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      <title>Mathematics and Stock Market  by MADHAV SINGH</title>
      <link>https://padlet.com/f2015352/x5o5xr4brzh8</link>
      <description>Abhishek Yadav and Madhav Singh</description>
      <language>en-us</language>
      <pubDate>2015-09-22 18:05:06 UTC</pubDate>
      <lastBuildDate>2023-01-22 16:36:12 UTC</lastBuildDate>
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      <item>
         <title>Stock Market</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/71572896</link>
         <description><![CDATA[<p>A&nbsp;<b>stock market</b>&nbsp;or&nbsp;<b>equity market</b>&nbsp;is the aggregation of buyers and sellers (a loose network of economic transactions, not a physical facility or discrete entity) of stocks&nbsp;(also called shares); these may include&nbsp;securities listed on a&nbsp;stock exchange&nbsp;as well as those only traded privately.<br></p><p>Stocks can be categorized in various ways. One common way is by the country where the company is domiciled. For example,&nbsp;Nestle&nbsp;and&nbsp;Novartis&nbsp;are domiciled in Switzerland, so they may be considered as part of the Swiss stock market, although their stock may also be traded at exchanges in other countries.</p><p>At the close of 2012, the size of the world stock market (total market capitalisation) was about US$55 trillion.By country, the largest market was the United States (about 34%), followed by Japan (about 6%) and the United Kingdom (about 6%).&nbsp;This went up more in 2013.</p>]]></description>
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         <pubDate>2015-09-22 18:06:19 UTC</pubDate>
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      <item>
         <title>Predicting Financial Markets</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72118266</link>
         <description><![CDATA[]]></description>
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         <pubDate>2015-09-25 09:46:19 UTC</pubDate>
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      <item>
         <title>The Mathematics of markets</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72118498</link>
         <description><![CDATA[]]></description>
         <enclosure url="http://www.economist.com/node/21542732" />
         <pubDate>2015-09-25 09:48:39 UTC</pubDate>
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      <item>
         <title>Can Math Beat Financial Markets?</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72119837</link>
         <description><![CDATA[]]></description>
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         <pubDate>2015-09-25 09:59:08 UTC</pubDate>
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      </item>
      <item>
         <title>Bringing Math to the Market</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72120991</link>
         <description><![CDATA[<p>Introduction to basics of stock market and mathematics</p>]]></description>
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         <pubDate>2015-09-25 10:09:09 UTC</pubDate>
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      <item>
         <title>Basics of Stock Market&amp;nbsp;</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72121557</link>
         <description><![CDATA[]]></description>
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         <pubDate>2015-09-25 10:14:15 UTC</pubDate>
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      <item>
         <title>Basic Statistics</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72123170</link>
         <description><![CDATA[<h1><ol><li><span style="font-size: 13px;">Mean</span></li><li><span style="font-size: 13px;">Median</span></li><li><span style="font-size: 13px;"> Average</span></li><li><span style="font-size: 13px;"> Standard Deviation</span></li><li><span style="font-size: 13px;"> z-scores</span></li><li><span style="font-size: 13px;">p-value</span><br></li></ol></h1>]]></description>
         <enclosure url="https://controls.engin.umich.edu/wiki/index.php/Basic_statistics:_mean,_median,_average,_standard_deviation,_z-scores,_and_p-value" />
         <pubDate>2015-09-25 10:29:21 UTC</pubDate>
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      <item>
         <title>Journal - Mathematics of Financial Markets</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72287414</link>
         <description><![CDATA[]]></description>
         <enclosure url="http://wwwf.imperial.ac.uk/~mdavis/docs/math2001.pdf" />
         <pubDate>2015-09-26 14:18:21 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72287414</guid>
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      <item>
         <title>Algorithms related to Market</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72287851</link>
         <description><![CDATA[<p>Algorithm Trading&nbsp;(automated trading, black-box trading, or simply algo-trading) is the process of using computers programmed to follow a defined set of instructions for placing a trade in order to generate better profits. The defined sets of rules are based on timing, price, quantity or any mathematical model.</p>]]></description>
