Analysis of market efficiency for the Shanghai stock market over time

In this paper, we analyze market efficiency for the Shanghai stock market over time using a model-free method known as multifractal detrended fluctuation analysis. Through analyzing the change of scale behavior, we find that the price-limited reform improved the efficiency in the long term, but the influence in the short term was very minor. Employing the method of moving window, using three different measures we find that the Shanghai stock market became more and more efficient after the reform. We also implement the same procedure on volatility series and find the evidence of inefficiency.     

Equilibrium in natural catastrophe insurance market under disaster-resistant technologies,financial innovations and government interventions

Natural disasters increase in number and severity. Studies have shown the failure of the catastrophe insurance market by listing many causes or through developing economic models (Charpentier and Le Maux, 2014; Kousky and Cooke, 2012; Ibragimov et al., 2009). However, they have not considered the effect of the following factors on market equilibrium: advanced disaster-resistant technologies used by insureds, alternative financial innovations employed by insurers, and various disaster policies that are implemented by governments. To fill this gap, this study examines how these three factors affect the market equilibrium by changing the supply of, and demand for insurance and determines which factor(s) contributes to the market equilibrium. Furthermore, we derive the formula of position size which gives criteria for selecting index-based contracts. Overall annual numbers and insured losses of catastrophes are collected by peril type and by occurrence region listed in Sigma, which is issued by Swiss Re annually. The comparative static equilibrium analysis demonstrates that the improvement of market equilibrium is significant at low level of loss correlation in all cases. The empirical findings give insurers good references for business and geographical diversification in portfolio of catastrophe insurance policies.     

Empirical scaling laws and the aggregation of non-stationary data

Widely cited evidence for scaling (self-similarity) of the returns of stocks and other securities is inconsistent with virtually all currently-used models for price movements. In particular, state-of-the-art models provide for ubiquitous, irregular, and oftentimes high-frequency fluctuations in volatility (“stochastic volatility”), both intraday and across the days, weeks, and years over which data is aggregated in demonstrations of self-similarity of returns. Stochastic volatility renders these models, which are based on variants and generalizations of random walks, incompatible with self-similarity. We show here that empirical evidence for self-similarity does not actually contradict the analytic lack of self-similarity in these models. The resolution of the mismatch between models and data can be traced to a statistical consequence of aggregating large amounts of non-stationary data.     

A multiplicative model for volume and volatility

We first present prima facie evidence for the predictions generated by the mixture of distributions hypothesis, using daily German stock returns and their corresponding daily trading volumes and number of trades. These last two variables are used as proxies for the stochastic rate of information arrival when one wishes to explain GARCH effects by adhering to the mixture of distributions hypothesis. We show that there is no need for these proxies when the stochastic rate of information arrival follows an inverted gamma distribution. Daily trading volume and the daily number of trades, however, empirically provide an explanation for the occurrence of conditional heteroskedasticity of the GARCH form. We estimate several specifications where daily trading volume is included in the conditional variance equation additively and multiplicatively. The new multiplicative specification clearly outperforms the additive specification.     

Optimal Market Making in the Foreign Exchange Market

Abstract

This paper is concerned with optimal market making in the foreign exchange market. The market maker's holdings in the different currencies are modelled as stochastic processes that are influenced by both the stochastic exchange rates and the stochastic customer buy and sell orders. The market maker can control their own bid and ask price quotes and, additionally, can buy and sell at other market participants' quotes. The resulting stochastic control problem consists of a controlled diffusion problem for the optimal quotes and a singular control problem for optimal trades at other market participants' quotes. A Markov chain approximation is used to derive optimal strategies.     

电子商务与传统商务发展趋势的博弈分析

在消费者对商品价格与供货时间的偏好假设下,建立一个厂商关于电子商务与传统商务交易方式选择的完全信息静态博弈模型,其纳什均衡表明了电子商务与传统商务潜在的发展趋势,特别是两者可能的市场剖分关系.确切而言,若市场满足既定假设,均衡条件下的电子商务交易方式表现为较长的供货时间及低于传统商务约40%的市场交易价格,将获得三分之一的市场份额.     

Theory of Economic Equilibrium

Abstract

New concepts of economics such as an average demand matrix of society, strategy of a firm and consumer behaviour, and others are introduced. We give sufficient conditions for technological mapping under which there exist both the Walras equlibrium state and optimal Walras equilibrium one. We obtain the set of equations which equilibrium price vector solves. The theory of interindustry economic equilibrium is developed. The model of economy with regular interests of consumers is proposed.     

A jump diffusion model for spot electricity prices and market price of risk

We construct a jump-diffusion model with seasonality, mean-reversion, time-dependent jump intensity and heteroskedastic disturbance for electricity spot prices, while keeping the analytical tractability of futures prices. We find that the jump component plays a considerably larger role than the diffusion component in the variance of spot prices. Moreover, the jump intensity is much higher during summer and winter. We also explore the seasonal market price of risk (MPR) with different maturities, from one month to five months. Our results show that the diffusion risk and the jump risk are priced quite differently.     

How fast do stock prices adjust to market efficiency? Evidence from a detrended fluctuation analysis

In this paper we analyse price fluctuations with the aim of measuring how long the market takes to adjust prices to weak-form efficiency, i.e., how long it takes for prices to adjust to a fractional Brownian motion with a Hurst exponent of 0.5. The Hurst exponent is estimated for different time horizons using detrended fluctuation analysis–a method suitable for non-stationary series with trends–in order to identify at which time scale the Hurst exponent is consistent with the efficient market hypothesis. Using high-frequency share price, exchange rate and stock data, we show how price dynamics exhibited important deviations from efficiency for time periods of up to 15 min; thereafter, price dynamics was consistent with a geometric Brownian motion. The intraday behaviour of the series also indicated that price dynamics at trade opening and close was hardly consistent with efficiency, which would enable investors to exploit price deviations from fundamental values. This result is consistent with intraday volume, volatility and transaction time duration patterns.     

Estimating the efficient price from the order flow: A Brownian Cox process approach

At the ultra high frequency level, the notion of price of an asset is very ambiguous. Indeed, many different prices can be defined (last traded price, best bid price, mid price, etc.). Thus, in practice, market participants face the problem of choosing a price when implementing their strategies. In this work, we propose a notion of efficient price which seems relevant in practice. Furthermore, we provide a statistical methodology enabling to estimate this price from the order flow.