Research articles for the 2020-04-03

Business-Cycle Macroeconomics in an Asset Pricing Financial Economy
Tse, Wai Man
SSRN
The paper introduces a portfolio-based Keynesian dynamic stochastic general disequilibrium model. It is a phase-switching macroeconomic model with three financial instruments of stocks, credits, and debt. It tracks the last 30 years' U.S. monthly financial and economic data even the 2008 Great Recession. Jump credit risks induce cyclical financial and macroeconomic fluctuations. Market risk premium and credit risks show a significant impact of the financial sector on the real economy. To promote financial and economic growth, it found cutting interest rates most effective at peak and trough. Credits should be increased during trough but reduced during peak. Enhancing consumption growth stimulates GDP growth in a recession.

COVID-19 Pandemic and Economic Crisis: The Nigerian Experience and Structural Causes
Ozili, Peterson K
SSRN
We are in the midst of the worst recession since the global financial crisis. The economic downturn in Nigeria was triggered by a combination of declining oil price and spillovers from the COVID-19 outbreak, which not only led to a fall in the demand for oil products but also stopped economic activities from taking place when social distancing policies were enforced. The government responded to the crisis by providing financial assistance to businesses, not to households, that were affected by the outbreak. The monetary authority adopted accommodative monetary policies and offered a targeted 3.5trillion loan support to some sectors. These efforts should have prevented the economic crisis from occurring but it didn’t. Economic agents refused to engage in economic activities for fear of contracting the COVID-19 disease that was spreading very fast at the time. In this paper, I analyse the COVID-19 spillovers to Nigeria and the structural weaknesses in Nigeria’s infrastructure that helped bring on the current economic crisis and discuss prospects for reform.

COVID-19 and the Equity Market. A March 2020 Tale.
Ye, Ziwen,Florescu, Ionut
SSRN
In March 2020 the U.S. equity market is suffering large losses. This is primarily due to COVID-19, which probably also caused a drop in the shale oil price. US market indices are fluctuating this month much more than any time in history. In this short note, we are using two high frequency market measures we developed in our past work to create a market wide indicator we call Number of Detected Anomalies (NoDA). NoDA is a market-wide signal focused on analyzing intraday trading activity in the US equity markets. Although the cause of the current market event is very different from anything we have seen before, the market participants seem to take a typical attitude to unpredictable events, one of expectation and price discovery. In this work we are able to analyze specific public historical events and determine market reaction as measured by the NoDA indicator.

Cash-flow Risk and Industry Response to COVID-19 Outbreak
Sinagl, Petra
SSRN
The COVID-19 outbreak has caused a negative shock to aggregate consumption. The central question addressed in this paper is how US industries react to this negative shock. I show that the long-term cash-flow risk measured using data until 2018 predicted which US industries will perform the worst during the current crisis. Industries with a high cash-flow risk have experienced abnormally low excess returns, high systematic risk and low risk-adjusted returns. This paper contributes to the recognition of cash-flow risk as an important driver of equity risk and returns.

Computation of Option Greeks Under Hybrid Stochastic Volatility Models Via Malliavin Calculus
Yilmaz, Bilgi
SSRN
This study introduces computation of option sensitivities (Greeks) using the Malliavin calculus under the assumption that the underlying asset and interest rate both evolve from a stochastic volatility model and a stochastic interest rate model, respectively. Therefore, it integrates the recent developments in the Malliavin calculus for the computation of Greeks: Delta, Vega, and Rho and it extends the method slightly. The main results show that Malliavin calculus allows a running Monte Carlo (MC) algorithm to present numerical implementations and to illustrate its effectiveness. The main advantage of this method is that once the algorithms are constructed, they can be used for numerous types of option, even if their payoff functions are not differentiable.