         <enclosure url="http://www.investopedia.com/articles/active-trading/101014/basics-algorithmic-trading-concepts-and-examples.asp" />
         <pubDate>2015-09-26 14:31:01 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/72287851</guid>
      </item>
      <item>
         <title>What is a mathematical model?</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73913488</link>
         <description><![CDATA[<p>A&nbsp;<b>mathematical model</b>&nbsp;is a description of a system using&nbsp;mathematical concepts. The process of developing a mathematical model is termed as mathematical modeling. Mathematical models are used in science, engineering, social science and finance. A model may help to explain a system and to study the effects of different components, and to make predictions about behaviour.</p>]]></description>
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         <pubDate>2015-10-06 09:49:56 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73913488</guid>
      </item>
      <item>
         <title>Black–Scholes Model</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73915996</link>
         <description><![CDATA[<p>The&nbsp;<b>Black–Schole</b>&nbsp;model is a&nbsp;mathematical model of financial market&nbsp;having&nbsp;derivative &nbsp;investment instruments. From the model, one can deduce the&nbsp;<b>Black–Scholes formula</b>, which gives a theoretical estimate of the price of&nbsp;European-styleoptions. The formula led to a boom in options trading markets around the world. lt is widely used, although often with adjustments and corrections, by options market participants.&nbsp;Many empirical tests have shown that the Black–Scholes price is very close to the observed prices.</p>]]></description>
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         <pubDate>2015-10-06 10:07:20 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73915996</guid>
      </item>
      <item>
         <title>Input Output Models</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73916050</link>
         <description><![CDATA[<span style="font-size: 13px;">In&nbsp;economics, an&nbsp;</span><b style="font-size: 13px;">input–output model</b><span style="font-size: 13px;">&nbsp;is a quantitative economic technique that represents the interdependencies between different branches of a national economy or different regional economies.&nbsp;Wassily</span><a href="https://en.wikipedia.org/wiki/Wassily_Leontief" style="font-size: 13px;"> </a><span style="font-size: 13px;">Leontief&nbsp; earned the Noble Price in Economics&nbsp;for his development of this model.</span><b style="font-size: 13px;"><br></b>]]></description>
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         <pubDate>2015-10-06 10:07:50 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73916050</guid>
      </item>
      <item>
         <title>Brownian model of financial markets</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73916302</link>
         <description><![CDATA[<h1><p>The <b>Brownian motion model</b> for financial markets concerned with defining the concepts of financial assets and markets, portfolios, gains and wealth in terms of continuous-time stochastic process. <span style="font-size: 13px;">Under this model, these assets have continuous prices evolving continuously in time and are driven by Brownian motion processes. This model requires an assumption of perfectly divisible assets and a frictionless market i.e. that no transaction costs occur either for buying or selling. Another assumption is that asset prices have no jumps, that is there are no surprises in the market.</span></p></h1>]]></description>
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         <pubDate>2015-10-06 10:10:04 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73916302</guid>
      </item>
      <item>
         <title>Black Model</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73917220</link>
         <description><![CDATA[<p>The&nbsp;<b>Black model </b>is a variant of the&nbsp;Black-Scholes&nbsp;option pricing model. Its primary applications are for pricing options on future contracts,&nbsp;bond options, interest rate caps / floors, and&nbsp;swaptions.<span style="font-size: 13px;">&nbsp;It was first presented in a paper written by&nbsp;Fisher Black </span><span style="font-size: 13px;">in 1976.</span></p>]]></description>
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         <pubDate>2015-10-06 10:17:54 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73917220</guid>
      </item>
      <item>
         <title>Binomial Options Pricing Model</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73917707</link>
