nep-fmk New Economics Papers
on Financial Markets
Issue of 2021‒02‒01
fifteen papers chosen by

  1. Stock Prices, Lockdowns, and Economic Activity in the Time of Coronavirus By Steven J. Davis; Dingqian Liu; Xuguang Simon Sheng
  2. How Do Volatility and Return Series Interact? By Söylemez, Arif Orçun
  3. Diversifier or More? Hedge and Safe Haven Properties of Green Bonds During COVID-19 By Arif, Muhammad; Naeem, Muhammad Abubakr; Farid, Saqib; Nepal, Rabindra; Jamasb, Tooraj
  4. How dark is the dark side of diversification? By Pedro Cadenas; Henryk Gzyl; Hyun Woong Park
  5. The flow-performance relationship of global investment Funds By Julien Ciccone; Luca Marchiori; Romuald Morhs
  6. International characteristic-based asset pricing By Jagannathan, Murali; Jiao, Wei; Wermers, Russ
  7. Implied cost of capital and mutual fund performance By Hendriock, Mario
  8. Insider trading in the run-up to merger announcements. Before and after the UK's Financial Services Act 2012 By Rebecaa Pham; Marcel Ausloos
  9. The Value of Intermediation in the Stock Market By Marco Di Maggio; Mark Egan; Francesco A. Franzoni
  10. Hedge funds and the positive idiosyncratic volatility effect By Bali, Turan G.; Weigert, Florian
  11. Deep reinforcement learning for portfolio management By Gang Huang; Xiaohua Zhou; Qingyang Song
  12. A general framework for a joint calibration of VIX and VXX options By Martino Grasselli; Andrea Mazzoran; Andrea Pallavicini
  13. Are hedge funds' charitable donations strategic? By Agarwal, Vikas; Lu, Yan; Ray, Sugata
  14. Extreme-Strike Comparisons and Structural Bounds for SPX and VIX Options By Andrew Papanicolaou
  15. Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media By Marlene Amstad; Leonardo Gambacorta; Chao He; Dora Xia

  1. By: Steven J. Davis; Dingqian Liu; Xuguang Simon Sheng
    Abstract: Stock prices and workplace mobility trace out striking clockwise paths in daily data from mid-February to late May 2020. Global stock prices fell 30 percent from 17 February to 12 March, before mobility declined. Over the next 11 days, stocks fell another 10 percentage points as mobility dropped 40 percent. From 23 March to 9 April, stocks recovered half their losses and mobility fell further. From 9 April to late May, both stocks and mobility rose modestly. This dynamic plays out across the 35 countries in our sample, with a few notable exceptions. We also find that stricter lockdown policies, both in-country and globally, drove larger declines in national stock prices conditional on pandemic severity, workplace mobility, and income support and debt relief policies. Looking more closely at the two largest economies, the pandemic had greater effects on stock market levels and volatilities in the U.S. than in China. Narrative evidence confirms the dominant – and historically unprecedented – role of pandemic-related developments for stock prices in both countries. The size of the global stock market crash in reaction to the pandemic is many times larger than a standard asset-pricing model implies.
    JEL: E32 E44 E65 G12 G18 I18
    Date: 2021–01
  2. By: Söylemez, Arif Orçun
    Abstract: Literature in the last forty years is swamped with a myriad of studies on the relationshipbetween asset returns and volatility. Although the correlation between these two variablesis already well-documented, our knowledge regarding their causal relationship remains limited. This study formally investigates the true dynamic relationship between the VIX implied volatility index and the S&P500 returns. Innovation accounting results indicate strong influence of S&P500 returns on VIX but not vice versa. Plus, unexpected S&P500 losses tend to increase VIX temporarily, while return shocks in general have permanent impact on VIX in the adverse direction of the shock.
