# Research articles for the 2019-11-12

'Explosions' of Corn Futures Prices
Salov, Valerii
SSRN
The CME Globex Corn futures Time and Sales data, during the United States Department of Agriculture, USDA, news, are studied. The price fluctuations of high frequency and magnitude resemble explosions caused by chemical or nuclear branched chain reactions. The structure of the jumps and mechanisms of its dynamics are analyzed. Suggested equations satisfactory describe the volume rates. There is a relationship between the maximum profit strategy and cumulative volume.

A Mixed Bond and Equity Fund Model for the Valuation of Segregated Fund Policies
SSRN
Segregated fund and variable annuity policies are typically issued on mutual funds invested in both fixed income and equity asset classes. However, due to the lack of specialized models to represent the dynamics of fixed income fund returns, the literature has primarily focused on studying long-term investment guarantees on single-asset equity funds. This article develops a mixed bond and equity fund model in which the fund return is linked to movements of the yield curve. Theoretical motivation for our proposed specification is provided through an analogy with a portfolio of rolling horizon bonds. Moreover, basis risk between the portfolio return and its risk drivers is naturally incorporated into our framework. Numerical results show that the fit of our model to segregated fund data is adequate. Finally, the valuation of segregated fund policies is illustrated and it is found that the interest rate environment can have a substantial impact on guarantee costs.

An IPO Pitfall: Patent Lawsuits
SSRN
I document a previously unexplored substantial cost of an initial public offering (IPO): patent lawsuits. I find that firms become targets of excessive patent lawsuits shortly before IPO completions, and the litigation intensity persists after firms become public. However, firms that withdraw their IPO filings do not experience an increase after the withdrawal date. Unlike IPOs, seasoned equity offerings (SEO) do not yield an increase in lawsuits. Overall, these results show that going public makes firms vulnerable to costly lawsuits. Moreover, the percentage of IPO firms affected from patent lawsuits has been perilously soaring in the last two decades.

An alternative quality of life ranking on the basis of remittances
Dóra Gréta Petróczy
arXiv

Remittances mean an important connection between people working abroad and their home countries. This paper considers these transfers as a measure of preferences revealed by the workers, underlying a ranking of countries around the world. We use the World Bank bilateral remittances data of international salaries and interpersonal transfers between 2010 and 2015 to compare European countries. The suggested least squares method implies that the ranking is invariant to country sizes and satisfies the axiom of bridge country independence. Our ranking reveals a crucial aspect of quality of life and may become an alternative to various composite indices.

An analysis of Uniswap markets
Guillermo Angeris,Hsien-Tang Kao,Rei Chiang,Charlie Noyes,Tarun Chitra
arXiv

Uniswap---and other constant product markets---appear to work well in practice despite their simplicity. In this paper, we give a simple formal analysis of constant product markets and their generalizations, showing that, under some common conditions, these markets must closely track the reference market price. We also show that Uniswap satisfies many other desirable properties and numerically demonstrate, via a large-scale agent-based simulation, that Uniswap is stable under a wide range of market conditions.

Analytical solution of $k$th price auction
Martin Mihelich,Yan Shu
arXiv

We provide an exact analytical solution of the Nash equilibrium for the $k$th price auction by using inverse of distribution functions. As applications, we identify the unique symmetric equilibrium where the valuations have polynomial distribution, fat tail distribution and exponential distributions.

Branching Particle Pricers with Heston Examples
Michael A. Kouritzin,Anne MacKay
arXiv

The use of sequential Monte Carlo within simulation for path-dependent option pricing is proposed and evaluated. Recently, it was shown that explicit solutions and importance sampling are valuable for efficient simulation of spot price and volatility, especially for purposes of path-dependent option pricing. The resulting simulation algorithm is an analog to the weighted particle filtering algorithm that might be improved by resampling or branching. Indeed, some branching algorithms are shown herein to improve pricing performance substantially while some resampling algorithms are shown to be less suitable in certain cases. A historical property is given and explained as the distinguishing feature between the sequential Monte Carlo algorithms that work on path-dependent option pricing and those that do not. In particular, it is recommended to use the so-called effective particle branching algorithm within importance-sampling Monte Carlo methods for path-dependent option pricing. All recommendations are based upon numeric comparison of option pricing problems in the Heston model.

Calibrating Gompertz in Reverse: Mortality-adjusted (Biological) Ages around the World
Milevsky, Moshe A.
SSRN
This paper develops a statistical and methodological framework for inverting the Gompertz-Makeham (GM) law of mortality for heterogenous populations in a manner consistent with a compensation law of mortality (CLaM), to formally define a global mortality-adjusted (biological) age. It implements and calibrates this framework using rates from the Human Mortality Database (HMD) to illustrate its salience and applicability. Among other things, this paper demonstrates that when properly benchmarked, the global mortality-adjusted (biological) age of a 55-year-old Swedish male is 48, whereas a 55-year-old Russian male is closer in age to 67. The motivation for this (new) framework for presenting age and relative aging is that this metric could be used for pension and retirement policy. In a world of growing mortality heterogeneity and the need for salient longevity metrics beyond simple life expectancy, â€œbiological ageâ€ might help capture the publicâ€™s attention and induce them to take action, for example to work longer and retire later. Perhaps a mortality-adjusted (biological) age could even be used to determine pension eligibility.

