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lang help home search wavelets in trading stock price prediction via discovering multi-frequency trading patterns stock price prediction via discovering multi-frequency trading patterns liheng zhang (university of central florida) charu aggarwal (ibm t. j. watson research center) guo-jun qi (university of central florida) stock prices are formed based on short and/or long-term commercial and trading activities that reflect different frequencies of trading patterns. however, these patterns are often elusive as they are affected by many uncertain political-economic factors in the real world, such as corporate performances, government policies, and even breaking news circulated across markets. moreover, time series of stock prices are non-stationary and non-linear, making the prediction of future price trends much challenging. to address them, we propose a novel state frequency memory (sfm) recurrent network to capture the multi-frequency trading patterns from past market data to make long and short term predictions over time. inspired by discrete fourier transform (dft), the sfm decomposes the hidden states of memory cells into multiple frequency components, each of which models a particular frequency of latent trading pattern underlying the fluctuation of stock price. then the future stock prices are predicted as a nonlinear mapping of the combination of these components in an inverse fourier transform (ift) fashion. modeling multi-frequency trading patterns can enable more accurate predictions for various time ranges: while a short-term prediction usually depends on high frequency trading patterns, a long-term prediction should focus more on the low frequency trading patterns targeting at long-term return. unfortunately, no existing model explicitly distinguishes between various frequencies of trading patterns to make dynamic predictions in literature. the experiments on the real market data also demonstrate more competitive performance by the sfm as compared with the state-of-the-art methods. more on http://www.kdd.org/kdd2017/ views: 806 kdd2017 video 30:26 want a job in a hedge fund? know wavelets to increase your odds this is just another way of saying you need advanced math as more candidates come out of so many math/financial engineering courses http://quantlabs.net/blog/2016/08/want-a-hedge-fund-job-know-a-wavelet-to-improve-your-odd/ views: 497 bryan downing 36:35 an example of financial analysis using the matlab live editor views: 20161 dmitri nesteruk 00:37 non-shift invariant wavelet and time series wavelets "crawling" depending on the offset in time. some research on the enzobot trading system. views: 19 davide pasca 03:05 time series classification using wavelet scattering transform this is a ~3-minute video highlight produced by undergraduate students charlie tian and christina coley regarding their research topic during the 2017 amalthea reu program at florida institute of technology in melbourne, fl. they were mentored by doctoral student kaylen bryan and professor dr. adrian peter (engineering systems department). more details about their project can be found at http://www.amalthea-reu.org. views: 2300 the amalthea reu program 07:14 end of day trading part 2 peaks and troughs end of day trading part 2 covers peaks and troughs. using the new york closing price charts to look at where you find medium term highs and lows, or peaks and troughs. end of day trading systems on any market can use these simple price action strategies to improve their trading results. http://www.staceyburketrading.com views: 1491 stacey burke trading 01:16:19 8. time series analysis i mit 18.s096 topics in mathematics with applications in finance, fall 2013 view the complete course: http://ocw.mit.edu/18-s096f13 instructor: peter kempthorne this is the first of three lectures introducing the topic of time series analysis, describing stochastic processes by applying regression and stationarity models. license: creative commons by-nc-sa more information at http://ocw.mit.edu/terms more courses at http://ocw.mit.edu views: 151890 mit opencourseware 05:07 using fourier analysis to time a gold swing trade although the bullish trend rebound in gold remains intact our fourier analysis and hurst projections say that this is not the time to be a bullish swing trader in the gld etf. http://www.tradingfives.com/blog2 views: 5028 tradingfives 09:46 the hilbert transform in this video you will learn about the hilbert transform, which can be used to compute the "analytic signal" (a complex time series from which instantaneous power and phase angles can be extracted). this video uses the following matlab files: http://mikexcohen.com/lecturelets/hilbert/hilbertx.m mikexcohen.com/lecturelets/sampleeegdata.mat for more information about spectral analysis: https://www.udemy.com/fourier-transform-mxc/?couponcode=mxc-fourier10 for more information about matlab programming: https://www.udemy.com/matlab-programming-mxc/?couponcode=mxc-matlab10 for more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/ views: 10124 mike x cohen 22:34 how much money do you really need for trading full time i talk about in this video how much $ you need to start living off of trading notes here i talk about in this video how much $ you need to start living off of trading http://quantlabs.net/blog/2016/08/how-much-money-do-you-really-need-for-trading-full-time/ views: 286 bryan downing 07:00 how dtw (dynamic time warping) algorithm works in this video we describe the dtw algorithm, which is used to measure the distance between two time series. it was originally proposed in 1978 by sakoe and chiba for speech recognition, and it has been used up to today for time series analysis. dtw is one of the most used measure of the similarity between two time series, and computes the optimal global alignment between two time series, exploiting temporal distortions between them. source code of graphs available at https://github.com/tkorting/youtube/blob/master/how-dtw-works.m the presentation was created using as references the following scientific papers: 1. sakoe, h., chiba, s. (1978). dynamic programming algorithm optimization for spoken word recognition. ieee trans. acoustic speech and signal processing, v26, pp. 43-49. 2. souza, c.f.s., pantoja, c.e.p, souza, f.c.m. verificação de assinaturas offline utilizando dynamic time warping. proceedings of ix brazilian congress on neural networks, v1, pp. 25-28. 2009. 3. mueen, a., keogh. e. extracting optimal performance from dynamic time warping. available at: http://www.cs.unm.edu/~mueen/dtw.pdf views: 20154 thales sehn körting 11:36 harmonic stock analysis using 4th and 8th harmonic to analyse google. views: 1642 olga morales 01:32 an introduction to the financial signal processing lab arta babaee, from the department of electrical and electronic engineering, gives an introduction to the financial signal processing laboratory at imperial college london, of which he is a co-founder. find out more at www.fsplab.com/ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - if you are a member of a financial institution or start up and are interested in partnering with imperial college london through the ibp fintech chapter please contact us at [email protected] or visit www.imperial-business-partners.com. views: 282 imperial business partners more videos » joomla articles display 04:19 joomla 3.x. what are featured articles and how to display them this tutorial shows how to display them featured articles in joomla 3.x. choose your joomla template now: http://www.templatemonster.com/joomla-templates.php?utm_source=youtube&utm_medium=link&utm_campaign=jootuts103 more joomla tutorials: http://www.templatemonster.com/help/cms-blog-templates/joomla/joomla-tutorials/ subscribe our channel: https://www.youtube.com/user/templatemonsterco/ follow us: facebo