    Keywords: Volatility feedback hypothesis; Leverage effect; Endogeneity
    JEL: C01 G10 G14
    Date: 2020–09
  3. By: Arif, Muhammad (Department of Business Administration, Shaheed Benazir Bhutto University, Shaheed Benazirabad, Pakistan); Naeem, Muhammad Abubakr (School of Economics and Finance, Massey University, New Zealand and Business Administration Department, Faculty of Management Sciences, ILMA University, Karachi, Pakistan); Farid, Saqib (School of Business and Economics, University of Management and Technology, Pakistan); Nepal, Rabindra (Faculty of Business and Law, School of Accountancy Economics and Finance, University of Wollongong, Australia); Jamasb, Tooraj (Department of Economics, Copenhagen Business School)
    Abstract: Against the backdrop of the Covid-19 pandemic, this study explores the hedging and safe-haven potential of green bonds for conventional equity, fixed income, commodity, and forex investments. We use the cross-quantilogram approach that provides a better understanding of the dynamic relationship between assets under different market conditions. Our full sample results show that the green bond index could serve as a diversifier asset for medium- and long-term equity investors. Besides, it can also serve as a hedging and safe haven instrument for currency and commodity investments. Moreover, the sub-sample analysis of the pandemic crisis period shows a heightened short- and medium-term lead-lag association between the green bond index and conventional investment returns. However, the green bond index emerges as a significant hedging and safe-haven asset for the long-term investors of conventional financial assets. Our results offer insights for long-term investors whose portfolios comprise conventional assets such as equities, commodities, forex, and fixed income securities. Further, our findings reveal the potential role that the green bond investments could play in global financial recovery efforts without compromising the low-carbon transition targets.
    Keywords: Green bonds; Hedge; Safe-haven; Cross-quantilogram; COVID-19
    JEL: G10 G11 G19 Q01
    Date: 2020–10–11
  4. By: Pedro Cadenas (Denison University); Henryk Gzyl (IESA); Hyun Woong Park (Denison University)
    Abstract: Against the widely held belief that diversification at banking institutions contributes to the stability of the financial system, Wagner (2010) found that diversification actually makes systemic crisis more likely. While it is true, as Wagner asserts, that the probability of joint default of the diversified portfolios is larger; we contend that, as common practice, the effect of diversification is examined with respect to a risk measure like VaR. We find that when banks use VaR, diversification does reduce individual and systemic risk. This, in turn, generates a different set of incentives for banks and regulators.
    Date: 2020–12
  5. By: Julien Ciccone; Luca Marchiori; Romuald Morhs
    Abstract: We study how globalization affects the response of mutual fund flows to past performance. For that purpose, we use a novel dataset on bond funds from the internationalized Luxembourg fund industry. We find that flows into global funds, i.e. funds issuing shares in several currencies, are more sensitive to past performance than flows to domestic funds, i.e. funds distributing shares in mainly one currency. Moreover, global funds exhibit a higher flow sensitivity to low and high performance, while flows to domestic funds are more reactive to medium performance. These results are robust to using alternative measures of globalization to define domestic and global funds, like the geographical diversification in the distribution of shares and the geographical and currency diversification in the asset portfolio. Thus, the globalization dimension of mutual funds, neglected by related studies, raises the sensitivity of flows to past performance and needs to be taken into account by supervisory and regulatory authorities.
    Keywords: Mutual Funds, Multi-currency issuance, Globalization, Flow-performance relationship
    JEL: F30 G11 G23
    Date: 2021–01
  6. By: Jagannathan, Murali; Jiao, Wei; Wermers, Russ
    Abstract: In this paper, we develop characteristic-based asset-pricing models for international stocks. We price stocks using passive portfolios created based on observable characteristics: market capitalization, book-to-market, prior-year return, growth of total assets, and operating profitability, each separately created for a given geographical region of the world. As such, our approach allows for segmentation in characteristic-based asset pricing among regions. Using a resampling micro-portfolio approach recently introduced by Barras (2018), we find that market capitalization is the most powerful characteristic in pricing international stocks, and that a threecharacteristic model based on market capitalization, book-to-market, and prior-year return has the lowest pricing errors. We also show that characteristic-based benchmarks exhibit much lower pricing errors, relative to global factor-based models. We further apply our characteristic models to the equity holdings of U.S. funds that invest in international stocks. International index funds exhibit zero abnormal returns, while active funds that charge higher fees and that mainly invest in emerging markets and small or mid-capitalization stocks exhibit positive and significant abnormal returns. These results indicate that U.S.-domiciled active managers are able to generate abnormal returns in less-efficient sectors of non-U.S. stock markets, when expected returns are measured using characteristic-based pricing.
