Exchange Rate Models

In Neuroscience, mathematical modelling involving multiple spatial and temporal scales can unveil complex oscillatory activity such as excitability, subthreshold oscillations, spiking or bursting. While the number of slow and fast variables and the geometry of the system determine the type of the complex oscillations, canard structures define boundaries between them. In this study, we use geometric singular perturbation theory to identify and characterise boundaries between different dynamical regimes of multiple-timescale firing rate models of the developing spinal cord. These rate models are either three or four dimensional with state variables chosen within an overall group of two slow and two fast variables. The fast subsystem corresponds to a recurrent excitatory network with fast activity-dependent synaptic depression, and the slow variables represent the cell firing threshold and slow activity-dependent synaptic depression, respectively. We start by studying canard-induced bursting and mixed-mode oscillations in two different three-dimensional rate models. Then, in the full four-dimensional model we show that a canard-mediated slow passage creates dynamics that combine these complex oscillations and

ii BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements, and from time to time by other economists, and are published by the Bank. The views expressed in them are those of their authors and not necessarily the views of the BIS.

In this paper, we offer new evidence on the predictability of exchange rate with commodity prices using the Westerlund and Narayan (2015) estimator. The estimator allows us to control for any possible bias in the estimation process due to the presence of persistence, endogeneity and conditional heteroscedasticity effects in our predictors. We further account for the role of asymmetries and structural breaks both for the in-sample and outof-sample forecasts. In particular, we evaluate whether such considerations matter for the forecast performance of the predictive model for exchange rate. Monthly data of five major tradable currency pairs in the world and disaggregated commodity price indices over the period of 1960-2017 are utilized. We find significant improvements in both the in-sample and out-of-sample forecast performance of the predictive model for exchange rate using this estimator and particularly when asymmetries and structural breaks are accommodated. While the results are robust to multiple currency pairs, commodity price indices, breaks and forecast horizons, however, the choice of data frequency has implications on the forecast outcome. Essentially, the forecast accuracy of the proposed predictive model seems to diminish with lower data frequencies.

We use a novel database of a panel of quarterly survey of exchange rates forecasts available on the Bloomberg platform, for the following five bilateral exchange rates: EUR/GBP, EUR/JPY, EUR/USD, GBP/USD and USD/JPY, for the timespan ranging from the third quarter 2006 up to the fourth quarter of 2011. We find that forecasters are on average irrational, failing to identify the true data generating process of bilateral exchange rates and generally overreacting to past observed information. Moreover, exploring individual performance, we can state that financial analysts irrationally do not look at their past forecast errors to improve the quality of their later forecasts.

The generation of precise respiratory rhythms is vital for birds, which must generate specific pressure patterns to perform several activities, song being one of the most demanding ones. These rhythms emerge as the interaction between a peripheral system and a set of neural nuclei which control the action of expiratory and inspiratory muscles. A computational model was proposed recently to account for this interaction. In this work, we describe the set of solutions that this model can display as its parameters are varied, and compare experimental records of air sac pressure patterns with the predictions of the model.

The increased use of financial derivatives like interest rate and currency swap contracts has drawn much attention, as it exposes banks to non-performance by their counterparts. This credit risk exposure is of great concern to monetary authorities, e.g. the Bank for International Settlements. In this paper a method for the determination of credit risk exposure is developed, in which the exposure is a function of interest rates, exchange rates, and lives of the contracts. To quantify the credit risk exposure, simulations of the variables have been used.

This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. Using survey data of market expectations, we ask which popular exchange rate models appear to be consistent with expectation formation of market forecasters. Exchange rate expectations are found to be correlated with inflation differentials and productivity differentials, indicating that the relative PPP and Balassa-Samuelson effect are common inputs into expectation formation of market forecasters.

We use a novel database of a panel of quarterly survey of exchange rates forecasts available on the Bloomberg platform, for the following five bilateral exchange rates: EUR/GBP, EUR/JPY, EUR/USD, GBP/USD and USD/JPY, for the timespan ranging from the third quarter 2006 up to the fourth quarter of 2011. We find that forecasters are on average irrational, failing to identify the true data generating process of bilateral exchange rates and generally overreacting to past observed information. Moreover, exploring individual performance, we can state that financial analysts irrationally do not look at their past forecast errors to improve the quality of their later forecasts.