Sun, Guofeng
SSRN
Banks' shadow, or money creation by banks beyond traditional loans, plays an important role in China's money-creation process, posing a number of challenges to monetary policy operations and financial risk management. This paper analyzes the money-creation mechanisms of China's shadow banking sector in detail, provides accurate measurements, investigates its effects on financial risk, and surveys recent regulation. To strengthen supervision, China's regulators should closely track the evolution of various shadow banking channels, both on- and off-balance sheet. Specific macroprudential regulation tools, such as asset reserves and risk reserves, should be applied separately to banks' shadow and traditional shadow banking.

Climate Change and the Financial System
Monasterolo, Irene
SSRN
There is growing awareness of the fact that the financial system can play a major role in achieving the global climate and sustainability targets by driving new green investments. However, financial actors are not pricing yet climate risks and opportunities in their portfoliosâ€™ risk management strategies, thus exposing investors, the economy and society to new sources of financial instability from carbon stranded assets. In this article, we present the characteristics of climate financial risks, we discuss why traditional approached donâ€™t allow to integrate such risks in climate scenarios and why it matters for climate and financial policies' assessment. Then, we discuss a growing stream of research in climate finance risk metrics and methods (e.g. Climate Value at Risk, Climate Spread, Climate Stress-test) to assess investorsâ€™ exposure to forward-looking climate risks, price such risks in financial contracts and investorsâ€™ portfolios, and evaluate the largest losses that could lead to financial instability.

