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Religare Commodities Metals and Energy Research
Religare Enterprises Ltd is a Ranbaxy promoter group company 6 Regional offices Northern Regional Office Gujarat Regional Office 25 Zonal Offices Presence through more than 900 locations-Pan India Present across more than 320 Cities & Towns Total group employees 6, 500 plus Client Interfaces through the Retail, Wealth and Institutional spectrums Among the largest Retail brokerage branch network, going beyond Tier-I and Tier-II cities in India Overseas presence with a representative office in London, with aggressive plans of straddling other parts of the globe in this financial year Religare Data Centre has ISO/IEC 27001: 2005 certification Mumbai Regional Office Eastern Regional Office Southern Regional Office Maharashtra Regional Office
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Business Structure Client Interface Retail Spectrum Institutional Spectrum To cater to a large number of retail clients by offering all products under one roof through the Branch Network and Online mode To Forge & build strong relationships with Corporate clients and Institutions To provide customized wealth advisory services to High Net worth (HNI) Individuals Institutional Broking Wealth Advisory Services Equity and Commodity Trading Personal Finance Services Mutual Funds Insurance Savings Products Personal Credit Personal Loans against Shares Online Investment Banking Merchant Banking Transaction Advisory Corporate Finance Wealth Spectrum Portfolio Management Services International Advisory Fund Management Service (AFMS) Priority Equity Client Services Arts Initiative
Operating Structure Customized Solutions Key Facts • Retail Division: – Looking after the retail investors or individual clients. Either they trade themselves or dealers trade on their behalf on the basis of the research calls given by the Religare research team after Religare Commodities Ltd Corporate Desk the client’s confirmation. • Corporate Desk – This desk deals exclusively with the Corporates, assisting them in the hedging strategies or giving them the right Arbitrage Desk business solution for treasury investments • Arbitrage Desk – This desk provides delivery-based Spotfutures arbitrage to high net worth client investments • Mandi Division (Rural) – This division specially caters to needs of clients who are in rural markets, such as farmers, traders, etc
Commodities Research • Commodities Research has been classified into two. • Metals and Energy Research • Agri Research Scope Research supports intraday traders to maximize wealth on short-term volatility. Research Prepares periodic reports for medium term wealth maximization. Research supports corporate and institutional team for Presales and Postsales Research
Metal Model for High Frequency prediction Variables Used Name Variables Gold gold Silver silver Copper copper_usd Crude Oil Light sweet Crude_nymex Euro/USD euro_usd Dow Index dow For gold the international interbank spot data is taken in ($/Oz), silver data taken from international interbank spot in ($/Oz), copper prices are taken from LME 3 months forward ($/ton), crude oil taken from NYMEX ($/bbl), euro/usd is taken form spot interbank refrence rate, Dow taken as INDEX data declared by NYSE.
Correlation Matrix Gold silver Copper euro_usd crude_nymex dow Gold 1. 0 0. 8 0. 6 0. 8 0. 4 0. 7 silver 0. 8 1. 0 0. 4 0. 6 0. 0 0. 6 Copper 0. 6 0. 4 1. 0 0. 5 0. 3 euro_usd 0. 8 0. 6 0. 5 1. 0 0. 3 0. 9 crude_nymex 0. 4 0. 0 0. 5 0. 3 1. 0 0. 7 dow 0. 7 0. 6 0. 3 0. 9 0. 0 1. 0 Correlation analysis shows that there is a good correlation between gold and euro_usd and then gradually sloping towards silver and then dow, copper and crude_nymex. Crude has shown the least correlation to gold and then copper.
Regression results R 2 shows a high degree of fit, and SD for residual is well into range.
Analysis and conclusion The model shows a greater degree of fit i. e R 2 of 0. 9 and hence can be considered as a good model for gold price prediction. The scatter diagram for residual fits shows that the predictor maximum deviation ranges from -40 to +40 but well remain in the median range of $2 -4. The below scatter chart plots the residual with date.
Scope for Future Work • The selection of independent variables was subjected to availability of high frequency data (daily) so more independent variables should be introduced. • Dow and euro_usd shows high correlation and hence may pose a problem of multicolinearity but P (Probability of hypothesis) has not eliminated either of the variables. • Elimination of one of the variables changes the model, but eventually elimination of Dow from the model keeps the fitness intact, hence dow can be significantly removed, future work will include addition of such not correlated exogenous independent variable in the equation. • The model may be fitted with Indian data for making it relevant to Indian market.
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