    Keywords: International asset pricing,Characteristic-based asset-pricing models,International mutual funds
    JEL: G12 G15 G23
    Date: 2020
  7. By: Hendriock, Mario
    Abstract: This study provides evidence for a positive association between mutual fund holdings'implied cost of capital (ICC) and future performance. Consistent with large transactioncosts of ICC-based investments impeding their exploitation and employing a ICC-basedstrategy reflecting skill, family-level trading efficiency and manager-level SAT scorepositively correlate with fund-level ICC. A negative association between ICC and mid-year risk shifting corroborates the notion of fund managers decisively choosing andrelying on high-ICC strategies. Institutional investors able to identify funds with highICC direct their investments accordingly, whereas flows of retail funds are unaffected,consistent with limited investor attention and financial literacy.
    Keywords: implied cost of capital,mutual funds,portfolio choice,financial forecasting
    JEL: G11 G14 G17 G23 G31 M41
    Date: 2020
  8. By: Rebecaa Pham; Marcel Ausloos
    Abstract: After the 2007/2008 financial crisis, the UK government decided that a change in regulation was required to amend the poor control of financial markets. The Financial Services Act 2012 was developed as a result in order to give more control and authority to the regulators of financial markets. Thus, the Financial Conduct Authority (FCA) succeeded the Financial Services Authority (FSA). An area requiring an improvement in regulation was insider trading. Our study examines the effectiveness of the FCA in its duty of regulating insider trading through utilising the event study methodology to assess abnormal returns in the run-up to the first announcement of mergers. Samples of abnormal returns are examined on periods, under regulation either by the FSA or by the FCA. Practically, stock price data on the London Stock Exchange from 2008-2012 and 2015-2019 is investigated. The results from this study determine that abnormal returns are reduced after the implementation of the Financial Services Act 2012; prices are also found to be noisier in the period before the 2012 Act. Insignificant abnormal returns are found in the run-up to the first announcement of mergers in the 2015-2019 period. This concludes that the FCA is efficient in regulating insider trading.
    Date: 2020–12
  9. By: Marco Di Maggio (Harvard Business School; National Bureau of Economic Research (NBER)); Mark Egan (Harvard University - Business School (HBS); National Bureau of Economic Research (NBER)); Francesco A. Franzoni (USI Lugano; Swiss Finance Institute; Centre for Economic Policy Research (CEPR))
    Abstract: Brokers play a critical role in intermediating institutional transactions in the stock market. Despite the importance of brokers, we have limited information on what drives investors’ choices among them. We develop and estimate an empirical model of broker choice that allows us to quantitatively examine each investor’s responsiveness to execution costs, access to research, and order flow information. Studying over 300 million institutional trades, we find that investor demand is relatively inelastic with respect to trading commissions and that investors are willing to pay a premium for access to formal (top research analysts) and informal (order-flow information) research. There is also substantial heterogeneity across investors. Relative to other investors, hedge funds tend to be more price insensitive, place less value on sell-side research, and place more value on order-flow information. Using trader-level data, we find that investors are more likely to execute trades through intermediaries who are located physically closer and are less likely to trade with those that have engaged in misconduct in the past. Lastly, we use our empirical model to investigate soft-dollar arrangements and the unbundling of equity research and execution services related to the MiFID II regulations. We find that the bundling of execution and research potentially allows hedge funds and mutual funds to under-report management fees by 10%.
    Keywords: Financial Intermediation, Institutional Investors, Research Analysts, Broker Networks, Equity Trading
    JEL: L11 G14 G23 G24
    Date: 2021–01
  10. By: Bali, Turan G.; Weigert, Florian
    Abstract: While it is established that idiosyncratic volatility has a negative impact on the cross-section of future stock returns, the relationship between idiosyncratic volatility and future hedge fund returns is largely unexplored. We document that hedge funds with high idiosyncratic volatility outperform and this pattern is explained by the positive return effect of idiosyncratic volatility in their equity portfolio holdings. Hedge funds select stocks wisely by picking high-volatility stocks when they are undervalued and shying away from high-volatility stocks when they are overvalued or display lottery-like payoffs. They also trade derivatives in a way to profit from the positive volatility effect.