We use survey data on five bilateral exchange rates to provide empirical evidence of the fact that professional forecasters of foreign exchange rates behave irrationally, in the specific sense that they respond inaccurately to available information in the market when forming their predictions. In particular, we find systematic biases in the forecasts resulting in the overreaction of analysts to past information contained in the exchange rate dynamics: forecasters change their prediction more than it would be rational on the basis of past realized changes. In addition, forecasters are heterogeneous in their irrationality: low performers in previous periods show a more pronounced overreaction effect. This can be read as an indication of perpetration of past errors and continued inability to learn from the past. In the second part of the paper, we exploit the novel structure of our dataset, which consists of survey data extracted from the Bloomberg platform and readily available to anyone. This feature allows us to consider their own and others' past forecasts as part of the information set that analysts use in making their predictions. By using past forecasts as proxies for relevant macroeconomic variables, we find evidence that analysts fail to correctly process not only the information contained in the spot rate past dynamics but also the information in this broader set. We see this as confirmation of the existence of inefficiency and heterogeneity between low and high performers also when full information is available.

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.

Traditional exchange rate models are based on differences in macroeconomic fundamentals. However, despite being well grounded in economic theory they have a rather poor out-of-sample forecasting record. This empirical failure may be a result of the overly restrictive choice of macroeconomic fundamentals. We suggest using the sovereign yield spread level and slope as proxies of the market's expectations for current and future fundamentals and find promising results when we investigate the out-of-sample forecasting accuracy of these variables. Using the yield spread level and slope as a set of unobservable fundamentals, our approach outperforms traditional exchange rate models for most considered currencies and horizons. It is also superior to a random walk in terms of direction of change forecasts and profitability.

This paper uses monthly data on euro exchange rates vis-à-vis major currencies, covering the period 1999-2012, to compare the forecasting ability of alternative stochastic exchange rate representations. In particular, we test the out-of-sample forecasting performance of a random walk, a non-linear Markov switching regimes process, and a vector autoregressive representation reflecting the dynamics of linear structural exchange rate models. These statistical models are evaluated in terms of the root mean square error of one-month to twelve-month out-of-sample forecasts. The empirical evidence points to the random walk puzzle, that is, the superiority of the naïve model in forecasting exchange rates before the crisis of 2008. However, this outcome is consistently reversed following the 2008 financial turmoil and the naïve model seems to regain some of its forecasting power only after 2011. These results suggest that different stochastic representations are appropriate for the exchange ...

We compare the accuracy of vector autoregressive and vector error correction models in forecasting the exchange rates of the euro (EUR) against the U.S. dollar (USD) and the Japanese yen (JPY) when using monetary and capital flows related variables. For the EUR/USD exchange rate monetary and capital flows models tend to outperform the random walk model for long-term predictions (more than six months), but fail to reject the test of equality of forecasting accuracy against the random walk model for all forecasting horizons but one. On the other hand, the best monetary model for the EUR/JPY exchange rate outperforms the random walk model on all horizons, and does so significantly for more than six months ahead. Models based on capital flow variables fail to beat the predictions of the random walk model for all forecasting horizons.

*We would like to thank, without implicating, the 1998 ESEM's participants, Marine Carrasco, Ronald MacDonald and an anonymous referee for useful comments on earlier drafts of this paper. All remaining errors are ours. 1 MacDonald and Taylor (1994) stands as a notable exception. But these authors investigate the empirical relevance of different monetary models reduced forms, without focusing on the uncovered interest parity (UIP) condition which is theoretically required but empirically rejected. More recent invalidations of Meese and Rogoff's results can be found in MacDonald (1997) or Clark and MacDonald (1998). However, these studies use real effective exchange rates of quarterly or annual frequencies, which may favor the long-run predictability of the exchange rates.

