Price-Bands: A Technical Tool for Stock Trading

Trading frequency can be said as the implementation from trader of commerce. This case based on positive or negative trader reaction given by trader information. Stock trading in BEI always fluctuate with price of volume value and frequency particularly. Frequency itself shows the company involved or not. In trading frequency, if the indicator frequency it self shown the higher point, it means better. In spite of the most important thing is how the fluctuation or value conversion itself. On the frequencies we also could see which stocks is interested by the investor. When trading frequency high, it may be create sense of interest from investors.The aim of this research, in order to know how far the effect of trading frequency (X) with stock value (Y) using cover stock value. The information used is begin 2008 with sample from twelve property and real estate companies. According to the research can be conclude from twelve companies in Indonesia Stock Exchange in 2008, 75 % of trading frequency samples doesn’t have signification degree between trading frequency and stock value. This case can be explained count on smaller than t tableEvaluation of this research is the trading measuring frequency at property sector and real estate not influence to stock priceKeywords : Trading Frequency, Stock Price

Download Full-text

A Study On Technical Analysis With Reference To International Forex

Think India ◽

10.26643/think-india.v22i3.8470 ◽

2019 ◽

Vol 22 (3) ◽

pp. 1129-1144

Author(s):

Bichith C. Sekhar ◽

A. Umamaheswari

Keyword(s):

Foreign Exchange ◽

Abnormal Return ◽

Foreign Exchange Market ◽

Relative Strength ◽

Exchange Market ◽

Strength Index ◽

Technical Tool ◽

Alpha Beta ◽

Decentralized Market ◽

Currency Conversion

The foreign exchange market (Forex, FX, or currency market) is a global decentralized market for the trading of currencies. The foreign exchange market assists international trade and investments by enabling currency conversion. Our study is to test the technical tools to analyze about the technical impact and its return in the market. For this purpose 13 cross currency pairs were taken as sample size and Jensen’s Alpha, Beta, Relative Strength Index, and Buy and Hold Abnormal Return were used as technical tool for analysis and the conclusion is that it’s not preferred to invest in JPY pairs as the volatility and the return are not up to the mark and its preferred to invest in EURCAD as the return was high when compared to other scripts and the market was moving accordingly to its cross currency pair.

Download Full-text

Zwischenevaluation des Wald-Wild-Management-Instruments (WWMI) im Pilotprogramm effor2 «Wald und Wild» | Preliminary evaluation of the Game-Forest-Management-Tool (GFMT) in the effor2 pilot programme «Game and Forest»

Schweizerische Zeitschrift fur Forstwesen ◽

10.3188/szf.2003.0305 ◽

2003 ◽

Vol 154 (8) ◽

pp. 305-313 ◽

Cited By ~ 1

Author(s):

Roman Eyholzer ◽

Martin Baumann ◽

Rolf Manser

Keyword(s):

Forest Management ◽

Management Practice ◽

Management Tool ◽

Preliminary Evaluation ◽

Optimal Contract ◽

Technical Tool ◽

Entire Study ◽

Pilot Programme ◽

Complex Problems ◽

Entire Study Area

Faced with the challenging task of balancing forest interests and wildlife, the Swiss Forest Agency initiated the pilot programme«Game and Forest», which is committed to a philosophy of goal-oriented management practice and a redesign of forestry subsidizing. Within this programme the diverse goals of forestry and hunting have been amalgamated to a superimposed goal and set out in a corresponding contract. The Game-Forest-Management-Tool (GFMT) has been divised to simulate the effect of various strategies to deal with the complex problems of forest-wildlife. Optimal contract-fulfilling procedures can be simulated on a PC using this technical tool. The efficiency of the measures suggested by simulations that were carried out are being tested in a study area within the pilot programme, «Game and Forest». Half way through this trial, after two years, we can say that there has been no significant increase of non-browsed areas. In 2004, after the collection of data for the entire study area, we will be able to tell whether applying this computer simulated strategy truly leads to an augmentation of non-browsed area and a decrease in bark-peeled forests in the pilot area.

Download Full-text

How Smooth Is Price Discovery? Evidence from Cross-listed Stock Trading

SSRN Electronic Journal ◽

10.2139/ssrn.1912954 ◽

2012 ◽

Author(s):

Haiqiang Chen ◽

Paul Moon Sub Choi ◽

Yongmiao Hong

Keyword(s):

Price Discovery ◽

Stock Trading

Download Full-text

A Cointegrating Stock Trading Strategy for Tanker Shipping Companies

SSRN Electronic Journal ◽

10.2139/ssrn.3275126 ◽

2018 ◽

Author(s):

Nektarios Michail ◽

Konstantinos Melas

Keyword(s):

Trading Strategy ◽

Stock Trading

Download Full-text

Can Twitter Help Predict Firm-Level Earnings and Stock Returns?

The Accounting Review ◽

10.2308/accr-51865 ◽

2017 ◽

Vol 93 (3) ◽

pp. 25-57 ◽

Cited By ~ 83

Author(s):

Eli Bartov ◽

Lucile Faurel ◽

Partha S. Mohanram

Keyword(s):

Stock Market ◽

Stock Returns ◽

Future Prospects ◽

Traditional Media ◽

Stock Trading ◽

Firm Level ◽

Quarterly Earnings ◽

Announcement Returns ◽

Twitter Activity ◽

Original Information

ABSTRACT Prior research has examined how companies exploit Twitter in communicating with investors, and whether Twitter activity predicts the stock market as a whole. We test whether opinions of individuals tweeted just prior to a firm's earnings announcement predict its earnings and announcement returns. Using a broad sample from 2009 to 2012, we find that the aggregate opinion from individual tweets successfully predicts a firm's forthcoming quarterly earnings and announcement returns. These results hold for tweets that convey original information, as well as tweets that disseminate existing information, and are stronger for tweets providing information directly related to firm fundamentals and stock trading. Importantly, our results hold even after controlling for concurrent information or opinion from traditional media sources, and are stronger for firms in weaker information environments. Our findings highlight the importance of considering the aggregate opinion from individual tweets when assessing a stock's future prospects and value.

Download Full-text