Energy Crypto Currencies and Leading US Energy Stock Prices: Are Fibonacci Retracements Profitable?
Gurrib, Ikhlaas
SSRN
The aim of this study is to investigate if Fibonacci retracements levels, as a popular technical analysis indicator, can serve to predict stock prices of leading US energy companies and energy crypto currencies. The methodology centers on the application of Fibonacci retracements as a trading system. Daily stock prices from the top ten constituents of the S&P Composite 1500 Energy Index are sourced, spanning from 21st November 2017 to 17th January 2020. The performance of the Fibonacci’s tool is captured using the Sharpe measure. The model is also benchmarked against the naïve buy-and-hold strategy. We also tested if the use of Fibonacci retracements, coupled with a price crossover strategy results into higher return per unit of risk. Findings support the Fibonacci retracement tool captures the price movements of energy stocks better than energy cryptos. Further, price violations tend occur more during downtrends compared to uptrends, suggesting the Fibonacci tool does not capture price increases during downtrends as well as price decreases during uptrends. Less consecutive retracement breaks occurred as we move from 1 to 3 days prior. While a Fibonacci based strategy resulted in superior returns to a naïve buy and hold model, the Sharpe and Sharpe per trade values were low. Complementing the Fibonacci tool with a price cross strategy did not improve the results significantly, and resulted in fewer or no trades for some constituents.

European Corona Solidarity Bonds
Insalaco, Giuseppe,Schaanning, Eric
SSRN
We propose to fund the collective effort against the COVID-19 pandemic and its economic fallout by issuing European Corona Solidarity Bonds (ECSBs) which are backed by revenues on a new EU-wide universal tax on financial assets, collected at the source.To combat the pandemic, governments need to significantly increase spending. It is in the EU’s shared interest that all governments (are able to) do all that is needed, act promptly and decisively. The required increases in public spending risk compromising the financial stability of indebted countries. This paper attempts to sketch one possible solution how to: • Generate a sufficient amount of funding to fight the economic COVID-19 fallout (500 billion â€" 2 trillion probably),• Quickly (in less than one month),• Without increasing sovereign debt levels (as these may become unsustainable for some heavily affected countries),• Without resorting to debt mutualisation (as a political agreement seems unlikely) • Without using monetary financing,• In a way that ideally could be perceived as “fair”, or at least socially acceptable.We propose that issuance of European Corona Solidarity Bonds (ECSBs), backed by revenues on a universal tax on financial assets may achieve these goals. Initial estimates of our proposal suggest that a 10-year ECSB issuance backed by a 1 basis point annual tax would support a bond issuance of 100 billion euro. Without leading to a significant distortion of markets, the scheme could realistically be scaled up to 1-2 trillion euro and be implemented as a complement to further fiscal, regulatory and monetary measures.

In Search of Gold: Insights From Google Searches on Portfolio Hedging Effectiveness
Prange, Philipp
SSRN
Online investor attention, measured by Google searches, may provide valuable information for the assessment of the co-movement between financial assets. In our empirical analysis, we draw upon an extension of the dynamic conditional correlation model and find that online investor attention is a statistically significant determinant of the time-varying correlations between stocks and gold-, silver-, and crude oil future contracts. Our results, relying on daily data over eleven years, suggest that market participants may enrich asset allocation strategies by means of online investor attention. Taking a practical point of view, we demonstrate that the informational content of Google searches increases the hedging effectiveness of combined portfolios.

Modeling Financial Market Movement with Winning and Losing Streaks: Sticky Extrema Processes
Feng, Runhuan,Jiang, Pingping,Volkmer, Hans
SSRN
Winning streaks appear frequently in all financial markets including equity, commodity, foreign exchange, real estate, etc. Most stochastic process models for financial market data in the current literature focus on stylized facts such as fat-tailedness relative to normality, volatility clustering, mean reversion. However, none of existing financial models captures the pervasive feature of persistent extremes: financial indices frequently report record highs or lows in concentrated periods of time. The lack of persistent extremes in a quantitative model for asset pricing can have grave impact on the valuation and risk management of financial instruments. The new model in this paper enables us to measure and assess the impact of persistent extremes on financial derivatives and to more accurately predict option values. In addition, the model in this paper reveals a paradox that investors who bet on the growth of financial market may be worse off with pervasive winning streaks in the market. This model in this paper describes the phenomenon of market overreaction at the macro level, which complements existing behavior finance literature on this subject that explain market reactions by psychological reasoning and evidence. The paper also explores the possibility of using the model for measuring the tendency of overbought stocks and indices.