Airline traffic forecasting is important to airlines and regulatory authorities. This paper examines a number of approaches to forecasting short-to medium-term air traffic flows. It contributes as a rare replication, testing a variety of alternative modelling approaches. The econometric models employed include autoregressive distributed lag (ADL) models, time-varying parameter (TVP) models and an automatic method for econometric model specification. A vector autoregressive (VAR) model and various univariate alternatives are also included to deliver unconditional forecast comparisons. Various approaches for taking into account interactions between contemporaneous air traffic flows are examined, including pooled ADL models and the enhanced models with the addition of a "world trade" variable. Based on the analysis of a number of forecasting error measures, it is concluded that pooled ADL models that include the "world trade" variable outperform the alternatives, and in particular univariate methods; and, second, that automatic modelling procedures are enhanced through judgmental intervention. In contrast to earlier results, the TVP models do not improve accuracy. Depending on the preferred error measure, the difference in accuracy may be substantial. c

We examine the potential gains of using exchange rate forecast models and forecast combination methods in the management of currency portfolios for three exchange rates, the euro (EUR) versus the US dollar (USD), the British pound (GBP) and the Japanese yen (JPY). We use a battery of econometric specifications to evaluate whether optimal currency portfolios implied by trading strategies based on exchange rate forecasts outperform single-currency and the equally weighted portfolio. We assess the differences in profitability of optimal currency portfolios for different types of investor preferences, different trading strategies, different composite forecasts and different forecast horizons. Our results indicate that the benefits of integrating exchange rate forecasts from stateof-the-art econometric models in currency portfolios are sensitive to the trading strategy under consideration and vary strongly across prediction horizons.

The extant literature on exchange rate forecasting on the basis of the Dornbusch-Frankel, Frenkel-Bilson and Hooper-Morton models prominently reveals the dominance of the autoregressive models over the theory-based models. Some studies have however attempted to upturn the results by including the lagged dependent variable in the theory-based models which somewhat implies comparing a modified random walk with a traditional random walk. We follow a different approach both in terms of theory and methodology. We offer an innovative exposition of the Portfolio Balance theory to stock price-exchange rate nexus. Consequently, a predictive model for exchange rate where stock price is a predictor is formulated. The formulated model is expressed in both linear and nonlinear form in order to account for the role of asymmetric changes in stock prices in exchange rate forecasting. Thereafter, we employ the Lewellen (2004) and Westerlund and Narayan (2014) methods which account for any inherent statistical properties of the predictors. Our results validate the Portfolio Balance theory where we show that the sector-level stock prices consistently turn up as good predictors of the exchange rates. The predictive model proposed in this work does not require the inclusion of a lagged dependent variable to beat the autoregressive models which is the practice in the existing literature. We further demonstrate that asymmetry matters to a large extent in the nexus both for the in-sample and out-of-sample predictability.

Airline traffic forecasting is important to airlines and regulatory authorities. This paper examines a number of approaches to forecasting short-to medium-term air traffic flows. It contributes as a rare replication, testing a variety of alternative modelling approaches. The econometric models employed include autoregressive distributed lag (ADL) models, time-varying parameter (TVP) models and an automatic method for econometric model specification. A vector autoregressive (VAR) model and various univariate alternatives are also included to deliver unconditional forecast comparisons. Various approaches for taking into account interactions between contemporaneous air traffic flows are examined, including pooled ADL models and the enhanced models with the addition of a "world trade" variable. Based on the analysis of a number of forecasting error measures, it is concluded that pooled ADL models that include the "world trade" variable outperform the alternatives, and in particular univariate methods; and, second, that automatic modelling procedures are enhanced through judgmental intervention. In contrast to earlier results, the TVP models do not improve accuracy. Depending on the preferred error measure, the difference in accuracy may be substantial. c

In this paper we introduce a class of tentatively plausible, fixed-coefficient models of money demand and evaluate their forecast performance. When these models are reestimated allowing all coefficients to vary over time, the forecasting performance improves dramatically. Aside from offering insights about improved methods of analyzing time series data, the most promising direct use for point estimates derived from time-varying coefficients is as an aid in calibrating proposed models of the kind discussed here.

After the Liberalization, Privatization & Globalization policy in India there was a drastic change in the market conditions and also there was changes observed in the behavioral and investment pattern of investor's towards investments. After going through microscopic analysis it is found that the research was conducted in the space of financial risk adjusted returns, financial planning, investor's behavior and so on. But there was no significant study was made to know the perceptions of the investor's in making the investments in selected portfolios. Hence there exists a gap in the research. There must be a proper study to be conducted to find out behavioral elements of the investors to identify their attitude towards their investments. Hence, to fulfill the gap the following study has been initiated.

