Accurate prediction of stock market behavior is a challenging issue for financial forecasting. Artificial neural networks, such as multilayer perceptron have been established as better approximation and classification models for this domain. This study proposes a chemical reaction optimization (CRO) based neuro-fuzzy network model for prediction of stock indices. The input vectors to the model are fuzzified by applying a Gaussian membership function, and each input is associated with a degree of membership to different classes. A multilayer perceptron with one hidden layer is used as the base model and CRO is used to the optimal weights and biases of this model. CRO was chosen because it requires fewer control parameters and has a faster convergence rate. Five statistical parameters are used to evaluate the performance of the model, and the model is validated by forecasting the daily closing indices for five major stock markets. The performance of the proposed model is compared with four state-of-art models that are trained similarly and was found to be superior. We conducted the Deibold-Mariano test to check the statistical significance of the proposed model, and it was found to be significant. This model can be used as a promising tool for financial forecasting.

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A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction

A quantum artificial neural network for stock closing price prediction

The economic growth of India has positioned it as one of the rapidly growing economies the world over and it is expected to be one of the top three economies globally over the next decade. Contrary to a slowdown in the earnings of Indian corporates due to excess existing capacity and the inability of banks to lend, the stock market ie Bombay Stock Exchange has performed well. The objective of the present research is to investigate the link that exists, if any, between BSE Sensex and macroeconomic variables such as Index of Industrial Production (IIP), inflation, the rate of interest, the price of gold, rate of exchange, FII and supply of money for the period April 1999-March 2017. The study also seeks to determine the strength of the link between the independent parameters and the dependent parameter ie BSE Sensex in the short run and long run based on the test of Johansen Cointegration, Granger Causality, and the Vector Error Correction mechanism. The analysis through the Vector Error Correction Model (VECM) confirms that there exists a long-run causality between the macroeconomic variables of Index of Industrial Production (IIP), inflation, interest rates, gold prices, exchange rate, foreign institutional investment, money supply and BSE Sensex. It establishes that there does exist a short run causality between Inflation and BSE Sensex and Money Supply and BSE Sensex. The results importantly show that BSE Sensex causes changes in the exchange rate and money supply, FII, gold prices and IIP.

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An Investigation of the Macroeconomic Factors Affecting the Indian Stock Market

This paper investigates the effect of selected macroeconomic factors viz. remittances, money supply, exchange rate, and interest rate on stock market performance based on literatures available in international and Nepalese context. The major objective of this paper is to find out the new area of research in Nepalese perspective with the help of literature review. The study demonstrates that remittance and money supplypositively affect the stock market whereas interest rate and exchange rate negatively affect the stock market performance. However, there is lack of consensus on the effect of each macroeconomic variables on stock market performance as it has number of literatures available which are similar as well as opposite to these findings. Thus, similar study can be extended employing different methodology with this combination of variables in Nepalese context that may better describe and analyze the performance of Nepalese stock market and helps to reduce the confusion among the literatures. NCC Journal Vol. 3, No. 1, 2018, page: 134-142

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Determinants of Stock Market Performance

The paper revisits the author’s previous paper to examine short-run and long-run dynamic relationships between macroeconomic variables and stock prices in Korea. The data is updated to the period for which monthly data are available from January 1986 to June 2018 (390 observations) retrieved from the Bank of Korea. The results of Johansen cointegration test indicate that at least one cointegrating equation exists, confirming there is a long-run equilibrium relationship between macroeconomic variables and stock prices in Korea. The results of vector error correction estimates confirm that: 1) the coefficient of the error correction term is significant with a negative sign, which is, a long-run dynamic relationship is observed between macroeconomic variables and stock prices; 2) for short-run dynamics, the nominal exchange rate of the Korean won per the US dollar is positively related to stock prices, while interest rates are negatively related to stock prices in the short-run; 3) the coefficient of global financial crises is insignificant, that is, the changes of stock prices are determined largely by their own dynamics in the model. The results suggest only that the global financial crises neither cause instability in the cointegrating vector, nor affect significant changes in the endogenous variables in the model.

https://www.koreascience.or.kr:443/article/JAKO202029062616203.pdf

An Exploration of Dynamic Relationships between Macroeconomic Variables and Stock Prices in Korea Revisited

The rapid growth of Indian economy during the last two decades raises empirical questions regarding the fundamental connection between stock price and key macroeconomic indicators. This paper aims to examine long and short run relations between selected macroeconomic indicators and stock market returns with reference to India. This study employs monthly data from July 2001 to July 2015 since major stock market reforms viz., ban of Badla system, introduction of rolling settlement and introduction of stock derivatives, were all implemented in July 2001. With the help of cointegration and error correction model (ECM), the study reveals the presence of long run relation between the BSE Sensex and select macroeconomic indicators viz., Exchange Rate, wholesale price index, T-bill rates and M3.

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Macroeconomic Factors and the Indian Stock Market: Exploring Long and Short Run Relationships

This study examines the dynamic linkages of Nifty stock index and Nifty index futures contract traded on the home market, National Stock Exchange (NSE) and on the off-shore market, Singapore Stock Exchange (SGX). The study uses daily closing prices of the Nifty index and the Nifty futures contract traded on both the exchanges for the period July 15, 2010 to July 15, 2016.  The study finds a causality running from the returns of the spot market to the returns from the Nifty futures market in both the exchanges, NSE and SGX, with the help of Vector Error Correction model and Granger causality test. Variance Decomposition and Impulse Response Analysis also confirm that the spot market is the leading market in price discovery, making it the most efficient amongst others.

Dynamic Linkages between Singapore and NSE listed NIFTY Futures and NIFTY Spot Markets

This paper empirically examines the effect of weekly options introduction on the benchmark index of Indian stock market, NIFTY50. The paper evaluates the possible stabilizing or destabilizing nature of impact on underlying volatility focusing on the relation between information and volatility using GARCH framework. The results indicate that the onset of weekly index options has improved the information assimilation and reduced the persistence of old information on volatility. Further, similar changes are not evident on a control index, NIFTY NEXT50. Overall, the results indicate an increase in market efficiency with weekly index options trading. 

Does options improve the information absorption? Evidence from the introduction of weekly index options

The study looks at the impact of three major regulatory changes that happened on the historic day of 2 July 2001, when badla was banned, rolling settlement replaced accounting period settlement for...

Kiran Kumar Kotha

Papers

Macroeconomic Factors and the Indian Stock Market: Exploring Long and Short Run Relationships

Dynamic Linkages between Singapore and NSE listed NIFTY Futures and NIFTY Spot Markets

Does options improve the information absorption? Evidence from the introduction of weekly index options

Market quality, market reforms and investor familiarity: evidence from the Indian stock market