College Costs, Household Savings, and Stock Market Participation
Vasilenko, Alexey
SSRN
This paper studies the effect of changes in expected college costs on household savings, asset allocation, and stock market participation. Using household-level data for households with children, I first find that a $1,000 increase in in-state college tuition leads to a 1.7% higher probability of stock market participation and larger savings but does not affect the share of risky assets. After that, I exploit the introduction of a financial aid program for students from military families in 2009 and show that this program had a negative effect on the probability of stock market participation, the share of risky assets, and savings. Finally, I investigate the relation between in-state college tuition and investment in 529 college savings plans using portfolio-level data and demonstrate that in-state college tuition is positively associated with flows to these plans Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration Angelica Gianfreda,Francesco Ravazzolo,Luca Rossini arXiv This paper compares alternative univariate versus multivariate models, frequentist versus Bayesian autoregressive and vector autoregressive specifications, for hourly day-ahead electricity prices, both with and without renewable energy sources. The accuracy of point and density forecasts are inspected in four main European markets (Germany, Denmark, Italy and Spain) characterized by different levels of renewable energy power generation. Our results show that the Bayesian VAR specifications with exogenous variables dominate other multivariate and univariate specifications, in terms of both point and density forecasting. Corporate Finance and Sustainability: A Teaching Note Schoenmaker, Dirk,Schramade, Willem SSRN In the transition to a sustainable economy, companies are increasingly adopting the goal of long-term value creation, which integrates financial, social and environmental value. That raises the fundamental question in corporate finance about the objective of the corporation. The current objective is maximising profit, which boils down to maximising shareholder value. But the shareholder model is holding companies back from sustainable business practices. An enhanced shareholder view recognises that it is instrumental to treat the other stakeholders well in order to preserve long-term shareholder value.An alternative view is to broaden the objective of the corporate to optimising the integrated value, which combines the financial, social and environmental value. In that way, the interests of stakeholders are ranked equally. Such a move to the stakeholder model requires new rules for corporate governance and decision-making on corporate investments to deal with the various interests of the stakeholders. Creating Intangible Capital DÃ¶ttling, Robin,Ladika, Tomislav,Perotti, Enrico C. SSRN We propose a new framework for intangible capital creation by the joint investment of firm resources and skilled human capital, subject to a double moral hazard. First, key employees are free to leave with some intangibles, so firms must reward them in deferred form, creating uninsurable risk. Thus high-intangible firms require less upfront funding and have larger free cash flow, yet still follow a prudent financial policy to insure unvested claims. Second, firm spending on intangible investment is easily diverted. Promising large payoffs to human capital exacerbates moral hazard, as diversion prompts skilled employees to depart and forfeit unvested claims. Balancing incentives requires firms to have more cash in good states (to reduce the cost of compensation), and more inside equity to avoid diversion risk. The model can explain several puzzling trends and generates new implications for measuring investment, firm value, and returns to labor. Credit Risk Assessment by Ordered Fuzzy Numbers WÃ³jcicka-WÃ³jtowicz, Aleksandra,Lyczkowska-Hanckowiak, Anna,Piasecki, Krzysztof Maciej SSRN Credit risk assessment usually is a complex process which consists of many successive steps and numerous criteria. Selection of good customers and rejection of potentially bad ones is vital as it directly and significantly affects the quality of bankâ€™s credit portfolio. Also, ordering the decision alternatives is an important part of the whole decision-making analysis which takes place before making a final decision. The importance and complexity of the problem on one hand call for strictly analytical methods, however, on the other, also for a method which enables intuitive decision-making, imprecision and inaccurate linguistic ranks based on expertsâ€™ personal experience. The paper presents the utility of Simple Additive Weighting (SAW) method (which belongs to the multicriteria decision-making approach) in case of a credit risk assessment. The presented illustrative example bases on expertsâ€™ knowledge and their perception and evaluation of various linguistic, frequently imprecise criteria. Therefore, the order scale is described by ordered fuzzy numbers (OFN). Detecting Insider Information in Retail Trading Chung, Ling Tak Douglas SSRN Since insider transactions are implemented through personal accounts, the NYSE classifies these trades as retail transactions. Indeed, imbalances of retail trading and insider trading move in lockstep and predict stock returns in the cross-section. A high-minus-low strategy in retail trading imbalances yields an average weekly alpha of 0.15%, of which at least half can be attributed to insider trading. Further, retail trading contains no incremental information about future stock returns for stocks with insider trading and the return predictability of insider trading is stronger among small firms and amid market turbulence. Deviations from Zipf's law contain more information than Zipf's law itself Giordano De Marzo,Andrea Gabrielli,Andrea Zaccaria,Luciano Pietronero arXiv Rank size plots of very different systems are usually fitted with Zipf's law, however, one often observes strong deviations at large sizes. We show that these deviations contain essential and general information on the evolution and the intrinsic cutoffs of the system. In particular, if the first ranks show deviations from Zipf's law, the empirical maximum represents the intrinsic upper cutoff of the physical system. Moreover, pure Zipf's law is always present whenever the underlying power-law size distribution is undersampled. Estimating and Forecasting Volatility Using Arima Model: A Study on Nse, India. Wadhawan, Dikshita,Singh, Harjit SSRN Volatility had been used as an indirect means for predicting risk accompanied with the asset. Volatility explains the variations in returns. Forecasting volatility had been a stimulating problem in the financial systems. The study examined the different volatility estimators and determined the efficient volatility estimator. The study described the accuracy of forecasting technique with respect to various volatility estimators. The methodology of volatility estimation includes Close, Garman-Klass, Parkinson, Roger-Satchell and Yang-Zhang methods and forecasting is done through ARIMA technique. The study evaluated the efficiency and bias of various volatility estimators. The comparative analyses based on various error measuring parameters like ME, RMSE, MAE, MPE, MAPE, MASE, ACF1 gave the accuracy of forecasting with the best volatility estimator. Out of five volatility estimators analysed over a period of 10 years and critically examined for forecasting volatility, the research obtained Parkinson estimator as the most efficient volatility estimator. Based on various error measuring parameters, Parkinson estimator had been examined as more accurate estimator than any other estimator based on RMSE, MPE and MASE in forecasting through ARIMA Technique. The study suggests that the forecasted values had been accurate based on the values of MAE and RMSE. This research was conducted in order to meet out the demand of knowing the efficient volatility estimator for forecasting volatility