         <description><![CDATA[<p>In finance, the&nbsp;<b>binomial options pricing model</b>&nbsp;(BOPM) provides a generalizable numerical method&nbsp;for the valuation of&nbsp;options. The binomial model was first proposed by&nbsp;Cox, Ross&nbsp;and&nbsp;Rubinstein&nbsp;in 1979. The model uses a “discrete-time” model of the varying price over time of the&nbsp;underlying&nbsp;financial instrument. In general, binomial options pricing models do not have closed-form.It is slower than the Black-Scholes model but more accurate.</p>]]></description>
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         <pubDate>2015-10-06 10:22:02 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73917707</guid>
      </item>
      <item>
         <title>Monte Carlo option model</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73918588</link>
         <description><![CDATA[<b>Monte Carlo option model</b>&nbsp;to calculate the value of an&nbsp;option with multiple sources of uncertainty or with complicated features. Monte Carlo Methods are particularly useful in the valuation of options with multiple sources of uncertainty or with complicated features, which would make them difficult to value through a straightforward Black-Scholes style or&nbsp;lattice based computation.]]></description>
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         <pubDate>2015-10-06 10:29:21 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/73918588</guid>
      </item>
      <item>
         <title>Using Linear Functions to Predict The Stock Market Math Unit</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74249620</link>
         <description><![CDATA[]]></description>
         <enclosure url="https://www.youtube.com/watch?v=ykXmjMUOLyw" />
         <pubDate>2015-10-07 14:32:19 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74249620</guid>
      </item>
      <item>
         <title>STOCK MARKET PERCENTAGES AND MATHEMATICS</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74258716</link>
         <description><![CDATA[<p>Imagine&nbsp;a stock that&nbsp;falls&nbsp;fifty percent&nbsp;one day and rises&nbsp;fifty percent&nbsp;the next day. Seems like you’d have broken even, right? Wrong. This is the beauty of mathematics, and it occurs in the stock market all the time. While this shouldn’t be a significant problem for your investments, it can often be misleading and confusing when researching and analyzing&nbsp;stocks.</p><p>Let’s use the example of a recently volatile stock known as&nbsp;E-Trade Financial (ETFC). The stock price experienced a large sell off and dropped to $8.59 per share, a 58.7% drop. The&nbsp;next day a rally occurred in the stock market and E-Trade’s stock soared up 40.9%. This left the stock at $5.00 at the end of the day. This is a key example of how the percentage mathematics used in stock prices can easily be misleading to casual investors.</p><p>Now let’s break down this problem in simpler terms. Suppose you bought XYZ stock&nbsp;at $10 per share. It remains around $10 per share and suddenly it falls 80% one day due to a sell off and ends the day at a meager $2 per share. The next day, the aggregate&nbsp;stock market sentiment is the stock was oversold, so a rally occurs and the stock soars up 50%. If you were a long term investor during all this madness, you’d still be down significantly. A 50% rally in a $2 per share stock will only result in a $3 stock price. Which means despite the face value of 80%-50%=30%, you are actually down 70% on your investment of XYZ stock because the price per share ultimately went from $10 to $3.</p>]]></description>
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         <pubDate>2015-10-07 14:56:45 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74258716</guid>
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      <item>
         <title>Journal - Prediction of Stock Price Movement Using
Continuous Time Models</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74269159</link>
         <description><![CDATA[]]></description>
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         <pubDate>2015-10-07 15:25:58 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74269159</guid>
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      <item>
         <title>Summary - Mathematics of Financial Markets</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74310287</link>
         <description><![CDATA[<p><span style="font-size: 13px;">Mathematical Finance is the basis </span><span style="font-size: 13px;">of a huge industry at the centre of modern global economic development, and the source of a great deal of mathematics. Further, the theory and applications have proceeded in parallel in a closely-linked way. Different types of mathematical models have helped in formulating different types of marketing strategies. Bachelier’s theory brought the idea of “Brownian Motion” in the year 1900. Bachelier’s main objective was to study the valuation of options. His ideas were supported by other scientists such as Einstein, Wiener, Kolmogorov and Kiyoshi. Paul-Andr´e Meyer’s supermartingale decomposition theorem opened the way to defining stochastic calculus. The net effect of these developments was to turn stochastic analysis accessible to science. In 1965 Paul Samuelson introduced the standard model, namely </span><i style="font-size: 13px;">geometric </i><span style="font-size: 13px;">Brownian motion and Ito calculus. The famous Black-Scholes formula was published in 1973. By 1980 arbitrage pricing theory was established and a close link with martingale theory was seen by Harrison, Kreps and Pliska. Various developments such as The Binomial Model, The Fundamental Theorem of Asset Pricing and many other models led to growth of the branch of Mathematical Finance.</span></p>]]></description>