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Whois Information

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Domain Name: TEXTFORM.INFO
Registry Domain ID: D503300000129236496-LRMS
Registrar WHOIS Server: whois.namecheap.com
Registrar URL: www.namecheap.com
Updated Date: 2018-10-02T20:33:49Z
Creation Date: 2018-08-03T11:07:41Z
Registry Expiry Date: 2019-08-03T11:07:41Z
Registrar Registration Expiration Date:
Registrar: NameCheap, Inc
Registrar IANA ID: 1068
Registrar Abuse Contact Email: [email protected]
Registrar Abuse Contact Phone: +1.6613102107
Reseller:
Domain Status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited
Registrant Organization:
Registrant State/Province: Panama
Registrant Country: PA
Name Server: IGOR.NS.CLOUDFLARE.COM
Name Server: HOPE.NS.CLOUDFLARE.COM
DNSSEC: unsigned
URL of the ICANN Whois Inaccuracy Complaint Form is https://www.icann.org/wicf/
>>> Last update of WHOIS database: 2019-02-03T21:55:24Z <<<

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Access to AFILIAS WHOIS information is provided to assist persons in determining the contents of a domain name registration record in the Afilias registry database. The data in this record is provided by Afilias Limited for informational purposes only, and Afilias does not guarantee its accuracy. This service is intended only for query-based access. You agree that you will use this data only for lawful purposes and that, under no circumstances will you use this data to(a) allow, enable, or otherwise support the transmission by e-mail, telephone, or facsimile of mass unsolicited, commercial advertising or solicitations to entities other than the data recipient's own existing customers; or (b) enable high volume, automated, electronic processes that send queries or data to the systems of Registry Operator, a Registrar, or Afilias except as reasonably necessary to register domain names or modify existing registrations. All rights reserved. Afilias reserves the right to modify these terms at any time. By submitting this query, you agree to abide by this policy.

The Registrar of Record identified in this output may have an RDDS service that can be queried for additional information on how to contact the Registrant, Admin, or Tech contact of the queried domain name.

  REFERRER http://whois.afilias.info

  REGISTRAR Afilias Global Registry Services

SERVERS

  SERVER info.whois-servers.net

  ARGS textform.info

  PORT 43

  TYPE domain

DOMAIN

  NAME textform.info

  HANDLE D503300000129236496-LRMS

  CREATED 2018-03-08

STATUS
clientTransferProhibited https://icann.org/epp#clientTransferProhibited

NSERVER

  IGOR.NS.CLOUDFLARE.COM 173.245.59.119

  HOPE.NS.CLOUDFLARE.COM 173.245.58.163

OWNER

ADDRESS

  STATE Panama

  COUNTRY PA

  REGISTERED yes

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