Research
A Note on Chebyshev Inequality: To Explain or to Predict
The question is: What proportion of the total probability of a random varriable X lies within a certain interval of the mea? What is the probability of being hit by a meteor greater in size than five times the standard deviation above the mean? Because it can be applied to completely arbitrary distributions (unknown except for mean and variables), the inequality generally gives a poor bound compared to what might be deduced if more aspects are known about the distribution involved.
The Stock Market Volatility and Regime Changes: A Test in Econometrics
This paper applies the Markov switching heteroscedasticity model to stock return for India. The Markov switching model in our study takes into account the chance of regime shift, a possibility outside the purview of the GARCH model. Our finding tells us that the high variance of the transitory component tends to be short lived. Although parameters estimating the impact of time-varying expected returns and the delivery system are in some cases qualitatively different between the regimes, the differences do not produce significant changes in our model of stock returns.
Deriving Kalman Filter – An Easy Algorithm
The Kalman filter may be easily understood by the econometricians, and forecasters if it is cast as a problem in Bayesian inference and if along the way some well-known results in multivariate statistics are employed. The aim is to motivate the readers by providing an exposition of the key notions of the predictive tool and by laying its derivation in a few easy steps. The paper does not deal with many other ad hoc techniques used in adaptive Kalman filtering.
Delta- Hedging: Comments and a Case in Mathematical Finance
The paper questions the ability of arbitrageurs to ascertain value with some confidence and to realize it quickly. The discussion in the paper suggests a reason why some markets are more attractive for arbitrage than others The paper identifies a number of so-called anomalies in which particular investment strategies have may not earn higher returns than their systematic risk. Our analysis offers a different mathematical approach to understanding these anomalies than does the standard efficient market theory.
Markov Switching Heteroscadasticity Model of Stock Return: A Test
This paper applies the Markov switching heteroscedasticity model to stock return for India. The Markov switching model in our study takes into account the chance of regime shift, a possibility outside the purview of the GARCH model. Our finding tells us that the high variance of the transitory component tends to be short lived.
Money as a Medium of Exchange: Then and Now: Can Technology Be A Facilitator of Exchange?
This paper deals with the origin of money through its function as a medium of exchange. Barter can give rise to money through necessitating the use of a standard of value even before calling for the use of a medium of exchange. In a given society at any point in time money is defined in principle simply as the subset of total financial assets and commodities which are actually performing monetary functions. Three main functions are usually suggested. Money is thought to be that which serves as a medium of exchange, standard of value and store of value. Defining money in a particular context would simply involve a judgment as to which items currently possess these properties to a greater or lesser extent. The paper also ascertains whether money originated through its function as a medium of exchange, can explain the dynamics of monetary exchange of most recent days. The paper also ascertains if technological changes can improve the efficiency of the trading process.
The Myth of Equilibrium and The Myth of Optimization: Outside Natural Sciences: A Graduate Lecture
Both the optimization and equilibrium principles turn out to be more akin to common sense than to science. They have been postulated as describing markets, but lack the required empirical underpinning. Optimization is not a magic cure. In order to particularly circumvent some of the technical obstacles for a control problem , it turns out to be practically effective to reduce the system dynamics to a system of ordinary differential equations of considerably higher dimension, Such an approach might replace a theoretical difficulty by a greatly increased computational problem.
Tax Perception and Sample Selection Bias: Microeconometrics
This paper econometrically compares the perceived marginal tax rates and the actually computed marginal tax rates and tries to find out if consumers could accurately perceive the marginal tax rates. Econometrically, the paper highlights that sample selectivity operates through unobservable elements and their correlation with unobservables influencing the variable of primary interest. Sample selection bias will not arise purely because of difference in observable characteristics. Although our paper is illustrative, it highlights the generality of the issue and its relevance to many economic examples
Does Adam Smiths Invisible Hand Work for Financial Markets: Comments
Adam Smith theory of the Invisible Hand is fundamentally flawed. The neoclassical theory based on it relies on market models in which economic agents interact with the market forces that are not governed by Universal Law of Nature; such models ignore correlations that lead to booms and depressions. To prove rigorous theorems financial economists also assume that market fluctuations follow a certain statistical distribution a la a thermodynamic equilibrium approach. Do they really score a major breakthrough? No - the dominant ‘equilibrium principle’ of the market is only a hope, not a reality: It lacks proper empirical underpinning. Statistics and mathematics do not help.
Financial Time Series -Recent Trends in Econometrics
The paper points to a coverage of the latest research techniques and findings relating to the econometric analysis of financial markets. It contains a wealth of new materials reflecting the developments during the last decade or so. Particular attention is paid to the wide range of nonlinear models that are used to analyze financial data observed at high frequencies and to the long memory characteristics found in financial time series. There is also a discussion, briefly, of the treatment of volatility, chaos, the Fed model, stochastic estimation and Bayesian estimation, the Fed model and tail dependent time series models.
