nep-fmk New Economics Papers
on Financial Markets
Issue of 2019‒12‒23
eight papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach. By Mohamed CHIKHI; Claude DIEBOLT; Tapas MISHRA
  2. Defining an intrinsic "stickiness" parameter of stock price returns By Naji Massad; Jørgen Vitting Andersen
  3. Systemic Risk: Fire-Walling Financial Systems Using Network-Based Approaches By V. Sasidevan; Nils Bertschinger
  4. Valuing Private Equity Strip by Strip By Arpit Gupta; Stijn Van Nieuwerburgh
  5. BitMEX Funding Correlation with Bitcoin Exchange Rate By Sai Srikar Nimmagadda; Pawan Sasanka Ammanamanchi
  6. Interbank transactions on the intraday frequency: -Different market states and the effects of the financial crisis- By Anastasios Demertzidis
  7. Does stock market capitalization cause GDP? A causality study for Central and Eastern European countries By Prats Albentosa, María Asuncíon; Sandoval, Beatriz
  8. Examining risk and return profiles of renewable energy investment in developing countries: The Case of the Philippines By Saculsan, Phoebe; Kanamura, Takashi

  1. By: Mohamed CHIKHI; Claude DIEBOLT; Tapas MISHRA
    Abstract: Despite an inherent share of unpredictability, asset prices such as in stock and Bitcoin markets are naturally driven by significant magnitudes of memory; depending on the strength of path dependence, prices in such markets can be (at least partially) predicted. Being able to predict asset prices is always a boon for investors, more so, if the forecasts are largely unconditional and can only be explained by the series’ own historical trajectories. Although memory dynamics have been exploited in forecasting stock prices, Bitcoin market pose additional challenge, because the lack of proper financial theoretic model limits the development of adequate theory-driven empirical construct. In this paper, we propose a class of autoregressive fractionally integrated moving average (ARFIMA) model with asymmetric exponential generalized autoregressive score (AEGAS) errors to accommodate a complex interplay of ‘memory’ to drive predictive performance (an out-of-sample forecasting). Our conditional variance includes leverage effects, jumps and fat tail-skewness distribution, each of which affects magnitude of memory both the stock and Bitcoin price system would possess enabling us to build a true forecast function. We estimate several models using the Skewed Student-t maximum likelihood and find that the informational shocks in asset prices, in general, have permanent effects on returns. The ARFIMA-AEGAS is appropriate for capturing volatility clustering for both negative (long Value-at-Risk) and positive returns (short Value-at-Risk). We show that this model has better predictive performance over competing models for both long and/or some short time horizons. The predictions from this model beats comfortably the random walk model. Accordingly, we find that the weak efficiency assumption of financial markets stands violated for all price returns studied over longer time horizon.
    Keywords: Asset price; Forecasting; Memory; ARFIMA-AEGAS; Leverage effects and jumps; Market Efficiency.
    JEL: C14 C58 C22 G17
    Date: 2019
  2. By: Naji Massad (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Jørgen Vitting Andersen (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, CNRS - Centre National de la Recherche Scientifique)
    Abstract: We introduce a non-linear pricing model of individual stock returns that defines a "stickiness" parameter of the returns. The pricing model resembles the capital asset pricing model (CAPM) used in finance but has a non-linear component inspired from models of earth quake tectonic plate movements. The link to tectonic plate movements happens, since price movements of a given stock index is seen adding "stress" to its components of individual stock returns, in order to follow the index. How closely individual stocks follow the index's price movements, can then be used to define their "stickiness".
    Keywords: non-linear CAPM,stickiness of stock returns
    Date: 2019–10
  3. By: V. Sasidevan; Nils Bertschinger
    Abstract: The latest financial crisis has painfully revealed the dangers arising from a globally interconnected financial system. Conventional approaches based on the notion of the existence of equilibrium and those which rely on statistical forecasting have seen to be inadequate to describe financial systems in any reasonable way. A more natural approach is to treat financial systems as complex networks of claims and obligations between various financial institutions present in an economy. The generic framework of complex networks has been successfully applied across several disciplines, e.g., explaining cascading failures in power transmission systems and epidemic spreading. Here we review various network models addressing financial contagion via direct inter-bank contracts and indirectly via overlapping portfolios of financial institutions. In particular, we discuss the implications of the "robust-yet-fragile" nature of financial networks for cost-effective regulation of systemic risk.
