an instrument over Averages a specified time frame, divided by the number of data points, to give a single trend line Simple Moving Average (SMA) Exponential Moving Average (EMA) • The most basic MA, which is just a • A type of moving average that gives straight calculation of the mean price more weight to recent prices which of a set of values over a given time involves three steps. periods. • The SMA is computed first. Next, we • If you were to calculate the SMA for a must calculate the multiplier for ten-day period, you would take the weighting the EMA. The final step summed value of the last ten days involves the use of formula to and divide the result by ten. compute the current EMA. Level 6, Kenanga Tower, 237 Jalan Tun Razak, 50400 Kuala Lumpur, Malaysia. Tel: (603) 2172 3888 Fax: (603) 2172 2729 Email: [email protected] Website: www.kenangafutures.com.my How MACD works? MACD is generated by subtracting the long term EMAs (26 period) from the short term EMAs (12 periods) to form the main line known as MACD line. -
Candlesticks, Fibonacci, and Chart Pattern Trading Tools
ffirs.qxd 6/17/03 8:17 AM Page iii CANDLESTICKS, FIBONACCI, AND CHART PATTERN TRADING TOOLS A SYNERGISTIC STRATEGY TO ENHANCE PROFITS AND REDUCE RISK ROBERT FISCHER JENS FISCHER JOHN WILEY & SONS, INC. ffirs.qxd 6/17/03 8:17 AM Page iii ffirs.qxd 6/17/03 8:17 AM Page i CANDLESTICKS, FIBONACCI, AND CHART PATTERN TRADING TOOLS ffirs.qxd 6/17/03 8:17 AM Page ii Founded in 1870, John Wiley & Sons is the oldest independent publishing company in the United States. With offices in North America, Europe, Australia, and Asia, Wiley is globally committed to developing and market- ing print and electronic products and services for our customers’ professional and personal knowledge and understanding. The Wiley Trading series features books by traders who have survived the market’s ever-changing temperament and have prospered—some by re- investing systems, others by getting back to basics. Whether a novice trader, professional, or somewhere in-between, these books will provide the advice and strategies needed to prosper today and well into the future. For a list of available titles, visit our web site at www.WileyFinance.com. ffirs.qxd 6/17/03 8:17 AM Page iii CANDLESTICKS, FIBONACCI, AND CHART PATTERN TRADING TOOLS A SYNERGISTIC STRATEGY TO ENHANCE PROFITS AND REDUCE RISK ROBERT FISCHER JENS FISCHER JOHN WILEY & SONS, INC. ffirs.qxd 6/17/03 8:17 AM Page iv Copyright © 2003 by Robert Fischer, Dr. Jens Fischer. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. PHI-spirals, PHI-ellipse, PHI-channel, and www.fibotrader.com are registered trademarks and protected by U.S. -
Technical-Analysis-Bloomberg.Pdf
TECHNICAL ANALYSIS Handbook 2003 Bloomberg L.P. All rights reserved. 1 There are two principles of analysis used to forecast price movements in the financial markets -- fundamental analysis and technical analysis. Fundamental analysis, depending on the market being analyzed, can deal with economic factors that focus mainly on supply and demand (commodities) or valuing a company based upon its financial strength (equities). Fundamental analysis helps to determine what to buy or sell. Technical analysis is solely the study of market, or price action through the use of graphs and charts. Technical analysis helps to determine when to buy and sell. Technical analysis has been used for thousands of years and can be applied to any market, an advantage over fundamental analysis. Most advocates of technical analysis, also called technicians, believe it is very likely for an investor to overlook some piece of fundamental information that could substantially affect the market. This fact, the technician believes, discourages the sole use of fundamental analysis. Technicians believe that the study of market action will tell all; that each and every fundamental aspect will be revealed through market action. Market action includes three principal sources of information available to the technician -- price, volume, and open interest. Technical analysis is based upon three main premises; 1) Market action discounts everything; 2) Prices move in trends; and 3) History repeats itself. This manual was designed to help introduce the technical indicators that are available on The Bloomberg Professional Service. Each technical indicator is presented using the suggested settings developed by the creator, but can be altered to reflect the users’ preference. -
Accumulation/Distribution Line -- Chart School