    Keywords: Hedge Funds,Idiosyncratic Volatility Puzzle,Equity Portfolio Holdings,Derivatives,Managerial Incentives,Investment Performance
    JEL: G11 G23
    Date: 2021
  11. By: Gang Huang; Xiaohua Zhou; Qingyang Song
    Abstract: The objective of this paper is to verify that current cutting-edge artificial intelligence technology, deep reinforcement learning, can be applied to portfolio management. We improve on the existing Deep Reinforcement Learning Portfolio model and make many innovations. Unlike many previous studies on discrete trading signals in portfolio management, we make the agent to short in a continuous action space, design an arbitrage mechanism based on Arbitrage Pricing Theory,and redesign the activation function for acquiring action vectors, in addition, we redesign neural networks for reinforcement learning with reference to deep neural networks that process image data. In experiments, we use our model in several randomly selected portfolios which include CSI300 that represents the market's rate of return and the randomly selected constituents of CSI500. The experimental results show that no matter what stocks we select in our portfolios, we can almost get a higher return than the market itself. That is to say, we can defeat market by using deep reinforcement learning.
    Date: 2020–12
  12. By: Martino Grasselli; Andrea Mazzoran; Andrea Pallavicini
    Abstract: We analyze the VIX futures market with a focus on the exchange-traded notes written on such contracts, in particular, we investigate the VXX notes tracking the short-end part of the futures term structure. Inspired by recent developments in commodity smile modeling, we present a multi-factor stochastic local-volatility model able to jointly calibrate plain vanilla options both on VIX futures and VXX notes. We discuss numerical results on real market data by highlighting the impact of model parameters on implied volatilities.
    Date: 2020–12
  13. By: Agarwal, Vikas; Lu, Yan; Ray, Sugata
    Abstract: We study whether hedge funds make charitable donations to further their business interests. We find that donations are driven by poor fund flows and performance. Post-donation, donor funds experience lower outflows compared to matched non-donors. One-off donations and donations to charities which hold fundraising events catering to the hedge fund community are more likely to mitigate outflows after poor performance. These findings are consistent with strategic motivations driving at least some donations. While the economics of donations initially appear quite favorable to the hedge funds, the benefits from donations are not scalable. Moreover, investors punish donors through greater redemptions if poor performance persists post-donation.
    Keywords: Hedge funds,Philanthropy,Trust,Charitable Donations,Capital Formation,Corporate Social Responsibility (CSR)
    JEL: D64 G23 G41
    Date: 2020
  14. By: Andrew Papanicolaou
    Abstract: This article explores the relationship between the SPX and VIX options markets. High-strike VIX call options are used to hedge tail risk in the SPX, which means that SPX options are a reflection of the extreme-strike asymptotics of VIX options, and vice versa. This relationship can be quantified using moment formulas in a model-free way. Comparisons are made between VIX and SPX implied volatilities along with various examples of stochastic volatility models.
    Date: 2021–01
  15. By: Marlene Amstad; Leonardo Gambacorta; Chao He; Dora Xia
    Abstract: Trade tensions between China and US have played an important role in swinging global stock markets but effects are difficult to quantify. We develop a novel trade sentiment index (TSI) based on textual analysis and machine learning applied on a big data pool that assesses the positive or negative tone of the Chinese media coverage, and evaluates its capacity to explain the behaviour of 60 global equity markets. We find the TSI to contribute around 10% of model capacity to explain the stock price variability from January 2018 to June 2019 in countries that are more exposed to the China-US value chain. Most of the contribution is given by the tone extracted from social media (9%), while that obtained from traditional media explains only a modest part of stock price variability (1%). No equity market benefits from the China-US trade war, and Asian markets tend to be more negatively affected. In particular, we find that sectors most affected by tariffs such as information technology related ones are particularly sensitive to the tone in trade tension.
    Keywords: stock returns, trade, sentiment, big data, neural network, machine learning
    JEL: F13 F14 G15 D80 C45 C55
    Date: 2021–01

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