No abstract

The current article takes account of the existing status of risk management practices of the Indian publicly listed companies and establishes the relationship of their risk management programme with the firms’ financial characteristics such as capital structure, assets’ size, asset tangibility, profitability and valuation multiples. To establish the relationship, a risk management score is constructed using publicly disclosed information for Bombay Stock Exchange (BSE) Sensex 30 companies. Results suggest that companies with more comprehensive risk management programmes are likely to enjoy lower costs of debt and have a higher propensity to invest in intangible assets. These firms with more comprehensive risk management programmes also demonstrate more stable cash flows, sales and net operating profit. It is also evident that firms that are deeply indulged in risk management activities are likely to have higher financial leverage as higher leverage increases a firm’s total risk, and their risk management activities act to balance that risk. Consequently, firms with extensive risk management activities can endure higher debt in their capital structure; hence, a risk management programme works as a substitute of equity capital.

Money market microstructure has recently started drawing attention in the empirical literature on financial markets of emerging market economies. In the Indian context, a GARCH(1, 1) model shows that policy instruments impact bid-ask spreads in the money market. Volatility of bid-ask spreads seems to be more persistent in the overnight market than in longer maturity segments. The results also suggest the dominance of policy interventions over the market microstructure across the term structure of the Indian money market. Unanticipated policy actions can delay mean reversion and, therefore, the return to stability.monetary policy, market microstructure, GARCH, persistence,

Globally, technology firms are characterized by high level of innovation, rapid obsolescence of technologies, high investment risk and unpredictability of future cash flows. All these make conventional discounted cash flow valuation methods inadequate for valuation of technology firms. This study aims to develop sector regression models for relative valuation of technology firms by evaluating firm-level determinants of price multiples. Results suggest that price to book is the most appropriate multiple for valuing developed market technological firms, whereas price to sales is the most apt multiple for emerging market firms. Variable selection by least absolute shrinkage and selection operator (lasso) validates that growth rate, research intensity and cash holding influence value of price multiples for both developed market and emerging market firms. Similarly, smaller firms tend to generate higher value of the multiples under both categories. Firms’ ESG practices is an important determinant of price multiples for developed market firms, however, it does not influence the multiples’ value for emerging market firms.

In the literature, currency in circulation is typically estimated either by specifying a standard currency demand equation based on the theory of transaction or portfolio demand for money or by a univariate time series model. The paper argues that while these approaches work well for low frequency data, their scopes become limited for high frequency series. Using the weekly data of currency in circulation from the year 1992-1993 to 1999-2000, the paper proposes an alternative approach of modelling the growth of currency in circulation by incorporating the 'day of the month' effect. The estimated equation behaves very well in and out of sample and the prediction performance achieved from the model has been good.