nep-fmk New Economics Papers
on Financial Markets
Issue of 2021‒05‒31
ten papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. A note on the CAPM with endogenously consistent market returns By Andreas Krause
  2. Three Remarks On Asset Pricing By Olkhov, Victor
  3. Measuring Financial Advice: aligning client elicited and revealed risk By John R. J. Thompson; Longlong Feng; R. Mark Reesor; Chuck Grace; Adam Metzler
  4. Predicting returns and dividend growth - the role of non-Gaussian innovations By Kiss, Tamás; Mazur, Stepan; Nguyen, Hoang
  5. Speculative asset price dynamics and wealth taxes By Mignot, Sarah; Tramontana, Fabio; Westerhoff, Frank H.
  6. The Treasury Market Flash Event of February 25, 2021 By Alex Aronovich; Dobrislav Dobrev; Andrew C. Meldrum
  7. Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units By Zihao Zhang; Stefan Zohren
  8. Pricing multivariate european equity option using gaussian mixture distributions and evt-based copulas By Hassane Abba Mallam; Diakarya Barro; Yameogo WendKouni; Bisso Saley
  10. Daily New Covid-19 Cases, The Movement Control Order, and Malaysian Stock Market Returns By Chia, Ricky Chee-Jiun; Liew, Venus Khim-Sen; Rowland, Racquel

  1. By: Andreas Krause
    Abstract: I demonstrate that with the market return determined by the equilibrium returns of the CAPM, expected returns of an asset are affected by the risks of all assets jointly. Another implication is that the range of feasible market returns will be limited and dependent on the distribution of weights in the market portfolio. A large and well diversified market with no dominating asset will only return zero while a market dominated by a small number of assets will only return the risk-free rate. In the limiting case of atomistic assets, we recover the properties of the standard CAPM.
    Date: 2021–05
  2. By: Olkhov, Victor
    Abstract: We make three remarks to the main CAPM equation presented in the well-known textbook by John Cochrane (2001). First, we believe that any economic averaging procedure implies aggregation of corresponding time series during certain time interval Δ and explain the necessity to use math expectation for both sides of the main CAPM equation. Second, the first-order condition of utility max used to derive main CAPM equation should be complemented by the second one that requires negative utility second derivative. Both define the amount of assets ξmax that delivers max to utility. Expansions of the utility in a Taylor series by price and payoff variations give approximations for ξmax and uncover equations on price, payoff, volatility, skewness, their covariance’s and etc. We discuss why market price-volume positive correlations may prohibit existence of ξmax and main CAPM equation. Third, we argue that the economic sense of the conventional frequency-based price probability may be poor. To overcome this trouble we propose new price probability measure based on widely used volume weighted average price (VWAP). To forecast price volatility one should predict evolution of squares of the value and the volume of market trades aggregated during averaging interval Δ. The forecast of the new price probability measure may be the main tough puzzle for CAPM and finance. However investors are free to chose any probability measure they prefer as ground for their investment strategies but should be ready for unexpected losses due to possible distinctions with real market trade price dynamics.
    Keywords: asset pricing, volatility, price probability, market trades
    JEL: C02 D40 D53 G10 G12
    Date: 2021–05–24
  3. By: John R. J. Thompson; Longlong Feng; R. Mark Reesor; Chuck Grace; Adam Metzler
    Abstract: Financial advisors use questionnaires and discussions with clients to determine a suitable portfolio of assets that will allow clients to reach their investment objectives. Financial institutions assign risk ratings to each security they offer, and those ratings are used to guide clients and advisors to choose an investment portfolio risk that suits their stated risk tolerance. This paper compares client Know Your Client (KYC) profile risk allocations to their investment portfolio risk selections using a value-at-risk discrepancy methodology. Value-at-risk is used to measure elicited and revealed risk to show whether clients are over-risked or under-risked, changes in KYC risk lead to changes in portfolio configuration, and cash flow affects a client's portfolio risk. We demonstrate the effectiveness of value-at-risk at measuring clients' elicited and revealed risk on a dataset provided by a private Canadian financial dealership of over $50,000$ accounts for over $27,000$ clients and $300$ advisors. By measuring both elicited and revealed risk using the same measure, we can determine how well a client's portfolio aligns with their stated goals. We believe that using value-at-risk to measure client risk provides valuable insight to advisors to ensure that their practice is KYC compliant, to better tailor their client portfolios to stated goals, communicate advice to clients to either align their portfolios to stated goals or refresh their goals, and to monitor changes to the clients' risk positions across their practice.
    Date: 2021–05
  4. By: Kiss, Tamás (Örebro University School of Business); Mazur, Stepan (Örebro University School of Business); Nguyen, Hoang (Örebro University School of Business)
    Abstract: In this paper we assess whether exible modelling of innovations impact the predictive performance of the dividend price ratio for returns and dividend growth. Using Bayesian vector autoregressions we allow for stochastic volatility, heavy tails and skewness in the innovations. Our results suggest that point forecasts are barely affected by these features, suggesting that workhorse models on predictability are sufficient. For density forecasts, however, we finnd that stochastic volatility substantially improves the forecasting performance.
