Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search

We examine the ability of online ticker searches (e.g. XOM for Exxon Mobil) to forecast abnormal stock returns and trading volumes. Specifically, we argue that online ticker searches serve as a valid proxy for investor sentiment — a set of beliefs about cash flows and investment risks that are not necessarily justified by the facts at hand — which is generally associated with less sophisticated, retail investors. Based on prior research on investor sentiment, we expect online search intensity to forecast stock returns and trading volume, and also expect that highly volatile stocks, which are more difficult to arbitrage, will be more sensitive to search intensity than less volatile stocks. In a sample of S&P 500 firms over the period 2005-2008, we find that, over a weekly horizon, online search intensity reliably predicts abnormal stock returns and trading volumes, and that the sensitivity of returns to search intensity is positively related to the difficulty of a stock being arbitraged. More broadly, our study highlights the potential of employing online search data for other forecasting applications.     

Did the introduction of Bitcoin futures crash the Bitcoin market at the end of 2017?

At the end of 2017, the Bitcoin price dropped significantly by approximately 70% over the two months. Since the introduction of Bitcoin futures coincided with this market crash, it is said that the new financial instrument might have caused the market crash. The literature states that the futures enabled investors to easily take a short position and hypothesizes that the selling pressure from futures could have potentially crashed the Bitcoin market. To evaluate this assumption, we investigate the empirical relationship between futures trading and the Bitcoin price by using high-frequency data. We find that Bitcoin futures trading was not significantly related to the returns on Bitcoin futures and spot returns. Therefore, we conclude that Bitcoin futures did not lead to the crash of the Bitcoin market at the end of 2017.     

A model of international asset pricing under imperfect commodity arbitrage

This paper examines the effect of imperfect international commodity arbitrage (i.e., violation of the law of one price), modeled as the existence of non-traded goods, on the structure of purchasing power risk, optimal portfolio rules of the risk-averse investors and the equilibrium yield relationship among assets. The major results of the paper include: (i) There are two separate sources of purchasing power risk, i.e., relative price risk and inflation risk; relative price risk is specific to the country in which the investor resides. (ii) In a world of n countries, investors may hold n + 1 hedge portfolios as vehicles to hedge against purchasing power risk; facing different relative prices, investors residing in different countries display divergent portfolio behavior. (iii) In equilibrium, investors are compensated in terms of excess return for bearing not only the systematic world market risk but also the systematic inflation and relative price risks.     

Retail investors’ trading and stock market liquidity

The paper investigates the relation between retail investors’ participation in trading and aggregate stock market liquidity. The findings show a positive and significant relation between retail investors’ trading and stock market liquidity. Examination of the determinants of retail investors’ trading reveals that, on average, retail investors with more diversified trading activity tend to trade when liquidity is higher, the frequency of their arrival to the market is not affected by the level of liquidity, and retail investors are willing to trade at a lower liquidity level as sellers than as buyers. Moreover, retail investors’ trading does not create price noise at the aggregate market level. Overall, the evidence suggests that retail investors contribute to market quality.     

Arbitrage,speculation and futures price fluctuations with boundedly rational and heterogeneous agents

This paper proposes a dynamic model for the futures market with three types of investors. The bounded rationality and heterogeneity of investors are taken into consideration. The equilibrium of the system and its stability conditions are derived with mathematical analysis. In the equilibrium, the futures price and the spot price converge to the equilibrium simultaneously. The equilibrium is determined by many factors, including the risk appetite and the rationality of investors, the trading costs, the arbitrage basis price and the fundamental price. When the stability conditions are violated, complex dynamics will emerge in the market. As shown by the simulations, the arbitrage is likely to destabilize the market. Moreover, when investors have the high degree of rationality, the equilibrium will become unstable and the futures market is inefficient. Statistical analysis indicates that the model can reproduce the stylized facts observed in the futures market, such as long memory, volatility clustering and fat tail of returns.

     

A topological invariant for competitive markets

This paper summarizes the concepts of global cones and limited arbitrage introduced in Chichilnisky (Economic Theory, 1995, 5, 79–108), and the corresponding results establishing that limited arbitrage is necessary and sufficient for the existence of a competitive equilibrium and for the compactness of Pareto frontier (announced in Chichilnisky (American Economic Review, 1992, 84, 427–434, and Chichilnisky (Bulletin of the American Mathematical Society, 1993, 29, 189–207). Using the same global cones I extend my earlier results to encompass ‘mixed economies’ based on Chichilnisky (CORE Discussion Paper No. 9527, 1995). I introduce a topological invariant for competitive markets which deepens the concept of limited arbitrage. This invariant encodes exact information on the equilibria and on the social diversity of the economy and all its subeconomies, and predicts a failure of effective demand.     

