An alternative measure of the “world market portfolio”: Determinants, efficiency, and information content

The world market portfolio plays an important role in international asset pricing, but is unobservable in practice. We first propose a framework for constructing a market proxy that corresponds to the “market portfolio” of financial theory. We then construct this proxy, analyze its determinants and test its efficiency and explanatory power over the period 1975-2007 with respect to the return generating processes of a broad asset universe. We show that its major determinants are traded assets and that it is not efficient. However, it is significant for explaining individual asset returns over an asset universe that includes stocks, bonds, money markets and commodities. The explanatory information is incremental to what is available in traded asset prices and the significance of this information is robust with respect to diversified portfolios generated by factor analysis and to characteristic-sorted portfolios as well as to various model specifications, including the single-index model, the Fama-French (1992) three factor model for stocks, and various specifications of multi-index models hedged and unhedged for foreign currency risk.     

Speculator activity and the cross-asset predictability of FX returns

This paper tests the gradual information diffusion hypothesis, which suggests that information spreads gradually across asset markets, to explain the role of speculator activity in the cross-asset return predictability of foreign exchange (FX) market strategies. We argue that the activity of speculators increase the rate of information diffusion across asset markets. Hence, we expect the predictive effect from the equity and commodity markets on FX market strategies to be weaker when speculators are active in the FX market. Our results show that, when speculator activity is high, the equity market's ability to predict the FX market dissipates, but not to the same extent as for the commodity market. Our findings suggest that speculators play a vital role in enhancing informational efficiency in the FX market.     

Futures Markets and Informational Efficiency: A Laboratory Examination

Through the use of laboratory market methodology, the effect of a futures market on the time path of asset prices is studied and competing models of asset pricing are analyzed. With replication of market conditions, the predictions of a rational expectations equilibrium model are relatively accurate whether or not futures markets are present. However, the presence of futures markets increases the speed with which an efficient equilibrium is achieved. While this more rapid adjustment can increase the variance of spot market prices as they move to equilibrium, this increased variance reflects efficiency gains due to better information.     

An unobserved component model of asset pricing across financial markets

Our research focuses on multifactor asset pricing models that investigate the importance of economic factors in the pricing of assets beyond the scope of the stock market. We present a Bayesian learning model of asset pricing across financial markets in which unobserved components are estimated using a Kalman filter (KF). Economic factors serve to drive the pricing of risk in the market, and agents update expectations recursively, as new information becomes available. We generally find that the Kalman filter provides superior performance and that economic factors like industrial production and unanticipated inflation provide consistent implications across financial markets.     

State transformation of information spillover in asset markets and effective dynamic hedging strategies

This paper aims to develop a strategy to effectively and dynamically hedge risk by considering regime transitions of spillover effects between assets. We take six assets (stocks, bonds, real estate, currency exchange, crude oil, and gold) that are commonly used to construct investment portfolios as examples and analyze asset price data between September 2002 and January 2022. In doing so, we aim to examine the information spillover of different asset prices in both bear and bull market environments to determine whether state transformation affects dynamic hedging effectiveness. Using Markov-Switching Factor-Augmented Vector Autoregression (MS-FAVAR), we construct a regimen-switching model using variables from finance and economic conditions as endogenous variables to define the state transformations of the information spillover. Empirical results reveal that the MS-FAVAR model highlights changes in information spillover during a financial crisis/economic recession. Using dynamic-weighted hedging portfolios constructed with different indicators, we find that hedging effectiveness and volatility vary depending on the state of information spillover between different asset markets and that bear markets significantly impacted hedging effectiveness. Results also show that the panic sentiment (the fear index) explains the probability of a bear market. It is suggested that the state transformation of information spillovers should be monitored periodically, and hedging portfolios should be dynamically adjusted (bear or bull market) with shifting fear sentiment.     

Statistical mechanics of asset markets with private information

Traders in a market typically have widely different, private information on the return of an asset. The equilibrium price of the asset may reflect this information more accurately if the number of traders is large enough compared to the number of the states of the world that determine the return of the asset. We study the transition from markets where prices do not reflect the information accurately into markets where it does. In competitive markets, this transition takes place suddenly, at a critical value of the ratio between number of states and number of traders. The Nash equilibrium market behaves quite differently from a competitive market even in the limit of large economies.     

The “make or take” decision in an electronic market: Evidence on the evolution of liquidity

This paper uses experimental asset markets to investigate the evolution of liquidity in an electronic limit order market. Our market setting includes salient features of electronic limit order markets, as well as informed traders and liquidity traders. We focus on the strategies of the traders and how these are affected by trader type, characteristics of the market, and characteristics of the asset. We find that informed traders use more limit orders than do liquidity traders. Our main result is that liquidity provision shifts as trading progresses, with informed traders increasingly providing liquidity in markets. The change in the behavior of the informed traders seems to be in response to the dynamic adjustment of prices to information; they take (provide) liquidity when the value of their information is high (low). Thus, a market-making role emerges endogenously in our electronic markets and is ultimately adopted by the traders who are least subject to adverse selection when placing limit orders.     