Not Coming Home: Trade and Economic Policy Uncertainty in American Supply Chain Networks
Charoenwong, Ben,Han, Miaozhe,Wu, Jing
SSRN
We study the relation between the supply chain network of American public firms and U.S. trade (U.S. TPU), non-trade (U.S. EPU), and foreign economic policy uncertainty (foreign EPU). U.S. TPU leads to trade creation. Rather than inducing production to come “home”, firms on average increase foreign supplier relationships and decrease domestic relationships, primarily driven by firms with more foreign customers. On average, all three sources of policy uncertainty do not appear correlated with firm profitability, but U.S. TPU is associated with lower long-term strategic investments. Meanwhile, foreign-country EPU shocks lead to trade diversion, American firms substitute sourcing from high EPU foreign countries to other foreign countries. Firms for which supply chain disruptions would be more severe and those with more bargaining power respond more to all measures of policy uncertainty. Firms indirectly exposed to foreign policy uncertainty suffer greater wealth loss than the directly exposed ones.

Option Pricing with Economic Regime Shifts
Wang, Tan,Zhao, Yonggan
SSRN
Assuming that one-period logarithmic returns of the underlying asset follow a hidden Markov process, we develop a valuation model for European call options. Unlike existing option pricing models, our pricing mechanism relies on the optimal non exponential-affine stochastic discount factor characterized with economic strength. Monthly S\&P 500 index options for the period, January 2014 to October 2018, are used for model validation. It is found that risk/return profiles under the optimal risk neutral probability measure associated with a non exponential-affine stochastic discount factor are drastically different across the regimes of economic strength. We use both the absolute pricing error and the model-implied volatility criteria to examine model performance. In comparison with alternative models, empirically evidenced unbalanced pricing errors for deeply in-the-money and deeply out-of-the-money options are substantially reduced.

PEREKONOMIAN INDONESIA (Indonesian Economy)
Asnah, Asnah,Sari, Dyana
SSRN
Indonesian Abstract: Jika seseorang mengatakan Indonesia sebagai negara yang berpendapatan rendah, barangkali ia tidak pernah membaca tentang perekonomian Indonesia dan untuk itulah buku ini ditulis, untuk menguraikan perekonomian Indonesia terkini, meski barangkali tidak lengkap, namun dapat memberi gambaran tentang pereknomian Indonesia masa kini. Buku ini belum selesai karena terbatasnya waktu dan padatnya kegiatan penulis. Disadari telah terjadi perubahan kondisi terkait isu Indonesia dicoret sebagai negara berkembang oleh AS, yang akan direvisi pada waktu mendatang. Demikian pula status Indonesia yang telah dikategorikan sebagai Negara Berpendapatan Menengah Atas pada akhir 2019. Demikian cepat perubahan perekonomian Indonesia yang nampaknya diperlukan informasi lebih baru untuk menjadikan sebuah buku yang representatif tentang perekonomian Indonesia pada 2020. Namun buku ini diluncurkan karena kebutuhan mahasiswa akan informasi yang relatif lebih baru dari yang lain, menjadikan keterpaksaan buku ini lebih awal disajikan. Tentunya disadari bahwa buku ini masih jauh dari sempurna, sehingga kritik dan saran diharapkan untuk melengkapi perbaikannya. English Abstract: If someone says that Indonesia is a low-income country, perhaps he has never read about the Indonesian economy and for this reason, this book was written, to describe the current Indonesian economy, although perhaps incomplete, can give an idea of ​​Indonesia's economy today.This book has not been completed because of the limited time and dense activity of the author. It is realized that there have been changes in conditions related to the issue of Indonesia crossed out as a developing country by the US, which will be revised in the future. Likewise, the status of Indonesia which has been categorized as a High Middle-Income Country at the end of 2019. So quickly changes in the Indonesian economy which seems to require more recent information to make a representative book on the Indonesian economy in 2020. But this book was launched because of the student's need for relative information more recent than others, making the compulsion of this book earlier presented.Of course, it is realized that this book is far from perfect, so criticism and suggestions are expected to complement its improvement.

Pension Literacy and Retirement Planning in an Emerging Economy
Adeabah, David
SSRN
This paper links pension literacy to retirement planning in an emerging economy. The results show that the correct knowledge about pension basics and savings rate have a positive effect on employees’ efforts to plan for their retirement. Conversely, employees’ correct knowledge about pension lump sum impair their retirement planning efforts. Enhanced retirement preparedness is associated with the correct knowledge of pension basics and lump sum, pension savings rate and lump sum or pension basics, savings rate and lump sum all together.

