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HTML5 Financial Charts Data visualization and analysis Xinfinit’s advanced HTML5 charting tool is also available separately from the managed data container and can be licensed for use with other tools and used in conjunction with any editor. It includes a comprehensive library of over sixty technical indictors, additional ones can easily be developed and added on request. 2 Features Analysis Tools Trading from Chart Trend Channel Drawing Instrument Selection Circle Drawing Chart Duration Rectangle Drawing Chart Intervals Fibonacci Patterns Chart Styles (Line, OHLC etc.) Andrew’s Pitchfork Comparison Regression Line and Channel Percentage (Y-axis) Up and Down arrows Log (Y-axis) Text box Show Volume Save Template Show Data values Load Template Show Last Value Save Show Cross Hair Load Show Cross Hair with Last Show Min / Max Show / Hide History panel Show Previous Close Technical Indicators Show News Flags Zooming Data Streaming Full Screen Print Select Tool Horizontal Divider Trend tool Volume by Price Horizonal Line Drawing Book Volumes 3 Features Technical Indicators Acceleration/Deceleration Oscillator Elliot Wave Oscillator Accumulation Distribution Line Envelopes Aroon Oscilltor Fast Stochastic Oscillator Aroon Up/Down Full Stochastic Oscillator Average Directional Index GMMA Average True Range GMMA Oscillator Awesome Oscillator Highest High Bearish Engulfing Historical Volatility Bollinger Band Width Ichimoku Kinko Hyo Bollinger Bands Keltner Indicator Bullish Engulfing Know Sure Thing Chaikin Money Flow Lowest Low Chaikin Oscillator MACD Commodity Channel Index MACD Forest Coppock Curve Mass Index Cutler RSI Median Price Directional Movement Index Momentum Directional Movement Minus Money Flow Index Directional Movement Plus Moving Average Directional Movement System Moving Average Centered 4 www.xinfinit.com Moving Average Exponential Slow Stochastic Oscillator Moving Average Momentum Standard Deviation Moving Average Rolling Stochastic Momentum Moving Average Triangular Stochastic RSI Moving Average Triple TRIX Moving Average Weighted True Range Negative Volume Index True Strength Indicator On Balance Volume Ultimate Oscillator Parabollic Stops and Reversals Vertical Horizontal Filter Positive Volume Index Volume Moving Average Price Rate of Change Vortex Indicator Relative Strength Index Williams’ % R 5 Features Mobile Support Xinfinit leverages the portability of HTML5 and Responsive Web Design (RWD). Able to display aggregated real-time data sources on desktops, tablets and smartphone browsers. Avoiding the constant struggle with version control and aligning the features of installed apps on different devices. 6 Benefits For IT Development Fully featured HTML5 Financial Charting tool right out of the box, flexible and reduced development effort. For Business Team Fast time to market with advanced HTML5 Charting features to meet customer demand. 7 Xinfinit GmbH Frauenlobstr. 2, 80337 München, Germany [email protected] w w w. x i n f i n i t . c o m html5-financial-charts-v9.

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INDEX Page numbers followed by n indicate note numbers. A Arnott, Robert, 391 Ascending triangle pattern, 140–141 AB model. See Abreu-Brunnermeier model Asks (offers), 8 Abreu-Brunnermeier (AB) model, 481–482 Aspray, Thomas, 223 Absolute breadth index, 327–328 ATM. See Automated teller machine Absolute difference, 327–328 ATR. See Average trading range; Average Accelerated trend lines, 65–66 true range Acceleration factor, 88, 89 At-the-money, 418 Accumulation, 213 Average range, 79–80 ACD method, 186 Average trading range (ATR), 113 Achelis, Steven B., 214n1 Average true range (ATR), 79–80 Active month, 401 Ayers-Hughes double negative divergence AD. See Chaikin Accumulation Distribution analysis, 11 Adaptive markets hypothesis, 12, 503 Ayres, Leonard P. (Colonel), 319–320 implications of, 504 ADRs. See American depository receipts ADSs. See American depository shares B 631 Advance, 316 Bachelier, Louis, 493 Advance-decline methods Bailout, 159 advance-decline line moving average, 322 Baltic Dry Index (BDI), 386 one-day change in, 322 Bands, 118–121 ratio, 328–329 trading strategies and, 120–121, 216, 559 that no longer are profitable, 322 Bandwidth indicator, 121 to its 32-week simple moving average, Bar chart patterns, 125–157. See also Patterns 322–324 behavioral finance and pattern recognition, ADX. See Directional Movement Index 129–130 Alexander, Sidney, 494 classic, 134–149, 156 Alexander’s filter technique, 494–495 computers and pattern recognition, 130–131 American Association of Individual Investors learning objective statements, 125 (AAII), 520–525 long-term, 155–156 American depository receipts (ADRs), 317 market structure and pattern American FinanceCOPYRIGHTED Association, 479, 493 MATERIALrecognition, 131 Amplitude, 348 overview, 125–126 Analysis pattern description, 126–128 description of, 300 profitability of, 133–134 fundamental, 473 Bar charts, 38–39 Andrews, Dr.