A Rational Expectations Model of Financial Contagion

We develop a multiple asset rational expectations model of asset prices to explain financial market contagion. Although the model allows contagion through several channels, our focus is on contagion through cross-market rebalancing. Through this channel, investors transmit idiosyncratic shocks from one market to others by adjusting their portfolios' exposures to shared macroeconomic risks. The pattern and severity of financial contagion depends on markets' sensitivities to shared macroeconomic risk factors, and on the amount of information asymmetry in each market. The model can generate contagion in the absence of news, as well as between markets that do not directly share macroeconomic risks.     

The Behavior of an Institutional Investor with Arbitrage Opportunities and Liquidity Risk

This study analyzes the efficiency of liquidity flows in stabilizing distressed markets from a theoretical perspective. We show that even in the event of a major negative market shock, a financial institution can increase its investment in the market when there is a strong incentive for arbitrage profit. However, the institution may choose to reduce its investment if the fear from liquidity risk exceeds the arbitrage incentive. In addition, our model reveals a positive relationship between funding liquidity and market liquidity. Our findings help to explain several financial issues in distressed markets, including the flight to quality, liquidity dry-ups, asset fire sales, and market shock amplifications.     

The Effect of Sequential Information Arrival on Asset Prices: An Experimental Study

A complete understanding of security markets requires a simultaneous explanation of price behavior, trading volume, portfolio composition (ie., asset allocation), and bid-ask spreads. In this paper, these variables are observed in a controlled setting—a computerized double auction market, similar to NASDAQ. Our laboratory allows experimental control of information arrival—whether simultaneously or sequentially received, and whether homogeneous or heterogeneous. We compare the price, volume, and share allocations of three market equilibrium models: telepathic rational expectations, which assumes that traders can read each others minds (strong-form market efficiency); ordinary rational expectations, which assumes traders can use (some) market price information, (a type of semi-strong form efficiency); and private information, where traders use no market information. We conclude 1) that stronger-form market models predict equilibrium prices better than weaker-form models, 2) that there were fewer misallocation forecasts in simultaneous information arrival (SIM) environments, 3) that trading volume was significantly higher in SIM environments, 4) and that bid-ask spreads widen significantly when traders are exposed to price uncertainty resulting from information heterogeneity.     

Liquidity in the cryptocurrency market and commonalities across anomalies

We examine how liquidity affects cryptocurrency market efficiency and study commonalities in anomaly performance in cryptocurrency markets. Based on the unique features of cryptocurrencies, we build a model with anonymous traders valuing cryptocurrencies as payments for goods and investment assets, and find that decreases in funding liquidity translate into lower asset liquidity in the cryptocurrency market. Empirically, we observe that many widely recognized stock market anomalies also exist in the cryptocurrency market, although some have opposite long and short legs. We also find evidence that a decrease in cryptocurrency liquidity enhances anomalous returns while preventing the cryptocurrency market from achieving efficiency.     

The Risk‐Return Relation in International Stock Markets

We investigate the risk‐return relation in international stock markets using realized variance constructed from MSCI (Morgan Stanley Capital International) daily stock price indices. In contrast with the capital asset pricing model, realized variance by itself provides negligible information about future excess stock market returns; however, we uncover a positive and significant risk‐return tradeoff in many countries after controlling for the (U.S.) consumption‐wealth ratio. U.S. realized variance is also significantly related to future international stock market returns; more importantly, it always subsumes the information content of its local counterparts. Our results indicate that stock market variance is an important determinant of the equity premium.     

Linkages between Indian and US financial markets: impact of global financial crisis and Eurozone debt crisis

This paper examines inter-linkages between Indian and US equity, foreign exchange and money markets using the vector autoregressive-multivariate GARCH-BEKK framework. We investigate the impact of global financial crisis (GFC) and Eurozone debt crisis (EZDC) on the conditional volatility and conditional correlation estimates derived from the multivariate GARCH model for Indian and US financial markets. Our results indicate that there is significant bidirectional causality-in-mean between the Indian stock market returns and the Rs./USD market returns, and significant unidirectional causality-in-mean from the US stock market returns to the Indian stock market returns. As regards volatility spillovers, we find that volatility in the Indian stock market rises in response to domestic as well as US financial market shocks but Indian financial market shocks do not impact the US markets. Further, impact of the recent crisis episodes on the covariance matrix is found to be significant. We find that volatility in the Indian and US financial markets significantly amplified during GFC. The conditional correlations across asset markets were significantly accentuated in the wake of the two crisis episodes. The impact of GFC on cross-market conditional correlations is higher for majority of the asset market pairs in comparison to the EZDC.     