    Date: 2019–12
  4. By: Arpit Gupta; Stijn Van Nieuwerburgh
    Abstract: We propose a new valuation method for private equity investments. First, we construct a cash-flow replicating portfolio for the private investment, applying Machine Learning techniques on cash-flows on various listed equity and fixed income instruments. The second step values the replicating portfolio using a flexible asset pricing model that accurately prices the systematic risk in bonds of different maturities and a broad cross-section of equity factors. The method delivers a measure of the risk-adjusted profit earned on a PE investment and a time series for the expected return on PE fund categories. We apply the method to buyout, venture capital, real estate, and infrastructure funds, among others. Accounting for horizon-dependent risk and exposure to a broad cross-section of equity factors results in negative average risk-adjusted profits. Substantial cross-sectional variation and persistence in performance suggests some funds outperform. We also find declining expected returns on PE funds in the later part of the sample.
    JEL: G00 G11 G12 G23 G32 R30 R51
    Date: 2019–11
  5. By: Sai Srikar Nimmagadda; Pawan Sasanka Ammanamanchi
    Abstract: This paper examines the relationship between Inverse Perpetual Swap contracts, a Bitcoin derivative akin to futures and the margin funding interest rates levied on BitMEX. This paper proves the Heteroskedastic nature of funding rates and goes onto establish a causal relationship between the funding rates and the Bitcoin inverse Perpetual swap contracts based on Granger causality. The paper further dwells into developing a predictive model for funding rates using best-fitted GARCH models. Implications of the results are presented, and funding rates as a predictive tool for gauging the market trend is discussed.
    Date: 2019–11
  6. By: Anastasios Demertzidis (University of Kassel)
    Abstract: The focus of this paper lies in the study of the intraday distribution of the number of transactions and transaction volume (absolute and mean per transaction) in the interbank credit market e-MID in different market states around the events of the financial crisis of 2007. The results show that the distributions of the number and of the volume of transactions can be characterized as U-shaped and the distribution of the mean per transaction as three-peaked. However, there are important differences when it comes to the comparison of the different market states and the differentiation between sell and buy transactions. Moreover, this study detects stylized facts about the market regarding the number of trades and the volume during the day. Sell transactions are higher in each market state. This highlights the fact that this market is used widely to deposit excessive liquidity in all intervals during the day. Furthermore, differences within these variables during different market states can be observe, which highlights the importance of this analysis. This study can strengthen our understanding of the interbank credit market as it is important for policy makers and the daily trading strategies of banks. Additionally, implications can be seen as the basis for further empirical and econometric research.
    Keywords: Interbank credit market, e-MID, intraday frequency, financial crisis
    JEL: C46 G01 G12 G15 Y10
    Date: 2019
  7. By: Prats Albentosa, María Asuncíon; Sandoval, Beatriz
    Abstract: This paper analyses the relationship between stock market capitalization and real GDP in ten Central and Eastern European countries (CEECs) that joined the European Union in 2004 and 2007, with the objective of determining if the financial markets have played a role as a driver of the economic development in these countries or vice versa. The methodology is based on the application of three different measures of causality between the relevant variables, in order to determine the existence and the direction of causality. Using a cointegrated Vector Autoregressive model (VAR), the authors study the relationship between the relevant variables through the following tests: Granger causality test, Toda-Yamamoto approach and Frequency Domain approach. The results obtained suggest evidence of the existence of this relationship, in both directions, in a significant number of this group of countries, and especially in those there is a long-term relationship.
    Keywords: stock market development,economic growth,Granger causality,Toda-Yamamoto,Frequency Domain
    JEL: C32 F43 G15
    Date: 2019
  8. By: Saculsan, Phoebe; Kanamura, Takashi
    Abstract: This paper examines the risk and return profiles of energy companies with renewable energy (RE) investment in developing countries taking the Philippines as our country case study. First, we analyze the impact of the global RE project specific risk and country risk on RE projects using a simple capital asset pricing model (CAPM) by benchmarking stock returns of these companies to either the global S&P (S&PGCE) index or to the local Philippine Stocks Exchange (PSE) index. Our findings show that on short- and mid- to long term investment interval, a “pure” RE company, the Energy Development Corporation (EDC), is affected by both these risks examined, while those with partial investment in renewables are affected only on the short-term. Next, we calculated these companies’ abnormal returns by using the Jensen’s alpha. Results show that EDC's alpha values are positive on all short- and medium-to-long term investments and on both indices, suggesting that Philippine RE companies are possibly underestimated on both the global RE market and the Philippine stock market. Lastly, we examined the latest Feed-in Tariff (FIT) level by using the beta results of EDC and the FIT structure of solar PV. Results show that the FIT rate generates profit to both the global and local RE companies’ risk and returns from the investors’ perspective, but is higher than the desired FIT rate from the policymakers’ perspective. This paper aids in investment decision-making by showing that differences in investment timeframes and RE shares could impact investment outcomes in developing countries.
    Keywords: renewable energy investment; capital asset pricing model (CAPM); developing countries; Philippines
    JEL: G12 G15 Q20
    Date: 2019–12

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