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A Novel Hybrid Model for Stock Price Forecasting Based on Metaheuristics and Support Vector Machine
data Article A Novel Hybrid Model for Stock Price Forecasting Based on Metaheuristics and Support Vector Machine Mojtaba Sedighi 1,2,* , Hossein Jahangirnia 3, Mohsen Gharakhani 4 and Saeed Farahani Fard 5 1 Department of Finance, Qom Branch, Islamic Azad University, Qom 3749113191, Iran 2 Young Researchers and Elite Club, Qom Branch, Islamic Azad University, Qom 88447678, Iran 3 Department of Accounting, Qom Branch, Islamic Azad University, Qom 3749113191, Iran; [email protected] 4 Department of Finance, Iranian Institute of Higher Education, Tehran 13445353, Iran; [email protected] 5 Department of Management and Economics, University of Qom, Qom 3716146611, Iran; [email protected] * Correspondence: [email protected] Received: 2 May 2019; Accepted: 20 May 2019; Published: 22 May 2019 Abstract: This paper intends to present a new model for the accurate forecast of the stock’s future price. Stock price forecasting is one of the most complicated issues in view of the high ﬂuctuation of the stock exchange and also it is a key issue for traders and investors. Many predicting models were upgraded by academy investigators to predict stock price. Despite this, after reviewing the past research, there are several negative aspects in the previous approaches, namely: (1) stringent statistical hypotheses are essential; (2) human interventions take part in predicting process; and (3) an appropriate range is complex to be discovered. Due to the problems mentioned, we plan to provide a new integrated approach based on Artiﬁcial Bee Colony (ABC), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Support Vector Machine (SVM).
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Tradescript.Pdf
Service Disclaimer This manual was written for use with the TradeScript™ language. This manual and the product described in it are copyrighted, with all rights reserved. This manual and the TradeScript™ outputs (charts, images, data, market quotes, and other features belonging to the product) may not be copied, except as otherwise provided in your license or as expressly permitted in writing by Modulus Financial Engineering, Inc. Export of this technology may be controlled by the United States Government. Diversion contrary to U.S. law prohibited. Copyright © 2006 by Modulus Financial Engineering, Inc. All rights reserved. Modulus Financial Engineering and TradeScript™ are registered trademarks of Modulus Financial Engineering, Inc. in the United States and other countries. All other trademarks and service marks are the property of their respective owners. Use of the TradeScript™ product and other services accompanying your license and its documentation are governed by the terms set forth in your license. Such use is at your sole risk. The service and its documentation (including this manual) are provided "AS IS" and without warranty of any kind and Modulus Financial Engineering, Inc. AND ITS LICENSORS (HEREINAFTER COLLECTIVELY REFERRED TO AS “MFE”) EXPRESSLY DISCLAIM ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE AND AGAINST INFRINGEMENT. MFE DOES NOT WARRANT THAT THE FUNCTIONS CONTAINED IN THE SERVICE WILL MEET YOUR REQUIREMENTS, OR THAT THE OPERATION OF THE SERVICE WILL BE UNINTERRUPTED OR ERROR-FREE, OR THAT DEFECTS IN THE SERVICE OR ERRORS IN THE DATA WILL BE CORRECTED. FURTHERMORE, MFE DOES NOT WARRANT OR MAKE ANY REPRESENTATIONS REGARDING THE USE OR THE RESULTS OF THE USE OF THE SERVICE OR ITS DOCUMENTATION IN TERMS OF THEIR CORRECTNESS, ACCURACY, RELIABILITY, OR OTHERWISE.
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3 Ways to Spot Trend Reversals with the Mass Index
3 Ways to Spot Trend Reversals with the Mass Index If you carefully observe any bar chart, you can see that even when the stock price is trending upwards or downwards, the price is actually ranging. The only difference between trending and ranging markets is the direction of the range. Once you draw an equidistant channel on any price chart, the ranging nature of price becomes more evident. Figure 1: Theory Behind the Mass Index Indicator When Donald Dorsey developed the Mass Index indicator, his rationale was that if the prevailing trend were going to change, the price range would have to widen. If you are having difficulty imagining the situation, look at figure 1, do you see what we mean? Although the Mass Index is great at signaling a potential change in the trend, it will not tell you which direction the trend is changing. After all, an uptrend can gain additional bullish momentum and that will also help make the range much wider. You have to remember that when the Mass Index technical indicator line is going up, the climbing line is only signaling that the volatility of the stock is going up. However, the Mass Index indicator line does not signify any directional bias of the stock. That’s why you need to incorporate other technical analysis tools into your mass index trading strategies in order to identify the change of direction of the prevailing trend. Consider an analogy for a moment, you are driving a car and the mass index calculator, which shows volatility of the stock, is your speedometer.
