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| Author | : Shi Yun Wang |
| Publisher | : |
| Total Pages | : 172 |
| Release | : 1997 |
| Genre | : Futures market |
| ISBN | : |
| Author | : Xavier Giroud |
| Publisher | : |
| Total Pages | : |
| Release | : 2004 |
| Genre | : |
| ISBN | : |
A considerable literature in market microstructure has analyzed the information flows between stock index futures and spot markets. Most of those studies estimate deviations from the cost-of-carry model within the framework of vector equilibrium correction models (VECM). The typical finding is that futures prices lead spot prices and are the primary source of price discovery. Purely linear models can, however, lead to fallacious or at least incomplete inference in the presence of significant nonlinearities in the return generating process. Recent research has reported evidence for nonlinearity in the distribution of stock market returns. According to this literature, their empirical distribution can be characterized by a mixture of normal distributions whose dependence is well described by a hidden Markov chain. This thesis contributes to the former field by allowing for Markovian regime switches in the cointegrated system. The empirical analysis is carried out using high-frequency data for the German and Swiss markets, i.e. two closely interrelated markets which differ substantially in terms of liquidity. This thesis consists of three major parts. In the first part, an MS-VECM is estimated for each market and tested against the linear VECM. In both cases, the linear model is strongly rejected. The Markovian chain consists of three regimes, which can be well described in terms of volatility. Price discovery differs from regime to regime, but the overall evidence is consistent with the well-documented leading role of futures markets. The MS-VECM provides additional insights into the dynamics of price discovery. Interestingly, shocks are absorbed more rapidly in regimes of high volatility. A possible explanation is provided, based on trading activity. Intraday volatility is shown to be associated with the volume of trading. Heavy trading reveals more information per unit of time and thus improves index arbitrage and informational.
| Author | : Samuel Okafor |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2020 |
| Genre | : |
| ISBN | : |
Markov chain models are commonly used in stock market analysis, manpower planning, and in many other areas because of its efficiency in predicting long run behaviour. This study proposes a simple predicting tool to forecast the future behaviour of stock prices. The study analyses the stock price model using Akaikes Information Criterion (AIC) and Bayes Information Criterion (BIC). The analysis shows that the AIC supports a second order model whereas the BIC supports a first order model. The maximum likelihood function was found to be of the second order. Apparently, the stock price model is time dependent and time homogeneous and thus, best forecasted using a second order model. As described by the GARCH model, the presence of time varying conditional volatility of stock prices, and a lasting effect of today's shock on forecast were found. These results agree with the Markov model based on the AIC. The returns were explored for both short and long run behaviours and it was found that if there is a transition between the states of the return in a current week, the expected return would be higher than the overall average return and this would be realized within the next one week, but if the return is in a stable state then the expected return may move above the overall average return after two weeks.The result also shows that in the long run, the stock price is more stable, and the stock return has a higher probability of remaining in an upward state than in a downward state. This paper uniquely contributes to the literature by demonstrating that NSE series can be modelled as a three-state movement - the upward state, the stable state, and the downward state. This method could help investors save time and make optimal decisions.
| Author | : Dong-chun Lim |
| Publisher | : |
| Total Pages | : 290 |
| Release | : 1996 |
| Genre | : Stock exchanges |
| ISBN | : |
| Author | : Charles M.S. Sutcliffe |
| Publisher | : Routledge |
| Total Pages | : 534 |
| Release | : 2018-01-18 |
| Genre | : Business & Economics |
| ISBN | : 1351148559 |
The global value of trading in index futures is about $20 trillion per year and rising and for many countries the value traded is similar to that traded on their stock markets. This book describes how index futures markets work and clearly summarises the substantial body of international empirical evidence relating to these markets. Using the concepts and tools of finance, the book also provides a comprehensive description of the economic forces that underlie trading in index futures. Stock Index Futures 3/e contains many teaching and learning aids including numerous examples, a glossary, essay questions, comprehensive references, and a detailed subject index. Written primarily for advanced undergraduate and postgraduate students, this text will also be useful to researchers and market participants who want to gain a better understanding of these markets.
| Author | : Ersan Ersoy |
| Publisher | : |
| Total Pages | : 18 |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
In perfectly frictionless and rational markets, spot markets and futures markets should simultaneously reflect new information. However, due to market imperfections, one of these markets may reflect information faster than the other and therefore may lead to the other. This study examines the lead-lag relationship between stock index and stock index futures, in terms of both price and volatility, by using 5 minute data over 2007-2010 period. The findings of this study indicate that a stable long-term relationship between Turkish stock index and stock index futures exists, however stock index futures do not lead stock index and there is a two way interaction between them. Therefore either of the markets is dominant over the other one in the price formation process.
| Author | : James L. Grant |
| Publisher | : |
| Total Pages | : |
| Release | : 2005 |
| Genre | : |
| ISBN | : |
This paper gives a long-term assessment in intraday prices reversal in the US stock index futures market following large price changes at the market open, We find highly significant intraday reversal in our yearly and day-of-the-week investigations. Moreover, the strength of the intraday overreaction phenomenon seems more pronounced following large positive price changes at the market open. That being said, the question of whether a trader con consistently profit from this information remains open at the significance of intraday price reversals is sharply reduced when gross trading results are adjusted by a bid-ask proximity for transactions costs.
| Author | : Álvaro Cartea |
| Publisher | : Cambridge University Press |
| Total Pages | : 360 |
| Release | : 2015-08-06 |
| Genre | : Mathematics |
| ISBN | : 1316453650 |
The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.
| Author | : Sarveshwar Inani |
| Publisher | : |
| Total Pages | : |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
This research aims to revisit the price discovery relationship between spot and futures prices of Indian equity index S&P CNX Nifty, using neural network approach. This study uses minute-by-minute prices of 167 trading days ranging from January, 2015 to August, 2015 to gain fresh insights on price discovery. The results reveal that change in futures prices lead the change in spot prices in training and testing of our sample. Neural network is an advanced methodology which is more effective in capturing non-linear relationship between spot and futures prices. Therefore, the results of this study could be considered more reliable and more robust as compared to previous studies for Indian market. Mean absolute error of the results indicates that, incorporation of futures returns in modelling spot returns improves the model by 30.8%. Whereas, inclusion of spot returns in modelling futures returns improves the results by only 25.4%. Though bidirectional spillover effect is present between spot and futures returns, but the futures returns are more dominant and more efficient. Therefore, it could be concluded that futures market serves as price discovery vehicle.
| Author | : Gregory Zuckerman |
| Publisher | : Penguin |
| Total Pages | : 401 |
| Release | : 2019-11-05 |
| Genre | : Business & Economics |
| ISBN | : 073521798X |
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