An energy based hedge fund - Free Essay Example

Sample details Pages: 7 Words: 2030 Downloads: 4 Date added: 2017/06/26 Category Uncategorized Essay Type Argumentative essay Level High school Did you like this example? Introduction The concept of trading stocks should not need an explanation for the seasoned high net worth individual (HNWI) or small investment fund owner. However just for the sake of revision we shall reiterate a few important definitions throughout the course of this report and in the glossary at the end. The aims of this brief report are to: Develop a simple technical trading system for a hedge fund of interest to you the HNWI as well as the small investment fund investor. Construct a comprehensive comparison of the data with regards to the daily open/ high/ low/ close/ and volume for both the British Gas [(BG) Symbol: BGMD.OQ] and the National Grid Plc (Symbol: NGG) stocks. To develop the trading system according to a logical rule using training set, test set and a prediction set as the basis for the system recommended for the hedge fund (HF). Background The key factor to developing any kind of financial plan is in understanding the individual or group of individuals for whom it is being designed à ¢Ã¢â€š ¬Ã¢â‚¬Å" in this case it is specifically being designed with HNWIs like CEOs of multinational companies, politicians and the like in mind à ¢Ã¢â€š ¬Ã¢â‚¬Å" who typically indicate a willingness to take a little more risk on investment. According to (Magnum, 2007) à ¢Ã¢â€š ¬Ã…“there is a popular misconception that all hedge funds are volatile that they all use global macro strategies and place large directional bets on stocks, currencies, bonds, commodities, and gold, while using lots of leverage. In reality, less than 5% of hedge funds are global macro funds. Most hedge funds use derivatives only for hedging or dont use derivatives at all, and many use no leverage.à ¢Ã¢â€š ¬Ã‚  Knapp (2004) states that à ¢Ã¢â€š ¬Ã…“Everyone has a different level of risk they are willing to take or time they would have av ailable to dedicate to trading.à ¢Ã¢â€š ¬Ã‚  Lately the modern business trend has been to invest in metals, biotechs and small caps; however energy funds are also very profitable to invest in as you will see in this report. British Gas à ¢Ã¢â€š ¬Ã…“Is the biggest supplier of green power to homes in Great Britain and its electricity has the lowest CO2 emissions of any major UK energy supplier. As a responsible energy provider, it is planning for the future in two ways à ¢Ã¢â€š ¬Ã¢â‚¬Å" by investing in renewable energy and by focusing on improving efficiency and helping its customers reduce their carbon footprint.à ¢Ã¢â€š ¬Ã‚  British Gas (2007) National Grid Plc à ¢Ã¢â€š ¬Ã…“National Grid is dedicated to being the worldà ¢Ã¢â€š ¬Ã¢â€ž ¢s premier network utility. Its core skills lie primarily in the management of large and complex energy delivery networks. It owns, operates and develops the high-voltage electricity transmission network in England and Wales a nd Great Britains principal natural gas transportation system. Itsportfolio ofother businesses is mainly concerned with infrastructure provision and related services where it can exploit its core skills and assets to create value. These businesses operate in areas such as Wireless Network Infrastructure for broadcast and mobile telephones, Metering, Grain LNG Import, Interconnectors and Property.à ¢Ã¢â€š ¬Ã‚  Findings BG (BGMD.OQ) Don’t waste time! Our writers will create an original "An energy based hedge fund" essay for you Create order Calendar Year 2006 2005 High Price 805 582.5 Low Price 576 345.22 Close 694.52 571.71 High P/E 1,578.34 1,358.66 Low P/E 1,129.35 805.22 Year End P/E 1,361.73 1,333.51 Dividend Yield 0.01 0.01 Table 1 Source: https://stocks.us.reuters.com/stocks/performance.asp 2nd Dec. 2007 Table 1 above gives a summary of the BG stock over the two year period from the 1st January 2005 to the 31st December 2006. Table 2 below depicts the current year-to-date performance. BG (BGMD.OQ) Calendar Year 2007 Open 1016.00 Close 1018.00 High Price 1036.00 Low Price 1013.00 Volume 3,022,618 Year End Price 1,015.00 High P/E 1,017.00 Low P/E 1,015.00 Year End P/E 1,361.73 Change -0.29%-3.00 Table 2 Source: https://www.lse.co.uk/share-prices.asp 2nd Dec. 2007 The training set, test set and prediction BG and National Grid Plc rank 1 and 3 respectively amongst the top stocks