120 likes | 343 Views
Religare Commodities Metals and Energy Research. Northern Regional Office. Gujarat Regional Office. Mumbai Regional Office. Eastern Regional Office. Southern Regional Office. Maharashtra Regional Office. Religare Enterprises Ltd. Religare Enterprises Ltd is a Ranbaxy promoter group company
E N D
Northern Regional Office Gujarat Regional Office Mumbai Regional Office Eastern Regional Office Southern Regional Office Maharashtra Regional Office Religare Enterprises Ltd • Religare Enterprises Ltd is a Ranbaxy promoter group company • 6 Regional offices • 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
Corporate Structure Religare Finvest Ltd Religare Wealth Management Services Ltd Religare Securities Ltd Religare Capital Markets Ltd Religare Commodities Ltd Religare Enterprises Ltd Religare Finance Ltd Religare Insurance Broking Ltd Religare Venture Capital Pvt Ltd Religare Realty Ltd
Business Structure Client Interface
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 the client’s confirmation. • Corporate Desk • This desk deals exclusively with the Corporates, assisting them in the hedging strategies or giving them the right business solution for treasury investments • Arbitrage Desk • This desk provides delivery-based Spot-futures 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 Retail Division Corporate Desk Religare Commodities Ltd Arbitrage Desk Mandi Division
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 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 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 R2 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 R2 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.