This paper analyses the out-of-sample forecasting performance of three models for the USD/COP nominal exchange rate during the period 1984:I - 2004:I. The sticky price monetary (Dornbusch (1976) - Frankel (1979)) and the Balassa-Samuelson (which gives a central role to the productivity differentials) approaches are used. Additionally, the Purchasing Power Parity condition (PPP) is analyzed. The forecasting ability of these models is compared using a random walk as a benchmark model. The metrics employed in evaluating the forecasting performance are RMS, MAE, MAPE and U-Theil. It is found that despite the great ability to predict, no model outperforms the random walk. This conclusion strengthens the previous results in the nominal exchange rate modeling literature.

We examine the proposition that the random walk without drift is more powerful in predicting exchange rates than the random walk with drift. It is demonstrated that there is no theoretical reason why the random walk without drift always outperforms the random walk with drift and that this is an empirical issue. The results show that while the random walk without drift can outperform the random walk with drift in terms of the RMSE, it fails to do so in terms of the ability to predict the direction of change, measures that take into account magnitude and direction, and in terms of profitability. If the drift factor is allowed to change over time by estimating the model in time-varying parameter terms, the random walk with drift performs even better.

This research paper studies BSE-SENSEX companies profile to demonstrate a direct
correlation between the investment in stakeholder relationships and corporate
performance. Economic Value Added (EVA) is now being considered as an important
management tool across the corporate world for measuring and rewarding
performance inside the companies. Most of the companies measure performance with
accounting profits which are often seriously biased measure of true profitability. EVA
is an unbiased measure of true profitability. Unlike accounting profits, EVA indicates
the value to what extent created by management or agent for shareholders. The paper
aims at analyzing BSE-SENSEX Companies performance through EVA. For this
purpose, EVA has been calculated.taking certain assumptions as to the cost of equity
and operational profit adjustments. However, the study concludes that Among the 30
companies ONGC and Reliance Industries EVA were topped. Further the three
companies EVA were negative during the period of the study in the BSE-SENSEX
Companies. So the companies should improve their profit which is enough to face
their cost of capital.

India is the fastest-growing Venture Capital market in Asia and fastest developing
nations in the new millennium. It is one of the hotspots for investments with reaping rich
benefits. In that, Karnataka happens to be the state where it has been observed that, before the
information technology (IT) revolution since 1995 onwards; there were negligible diffusion
of venture capital funding, predominantly having an agro-based economy, Karnataka has
shifted their focus from Agriculture to IT and IT enabled services as it started enjoying the
benefits during the second-generation reforms starting from 1995 onwards. From the review
of different literature and statistical data, it can be inferred that with higher human capital and
social capital, Karnataka is exploring the venture capital market extensively. (C.K .Nath)
In this context, we made an attempt to study the growth and investment of venture capital
companies and their funds.

After the Liberalization, Privatization & Globalization policy in India there was a
drastic change in the market conditions and also there was changes observed in the behavioral
and investment pattern of investor’s towards investments. After going through microscopic
analysis it is found that the research was conducted in the space of financial risk adjusted
returns, financial planning, investor’s behavior and so on. But there was no significant study
was made to know the perceptions of the investor’s in making the investments in selected
portfolios. Hence there exists a gap in the research. There must be a proper study to be
conducted to find out behavioral elements of the investors to identify their attitude towards
their investments. Hence, to fulfill the gap the following study has been initiated

In the domain of conglomerate governance and value system, the 21st century has abetted
challenges with multi-disciplinary approach and an all inclusive growth towards a more contented
global society. The role of self- governance is a concept that is rooted in the difference between rules
and principles followed by inner self. By destroying the selfish motives and developing selfless inner
consciousness within the managers and therefore the corporates, it is the internal self-control, selftrained
and self-confidence where a value added system thrives and grows to develop in an
incongruent world. Mahatma Gandhi was so much comprehensible in this vision of self-governance
that changed into realizing the power and unity of the public during Swadeshi Movement. By
promoting indigenous products in place of imported goods, which ultimately made the country self
sufficient, as a part of burgeoning generation, thus, incorporating the idea of self- governance while
instituting the independent India. He was one of those colossal protagonists who laid the foundation
of modern Indian Nationalism, the noble edifice of India's freedom. He had widely acclaimed
achievements to his credit, chief among them being the founder and architect of the value system,
proliferating non-violence for unprejudiced training and development of the body, intellect and the
ardor of every individual. The visionary founder also, had a dream to see value added India’s
industrial structure and wanted to create the ‘Priceless Indian citizens of the World’, inspired by the
ideology of ‘Vasudhaiva Kutumbakam’. It is contrary to what Rudyard Kipling once said, “The East
is East and the West is West and never the twain shall meet”. But, the illustrious creator of the
sovereign India had a desire to blend the best of the East with the best of the West to create a new
environment, which may allow the future mankind to live and flourish without discord. This paper
focuses on India’s vision on self governance and creation of a value system with accord and
safeguarding the knowledge capital through proper utilization of resources bringing in a constructive
social change.