with high accuracy by the traders, option practitioners and various players of stock market. Fluctuations in Economic Uncertainty and Transmission of Monetary Policy Shocks: Evidence Using Daily Surveys from Brazil Burjack, Rafael,Qu, Ritong,Timmermann, Allan SSRN We use a unique Brazilian dataset on daily survey expectations to obtain direct measures of shocks to central bank target rates and changes in economic uncertainty. Using these measures, we gauge the effect of monetary policy shocks on economic uncertainty, term premia, inflation expectations, and bond yields in Brazil. We find strong evidence that inflation uncertainty is key to transmitting monetary policy shocks to the yield curve via time-varying term premia. Finally, Fed announcements have sizeable spillover effects on the Brazilian bond market, as positive shocks to US yields significantly raise term premia in Brazil through elevated exchange rate risk. HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction Raehyun Kim,Chan Ho So,Minbyul Jeong,Sanghoon Lee,Jinkyu Kim,Jaewoo Kang arXiv Many researchers both in academia and industry have long been interested in the stock market. Numerous approaches were developed to accurately predict future trends in stock prices. Recently, there has been a growing interest in utilizing graph-structured data in computer science research communities. Methods that use relational data for stock market prediction have been recently proposed, but they are still in their infancy. First, the quality of collected information from different types of relations can vary considerably. No existing work has focused on the effect of using different types of relations on stock market prediction or finding an effective way to selectively aggregate information on different relation types. Furthermore, existing works have focused on only individual stock prediction which is similar to the node classification task. To address this, we propose a hierarchical attention network for stock prediction (HATS) which uses relational data for stock market prediction. Our HATS method selectively aggregates information on different relation types and adds the information to the representations of each company. Specifically, node representations are initialized with features extracted from a feature extraction module. HATS is used as a relational modeling module with initialized node representations. Then, node representations with the added information are fed into a task-specific layer. Our method is used for predicting not only individual stock prices but also market index movements, which is similar to the graph classification task. The experimental results show that performance can change depending on the relational data used. HATS which can automatically select information outperformed all the existing methods. Hedging Option Greeks: Risk Management Tool for Portfolio of Futures & Options Wadhawan, Dikshita,Singh, Harjit SSRN Options are financial derivatives which are used as risk management tools for hedging the portfolios. The options traders can play safely in the volatile markets with the help of knowledge of the Greeks associated with the options. This study is focused at providing the knowledge of the Greeks and their implementation as risk management tools so as to enhance gains or avoid losses. Delta, Vega and Theta of the options as well as the other position. Greeks are associated with any option strategy and they equally impact the portfolio. The knowledge of the impact of Greeks on different strategies will lead to determine how much risk and the potential reward is associated with the portfolio. The study will focus on getting instrument rated with options trading perspective, in order to make investor handle any strategy scenario and hedge the risk so as to gain good rewards. This will also guide the investor to determine the risk-reward ratio, prior to entry in the trade. Options trading can be taken to the next level with the help of understanding of Greeks and their Hedging techniques. This knowledge will enhance the existing knowledge in context to the options hedging and will lead to the benefits in trading if Delta-Gamma neutralised strategy or Delta-Vega neutralised strategy will be employed along with the best market movement suited option strategy. Index Funds and the Future of Corporate Governance: Presentation Slides Bebchuk, Lucian A.,Hirst, Scott SSRN The presentation slides in this document provide an overview of our study Index Funds and the Future of Corporate Governance: Theory, Evidence, and Policy, which is forthcoming in the Columbia Law Review in December 2019. The slides build on and update our presentations at the 2019 ECGI Annual Meeting in Barcelona in which our study was awarded the ECGIâ€™s Cleary Gottlieb Steen Hamilton Prize.The slides begin by describing the agency-costs theory of index fund incentives that we put forward. Our agency-costs analysis shows that index fund managers have strong incentives to (i) underinvest in stewardship and (ii) defer excessively to the preferences and positions of corporate managers.The slides then present a summary of our empirical findings regarding the range of stewardship activities that index funds do and do not undertake. We discuss four dimensions of the Big Threeâ€™s stewardship activities: (1) The limited personnel time they devote to stewardship regarding most of their portfolio companies; (2) The small minority of portfolio companies with which they have any private communications; (3) Their focus on divergences from governance principles and their limited attention to other issues that could be significant for their investors; and (4) Their pro-management voting patterns. The slides also present a summary of our empirical evidence regarding five ways in which the Big Three may fail to undertake adequate stewardship:(1) The limited attention they pay to financial underperformance;(2) Their lack of involvement in the selection of directors and lack of attention to important director characteristics; (3) Their failure to take actions that would bring about governance changes that are desirable according to their own governance principles; (4) Their decision to stay on the sidelines regarding corporate governance reforms; and (5) Their avoidance of involvement in consequential securities litigation. The slides explain that this body of evidence is, on the whole, consistent with the incentive problems that our agency-costs framework identifies. Finally, the slides conclude by discussing the policy implications of the theory and evidence we put forward. Our study is part of a larger project on the incentives of investment managers that also includes The Agency Problems of Institutional Investors (with Alma Cohen) and The Specter of the Giant Three. Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach Yu Zheng,Bowei Chen,Timothy M. Hospedales,Yongxin Yang arXiv Partial (replication) index tracking is a popular passive investment strategy. It aims to replicate the performance of a given index by constructing a tracking portfolio which contains some constituents of the index. The tracking error optimisation is quadratic and NP-hard when taking the$\ell_0\$ constraint into account so it is usually solved by heuristic methods such as evolutionary algorithms. This paper introduces a simple, efficient and scalable connectionist model as an alternative. We propose a novel reparametrisation method and then solve the optimisation problem with stochastic neural networks. The proposed approach is examined with S\&P 500 index data for more than 10 years and compared with widely used index tracking approaches such as forward and backward selection and the largest market capitalisation methods. The empirical results show our model achieves excellent performance. Compared with the benchmarked models, our model has the lowest tracking error, across a range of portfolio sizes. Meanwhile it offers comparable performance to the others on secondary criteria such as volatility, Sharpe ratio and maximum drawdown.