Accumulation/Distribution Line -- Chart School Chart School Accumulation/Distribution Line Introduction - Volume and the Flow of Money There are many indicators available to measure volume and the flow of money for a particular stock, index or security. One of the most popular volume indicators over the years has been the Accumulation/Distribution Line. The basic premise behind volume indicators, including the Accumulation/Distribution Line, is that volume precedes price. Volume reflects the amount of shares traded in a particular stock and is a direct reflection of the money flowing into and out of a stock. Many times before a stock advances, there will be period of increased volume just prior to the move. Most volume or money flow indicators are designed to identify early increases in positive or negative volume flow to gain an edge before the price moves. (Note: the terms "money flow" and "volume flow" are essentially interchangeable.) Methodology (Click here to see a live example of the Acc/Dist Line) The Accumulation/Distribution Line was developed by Marc Chaikin to assess the cumulative flow of money into and out of a security. In order to fully appreciate the methodology behind the Accumulation/Distribution Line, it may be helpful to examine one of the earliest volume indicators and see how it compares. In 1963, Joe Granville developed On Balance Volume (OBV), which was one of the earliest and most popular indicators to measure positive and negative volume flow. OBV is a relatively simple indicator that adds the corresponding period's volume when the close is up and subtracts it when the close is down. -
Profiting with Chart Patterns.Book
Profiting with Chart Patterns by Ed Downs Profiting with Chart Patterns November 2016 Edition BK-02-01-01 Support Worldwide Technical Support and Product Information www.nirvanasystems.com Nirvana Systems Corporate Headquarters 9111Jollyville Rd, Suite 275, Austin, Texas 78759 USA Tel: 512 345 2545 Fax: 512 345 4225 Sales Information For product information or to place an order, please contact 800 880 0338 or 512 345 2566. You may also fax 512 345 4225 or send email to [email protected]. Technical Support Information For assistance in installing or using Nirvana products, please contact 512 345 2592. You may also fax 512 345 4225 or send email to [email protected]. To comment on the documentation, send email to [email protected]. © 2016 Nirvana Systems Inc. All rights reserved. Contents Chapter 1 Confirming Entries & Managing Exits What is a Pattern? ..........................................................................................................1-1 Psychology of Support Bounces ....................................................................................1-2 Goals of Chart Pattern Analysis.....................................................................................1-3 Chapter 2 Tools of the Trade 7 Chart Pattern Method..................................................................................................2-1 Pattern Timeframe .........................................................................................................2-2 Prior Move Test .............................................................................................................2-3 -
Package 'Quanttools'
Package ‘QuantTools’ October 14, 2016 Type Package Title Enhanced Quantitative Trading Modelling Version 0.5.0 Author Stanislav Kovalevsky Maintainer Stanislav Kovalevsky <[email protected]> Description Download and organize historical market data from multiple sources like Ya- hoo (<http://finance.yahoo.com>), Google (<https://www.google.com/finance>), Fi- nam (<http://www.finam.ru/profile/moex- akcii/sberbank/export/>) and IQFeed (<http://www.iqfeed.net/symbolguide/index.cfm?symbolguide=lookup>). Code your trad- ing algorithms in modern C++11 with powerful event driven tick processing API including trad- ing costs and exchange communication latency and transform detailed data seam- lessly into R. In just few lines of code you will be able to visualize every step of your trad- ing model from tick data to multi dimensional heat maps. URL https://quanttools.bitbucket.io/_site/index.html BugReports https://bitbucket.org/quanttools/quanttools/issues License GPL-3 Encoding UTF-8 LazyData false Depends data.table, R (>= 2.10) Imports methods, fasttime, RCurl, Rcpp (>= 0.12.6) LinkingTo Rcpp SystemRequirements C++11 RoxygenNote 5.0.1 NeedsCompilation yes Repository CRAN Date/Publication 2016-10-14 00:29:33 1 2 R topics documented: R topics documented: add_last_values . .3 add_legend . .4 back_test . .4 BBands . .5 bbands . .6 bw..............................................7 calc_decimal_resolution . .7 Candle . .8 Cost.............................................8 Crossover . .9 crossover . 10 distinct_colors . 11 dof.............................................. 11 Ema............................................. 12 ema ............................................. 12 empty_plot . 13 gen_futures_codes . 13 get_market_data . 14 hist_dt . 15 Indicator . 15 iqfeed . 16 iround . 20 lapply_named . 20 lines_ohlc . 21 lines_stacked_hist . 21 lmerge . 22 multi_heatmap . 23 na_locf . 24 Order . 24 plot_table . 25 plot_ts . 26 Processor . 27 returns .