nep-fmk New Economics Papers
on Financial Markets
Issue of 2020‒05‒25
five papers chosen by

  1. The Macroprudential Role of Stock Markets By Kyriakos T. Chousakos; Gary B. Gorton; Guillermo Ordoñez
  2. Investing in VIX futures based on rolling GARCH models forecasts By Oleh Bilyk; Paweł Sakowski; Robert Ślepaczuk
  3. Can heterogeneous agent models explain the alleged mispricing of the S&P 500? By Lux, Thomas
  4. EME bond portfolio flows and long-term interest rates during the Covid-19 pandemic By Peter Hördahl; Ilhyock Shim
  5. Chinese stock market performance in the time of novel coronavirus pandemic By Liew, Venus Khim-Sen; Puah, Chin-Hong

  1. By: Kyriakos T. Chousakos; Gary B. Gorton; Guillermo Ordoñez
    Abstract: A financial crisis is an event of sudden information acquisition about the collateral backing short-term debt in credit markets. When investors see a financial crisis coming, however, they react by more intensively acquiring information about firms in stock markets, revealing those that are weaker, which as a consequence end up cut off from credit. This cleansing effect of stock markets’ information on credit markets’ composition discourage information acquisition about the collateral of the firms remaining in credit markets, slowing down credit growth and potentially preventing a crisis. Production of information in stock markets, then, acts as a macroprudential tool in the economy.
    JEL: E32 E44 G01
    Date: 2020–05
  2. By: Oleh Bilyk; Paweł Sakowski (Quantitative Finance Research Group, Faculty of Economic Sciences, University of Warsaw); Robert Ślepaczuk (Quantitative Finance Research Group, Faculty of Economic Sciences, University of Warsaw)
    Abstract: The aim of this work is to compare the performance of VIX futures trading strategies built across different GARCH model volatility forecasting techniques. Long and short signals for VIX futures are produced by comparing one-day ahead volatility forecasts with current historical volatility. We found out that using the daily data over the seven-year period (2013-2019), strategy based on the fGARCH-TGARCH and GJR-GARCH specifications outperformed those of the GARCH and EGARCH models, and performed slightly below the “buy-and-hold” S&P 500 strategy. For the base GARCH(1,1) model, the training window size and the type gave stable results, whereas the performance across refit frequency, conditional distribution of returns, and historical volatility estimators varies significantly. Despite non-robustness of some investment strategies and some space for improvements, the presented strategies show their potential in competing with the equity and volatility benchmarks.
    Keywords: GARCH, VIX index, volatility futures, rolling forecasting, volatility, investment strategies, volatility exposure
    JEL: C4 C45 C61 C15 G14 G17
    Date: 2020
  3. By: Lux, Thomas
    Abstract: Tests of excessive volatility along the lines of Shiller (1981) and Leroy and Porter (1981) count among the most convincing pieces of evidence against the validity of the time-honored efficient market hypothesis. Recently, using Shillers distinction between ex-ante rational (fundamental) price and ex-post rational price, Schmitt and Westerhoff (2017) have demonstrated that the difference between S&P 500 market prices and their ex-post counterparts exhibits a bi-modal distribution speaking for the prevalence of long periods of either undervaluation or overvaluation. Schmitt and Westerhoff (2017) also show that this new stylized fact is shared by a large set of nonlinear behavioral models of speculative interactions between heterogeneous market participants. Most of these models allow some form of chartist or fundamentalist strategy, and the more recent members of this family of models also allow for agents switching between both alternatives according to some fitness criterion. Here I go one step further exploring which (if any) of this legacy of behavioral models fits best the data. I discuss econometric issues in the estimation of these highly complex nonlinear models, and estimate the parameters of different versions of seven canonical models. As it turns out, most of these models perform not better than a linear chartist-fundamentalist model, and often their fit is worse than the fit of this benchmark. Among the models considered here, the one proposed by Franke and Westerhoff (2012) is the only exception. Estimation of the model confidence set indicates that this model is not outperformed by other candidates, and depending on the setting and the confidence level, it is often found to be the single member of the model confidence set.
    Keywords: Stock market dynamics,bubbles and crashes,nonlinear dynamics,chartists and fundamentalists,model confidence set
    JEL: G12 G14 G17
    Date: 2020
  4. By: Peter Hördahl; Ilhyock Shim
    Abstract: Bond portfolio outflows from emerging market economies (EMEs) are typically associated with currency depreciation and rising domestic long-term interest rates. This relationship asserted itself in a particularly stark way during the Covid-19 crisis in mid-March 2020. The relationship between bond portfolio outflows and long-term rates varies across EMEs, depending on factors such as bond market depth, FX market functioning and sovereign risk. The impact of these factors on the relationship has been thrown into sharper relief during the Covid-19 pandemic. Recent policy responses, such as bond purchase programmes, duration swaps and efforts to stabilise exchange rates, can play an important role in maintaining financial stability in EMEs when they face bond outflows. Policy measures to develop deep and liquid bond markets and strengthen the resilience of local currency bond and FX markets are likely to enhance market functioning in the longer term.
    Date: 2020–05–20
  5. By: Liew, Venus Khim-Sen; Puah, Chin-Hong
    Abstract: This paper aims to quantify the effect of the deadly novel coronavirus (COVID-19) pandemic outbreak on Chinese stock market performance. Shanghai Stock Exchange Composite Index and its component sectorial indices are examined in this study. The pandemic is represented by a lockdown dummy, new COVID-19 cases and a dummy for 3 February 2020. First, descriptive analysis is performed on these indices to compare their performances before and during the lockdown period. Next, regression analysis with Exponential Generalized Autoregressive Conditional Heteroscedasticity specification is estimated to quantify the pandemic effect on the Chinese stock market. This paper finds that health care, information technology and telecommunication services sectors were relatively more pandemic-resistant, while other sectors were more severely hurt by the pandemic outbreak. The extent to which each sector was affected by pandemic and sentiments in other financial and commodity markets were reported in details in this paper. The findings of this paper are resourceful for investors to avoid huge loss amid pandemic outburst and the China Securities Regulatory Commission in handling future pandemic occurrence to cool down excessive market sentiments.
    Keywords: Novel coronavirus, COVID-19, SARS-CoV-2, pandemic, Chinese stock market, Exponential Generalized Autoregressive Conditional Heteroscedasticity
    JEL: G14 G15
    Date: 2020–04–01

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