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Indicators Nison Power Concept EAST & WEST CONFIRMATION
Instructors: Syl Desaulniers, Nison Certified Trainer™ Tracy Knudsen, Nison Certified Trainer™ Improve Your Process… Get BIG Results KAIZEN TRADING APPRENTICESHIP Bonus Session Address student trades, concerns, follow-up questions Analysis of current market conditions Awarding of Kaizen Technician™ certification Strict Candlestick Patterns Qualifications for Strict Candle Patterns: - Shape of Candle Lines or Pattern - Trend requirement is the same for strict and non-strict patterns Important Concept with Candle Lines/Patterns: - Confirmation: Using a move after the initial candle signal to validate a move - Less important with East/West Confirmation Candlestick Lines and Patterns In Order of Candle Progression - Least to Most Bullish - Least to Most Bearish - Risk/Reward Tradeoff comes with candle progression Strict Candlestick Patterns - Bullish Strict Candlestick Patterns - Bearish Trend Progression/Multiple Time Frames Monthly, Weekly, Daily, 4 Hour, 2 Hour, 60 Minute, 30 Minute, 15 Minute… • Involves monitoring the same instrument across different frequencies (or time compressions) • No real limit as to how many frequencies can be monitored or which specific ones to choose • Trades placed in direction of longer term trend have higher probability of success • There are general guidelines that most practitioners will follow Trend Progression/Multiple Time Frames • Looking at a stock through different time frames can be confusing as a new trader. Why? • Because each time frame looks different! • A stock may look great on the daily chart, but look horrible on a 5 minute chart. • How many timeframes should a trader use? • Using three different periods gives a broad enough reading on the market • using fewer than this can result in a considerable loss of data • while using more typically provides redundant analysis.
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A Survey of Forex and Stock Price Prediction Using Deep Learning
Review A Survey of Forex and Stock Price Prediction Using Deep Learning Zexin Hu †, Yiqi Zhao † and Matloob Khushi * School of Computer Science, The University of Sydney, Building J12/1 Cleveland St., Camperdown, NSW 2006, Australia; [email protected] (Z.H.); [email protected] (Y.Z.) * Correspondence: [email protected] † The authors contributed equally; both authors should be considered the first author. Abstract: Predictions of stock and foreign exchange (Forex) have always been a hot and profitable area of study. Deep learning applications have been proven to yield better accuracy and return in the field of financial prediction and forecasting. In this survey, we selected papers from the Digital Bibliography & Library Project (DBLP) database for comparison and analysis. We classified papers according to different deep learning methods, which included Convolutional neural network (CNN); Long Short-Term Memory (LSTM); Deep neural network (DNN); Recurrent Neural Network (RNN); Reinforcement Learning; and other deep learning methods such as Hybrid Attention Networks (HAN), self-paced learning mechanism (NLP), and Wavenet. Furthermore, this paper reviews the dataset, variable, model, and results of each article. The survey used presents the results through the most used performance metrics: Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Mean Square Error (MSE), accuracy, Sharpe ratio, and return rate. We identified that recent models combining LSTM with other methods, for example, DNN, are widely researched. Reinforcement learning and other deep learning methods yielded great returns and performances. We conclude that, in recent years, the trend of using deep-learning-based methods for financial modeling is rising exponentially.
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The Global Investment Outlook – New Year 2019 Release U.S
DEC 4 2018 (UPDATED TO NOV 30) Daniel E. Chornous, CFA Chief Investment Officer [email protected] Eric Savoie, MBA, CFA Senior Analyst, Investment Strategy [email protected] THE GLOBAL INVESTMENT OUTLOOK – NEW YEAR 2019 RELEASE U.S. 10-year T-Bond yield S&P 500 equilibrium Global purchasing managers' indices Equilibrium range Normalized earnings & valuations The S&P 500 Nov. '18 Range: 2141 - 3563 (Mid: 2852) is slightly below 65 16 5120 equilibrium (i.e. the band’s ISM Peak Aug 2018: 61.3 Our equilibrium model suggests an Nov. '19 Range: 2218 - 3691 (Mid: 2954)midpoint), and many Previous ISM Peak Feb 2011: 59.2 14 upward bias to interest rates for a very Current (30-November-18): 2760 other markets continue 60 long time into the future should 2560 to show significant discounts to their fair value. A significant rise in inflation and interest rates 12 inflation premiums and real rates of will eventually reduce the sustainable 55 interest ultimately return to their long- 1280 level for valuations, but normalizing 10 term norms. P/E’s and corporate profitability to Last Plot: 2.99% reflect current levels for these 50 8 Current Range: 2.12% - 3.90% (Mid: 3.01%) 640 critical variables suggests % stock market valuations are reasonable, but 45 6 320 certainly not Solid gains in “cheap” in all revenues and earnings 4 Led by the U.S., PMIs remain at 160 locations. propelled U.S. stocks in 40 particular, but threats to levels consistent with expansion, 2 But in the near-term, the pressure but the trend everywhere is both are accumulating.