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         <pubDate>2015-10-07 17:21:46 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74310287</guid>
      </item>
      <item>
         <title>Functions and Linear Models</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74312603</link>
         <description><![CDATA[]]></description>
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         <pubDate>2015-10-07 17:28:53 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74312603</guid>
      </item>
      <item>
         <title>Summary - Prediction of Stock Price Movement Using Continuous Time Models</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74312876</link>
         <description><![CDATA[<p>Mathematics plays a crucial role in functioning of financial markets and predicting the increment or decrement of the values of stocks.Complex financial systems can be described using mathematical concepts,known as mathematical models.
Continuous time mathematical models have a particular value for potentially only an infinitesimally short amount of time.Some of its types are Black-Scholes model,input-output model,brownian model and monte carlo model.
 The Monte Carlo techniques are used for simulating stock price processes. For predicting the direction of stock price (as indicated by the hit ratios), the GBM (Geometric Brownian motion) model or VG (Variance Gamma) model can be used in any Monte Carlo method as most of the times we found no significant differences as evidenced from the t-tests. The hit ratios obtained are “near” random walk behavior. This hints that predicting stock price movement is a very challenging task. Since the results of the hit ratios are at the same level where even a random predictor can produce them, the results are justifiable. 
For predicting the stock price values using the monte carlo method, the GBM model performs well under the QMC (Quasi monte carlo) method and the VG model performs well under the LSMC (Least squares monte carlo) method. The finding has important implications in risk management simulations. </p>]]></description>
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         <pubDate>2015-10-07 17:29:46 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74312876</guid>
      </item>
      <item>
         <title>Louis Bachelier</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74314952</link>
         <description><![CDATA[<p>Louis Bachelieron the Cenetary of Theorie De La Sp ´ Eculation </p>]]></description>
         <enclosure url="https://www.ifa.com/media/images/pdf%20files/bachelier100years.pdf" />
         <pubDate>2015-10-07 17:35:59 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74314952</guid>
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      <item>
         <title>Buffet and Mathematics</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74317579</link>
         <description><![CDATA[]]></description>
         <enclosure url="http://johnhcochrane.blogspot.in/2012/11/buffet-math.html" />
         <pubDate>2015-10-07 17:43:01 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74317579</guid>
      </item>
      <item>
         <title>What do you need to track down productive stocks?</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74321270</link>
         <description><![CDATA[<p>The finance industry has done such a good job of ensuring that share prices are divorced in investors minds from their underlying businesses that the most printed stock ratios on the web are always the <em>Dividend Yield</em> and the <em>PE Ratio</em>. These are great ratios, but useless for comparing companies on anything other than valuation grounds.</p><p>For investing in companies that can deliver extraordinary long term investment returns what one needs to understand is <em>how profitable a company is</em>, <em>what the company does with that profit</em> and<em>how a simple GCSE maths trick work wonders</em></p>]]></description>
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         <pubDate>2015-10-07 17:53:06 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74321270</guid>
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      <item>
         <title>What is the key ratio required to find great stocks?</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74322601</link>