Interest Rates and Insurance Company Investment Behavior
Ozdagli, Ali K.,Wang, Zixuan (Kevin)
SSRN
Life insurance companies, the largest institutional holders of corporate bonds, tilt their portfolios towards higher-yield bonds when interest rates decline. This tilt seems to be primarily driven by an increase in duration rather than credit risk and insurers do not seem to increase the credit risk of their bonds as interest rates decline. Moreover, the duration gap between their assets and liabilities deviates from zero for extended periods of time both in negative and positive directions. These patterns cannot be explained by incentives to reach for yield. We propose a new model of duration-matching under adjustment costs that conforms with these patterns and test other implications of this model.

Laplace versus the Normal Distribution for Daily Stock Market Returns
Harckbart, Gustavo
SSRN
Daily stock market return distributions seem to have tails that are much fatter than Normal Distribution models. This paper examines the possibility of the Laplace Distribution as a better alternative for modeling daily stock returns. Visual inspection of Q-Q plots seem to confirm the Laplace Distribution better fit to the data. The Laplace Distribution also managed to outperform the Normal Distribution in the K-S statistical tests, while being rejected by A-D tests. Although it seems like an improvement on the Normal hypothesis, the Laplace Distribution remains far from a perfect fit for real world stock market daily returns.

Libor Benchmark Reform: An Overview of Libor Changes and Its Impact on Yield Curves, Pricing and Risk
Burgess, Nicholas
SSRN
Libor is arguably the worlds most important number, with more than USD 200 trillion of derivatives, loans, securities and mortgages referencing this rate in the US markets alone. The Libor benchmark rate is being replaced with alternative reference rates (ARRs) and there is no guarantee the rate will continue to be quoted beyond 2021.In this paper Libor benchmark rate reform is discussed in detail and we assess the impact this has on yield curve construction, interest rate pricing and risk. We highlight why Libor is important, review its history and how it has evolved, which leads to a discussion as to what is wrong with Libor benchmarks. We outline market terminology with regards to both interest rates and yield curve construction, before proceeding to assess on the impact of Libor reform, reviewing the new benchmarks, fall-back rates and yield curve changes.We review yield curve calibration and in doing so provide many charts and Excel workbook illustrations to demonstrate new features of ARR yield curves. We explain how to both bootstrap and globally calibrate curves to imply forward rates & discount factors. Moreover, we outline the interpolation, optimization and solving process, showing how to calibrate curves in such a way to capture the necessary risk metrics required to compute analytical risk and rebuild curves for ultra-fast performance.It is hoped this paper will serve as a useful Libor benchmark rate reform and yield curve primer.

Litigation Risk and the Independent Director Labor Market
Donelson, Dain C.,Tori, Elizabeth,Yust, Christopher G.
SSRN
After decades of declining litigation risk, independent directors of public companies are viewed as effectively immune to personal litigation costs. However, the unexpected In re Investors Bancorp decision by the Delaware Supreme Court in 2017 lowered the liability threshold only for directors in derivative litigation over their own equity grants. The market, firms and directors all reacted to this rare increase in director-only litigation risk. First, Delaware firms experienced significant negative short-window returns, concentrated in firms with high R&D spending and high return volatility (higher risk firms), where equity compensation is most important. These results are consistent with investor concerns about attracting and/or retaining qualified directors. Further, higher risk Delaware firms added more qualified directors to the compensation committee. In contrast, lower risk Delaware firms decreased director equity compensation and their directors decreased insider trading activity. Overall, results are consistent with firms and directors differentially acting to mitigate litigation concerns.

Lock-in in Dynamic Health Insurance Contracts: Evidence from Chile
Atal, Juan Pablo
SSRN
Long-term health insurance contracts have the potential to efficiently insure against reclassification risk, but at the expense of other limitations like provider lock-in. This paper empirically investigates the workings of long-term contracts which are subject to this trade-off. Individuals are shielded against premium increases and coverage denial as long as they stay with their initial contract, but those that become higher risk are subject to premium increases or coverage denials upon switching, potentially leaving them locked-in with their original network of providers. I provide the first empirical evidence on the importance of this phenomenon using administrative panel data from the universe of the private health insurance market in Chile, where competing insurers offer long term contracts. I fit a structural model to yearly plan choices, and am able to jointly estimate evolving preferences for different insurance companies and supply-side underwriting in the form of premium risk-rating and coverage denial. To quantify the welfare effects of lock-in, I compare simulated choices under the current rules to those in a counterfactual scenario with no underwriting. The results show that consumers would be willing to pay around 13 percent more in yearly premiums to avoid lock-in. Finally, I study a counterfactual scenario where long-term contracts are replaced with community-rated spot contracts, and I find only minor general-equilibrium effects on premiums and on the allocation of individuals across insurers. I argue that these small effects are the result of large levels of preference heterogeneity uncorrelated to risk.

Making Good on LSTMs Unfulfilled Promise
Daniel Philps,Artur d'Avila Garcez,Tillman Weyde
arXiv

LSTMs promise much to financial time-series analysis, temporal and cross-sectional inference, but we find they do not deliver in a real-world financial management task. We examine an alternative called Continual Learning (CL), a memory-augmented approach, which can provide transparent explanations; which memory did what and when. This work has implications for many financial applications including to credit, time-varying fairness in decision making and more. We make three important new observations. Firstly, as well as being more explainable, time-series CL approaches outperform LSTM and a simple sliding window learner (feed-forward neural net (FFNN)). Secondly, we show that CL based on a sliding window learner (FFNN) is more effective than CL based on a sequential learner (LSTM). Thirdly, we examine how real-world, time-series noise impacts several similarity approaches used in CL memory addressing. We provide these insights using an approach called Continual Learning Augmentation (CLA) tested on a complex real world problem; emerging market equities investment decision making. CLA provides a test-bed as it can be based on different types of time-series learner, allowing testing of LSTM and sliding window (FFNN) learners side by side. CLA is also used to test several distance approaches used in a memory recall-gate: euclidean distance (ED), dynamic time warping (DTW), auto-encoder (AE) and a novel hybrid approach, warp-AE. We find CLA out-performs simple LSTM and FFNN learners and CLA based on a sliding window (CLA-FFNN) out-performs a LSTM (CLA-LSTM) implementation. While for memory-addressing, ED under-performs DTW and AE but warp-AE shows the best overall performance in a real-world financial task.

Market Power and Cost Efficiency in the African Banking Industry
Asongu, Simplice,Nting, Rexon Tayong,Nnanna, Joseph
SSRN
Purpose - In this study, we test the so-called â€˜Quiet Life Hypothesisâ€™ (QLH) which postulates that banks with market power are less efficient.Design/methodology/approach - We employ instrumental variable Ordinary Least Squares, Fixed Effects, Tobit and Logistic regressions. The empirical evidence is based on a panel of 162 banks consisting of 42 African countries for the period 2001-2011. There is a two-step analytical procedure. First, we estimate Lerner indices and cost efficiency scores. Then, we regress cost efficiency scores on Lerner indices contingent on bank characteristics, market features and the unobserved heterogeneity.Findings - The empirical evidence does not support the QLH because market power is positively associated with cost efficiency. Originality/value - Owing to data availability constraints, this is one of the few studies to test the QLH in African banking.