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Timeframeset
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View User Guide
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Using the Z-Trend Oscillator for Long-Term Bond Market Timing
Using the Z-TrendOscillator for Long-Term Bond Market Timing 6 Submitted by Robert T. Zukowski, CMT March4. 1996 Overview Because it reflects mass psychology, the Coppock Curve is labeled by tnost technicians attd traders as a setttimettt This paper examines the concept of modifying the indicator. As a result, the curve siguals market tops and Coppock Curve to better identify major tops attd bottoms bottoms quite well and proves to be a valuable addition to in the bond futures market for lottg-term positioning. The atty trader’s tool kit. Coppock combined art 1 l- and 14 modified versiott of the Coppock Curve is referred to as mouth ROC, smoothed over by a lo-tnottth weighted mov- the Z-Trend Oscillator. Most oscillators are used for trad- ing average, which cat1 be explaitted by the yearly titne ing periods of price consolidation, but the Z-Trend Oscil- cycles frequent in tnost tnarket indices. A buy signal oc- lator is specifically used for trading all market cottditiotts curs when the curve turns up or becotnes positively sloped from accumulation, to trending, to distribution. while below the zero litte. A sell sigttal occurs when the curve turns down or becomes negatively sloped while Introduction to Rate of Change and the above the zero line. Coppock Curve Otte of the older, sitnpler tcchttical ittdicators to un- The Problem - Indicator Consistency derstand is the rate of chattge or ROC for short. ROC catt When the Coppock Curve is applied to the monthly confirm tnarket trends and forewarn of market reversals. continuation chart of U.S.
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Bullish Pattern
International School of Financial Markets WWW.ISFM.CO.IN Best Stock Market School Gurgaon 0124-2200689, 9540008689 Reg. office: Plot no. 152 - P (LGF), Sec – 38, Medicity Road, NR Bakhtawar Chowk Phone : 0124-2200689, +91 9540008689, +91 9953147497, +91 9911878442 Web: www.isfm.co.in , Email : [email protected] Reg. office: Plot no. 152 - P (LGF), Sec – 38, Medicity Road, Near Medanta Hospital Contact No. - 0124-2200689, +919540008689, WWW.ISFM.CO.IN Accumulation The act of buying more shares of a security without causing the price to increase significantly. After a decline, a stock may start to base and trade sideways for an extended period. While this base builds, well-informed traders and investors may seek to establish or increase existing long positions. In that case, the stock is said to have come under accumulation. Accumulation Distribution Line A momentum indicator that relates price changes with volume. It relates the closing price to the range of prices (H - L). The closer the close is to the high, the more volume is added to the cumulative total. Advance Decline Line One of the most widely used indicators to measure the breadth of a stock market advance or decline. The AD line tracks the net difference between advancing and declining issues. It is usually compared to a market average WWW.ISFM.CO.INwhere divergence from that average would be an early indication of a possible trend reversal. AdvanceBest Decline Stock Ratio Market School The ratio of advancing issues over declining issues. Taking the moving average of the AD ratioGurgaon will smooth it so it can be used as an overbought and oversold indicator.
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Strategydesk Formula & Syntax Guide Version 3.3
TM StrategyDesk Formula & Syntax Guide Version 3.3 Brokerage services are provided by TD AMERITRADE, Inc., member FINRA/SIPC. TD AMERITRADE, Inc. and Think Tech, Inc. are both subsidiaries of TD AMERITRADE Holding Corporation. © 2009 Think Tech, Inc. All rights reserved. Used with permission. StrategyDesk is a trademark of TD AMERITRADE IP Company, Inc. Used with permission. TD AMERITRADE is a trademark jointly owned by TD AMERITRADE IP Company, Inc. and The Toronto-Dominion Bank. Used with permission. Page 1 of 32 StrategyDeskTM Formula and Syntax Guide Version 3.3 Updated August 24, 2009 StrategyDesk Formula Wizard................................................................................................ 3 Introduction to the Bar Function.............................................................................................. 5 Function Examples ................................................................................................................. 6 Quote Functions...................................................................................................................... 8 Technical Indicators.............................................................................................................. 11 Formula Operators................................................................................................................ 18 Trading Strategies................................................................................................................. 19 Trade Alerts .........................................................................................................................
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