         <description><![CDATA[<p>If a company issues shares it starts with some equity in the bank (cash) that it invests to hopefully make a profit. The profit that the company generates as a percentage of the equity invested is known as the&nbsp;<em>return on equity</em>&nbsp;(ROE).</p><p><strong>This simple profitability measure (<em>that stock market websites so rarely seem to print</em>) is the single most important ratio for finding huge wealth generating stocks</strong>. Why? The reason lies in what happens to the profit once its generated.</p>]]></description>
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         <pubDate>2015-10-07 17:56:49 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74322601</guid>
      </item>
      <item>
         <title>What happens to the profit?</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74323293</link>
         <description><![CDATA[<p>Profit is either paid out as dividends to shareholders or retained and reinvested in the business. Reinvesting this profit is where it gets interesting. That retained profit is&nbsp;<em>added back to the starting equity</em>&nbsp;to create an even&nbsp;<strong>larger capital base</strong>. If this capital can be reinvested at the same high return as the previous year then the next year's profits will be proportionally bigger. In a really great replicable and scalable business model this can repeat again and again over dozens of years… and the maths of what happens then can be startling.</p>]]></description>
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         <pubDate>2015-10-07 17:58:40 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74323293</guid>
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      <item>
         <title>What can be the result of compounding?</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74324455</link>
         <description><![CDATA[<p>If profits are fully retained by a company -&nbsp;<b>₹</b><b>10,000 invested at a 20% return (ROE) for 10 years becomes more than </b>₹<b>60,000 and after another 10 years becomes </b>₹<b>380,000.</b>&nbsp;That's 38 times your money in 20 years.</p><p>This is the kind of business that Warren Buffett in his understated manner would say had '<em>good economics</em>' and that's why it pays to play the stock market only in high ROE shares. You just can't get these kind of astonishing compounding returns in any low ROE business.</p>]]></description>
         <enclosure url="" />
         <pubDate>2015-10-07 18:00:49 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74324455</guid>
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      <item>
         <title>Where can you find high ROE companies?</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74324743</link>
         <description><![CDATA[<p>In order to find potentially great companies its worth using some&nbsp;stock screening option&nbsp;such as that at Stockopedia Premium to search for a consistent ROE of greater than a 12% average over the last 10 years with profit margins and asset turnover in the top quartile of their industry and only a moderate level of gearing. &nbsp;Analysing the durability of the competitive advantage&nbsp;is the next step and only then is it worth keeping an eye on the share price. Inderstanding intrinsic  and relative valuation will help finding the right buy point.</p>]]></description>
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         <pubDate>2015-10-07 18:01:42 UTC</pubDate>
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      </item>
      <item>
         <title>Isn&#39;t everyone trying to findgreat stocks?</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74325251</link>
         <description><![CDATA[<p>Perhaps they are - but do they really know what they are looking for? Generally what many traders are doing is chasing the&nbsp;<strong>speculative return</strong>&nbsp;- the portion of share returns due to the expansion of the P/E multiple.&nbsp;<strong>Over a lifetime the speculative return is zero</strong>&nbsp;as PE ratios will always revert back to the mean. All that an investor can end up with in the end is the&nbsp;<strong>investment return</strong>&nbsp;of a stock which is entirely down to the growth in its profits and any dividends paid out . One can only win in the long run by tracking down and sticking with a great company with sustainably high returns on equity.</p>]]></description>
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         <pubDate>2015-10-07 18:03:21 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74325251</guid>
      </item>
      <item>
         <title>Survey</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74335127</link>
         <description><![CDATA[]]></description>
         <enclosure url="https://docs.google.com/forms/d/1ViZKe8nVrKZyxYhOQPGbTOhReCWLbF3jhej-KnT4wHU/viewform?usp=send_form" />
         <pubDate>2015-10-07 18:31:17 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74335127</guid>
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      <item>
         <title></title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74340260</link>
         <description><![CDATA[]]></description>
         <enclosure url="http://money.howstuffworks.com/personal-finance/financial-planning/stock-market-trends.htm" />