Is bitcoin a safe haven or a hedging asset? Evidence from China

Based on daily data about Bitcoin and six other major financial assets (stocks, commodity futures (commodities), gold, foreign exchange (FX), monetary assets, and bonds) in China from 2013 to 2017, we use a VAR-GARCH-BEKK model to investigate mean and volatility spillover effects between Bitcoin and other major assets and explore whether Bitcoin can be used either as a hedging asset or a safe haven. Our empirical results show that (i) only the monetary market, i.e., the Shanghai Interbank Offered Rate (SHIIBOR) has a mean spillover effect on Bitcoin and (ii) gold, monetary, and bond markets have volatility spillover effects on Bitcoin, while Bitcoin has a volatility spillover effect only on the gold market. We further find that Bitcoin can be hedged against stocks, bonds and SHIBOR and is a safe haven when extreme price changes occur in the monetary market. Our findings provide useful information for investors and portfolio risk managers who have invested or hedged with Bitcoin.     

Animal Behavior in Capital markets: Herding formation dynamics,trading volume,and the role of COVID-19 pandemic

This paper provides new evidence on herding behavior. Using daily frequency data for 336 US listed firms over a five-year period, we investigate three important elements of financial herding behavior. First, trading volume, representing market interest, as a significant variable in capital markets apart from stock prices. Second, herding dynamics since herding formation is a dynamic process. Third, the reaction of possible financial herding to exogenous events-threats, as we use the pandemic event in order to investigate a market under stress. Even though the benchmark herding model used does not provide evidence of herding behavior, our results verify the significance of the above herding elements. We also find that trading volume and positive changes in trading volume result in increased cross-sectional absolute deviation (CSAD). Most importantly, we find that herding behavior is evident during the COVID-19 pandemic confirming that investors tend to herd during major crisis periods.     

“Small things matter most”: The spillover effects in the cryptocurrency market and gold as a silver bullet

The cryptocurrencies with small market capitalization are often overlooked despite they can potentially be the source of shocks to other cryptocurrencies in the market. To address this caveat, this paper attempts to investigate the spillover effects among 14 cryptocurrencies by employing transfer entropy. Our results suggest that among different types of cryptos, Bitcoin is still the most appropriate instrument for hedging, while Tether (USDT) which have a strong anchor with the US dollar is significantly volatile. Interestingly, we document that the small coins are more likely to be shock creators in the cryptocurrency market. Using the same approach, we further explored the link between gold prices and cryptocurrency prices. The results show that gold could be a good hedging instrument for cryptocurrencies due to its independence. In light of empirical results, it is advisable to carefully consider the coins with small capitalization. Further, investors should conduct portfolio rebalancing by including gold to hedge against the unexpected movement in the cryptocurrency market. Our paper not only contributes in terms of the application of advanced empirical methodology but also provides evidence on idiosyncratic features of the cryptocurrency market.     

金融危机背景下套利定价模型的浅析

金融危机给资本市场投资带来了更大的风险,也使得证券投资在定价分析上更加复杂化。从现代投资组合模型的演化和目前投资人普遍规避风险的倾向来看,套利定价模型是更有效的分析模型。投资者可以在结合资本市场实际情况和偏好的同时运用套利定价模型,以便在危机中做出理性的选择。     

Mispricing in the odd lots market in Brazil

We study the case of mispricing in the odd lots equity market in Brazil. Contrary to expectation, odd lot investors are paying higher prices than round lot investors. The pricing difference between markets is affected by market returns, volatility and spreads. Our main hypothesis is that; once the assets traded in the odd lot market are more illiquid than their counterparts, the mispricing is driven by liquidity factors. Additionally, we show that the mispricing yields an arbitrage opportunity that is not being traded away in the Brazilian market. Therefore, we propose regulators to review the market design for odd lots in Brazil. We argue that reducing the minimal trading unit in the round lots market would benefit investors.     

Managerial Perceptions of the Net Benefits of Foreign Listing: Canadian Evidence

This study provides some insights into managerial perceptions of the costs, benefits, and net benefits of foreign listing through a survey of Canadian firms that have listed their securities on the foreign exchanges in the U.S. and U.K. Access to foreign capital markets and increased stock marketability are perceived to be the major benefits. The SEC reporting and compliance requirements are cited as the major costs of foreign listings. Overall, benefits are perceived to outweigh costs although not significandy. Managerial perceptions of positive net benefits are strongly linked to the levels of trading volume in their firm's stock on foreign exchanges. This study is useful for managers contemplating foreign listings. Our findings indicate that the listing decision requires careful scrutiny in terms of potential costs and benefits which may depend on many firm specific factors. Firms conducting most of their business abroad and issuing a greater percentage of equity abroad are likely to have a greater appeal for foreign investors irrespective of their size and industry. While multiple listings on foreign exchanges may not imply higher foreign trading volumes, fewer domestic exchange listings are associated with higher foreign trading volumes.     

When do retail investors pay attention to their trading platforms?