in the UK. The daily closing prices from 01/01/05 to 31/10/07, with a total of 1034 days, were used. S1 is a sample stock showing very few ups and downs on the historical prices. It has a slight drop during the testing period (-3.00%). Figure 1 again reinforces the logic that S1 is generally upward mobile this means that it is a stock with a rising trend and low volatility during the testing period. It has a substantial gain of 46.58% during the testing period. Stock 1 (S1) British Gas: Stock symbol BGMD.OQ Figure 1 Loading Top of Form In order to optimise the parameters of trading rule the other stock sample has also been included as follows: National Grid Plc (NGG) Stock 2 (S2) Calendar Year 2007 2006 2005 Open 820 High Price 827.00 74.15 51.99 Low Price 813.00 48.39 44.18 Year End Price / Close 821.50 72.62 48.69 High P/E 813.00 -155.44 160.96 Low P/E 812.50 -101.44 136.78 Year End P/E 813.00 -152.23 150.74 Change -1.03%-8.50 Volume 1,283,226 Dividend Yield 0.36 0.49 Table 3 Source: https://stocks.us.reuters.com/stocks/performance.asp 2nd Dec. 2007 The ideal sell signals are located at the local maxima of the historical stock prices. We have hold signals when the stock price is neither close to the maxima nor minima. This information serves as criterion for us to construct the target signals for the training of our trading system. We choose continuous values as the output of the system to denote the strength of the trading signals. The actual trading signals are obtained from the threshold strength. The threshold levels can be served as parameters for investors to control the frequency of trading, as some investors prefer to trade frequently and some prefer to trade once in a while. Assuming that as the investors of the hedge fund, small fluctuations of prices would be of little interest to investors; trading would only be considered if the price difference is large enough to cover at least the transaction cost. Therefore, we select on ly those local extreme with a substantial gap in between. The local extreme we extracted has to exhibit the following characteristics: The extreme has to be alternative, i.e. a local minimum has to be followed by a maximum and vice versa. The price at a minimum (maximum) has to be lower (higher) than the prices at its two adjacent maxima (minima). Between every consecutive maximum/minimum pair, there exists a daily drop in price larger than the last. Between every consecutive minimum/maximum pair, there exists a daily rise in price larger than before. Finally, we construct the target trading signals from the extracted extreme. One advantage of this target signal generation over the traditional prediction of stock prices is that à ¢Ã¢â€š ¬Ã…“it has the ability to generate positive returns in both rising and falling equity and bond markets.à ¢Ã¢â€š ¬Ã‚  (Magnum, 2007) Generally there are many benefits to be derived from hedge funds. According to Magnum (2007) they are: à ¢Ã¢â€š ¬Ã…“Inclusion of hedge funds in a balanced portfolio reduces overall portfolio risk and volatility and increases returns. Huge variety of hedge fund investment styles à ¢Ã¢â€š ¬Ã¢â‚¬Å" many uncorrelated with each other à ¢Ã¢â€š ¬Ã¢â‚¬Å" provides investors with a wide choice of hedge fund strategies to meet their investment objectives. Academic research proves hedge funds have higher returns and lower overall risk than traditional investment funds. Hedge funds provide an ideal long-term investment solution, eliminating the need to correctly time entry and exit from markets. Adding hedge funds to an investment portfolio provides diversification not otherwise available in traditional investing.à ¢Ã¢â€š ¬Ã‚  The output is the strength of the trading signal and sigmoid function was used as the activation function. To evaluate the effectiveness of the trading signals, we derived the investment return IR. In specific, we are interested in buy and sell signals. So, for future reference when we need to indicate the IR for SELL signals it will be denoted as IRS and IRB to denote the IR for the BUY signals. For the BUY signals, a large positive IRB is desirable. On the other hand, for the SELL signals, a negative IRS is desirable. We applied the trading system to the previous two stocks as seen below in Table 4. In each stock, the first half of the historical daily closing prices were used as training set and the remainder were used as testing set. The