         <pubDate>2015-10-07 18:47:01 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74340260</guid>
      </item>
      <item>
         <title>How Do Stock Market Trends Work?</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74340356</link>
         <description><![CDATA[<p>You'v­e seen movies in which frantic stock traders&nbsp;are buying a thousand shares of a hot stock or dumping shares of a plummeting stock. You've seen commercials for brokerage firms that claim to have exciting prospects and strong portfolios. And you've probably heard a hundred different ways to predict the rise and fall of the stock market.</p><p>How do these traders and firms predict which shares will hit big? How do they know when to sell?</p><p>The truth is there is no magical way to predict the stock market. Many issues affect rises and falls in share prices, whether gradual changes or sharp spikes. The best way to understand how the market fluctuates is to study trends.</p><p>In this article we will discuss stock market trends, which help investors identify what stocks to buy and when. Keeping track of upswings and downswings over the history of individual stocks, as well as being aware of market-wide trends, helps investors plan buying and selling.</p><p>Many­ factors affect prices in the stock market, including inflation, interest rates, energy prices,&nbsp;oil prices&nbsp;and international issues, such as war, crime, fraud and political unrest.</p><p>Sudden rises or drops in stock prices are often called spikes. Spikes are extremely difficult, if not impossible, to predict. Stock market trends are like the behavior of a person. After you study how a person reacts to different situations, you can make predictions about how that person will react to an event. Similarly, recognizing a trend in the stock market or in an individual stock will enable you to choose the best times to buy and sell.</p><p>Source:</p>]]></description>
         <enclosure url="http://money.howstuffworks.com/personal-finance/financial-planning/stock-market-trends.htm" />
         <pubDate>2015-10-07 18:47:16 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74340356</guid>
      </item>
      <item>
         <title>Glossary</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74341976</link>
         <description><![CDATA[]]></description>
         <enclosure url="http://www.sundaramdirect.in/downloads/glossarysm.pdf" />
         <pubDate>2015-10-07 18:52:31 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74341976</guid>
      </item>
      <item>
         <title>Technical Analysis Tools</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74344049</link>
         <description><![CDATA[]]></description>
         <enclosure url="http://www.investopedia.com/slide-show/tools-of-the-trade/" />
         <pubDate>2015-10-07 18:59:30 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74344049</guid>
      </item>
      <item>
         <title>Technical Analysis Tools</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74344786</link>
         <description><![CDATA[]]></description>
         <enclosure url="http://i.investopedia.com/inv/pdf/tutorials/technicalanalysis.pdf" />
         <pubDate>2015-10-07 19:01:54 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74344786</guid>
      </item>
      <item>
         <title>JournalAn Introduction to Financial Mathematics </title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74345842</link>
         <description><![CDATA[]]></description>
         <enclosure url="http://www.tcs.tifr.res.in/~sandeepj/avail_papers/chapter.pdf" />
         <pubDate>2015-10-07 19:06:01 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74345842</guid>
      </item>
      <item>
         <title>Application - &amp;nbsp;Predicting crashes in financial markets
with the Log-Periodic Power Law</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74357229</link>
         <description><![CDATA[<p>Speculative bubbles seen in financial markets, show similarities in
the way they evolve and grow. This particular oscillating movement
can be captured by an equation called Log-Periodic Power Law. The
ending crash of a speculative bubble is the climax of this Log-Periodic
oscillation. The most probable time of a crash is given by a parameter
in the equation. By fitting the Log-Periodic Power Law equation to
a financial time series, it is possible to predict the event of a crash.
With a hybrid Genetic Algorithm it is possible to estimate the parameters
in the equation. Until now, the methodology of performing
these predictions has been vague. The ambition is to investigate if the
financial crisis of 2008, which rapidly spread through the world, could
have been predicted by the Log-Periodic Power Law. Analysis of the
SP500 and the DJIA showed the signs of the Log-Periodic Power Law
prior to the financial crisis of 2008. Even though the analyzed indices
started to decline slowly at first and the severe drops came much further,
the equation could predict a turning point of the downtrend.
