Fear and its implications for stock markets

The value of stocks, indices and other assets, are examples of stochastic processes with unpredictable dynamics. In this paper, we discuss asymmetries in short term price movements that can not be associated with a long term positive trend. These empirical asymmetries predict that stock index drops are more common on a relatively short time scale than the corresponding raises. We present several empirical examples of such asymmetries. Furthermore, a simple model featuring occasional short periods of synchronized dropping prices for all stocks constituting the index is introduced with the aim of explaining these facts. The collective negative price movements are imagined triggered by external factors in our society, as well as internal to the economy, that create fear of the future among investors. This is parameterized by a ``fear factor'' defining the frequency of synchronized events. It is demonstrated that such a simple fear factor model can reproduce several empirical facts concerning index asymmetries. It is also pointed out that in its simplest form, the model has certain shortcomings.Comment: 5 pages, 5 figures. Submitted to the Proceedings of Applications of Physics in Financial Analysis 5, Turin 200

Currency Exchange Rate Forecasting with Neural Networks

This is the published version. Copyright De GruyterThis paper presents the prediction of foreign currency exchange rates using artificial neural networks. Since neural networks can generalize from past experience, they represent a significant advancement over traditional trading systems, which require a knowledgeable expert to define trading rules to represent market dynamics. It is practically impossible to expect that one expert can devise trading rules that account for, and accurately reflect, volatile and rapidly changing market conditions. With neural networks, a trader may use the predictive information alone or with other available analytical tools to fit the trading style, risk propensity, and capitalization. Numerous factors affect the foreign exchange market, as they will be described in this paper. The neural network will help minimize these factors by simply giving an estimated exchange rate for a future day (given its previous knowledge gained from extensive training). Because the field of financial forecasting is too large, the scope in this paper is narrowed to the foreign exchange market, specifically the value of the Japanese Yen against the United States Dollar, two of the most important currencies in the foreign exchange market

Variation, jumps, market frictions and high frequency data in financial econometrics

We will review the econometrics of non-parametric estimation of the components of the variation of asset prices. This very active literature has been stimulated by the recent advent of complete records of transaction prices, quote data and order books. In our view the interaction of the new data sources with new econometric methodology is leading to a paradigm shift in one of the most important areas in econometrics: volatility measurement, modelling and forecasting. We will describe this new paradigm which draws together econometrics with arbitrage free financial economics theory. Perhaps the two most influential papers in this area have been Andersen, Bollerslev, Diebold and Labys(2001) and Barndorff-Nielsen and Shephard(2002), but many other papers have made important contributions. This work is likely to have deep impacts on the econometrics of asset allocation and risk management. One of our observations will be that inferences based on these methods, computed from observed market prices and so under the physical measure, are also valid as inferences under all equivalent measures. This puts this subject also at the heart of the econometrics of derivative pricing. One of the most challenging problems in this context is dealing with various forms of market frictions, which obscure the efficient price from the econometrician. Here we will characterise four types of statistical models of frictions and discuss how econometricians have been attempting to overcome them.

Price Discovery in Multiple-Dealer Markets: The Case of the Interbank Foreign Exchange Market

Price discovery is a principal function of financial markets. Yet, especially for dealership markets, financial economists know little about how prices are determined. In this paper I analyze the process of price discovery in the multiple-dealer, interbank spot market for foreign exchange. I use DM/$ quotes to calculate interbank dealers’ “information shares,” their proportional contributions to the variance of innovations in the implicit, efficient exchange rate. These information shares are used to analyze relationships between price discovery and dealer characteristics. Unlike the U.S. equity markets, where regional exchanges contribute relatively little to price discovery, less-active interbank dealers play a large role, impounding most of the information into quotes. A pooled analysis of dealers’ intraday information shares indicates that the lower the relative bid-ask spread and the greater the number of regional foreign exchange branches, the higher is a dealer’s contribution to price discovery. Dealer nationality, however, does not appear related to price discovery within dealers’ domestic markets.

OPTIONS-BASED FORECASTS OF FUTURES PRICES IN THE PRESENCE OF LIMIT MOVES

This analysis examines a simultaneous estimation option-based approach to forecast futures prices in the presence of daily price limit moves. The procedure explicitly allows for changing implied volatilities by estimating the implied futures price and the implied volatility simultaneously. Using 15 years of futures and futures options data for three agricultural commodities, we find that the simultaneous estimation approach accounts for the abrupt changes in implied volatility associated with limit moves and generates more accurate price forecasts than conventional methods that rely on only one implied variable.Demand and Price Analysis, Marketing,

Efficiency and price clustering in Islamic stocks: evidence from three Asian countries

Purpose: This paper aims to examine the extent of price clustering in a selection of Islamic stocks listed in Indonesia, Malaysia and Pakistan and also investigates the determinants of the phenomenon at the firm level. Design/methodology/approach: The author test the uniformity of price distribution in the selected securities. Then, the determinants of price clustering were investigated through multivariate analysis based on a binary logistic regression model. Following the arguments of Narayan et al. (2011), who emphasize the importance of considering firm heterogeneity when studying the phenomenon, the author conducts the empirical study at the firm level. Findings: The evidence indicates that Islamic stocks show a mild level of price clustering. Only half of the stocks under analysis rejected the uniformity test in the distribution of prices. In these cases, investors exhibited a preference for prices ending at zero and five. The evidence does not confirm the cultural clustering theories. Price clustering is found to be positively associated with price level and relative bid-ask spread. Overall, the negotiation hypothesis, which predicts that investors prefer round prices to minimize the costs associated with negotiations, best explains most of our results. Research limitations/implications: The existence of price clustering is difficult to reconcile with the prediction of the efficient market hypothesis that prices should follow a random walk. Moreover, the evidence indicates that Muslim investors share a preference for round prices in some settings, under the assumption that Islamic stocks are mostly traded by Muslim investors. Originality/value: To the authors best knowledge, this is the first study to address the subject of price clustering in Islamic stocks

Spartan Daily, September 27, 1972

Volume 60, Issue 6https://scholarworks.sjsu.edu/spartandaily/5641/thumbnail.jp

A survey of announcement effects on foreign exchange volatility and jumps

This article reviews, evaluates, and links research that studies foreign exchange volatility reaction to macro announcements. Scheduled and unscheduled news typically raises volatility for about an hour and often causes price discontinuities or jumps. News contributes substantially to volatility but other factors contribute even more to periodic volatility. The same types of news that affect returns—payrolls, trade balance, and interest rate shocks—are also the most likely to affect volatility, and U.S. news tends to produce more volatility than foreign news. Recent research has linked news to volatility through the former’s effect on order flow. Empirical research has confirmed the predictions of microstructure theory on how volatility might depend on a number of factors: the precision of the information in the news, the state of the business cycle, and the heterogeneity of traders’ beliefs.Foreign exchange

Spartan Daily, December 3, 1962

Volume 50, Issue 48https://scholarworks.sjsu.edu/spartandaily/4369/thumbnail.jp