The performance of model based option trading strategies

This paper analyzes returns to trading strategies in options markets that exploit information given by a theoretical asset pricing model. We examine trading strategies in which a positive portfolio weight is assigned to assets which market prices exceed the price of a theoretical asset pricing model. We investigate portfolio rules which mimic standard mean-variance analysis is used to construct optimal model based portfolio weights. In essence, these portfolio rules allow estimation risk, as well as price risk to be approximately hedged. An empirical exercise shows that the portfolio rules give out-of-sample Sharpe ratios exceeding unity for S&P 500 options. Portfolio returns have no discernible correlation with systematic risk factors, which is troubling for traditional risk based asset pricing explanations.     

The Downside of Asset Screening for Market Liquidity

This paper explores the tension between asset quality and market liquidity. I model an originator who screens assets whose cash flows are later sold in secondary markets. Screening improves asset quality but gives rise to asymmetric information, hindering trade of the asset cash flows. In the optimal mechanism (second‐best), costly retention of cash flows is essential to implement asset screening. Market allocations can feature too much or too little screening relative to second‐best, where too much screening generates inefficiently illiquid markets. Furthermore, the economy is prone to multiple equilibria. The optimal mechanism is decentralized with two tools: retention rules and transfers.     

外汇期权信息含量与在岸离岸市场效率

央行在“8·11”汇改后放松了汇率中间价的管理,采用更为市场化的方式形成中间价,这种变化对于人民币汇率衍生品市场的影响尚属未知。为此,本文从人民币期权组合的Black-Scholes隐含波动率历史报价数据中提取出在岸、离岸市场人民币期权的无模型隐含波动率和风险中性偏度,在将样本划分为汇改前后三个不同的阶段的基础上,检验了期权隐含指标对未来汇率分布的预测能力。实证结果表明,在“8·11”汇改之后,随着人民币中间价形成机制变得更加市场化,期权价格中包含了越来越多关于未来汇率分布的信息,在岸和离岸期权市场的信息效率都有显著提高,意味着人民币中间价形成机制的市场化能显著提升我国金融市场效率。因此,在兼顾金融安全的角度上,稳步促进人民币中间价形成机制市场化进程将有利于我国金融市场效率的提高。     

Optimal informed trading in the foreign exchange market

We formulate a market microstructure model of exchange determination that we employ to investigate the impact of informed trading on exchange rates and on foreign exchange (FX) market conditions. With our formulation, we show how strategic informed agents influence exchange rates via both the portfolio-balance and information effects. We outline the connection which exists between the private value of information, market efficiency, liquidity and exchange rate volatility. Our model is also consistent with recent empirical research on the micro-structure of FX markets.     

Explaining share price disparity with parameter uncertainty: Evidence from Chinese A- and H-shares

The price disparity between the A- and H-share markets for dual-listed firms in China is one of the most intriguing puzzles in the Mainland and Hong Kong financial markets. In this paper, we revisit this price disparity puzzle using the channel of parameter uncertainty. In the presence of information asymmetry and market segmentation, investors have different views on a firm’s asset volatility, and hence different valuations of the same reference firm. We estimate a structural model for equity pricing using a Bayesian approach, in which the uncertainty of investor model parameters is represented by the posterior standard deviation of the firm’s asset volatility. Our regression analysis shows that in addition to other market-based and macro factors, parameter uncertainty explains variations in price disparity.     

Financial Markets Where Traders Neglect the Informational Content of Prices

We model a financial market where some traders of a risky asset do not fully appreciate what prices convey about others' private information. Markets comprising solely such “cursed” traders generate more trade than those comprising solely rationals. Because rationals arbitrage away distortions caused by cursed traders, mixed markets can generate even more trade. Per‐trader volume in cursed markets increases with market size; volume may instead disappear when traders infer others' information from prices, even when they dismiss it as noisier than their own. Making private information public raises rational and “dismissive” volume, but reduces cursed volume given moderate noninformational trading motives.     

Equilibrium moment restrictions on asset returns: normal and crisis periods

Empirically, the covariance between stock returns varies with their volatility. We seek a robust theoretical explanation of this. With minimal assumptions, we model stochastic properties of equilibrium returns which result from the interaction between inter-temporal traders and noisy, price-sensitive short-term traders. The inter-temporal traders can have arbitrary investment rules, preferences and information. In all cases we find a set of restrictions between second moments of equilibrium returns. With two assets there is also a bound on the correlation between asset returns. Estimation with second moments of global stock returns supports our theoretical framework. Higher volatility in at least one market can increase comovement among markets. With globalization, covariances between two stock markets can also affect covariances between two other stock markets. We also find that the changes in trader behavior between normal and crisis periods lead to changes in the moment restrictions between asset returns.