The opposite of a speculative bubble is called an anti-bubble, moving
as a speculative bubble, but with a negative slope. This log-periodic
oscillation has been detected in most of the speculative bubbles that
ended in a crash during the Twentieth century and also for some antibubbles,
that have been discovered. Is it possible to predict the course
of the downtrend during the financial crisis of 2008, by applying this
equation? The equation has been applied to the Swedish OMXS30
index, during the current financial crisis of 2008, with the result of a
predicted course of the index.
</p>]]></description>
         <enclosure url="" />
         <pubDate>2015-10-07 19:56:30 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74357229</guid>
      </item>
      <item>
         <title>References-  Prediction of Stock Price Movement Using Continuous Time Models</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74359004</link>
         <description><![CDATA[<p><b>Journal by Masimba E. Sonono,Hopolang P. Mashel
Published On 22 May 2015</b></p><p>[1] Leung, M., Daouk, H. and Chen, A. (2000) Forecasting Stock Indices: A Comparison of Classification and Level Estimation
Models. International Journal of Forecasting, 16, 173-190. <a href="http://dx.doi.org/10.1016/S0169-2070(99)00048-5">http://dx.doi.org/10.1016/S0169-2070(99)00048-5</a>
[2] Maberly, E.D. (1986) The Informational Content of the Interday Price Change with Respect to Stock Index. Journal of 
M. E. Sonono, H. P. Mashele
191
Futures Markets, 6, 385-395. <a href="http://dx.doi.org/10.1002/fut.3990060304">http://dx.doi.org/10.1002/fut.3990060304</a>
[3] Wu, Y. and Zhang, H. (1997) Forward Premiums as Unbiased Predictors of Future Currency Depreciation: A NonParametric
Analysis. Journal of International Money and Finance, 16, 609-623.
<a href="http://dx.doi.org/10.1016/S0261-5606(97)00022-3">http://dx.doi.org/10.1016/S0261-5606(97)00022-3</a>
<p>[4] Aggarwal, R. and Demaskey, A. (1997) Using Derivatives in Major Currencies for Cross-Hedging Currency Risks in <span style="font-size: 13px;">Asian Emerging Markets. Journal of Future Markets, 17, 781-796.</span></p><a href="http://dx.doi.org/10.1002/(SICI)1096-9934(199710)17:7&lt;781::AID-FUT3">http://dx.doi.org/10.1002/(SICI)1096-9934(199710)17:7&lt;781::AID-FUT3</a>&gt;3.0.CO;2-J
[5] Imandoust, S. and Bolandraftar, M. (2014) Forecasting the Direction of Stock Market Index Movement Using Three
Data Mining Techniques: The Case of Tehran Stock Exchange. International Journal of Engineering Research and
Applications, 4, 106-117.
[6] Abidin, S. and Jaffar, M.M. (2012) A Review on Geometric Brownian Motion in Forecasting the Share Prices in Bursa
Malaysia. World Applied Sciences Journal, 17, 87-93.
[7] Abidin, S. and Jaffar, M.M. (2014) Forecasting Share Prices of Small Size Companies in Bursa Malaysia. Applied Mathematics
and Information Sciences, 8, 107-112. <a href="http://dx.doi.org/10.12785/amis/080112">http://dx.doi.org/10.12785/amis/080112</a>
[8] Mandelbrot, B.B. (1963) TheVariation of Speculative Prices. Journal of Business, 36, 394-419.
<a href="http://dx.doi.org/10.1086/294632">http://dx.doi.org/10.1086/294632</a>
[9] Fama, E. (1965) The Behaviour of Stock Market Prices. Journal of Business, 64, 34-105.