Multiple yield curve modelling with CBI processes
Claudio Fontana,Alessandro Gnoatto,Guillaume Szulda
arXiv

We develop a modelling framework for multiple yield curves driven by continuous-state branching processes with immigration (CBI processes). Exploiting the self-exciting behavior of CBI jump processes, this approach can reproduce the relevant empirical features of spreads between different interbank rates. We provide a complete analytical framework, including a detailed study of discounted exponential moments of CBI processes. The proposed framework yields explicit valuation formulae for all linear interest rate derivatives as well as semi-closed formulae for nonlinear derivatives via Fourier techniques and quantization. We show that a simple specification of the model can be successfully calibrated to market data.

New Bank and Transportation Stock Indexes from 1793 to 1871, with Comparisons Across Region and Sector, and Against Prior Indexes
McQuarrie, Edward F.
SSRN
Good data on US stock market returns before the advent of the Cowlesâ€™ (1939) dataset in 1871 have been scarce. Small samples and an inability to observe dividends render current estimates suspect. I report total return for a much larger sample of stocks before 1871 than heretofore seen. I observe prices and dividends for all the large banks trading in the markets of Boston, Philadelphia, Baltimore and Virginia, where past research had been confined mostly to banks headquartered in New York. I also observe prices and dividends for all the large turnpikes, canals, and railroads that traded in this period. In both cases I find significant survivorship bias in prior compilations. Banks that went bust or went to the wall in the Panics of 1819 and 1837 have been ignored. Early transportation firms that soared on speculation and then collapsed without ever paying a dividend have also been omitted from the record. Likewise, the dividend cuts and omissions characteristic of hard times have been overlooked. Net of correcting these survivorship biases, in the period before the Civil War I find significantly lower stock market returns than reported in Siegel (2014). I likewise find bonds out-performing stocks during this period. The paper concludes with a discussion of why stocks should have performed poorly, and bonds well, under the distinctive macroeconomic conditions that prevailed before the Civil War.

No Contest: Can Financial Reporting Standards Achieve Comparability in the Face of Financial Engineering
Olson, Erik,Sunder, Shyam
SSRN
By comparing the accounting of 10 transaction methods designed to achieve the same net economic effect for a firm borrowing a given amount of money, we show that these 10 methods, under the current financial reporting standards, have markedly different consequences for a firmâ€™s financial reporting. It follows that agents (e.g., managers, auditors, shareholders, and regulators, etc.) with different interests in financial reports may employ different methods of achieving the same net economic result. Accounting regulators can only specify how preparers should account for a given transaction; regulators have little control over the transactions and instruments firms choose to use. The broad range of financial reporting consequences of a given economic transaction, with regard to financial engineering, points to the difficulty â€" and even virtual impossibility â€" of regulators achieving comparability and consistency among firmsâ€™ financial reports. Despite attempts at regulation and the voluminous GAAP regulations, we reveal that managers remain free to engineer their transactions to publish their firmâ€™s desired (or engineered) financial reports since these accounting methods are largely reported inconsistently with no comparability.

Of Fogs and Bogs: Does Litigation Risk Make Financial Reports Less Readable?
Humphery-Jenner, Mark,Liu, Yun,Nanda, Vikram K.,Silveri, Sabatino,Sun, Minxing
SSRN
We hypothesize that firmsâ€™ attempts to reduce litigation risk can worsen financial report readability: as firms strive for disclosure accuracy and thoroughness, reports increase in size and complexity. Readability deteriorates with management exposure to securities class actions at the current firm or at another firm connected through, for instance, a board interlock or prior employment. Using an SEC rule change as an exogenous shock, we show adjustments to readability can moderate firm litigation risk. Furthermore, firms respond to exogenous shifts in the information environment, e.g., the impact of brokerage mergers on analyst following, by adjusting readability as circumstances warrant.

Operational Process Risk: A Further Discussion
Sommers, Fred
SSRN
This paper highlights a United States of America patent which outlines a method for measuring operational process risk.

Perturbation analysis of sub/super hedging problems
arXiv

We investigate the links between various no-arbitrage conditions and the existence of pricing functionals in general markets, and prove the Fundamental Theorem of Asset Pricing therein. No-arbitrage conditions, either in this abstract setting or in the case of a market consisting of European Call options, give rise to duality properties of infinite-dimensional sub- and super-hedging problems. With a view towards applications, we show how duality is preserved when reducing these problems over finite-dimensional bases. We finally perform a rigorous perturbation analysis of those linear programming problems, and highlight numerically the influence of smile extrapolation on the bounds of exotic options.

Policy Uncertainty and Bank Mortgage Credit
Kara, Gazi,Yook, Youngsuk
SSRN
We show that banks reduce the supply of jumbo mortgage loans when policy uncertainty increases, as measured by the timing of US gubernatorial elections in banks' headquarter states. We use high-frequency, geographically granular loan-level data to address an identification problem arising from the changing demand for loans: (1) The data allow for a difference-in-difference specification and for state/time (quarter) fixed effects; (2) we observe banks reduce lending not just in their home states but also outside their home states when their home states hold elections; (3) we observe important cross-sectional differences in the way banks with different characteristics respond to policy uncertainty. Overall, the findings suggest that policy uncertainty has a real effect on residential housing markets through banks' credit supply decisions and that it can spill over across states through lending by banks serving multiple states.