    Keywords: Bayesian VAR; Dividend Growth Predictability; Predictive Regression; Return Predictability
    JEL: C11 C58 G12
    Date: 2021–05–24
  5. By: Mignot, Sarah; Tramontana, Fabio; Westerhoff, Frank H.
    Abstract: Based on the seminal asset-pricing model by Brock and Hommes (1998), we analytically show that higher wealth taxes increase the risky asset's fundamental value, enlarge its local stability domain, may prevent the birth of nonfundamental steady states and, if they exist, reduce the risky asset's mispricing. We furthermore find that higher wealth taxes may hinder the emergence of endogenous asset price oscillations and, if they exist, dampen their amplitudes. Since oscillatory price dynamics may be associated with lower mispricing than locally stable nonfundamental steady states, policymakers may not always want to suppress them by imposing (too low) wealth taxes. Overall, however, our study suggests that wealth taxes tend to stabilize the dynamics of financial markets.
    Keywords: Asset price dynamics,wealth taxes,heterogeneous expectations,nonlinear dynamics,stability and bifurcation analysis
    JEL: D84 G12 G18 G41
    Date: 2021
  6. By: Alex Aronovich; Dobrislav Dobrev; Andrew C. Meldrum
    Abstract: The Treasury market flash event of February 25, 2021 underscores the pivotal role of high-speed liquidity provision in the most liquid electronic parts of the Treasury market. We find evidence that the sharp drop in prices that day was accompanied by a sudden drop in market depth and a brief deterioration in high-speed liquidity provision amid elevated transaction volumes, albeit to a much lesser extent than during the episode of severe illiquidity in March 2020. Similar to some previous episodes accompanied by moderately elevated economic and financial market uncertainty, market depth has recovered steadily since February 25 at a pace comparable to that observed following other such episodes, while high-speed liquidity provision appears to have rebounded fairly quickly. That said, market depth has taken over a month to partially recover, which suggests that Treasury market liquidity has been more heavily reliant on high-speed replenishment to meet trading demand and may remain fragile.
    Date: 2021–05–14
  7. By: Zihao Zhang; Stefan Zohren
    Abstract: We design multi-horizon forecasting models for limit order book (LOB) data by using deep learning techniques. Unlike standard structures where a single prediction is made, we adopt encoder-decoder models with sequence-to-sequence and Attention mechanisms, to generate a forecasting path. Our methods achieve comparable performance to state-of-art algorithms at short prediction horizons. Importantly, they outperform when generating predictions over long horizons by leveraging the multi-horizon setup. Given that encoder-decoder models rely on recurrent neural layers, they generally suffer from a slow training process. To remedy this, we experiment with utilising novel hardware, so-called Intelligent Processing Units (IPUs) produced by Graphcore. IPUs are specifically designed for machine intelligence workload with the aim to speed up the computation process. We show that in our setup this leads to significantly faster training times when compared to training models with GPUs.
    Date: 2021–05
  8. By: Hassane Abba Mallam; Diakarya Barro; Yameogo WendKouni; Bisso Saley
    Abstract: In this article, we present an approach which allows to take into account the effect of extreme values in the modeling of financial asset returns and in the valorisation of associeted options. Specifically, the marginal distribution of assets returns is modeled by a mixture of two gaussiens distributions. Moreover, we model the joint dependence structure of the returns using an extremal copula which is suitable for our financial data. Applications are made on the Atos and Dassault Systems actions of the CAC40 index. Monte-Carlo method is used to compute the values of some equity options: the call on maximum, the call on minimum, the digital option and the spreads option with the basket (Atos, Dassault systems).
    Date: 2021–05
  9. By: Sandoval Paucar, Giovanny
    Abstract: The article investigates the uncertainty and interdependence between the Colombian stock market and the main international markets. A Dynamic Conditional Correlation Model (DCC) is estimated to study the interdependence between selected stock markets and a GARCH model to analyze conditional volatility. To this end, a daily data sample is used, covering the period between January, 2001 and September, 2018. The results show that the subprime crisis period generates a significant positive effect on the conditional volatility. In addition, there is a significant co-movement in time between the Colombian stock market and national and international markets. Finally, I find evidence of financial contagion in periods of the subprime crisis and European debt
    Keywords: Dynamic conditional correlation, financial crises, multivariate GARCH, financial markets, interdependence
    JEL: C15 F32 F36 G15
    Date: 2021–05–25
  10. By: Chia, Ricky Chee-Jiun; Liew, Venus Khim-Sen; Rowland, Racquel
    Abstract: ABSTRACT The Movement Control Order (MCO) not only restricts movement of human being, it also reduces firms’ financial profits and brings significant impact to stock returns. The objective of this study is to examine the relation between Malaysian stock market returns and variables related to the novel Coronavirus (COVID-19) pandemic outbreak. The FTSE Bursa Malaysia KLCI Index and eight selected main indices from 2 January 2020 to April 30, 2020, which includes the first three MCOs, are considered in this study. The results show that daily new confirmed COVID-19 cases and deaths had negative but insignificant impact on the returns on indices. Interestingly, MCO had significant and positive impact on all the indices’ returns while oversea financial risks had negative impact on these returns. Furthermore, it is found that the degree of impacts of MCO and oversea financial risks varied positively with the firm size of the indices’ constituent companies. China’s decision on unchanged loan prime rate on the 20 February 2020 was a favorable news to the Malaysia stock markets as indicated by the positive returns on all the indices. Similarly, the degree of impact of the China interest policy also varied positively with the firms’ characteristics. These findings are useful for investors in the Bursa Malaysia to manage their investment portfolios based on their appetites for risk.
    Keywords: COVID-19; Movement Control Order; Pandemic outbreak; Bursa Malaysia
    JEL: G10 G14 H0
    Date: 2020

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