<a href="http://dx.doi.org/10.1086/294632">http://dx.doi.org/10.1086/294632</a>
[10] Madan, D.B. and Seneta, E. (1990) The Variance Gamma Model for Share Market Returns. Journal of Business, 64,
511-524. <a href="http://dx.doi.org/10.1086/296519">http://dx.doi.org/10.1086/296519</a>
</p>]]></description>
         <enclosure url="" />
         <pubDate>2015-10-07 20:08:16 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74359004</guid>
      </item>
      <item>
         <title>References - Mathematics of Financial Markets</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74359210</link>
         <description><![CDATA[<p><b>Journal by Mark Devis
Published On 3 Sep 2000</b></p><p>1. L. Bachelier: Th´eorie de la Sp´eculation. Ann. Sci. Ecole Norm. Sup. 17 (1900) 21–
86 [English translation in P. Cootner (ed.) The Random Character of Stock Prices.
MIT Press, 1964, reprinted Risk Books, London 2000]
2. P. L. Bernstein: Capital Ideas. The Free Press, New York 1992
3. F. Black and M. Scholes: The pricing of options and corporate liabilities. J. Political
Econom. 81 (1973) 637–654
4. J. Cox, S. Ross and M. Rubinstein: Option pricing, a simplified approach. J. Financial
Economics 7 (1979) 229–263
5. R. C. Dalang, A. Morton andW.Willinger: Equivalent martingale measures and noarbitrage
in stochastic securities market models, Stochastics and Stochastics Reports
29 (1989) 185–202
6. M. H. A. Davis: Option pricing in incomplete markets, in M. A. H. Dempster and
S. R. Pliska (eds.) Mathematics of Derivative Securities. Cambridge University Press
1997
7. F. Delbaen and W. Schachermayer: A general version of the fundamental theorem
of asset pricing. Math. Ann. 300 (1994) 463–520
8. F. Delbaen and W. Schachermayer: The fundamental theorem of asset pricing for
unbounded stochastic processes. Math. Ann. 312 (1998) 215–250
9. J. L. Doob: Stochastic Processes. Wiley, New York 1953
10. A. Einstein: U¨ ber die von der molekularkinetischen Theorie der Wa¨rme geforderte
Bewegung von in ruhenden Fl¨ussigkeiten suspendierten Teilchen. Annalen der
Physik 17 (1905) 549–560</p>]]></description>
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         <pubDate>2015-10-07 20:09:32 UTC</pubDate>
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      <item>
         <title>Application - How does the stock market affect the economy?</title>
         <author>f2015352</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74359668</link>
         <description><![CDATA[<p>Movements in the stock market can have a profound economic impact on the economy and everyday people. A collapse in share prices has the potential to cause widespread economic disruption. Most famously,&nbsp;the stock market crash of 1929&nbsp;was a key factor in causing the&nbsp;great depression&nbsp;of the 1930s. Yet, daily movements in the stock market can also have less impact on the economy than we might imagine. During the great recession of 2009-13, the stock market performed quite strongly. This rise in share prices was rather misleading to the state of the economy. Also, a fall in share prices doesn’t necessarily cause an economic downturn.</p><p>For example, the stock market crash of 1987, didn’t cause any lasting economic damage. (though it did influence monetary policy. UK cut interest rates in fear the stock market crash would cause a recession. Instead, low interest rates caused a boom.</p><p>Plummeting share prices can make headline news. But, how much should we worry when share prices fall? How does it impact on the average consumer? and how does it affect the economy?</p>]]></description>
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         <pubDate>2015-10-07 20:12:34 UTC</pubDate>
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      <item>
         <title>How I collected my data</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74489103</link>
         <description><![CDATA[<p>I collected data using internet. E-books,youtube videos and tutorials and Powerpoint presentations from slideshare helped in understanding the topic faster.</p>]]></description>
         <enclosure url="" />
         <pubDate>2015-10-08 13:37:40 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74489103</guid>
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      <item>
         <title>Link To Material</title>
         <author>f2015334</author>
         <link>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74489385</link>
         <description><![CDATA[<p>Most of the links are mentioned with the article itself. Slides having no link are mostly self written </p>]]></description>
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         <pubDate>2015-10-08 13:38:32 UTC</pubDate>
         <guid>https://padlet.com/f2015352/x5o5xr4brzh8/wish/74489385</guid>
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