objective now is to verify if the knowledge learned by the trader can be generalized to other stock. Similar to the calculations and tabulations made above, the trader is trained using the training sets. But this time, we tested the trader u sing the testing sets from other stocks. Table 4 summarizes the average result of the cases. It indicates that the trader trained by S1 gave the best performance. Using it to trade S1 gave better performance than the trader using S2 as training set. Another interesting observation is that the trader using S1 and S2 as training sets can make prods using selling signals when applied to testing set S1, which has an overall rising trend. BUYING Training Testing S1 S2 S1 -114.10% 71.30% S2 121.40% -286.80% SELLING Training Testing S1 S2 S1 (-112.5 %) -120.90% S2 9.20% -21.30% Table 4 The information above shows that the trader developed can be applied to other stocks. In particular, we can generate satisfactory results even if the training set and the testing set are data from two unrelated stocks. Conclusion Fidelity (2004) states that à ¢Ã¢â€š ¬Ã…“In order to have an effective technical trading system it is important to have the trading signals directly related to the historical prices.à ¢Ã¢â€š ¬Ã‚  For this hedge fund system we chose to operate mainly along the aggressive growth hedge fund style. According to Magnum (2004): à ¢Ã¢â€š ¬Ã…“Aggressive Growth: Invests in equities expected to experience acceleration in growth of earnings per share. It has generally high P/E ratios, low or no dividends; it is often smaller and micro cap stocks which are expected to experience rapid growth. It includes sector specialist funds such as technology, banking, or biotechnology. It hedges by shorting equities where earnings disappointment is expected or by shorting stock indexes; and it tends to be long-biased. Expected Volatility: Highà ¢Ã¢â€š ¬Ã‚  In this report we developed a simple technical trading system for an energy based hedge fund for the HNWI as well as the small investment fund investor. We also constructed a comprehensive comparison of the data with regards to the daily open/ high/ low/ close/ and volume for both the British Gas [(BG) Symbol: BGMD.OQ] and the National Grid Plc (Symbol: NGG) stocks; and we also developed the trading system according to a logical rule using training set, test set and a prediction set as the basis for the system recommended for the hedge fund (HF). The system tested and recommended is therefore to use price signals to know when to buy or sell. By selling stocks at higher price than they were purchased for, gains will be made. Glossary Hedge Fund A hedge fund is a fund that can take both long and short positions, use arbitrage, buy and sell undervalued securities, trade options or bonds, and invest in almost any opportunity in any market where it foresees impressive gains at reduced risk. Source: Magnum Training set In artificial intelligence, a training set consists of an input vector and an answer vector, and is used together with a supervised learning method to train a knowledge database (e.g. a neural net or a naive bayes classifier) used by an AI machine. In general, the intelligent system consists of a function taking one or more arguments and results in an output vector, and the learning methods task is to run the system once with the input vector as the arguments, calculating the output vector, comparing it with the answer vector and then changing somewhat in order to get an output vector more like the answer vector next time the system is simulated. Source: Wikipedia Bibliography Knapp, V. Test Technical Trading Ideas https://personal.fidelity.com/myfidelity/atn/archives/november2004.shtml Fidelity Investments 29th Nov. 2007 https://finance.yahoo.com/p?k=eupf_1 30th Nov. 2007 https://finance.yahoo.com/personal-finance/article/103918/The-20-Most-Intriguing-Billionaire-Heiresses 29th Nov. 2007 https://www.magnum.com/hedgefunds/abouthedgefunds.asp 30th Nov.2007 https://en.wikipedia.org/wiki/Training_set 1st Dec. 2007 https://www.lse.co.uk/share-prices.asp 2nd Dec. 2007 Cha S.M, and Chan L., Trading Signal Prediction https://64.233.167.104/search?q=cache:StombJ43ejcJ:www.cse.cuhk.edu.hk/~lwchan/papers/iconip00-trading.ps+prediction+set+tradinghl=enct=clnkcd=1gl=tt https://stocks.us.reuters.com/stocks/performance.asp 2nd Dec. 2007 https://www.nationalgrid.com/uk/About 3rd Dec. 2007