Political News and Stock Prices: Evidence from Trumpâ€™s Trade War
Fendel, Ralf,Burggraf, Tobias,Huynh, Toan Luu Duc
SSRN
This study investigates the impact of political news on stock price movements. Analyzing more than 3,200 tweets from US President Donald Trumpâ€™s Twitter account, we find that tweets related to the US-China trade war negatively predict S&P 500 returns and positively predict VIX. Granger causality estimates indicate that the causal relationship is one-directional â€" from Trump tweets to returns and VIX. Finally, the results vary across industries depending on their degree of trade intensity with China.

Stochastic Algorithmic Differentiation of (Expectations of) Discontinuous Functions (Indicator Functions)
Christian P. Fries
arXiv

In this paper, we present a method for the accurate estimation of the derivative (aka.~sensitivity) of expectations of functions involving an indicator function by combining a stochastic algorithmic differentiation and a regression.

The method is an improvement of the approach presented in [Risk Magazine April 2018].

The finite difference approximation of a partial derivative of a Monte-Carlo integral of a discontinuous function is known to exhibit a high Monte-Carlo error. The issue is evident since the Monte-Carlo approximation of a discontinuous function is just a finite sum of discontinuous functions and as such, not even differentiable.

The algorithmic differentiation of a discontinuous function is problematic. A natural approach is to replace the discontinuity by continuous functions. This is equivalent to replacing a path-wise automatic differentiation by a (local) finite difference approximation.

We present an improvement (in terms of variance reduction) by decoupling the integration of the Dirac delta and the remaining conditional expectation and estimating the two parts by separate regressions. For the algorithmic differentiation, we derive an operator that can be injected seamlessly - with minimal code changes - into the algorithm resulting in the exact result.

Stock Market Development: Evidence from Market Capitalization Trends
Bonga, Wellington Garikai,Sithole, Rodrick
SSRN
In this paper stock market development as proxied by market capitalisation is examined. The study period is January 2010 to May 2019. The data frequency is monthly. The paper concentrates on the Zimbabwe Stock Market, but briefly walks through Stock Markets in Africa. Examining stock market development is critical, as evidenced by growing number of debates on the dual link of economic growth and stock market development. The study applied the ARIMA model to examine the predictability of stock market development. Using the selection criteria for forecasting, two models have been found to be efficient, ARIMA (7, 1, 2) and ARIMA (12, 1, 2). Both models indicated the significance of past values of market capitalisation to determine current and future values. This implies that a previous level of stock market development determines the future levels of development. Forecasted values indicated a positive fluctuating growth in the near future. The study recommends policies that should aim at significantly raising the levels of stock market development to trigger economic development. Stock market development should not only be noticed in rise in market capitalisation, liquidity or index performance, but also in the quality of services rendered in the stock market.

The "power" dimension in a process of exchange
Alberto Banterle
arXiv

The field of study of this paper is the analysis of the exchange between two subjects. Circumscribed to the micro dimension, it is however expanded with respect to standard economic theory by introducing both the dimension of power and the motivation to exchange. The basic reference is made by the reflections of those economists, preeminently John Kenneth Galbraith, who criticize the removal from the neoclassical economy of the "power" dimension. We have also referred to the criticism that Galbraith, among others, makes to the assumption of neoclassical economists that the "motivation" in exchanges is solely linked to the reward, to the money obtained in the exchange. We have got around the problem of having a large number of types of power and also a large number of forms of motivation by directly taking into account the effects on the welfare of each subject, regardless of the means with which they are achieved: that is, referring to everything that happens in the negotiation process to the potential or real variations of the welfare function induced in each subject due to the exercise of the specific form of power, on a case by case basis, and of the intensity of the motivation to perform the exchange. In the construction of a mathematical model we paid great attention to its usability in field testing.

The Role of Discount Rates in Investment and Employment Growth
MÃ¸ller, Stig Vinther,Priestley, Richard
SSRN
We study the impact from time-varying risk premiums on real investment spending and employment. We use a new proxy for discount rate fluctuations and show for the first time that both short-run and long-run implications of dynamic labour market and investment models are confirmed in the data. In the short run, a decline in the discount rate implies both higher investment and employment growth, while the opposite pattern emerges in the long run, as predicted by theory. The effect from discount rates on investment and employment is strong both statistically and economically, suggesting that time-varying discount rates can be a key source of business cycle variations.

The Syndicate Structure of Securitized Corporate Loans
Guo, Zhengfeng,Zhang, Shage
SSRN
Securitized loans have lower lead bank shares but larger shares held by non-CLO institutional investors than non-securitized loans. The result can largely be explained by their degree of information asymmetry and credit risk. We find that lead banks increase their holdings after a non-securitized loan becomes securitized, but they do not reduce financial exposure to securitized facilities during the boom of the CLO market. Furthermore, we find that securitized loans do not perform differently from similar non-securitized loans. We conclude that differences in syndicate structure are likely shaped by participantsâ€™ investment preference rather than a manifestation of adverse selection.

