R. Venkataraman ¹, Thilak Venkatesan ²

Affiliations
1 Presidency College, Bangalore, IN
2 Bharathiar University, Coimbatore, IN

Abstract

Investors are always baffled about the risk-return characteristics of their investments. There is often the challenge of the alternative between active&passive investments. In case of active mutual funds there are numerous categories of active funds each tracking a different benchmark. It often leads to confusion about how the performance can be compared between one fund to another. The growth of ETFs' has been phenomenal in the recent years due to various advantages of an exchange traded fund compared to the mutual fund as lower cost of management, lesser dependence on fund manager, ease of transaction to name a few. In this context the research analysedthe passive ETF's&prominent Mutual funds both active and passive to justify superior returns at lower risk. The research was based on secondary data, for a period of 5 years i.e. from 2010 to 2015.The various tools used were Sharpe Ratio, Jenson's Alpha, Treynor's Ratio and Tracking error. The study recommends fund houses to implement proactive strategies to reduce tracking error and make ETF's a better alternative for investment.

Keywords

Mutual Funds, Exchange Traded Funds, Tracking Error and Jenson’s Alpha.

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Thilak Venkatesan ¹, M. S. Ponnamma ¹

Affiliations
1 Presidency College, Bangalore, IN

Abstract

The Indian Rupee is launching its foot print in global market, which can be characterized by the fact that Bhutan and Nepal peg their currencies to Indian Rupee. The Indian economy contributes a higher GDP growth compared to other emerging economies. The increase in the GDP, aids well for a strong foreign exchange along with other economic factors such as gross domestic savings, forex reserve, inflation and so on. The various initiatives taken by the government recently to attract more foreign capital through various investment schemes and reduce interest rate as well assists to achieve a stabilized exchange rate in India. The RBI is focused for capital account convertibility, with various measures to achieve a freely floating currency from the present managed float in India. In view of recent appreciation of Chinese Yuan, it became tough for policy makers to take up an immediate action in supporting the home-grown industries. In this context, the research focuses to find and evaluate the various macroeconomic factors affecting the exchange rate and to model the factors using Auto Regressive Distributive Lag, to enable to forecast the exchange rate. The research focuses on finding the significant factors influencing the volatility of the exchange rate.

Keywords

Macroeconomic Variables, Econometric Modeling, ADF Test, Vector Auto Regressive Model, ARDL.

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Thilak Venkatesan ¹, R. Venkataraman ²

Affiliations
1 Bharathiar University, Coimbatore, IN
2 Presidency College, Bangalore, IN

Abstract

Financial literacy will enable better decision making and efficient management of funds. The knowledge of basic foundations of time value can result in building a robust portfolio. The recent initiatives by the government on financial inclusion aids in promoting faster access to transfer benefits. The policy implementation on bank accounts for all, linking of Aadhar to the accounts, insurance of minimum sum assured for all and the basic annuation schemes are some of the initiatives well devised by the Modi Government. The RBI on the other hand, had initiated various financial literacy programmes to have significant inclusion. The key to successful inclusion is financial literacy. In this context, the paper attempted to identify factors that determine financial literacy. The data was collected through primary sources trough structured questionnaire. The tools used for the analysis was confirmatory factor analysis and structural equation modelling. The factors identified were financial attitude, behavioural factors, financial knowledge and influence and among the factors financial knowledge and influence were observed to predict financial literacy.

Keywords

Behavioural Finance, Financial Literacy, Financial Inclusion.

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