The subject of segment information disclosure practices among various companies are under
consideration by the users of the financial statements. The users of the financial statements and the
investors in general are keen to know the performance of the companies in which they are interested
for investing. In today’s business environment, the concept of globalization has entered every
business persons mind and therefore the companies go on a widespread hunt for entering the market
on a global platform. In the process of globalization, the information provided by the companies
should be useful for the investors in understanding the quantum of business they perform. Thus, The
Institute of Chartered Accountants of India has pronounced Accounting Standard 17 on Segment
Reporting. The researcher in this article tries to bring out the effect of firm-specific characteristics on
segment information disclosure with special reference to the Indian Listed Companies.

Investments are necessary for economic development. Financial investments are major source
of investment. Insurance is a major source of investment in India. A contract (policy) in which an
individual or entity receives financial protection or reimbursement against losses from an insurance
company. The aim of this study is to investigate relationship between educational level of investors
and their ULIP related practices. The study was carried out by using survey methodology. For that
responses were collected from 550 ULIP customers from 11 district of Vidarbha Region in
Maharashtra by using a reliable and valid questionnaire. The collected data was analyzed by using
chi-square test for investigating relation between educational qualification of ULIP investors and
various practices done by them regarding ULIP. The study results indicated significant relation
between educational qualification of ULIP investors and various practices done by them regarding
ULIP. It was concluded from the study results that there is significant relation between educational
qualification and approach to make an ULIP investment decision, primary financial goals for opting
ULIP, annual investment in ULIP, the criterion while investing in ULIP plan, the source from which
they purchased ULIP plan, the duration from which they are investing in ULIP plan, frequency of
checking value of investment and factors which determine the success of ULIP plan are significantly
related. Authors suggested that It is suggested that ULIP marketers need to focus attention on
creating confidence among customers by educating them regarding ULIP and by making them aware
of various advantages of ULIP. By considering that the there is significant relation between
investor’s education qualification and various practices performed by them regarding ULIP.

We compare the accuracy of vector autoregressive and vector error correction models in forecasting the exchange rates of the euro (EUR) against the U.S. dollar (USD) and the Japanese yen (JPY) when using monetary and capital flows related variables. For the EUR/USD exchange rate monetary and capital flows models tend to outperform the random walk model for long-term predictions (more than six months), but fail to reject the test of equality of forecasting accuracy against the random walk model for all forecasting horizons but one. On the other hand, the best monetary model for the EUR/JPY exchange rate outperforms the random walk model on all horizons, and does so significantly for more than six months ahead. Models based on capital flow variables fail to beat the predictions of the random walk model for all forecasting horizons.

It is demonstrated that the forecasting power of the flexible price monetary model of exchange rates can be enhanced by introducing dynamics through the use of a linear error correction specification. However, the introduction of nonlinearity, by using a polynomial in the error correction term, does not lead to any further improvement in forecasting accuracy and may even lead to deterioration. The results provide evidence against the proposition that the Meese-Rogoff puzzle can be explained in terms of failure to account for nonlinearity. It is also shown that the introduction of dynamics boosts the forecasting accuracy (in terms of the magnitude of the forecasting error) of the model relative to the static specification because dynamic specifications involve a random walk component. The empirical results lead to the conclusion that accounting for nonlinearity does not resolve the Meese-Rogoff puzzle.

Whether fluids or funds, find and follow their slop invariably. Foreign Portfolio Investment (FPI) is one such entity, which either boosts or impedes stock market movements and investment sentiment with each of its passing breeze. When economy is in trouble, when currency under depreciation pressure, current account in red, widening fiscal deficit then from a country's finance ministry to common retail investor in stocks market pray and wait eagerly for financial institutional investors pouring in their funds in the stock market. In turn the foreign portfolio investments raise the bar and motivate the performance of the corporate world. They bring in paradigm shift in the focus of industry by enhancing the PE expectations. No doubt FPIs do play miracles in the stock market but the question is how sustainable it is. In this paper an attempt is made to understand the role of FPI and its degree of influence on stock market indicators such as Price Earnings multiple(PE), Dividend Yield (DY), Book Value (BV) of NIFTY.