Buying and selling securities through online trading platforms has become increasingly popular among U.S. households in recent years. This study tracks U.S. households' attention to their online trading platforms using daily data for 2004 to August 2017. The analysis covers the 10 most popular online trading platforms among U.S. investors. The findings indicate that market shocks, captured by several proxies, as well as macroeconomic announcements attract investors' attention to trading platforms. We also document that the ostrich effect weakens when considering greater changes in the VIX. Our findings do not support the avoidance of information theory, but do support the theoretical argument that risk-averse agents engage in more information gathering when uncertainty prevails in hopes of reducing their risks.     

Intraday return predictability in the cryptocurrency markets: Momentum,reversal, or both

This paper reports evidence of intraday return predictability, consisting of both intraday momentum and reversal, in the cryptocurrency market. Using high-frequency price data on Bitcoin from March 3, 2013, to May 31, 2020, it shows that the patterns of intraday return predictability change in the presence of large intraday price jumps, FOMC announcement release, liquidity levels, and the outbreak of the COVID-19. Intraday return predictability is also found in other actively traded cryptocurrencies such as Ethereum, Litecoin, and Ripple. Further analysis shows that the timing strategy based on the intraday predictors produces higher economic value than the benchmark strategy such as the always-long or the buy-and-hold. Evidence of intraday momentum can be explained in light of the theory of late-informed investors, whereas evidence of intraday reversal, which is unique to the cryptocurrency market, can be related to investors’ overreaction to non-fundamental information and overconfidence bias.     

Why cryptocurrency markets are inefficient: The impact of liquidity and volatility

In this research, we study the multifractality, long-memory process, and efficiency hypothesis of six major cryptocurrencies (Bitcoin, Ethereum, Monero, Dash, Litecoin, and Ripple) using the time-rolling MF-DFA approach. For an in-depth analysis, this study uses the quantile regression approach to examine the determinants of efficient markets. The results show that all markets present evidence of long-memory property and multifractality. Furthermore, the inefficiency of cryptocurrency markets is time-varying, and Dash is the least inefficient market while Litecoin is the most inefficient. Finally, we find that higher liquidity improves but higher volatility weakens the efficiency of cryptocurrencies, depending on the quantiles. Therefore, we conclude that high liquidity with low volatility helps active traders to arbitrage away opportunities, resulting in market efficiency.     

美、欧央行监管比特币的做法及其对我国的启示

2015年12月5日,中国人民银行、银监会、证监会等五部委联合印发了《关于防范比特币风险的通知》,这对于保护社会公众的财产权益,保障人民币的法定货币地位,防范洗钱风险,维护金融稳定,具有重要的现实意义。美、欧央行对比特币的监管已先行一步,对我国具有一定的启示和借鉴。本文简要介绍了我国比特币交易情况及监管现状,归纳总结了美、欧央行监管比特币做法,提出我国应借鉴美、欧央行做法制定应急预案,防范比特币风险。     

Bid-ask dynamic pricing in financial markets with transaction costs and liquidity risk

According to the classic no arbitrage theory of asset pricing, in a frictionless market a No Free Lunch dynamic price process associated with any essentially bounded asset is a martingale under an equivalent probability measure. However, real financial markets are not frictionless. We introduce an axiomatic approach of Time Consistent Pricing Procedure (TCPP), in a model free setting, to assign to every financial position a dynamic ask (resp. bid) price process. Taking into account both transaction costs and liquidity risk this leads to the convexity (resp. concavity) of the ask (resp. bid) price. We prove that the No Free Lunch condition for a TCPP is equivalent to the existence of an equivalent probability measure R that transforms a process between the bid price process and the ask price process of every financial instrument into a martingale. Furthermore we prove that the ask (resp. bid) price process associated with every financial instrument is then a R super-martingale (resp. R sub-martingale) which has a càdlàg version.     

A new method to verify Bitcoin bubbles: Based on the production cost

As the first kind of digital cryptocurrency, the Bitcoin price cycle provides an opportunity to test bubble theory in the digital currency era. Based on the existing asset bubble theory, we verified the Bitcoin bubble based on the production cost with the application of VAR and LPPL models, and this method achieved good predictive power. The following conclusions are reached: (1) PECR is constructed to depict the deviation degree between the price and production cost, while BC is used to illustrate the bubble size in the price, and both are effective measures; (2) the number of unique addresses is a suitable measure of the use value of Bitcoin, and this result has passed the Granger causality test; (3) PECR and BC are verified via the LPPL model, and the next large bubble is expected in the second half of 2020. Considering that Bitcoin will see 'output halved' in May 2020, this prediction is a high-probability event.     

ISLAMIC FINANCE AS A PROGENITOR OF VENTURE CAPITAL

The antecedents of corporate limited liability are commonly seen to emerge amongst medieval Italian merchant bankers in so‐called commendas, commercial arrangements combining investors and entrepreneurs. Italian merchants trading with the Levant may have adapted the Islamic concept of a risk‐sharing partnership, the qirâd, as a model. Western corporations thus may owe their origins to the influence of Islam's entrepreneurial founder, Mohammed.