The Bank of Japan as a Real Estate Tycoon: Large-Scale REIT Purchases
Hattori, Takahiro,Yoshida, Jiro
SSRN
This is the first study analyzing the Bank of Japan’s purchases of real estate investment trusts (REITs) that started in 2010 as part of enhanced unconventional monetary policy. The Bank purchases REIT shares after observing a significantly negative return over the previous night and during the morning market. The Bank continues purchases daily until the overnight and morning REIT returns become positive. This counter-cyclical behavior contributes to the objective of decreasing risk premia and stimulating spending. Our study sheds light on the unique program of a central bank’s equity purchases.

The Framework of Consensus Equilibria for Mining-Pool Games and Related Stability of Gap Games Behaviors in Blockchain Ecosystems
Yuan, George Xianzhi
SSRN
The goal of this paper is to establish the general framework of consensus equilibria for Mining-Pool Games in Blockchain Ecosystems, and in particular to explain the stable in the sense for the existence of consensus equilibria related to mining gap game’s behaviors by using one new concept called “consensus games (CG)” in Blockchain Ecosystems, here, the Blockchain ecosystem mainly means the economic activities by taking into the account of three types of different factors which are expenses, reward mechanism and mining power for the work on blockschain by applying the key consensus called “Proof of Work” due to Nakamoto in 2008.In order to do so, we first give an outline how the general existence of consensus equilibria for Mining-Pool Games is formulated, and then used to explain the stable for Gap Games for Bitcoin in the sense by the existence of consensus equilibria under the framework of Blockchain consensus, we then establish a general existence result for consensus equilibria of general mining gap games by using the profit functions for miners as the payoffs in game theory. As applications, the general existence results for consensus equilibria of Gap games are established, which not only help us to claim the existence for the general stability for Gap games under the general framework of Blockchain ecosystems, but also allow us to illustrate a number of different phenomenons on the study of mining- pool games with possible impacts due to miners’ gap behaviors with scenarios embedded in Bitcoin economics. Our study on the explanation for the stability of mining gap game for Blockchain ecosystems shows that the concept of consensus equilibria may play a important role for the development of fundamental theory for consensus economics.

The Variance Risk Premium in Equilibrium Models
Bekaert, Geert,Engstrom, Eric,Ermolov, Andrey
SSRN
The equity variance risk premium is the expected compensation earned for selling variance risk in equity markets. The variance risk premium is positive and shows moderate persistence. High variance risk premiums coincide with the left tail of the consumption growth distribution shifting down. These facts, together with a positive, yet moderate, difference between the risk-neutral entropy and variance of the aggregate market return, refute the bulk of the extant consumption-based asset pricing models. We introduce a tractable habit model that does fit the data. In the model, the variance risk premium depends positively (negatively) on "bad" ("good") consumption growth uncertainty.

UNexpected Returns: A Model Free Approach
Wang, Mengchuan
SSRN
This paper studies the partitioning of stocks into groups with distinctive expected returns based on ex-ante firm characteristics, which can be used as comparable groups to compute the abnormal part of returns, that is, UNexpected returns. In order for stock expected returns to be similar within groups and disperse across groups, I introduce a methodology to select characteristics that best distinguish expected returns, and cutoffs points where returns are most sensitive to the underlying characteristics. I show that: 1) the combination of chosen characteristics changes over time; 2) there are significant differences in fund unexpected returns once the time-variation in comparable groups is incorporated; 3) and the resulting portfolios exhibit desirable properties as basis assets.

Who Benefits from Robo-advising? Evidence from Machine Learning
Rossi, Alberto G.,Utkus, Stephen P.
SSRN
We study the effects of a large U.S. hybrid robo-adviser on the portfolios of previously self- directed investors. Across all investors, robo-advising reduces investors’ holdings in money market mutual funds and increases bond holdings. It also reduces idiosyncratic risk by lowering the holdings of individual stocks and US and international active mutual funds and raising exposure to low-cost indexed mutual funds. It further eliminates home bias by significantly increasing international equity and fixed income diversification. Finally â€" over our sample period â€" it increases investors’ overall risk-adjusted performance, mainly by lowering investors’ portfolio risk. We use a machine learning algorithm, known as Boosted Regression Trees (BRT), to explain the cross-sectional variation in the effects of advice on portfolio allocations and performance. Investors who benefit from advice are those with little self-directed investment experience on the platform, those with prior high cash holdings, and those with high trading volume before adopting advice. Individuals invested in high-fee active mutual funds also display significant performance gains. Finally, we study the determinants of investors’ sign-up and attrition. Investors who benefit more from robo-advising are also more likely to sign-up and less likely to quit the service.