The concept of internal control in local government is not a novel concept, and that the system of control, more or less formalized way, works in any organization. Basically the control system is a set of all actions and measures which apply to activities performed in the organization are carried out in accordance with the interests of the organization.

While many explanations have been put forward for the failure of exchange rate models to outperform the random walk in out-of-sample forecasting, a simple explanation is the use of measures of forecasting accuracy that depend entirely on the magnitude of the forecasting error. By using simulated data representing the forecasts of eight models, it is demonstrated that the random walk can be outperformed if forecasting power is judged by measures of direction accuracy, by adjusting the root mean square error to take into account direction accuracy, and by using the risk-adjusted return obtained from a trading strategy based on the forecasts.

"Several explanations have been put forward for the Meese–Rogoff puzzle that exchange rate models cannot outperform the random walk in out-of-sample forecasting. We suggest that a simple explanation for the puzzle is the use of the root mean square error (RMSE) to measure forecasting accuracy, presenting a rationale as to why it is difficult to beat the random walk in terms of the RMSE. By using exactly the same exchange rates, time periods and estimation methods as those of Meese and Rogoff, we find that their results cannot be overturned even if the models are estimated with time-varying coefficients. However, we also find
that the random walk can be outperformed by the same models if forecasting accuracy is measured in terms of the ability to predict direction, in terms of a measure that combines magnitude and direction and in terms of profitability. "

"It is demonstrated that the conventional monetary model of exchange rates can (irrespective of the specification, estimation method or the forecasting horizon) outperform the random walk in out-of-sample forecasting if forecasting power is measured by direction accuracy and profitability. Claims of outperforming the random walk in terms of the root mean square error are false because they are typically based on the introduction of dynamics,
hence a random walk component, commonly without testing for the statistical significance of the difference between root mean square errors. And even if proper hypothesis testing reveals that a dynamic model outperforms the random walk, this amounts to beating the random walk by a random walk with the help of some explanatory variables. The failure of conventional macroeconomic models to outperform the random walk in terms of the root mean square error should be expected rather than considered to be a puzzle. "

Financial statements should focus on the true and fair view of state of affairs of the corporate entity. It is the responsibility of audit committee to authenticate the true and fair view of financial position. But, there are several undisclosed facts which are to be unearthed by audit committee are ignored. This leads to financial turmoil and loss of investor's confidence as well as investment made by them In this context, this paper is intended to examine the importance of disclosure practices of financial statements with reference to benchmarking of a select mutual funds' fact sheets. This paper focuses on the following objectives:

Stock market has now become a news item since every fall or rise either small or
big gets the coverage in the news at national or even local media. Everyday, we come
across the popular indices of stock exchanges namely SENSEX or NIFTY falling down
or rising up. These fluctuations take place due to number of factors internal as well as
external. But what we have observed recently, is the sharp fall in the values or prices of
shares the world over. The causes for this fall are not merely the local or indigenous; but
more important reason is the weakness in the capital markets in the globe in general and
in USA in particular. The present paper tries to emphasize on the significance of
weakness in the global capital markets and its adverse impact on the Indian capital
market.

The root of the word corporate governance is from ‘gubernate’ which means to steer. Corporate
governance would mean to steer an organization in the desired direction. Corporate governance
is a system by which organization are directed and controlled, it is a process by which company
objectives are established, achieved and monitored. So, it is concerned with relationship and
responsibilities between the boards, management and stake holders within a legal and regulatory
frame work.
The primary objective of this paper is to study the corporate governance policies and practices
and system in India .Goodness of corporate governance is checked on the basis of five basic
parameters i.e. transparency, ownership structure, board procedure, investor rights and
governance strategies.
During the study it was observed that, in India the legislative and regulatory framework for the
corporate governance is sound but the implementation part is poor. There is a huge gap between
what is de-jure and de-facto.The state is still lagging behind when it comes to particularly private
sector small and medium size industries. Major part of industrial set up is just their production
units. The government has also set up various committees, passed various regulations for the
development of the industries in the country. There is a further need to strengthen the existing
governance policies.