Time-Varying Beta in Functional Factor Models: Evidence from China
HorvÃ¡th, Lajos ,Li, Bo,Li, Hemei,Liu, Zhenya
SSRN
This paper introduces the functional factor models with the time-varying beta. The advantage of doing this is that functional factor models give the time-varying beta intuitively, from which we find that in the Chinese A-share market, with both the Fama-French 3-factor model and the 5-factor model, the market factor has a positive e ect on excess returns of A shares all the time, the size factor and the value factor have a positive impact on excess returns of A shares in a stable period, the investment factor had a positive e ect after the non-tradable share reform and has changed to a negative impact since the 2008 financial crisis, while the profitability factor always has a negative impact on A shares.

Toxic Expectations: Analyst Forecasts and Firm Pollution
Tirodkar, Mihir
SSRN
This research examines the association between analyst forecast bias and firm pollution from a behavioural perspective. Using a sample of firms in the Toxic Release Inventory (TRI) from 1987-2017, I find evidence of a systematic pessimism in analyst forecasts for the upcoming annual earnings of polluter firms. Pessimistic forecasts are correlated with total firm pollution, but not with pollution scaled by firm output. Of the included chemical subcategories, standard TRI chemicals are the most strongly associated with forecast pessimism. I also test whether individual analysts are persistently biased. Results indicate that both relatively optimistic and pessimistic analysts are persistently biased against polluting firms; both analyst types become increasingly pessimistic towards polluters as the forecast horizon shortens. Despite evidence of systematic analyst pessimism towards polluters, I find no evidence of abnormal returns generated through positive earnings surprises around earnings announcement dates.

Ultra-Simple Shillerâ€™s CAPE: How One Yearâ€™s Data Can Predict Equity Market Returns Better Than Ten
SSRN
Campbell and Shiller average 10 years of real S&P 500 earnings to construct its Cyclically Adjusted P/E ratio, or CAPE, which they then use to forecast its future 10-year returns. In essence, Campbell and Shiller kill two birds with one large stone - they use the 10-year average to reduce noise and also to obtain a measure of where in the economic cycle we currently are. We start by providing a theoretical foundation for the CAPE methodology, and demonstrate that the standard CAPE methodology does not accurately predict returns when CAPE is very depressed - an additional non-linear term is called for. In addition, we separate the problems of noise reduction and cyclicality, and kill three birds (noise reduction, cyclicality and nonlinearity) with three small stones. First, by eliminating the worst quarter's earnings each year, we reduce the noise in earnings by about 40%. Next, we measure our current position in the economic cycle using the Sales-to-Price ratio. Finally, we use a quadratic term to pick up the nonlinearity in the relationship between earnings yields and future returns, and use robust regression to minimize the impact of outliers.Our method provides significantly better out-of-sample forecasts of the return of the S&P 500 than does CAPE, while using less data and greatly reducing computational effort - there is, for example, no need to obtain data on CPI, or to average past earnings. We also avoid using traditional measures of significance such as t-statistics, and instead evaluate models using the correlation between their out-of-sample predictions of the future returns of the S&P 500 and its actual realized returns. Finally, we estimate the significance level of each predictor's predictions using simulation, freeing us from the tyranny of correcting t-statistics for endogeneity and overlapping observations.

What Do Almost 20 Years of Micro Data and Two Crises Say About the Relationship Between Central Bank and Interbank Market Liquidity? Evidence From Italy
Affinito, Massimiliano
SSRN
This paper studies the mutual interplay between central bank (CB) liquidity provisions and interbank market (IM) liquidity exchanges, exploring whether the relationship changes in the event of IM impairments and massive CB liquidity injections during global and sovereign crises. The analysis uses a data set containing 17 years of monthly bank-by-bank and counterparty-by-counterparty data collated from 1998 to 2015 in Italy. The results show the existence of complementarity. Banks receiving CB liquidity redistribute more to other banks. When CB liquidity increases exponentially during crises, some healthy banks specialise in interbank lending. The complementarity helps to offset euro area fragmentation via domestic interbank relationships and to adjust the collateral and maturity profiles of banks' liquidity.

What Valuation Models Do Analysts Use?
Demirakos, Efthimios,Strong, Norman C.,Walker, Martin
SSRN
This paper adopts a structured positive approach to explaining the valuation practices of financial analysts by studying the valuation methodologies contained in 104 analysts' reports from international investment banks for 26 large U.K.-listed companies drawn from the beverages, electronics, and pharmaceuticals sectors. We provide a descriptive analysis of the use of alternative valuation models focusing on the value-relevant attributes that analysts seek to forecast and the methodologies analysts use to convert the forecasts into estimates of firm value. We postulate and test a number of hypotheses relating to how the valuation practices of analysts vary systematically across industrial sectors. We find that: (1) the use of valuation by comparatives is higher in the beverages sector than in electronics or pharmaceuticals; (2) analysts typically choose either a PE model or an explicit multi-period DCF valuation model as their dominant valuation model; (3) none of the analysts use the price to cash flow as their dominant valuation model; and (4) contrary to our expectations, some analysts who construct explicit multi-period valuation models still adopt a comparative valuation model as their preferred model. We believe the study's findings are important for increasing our understanding of the valuation practices of financial analysts. The study also provides a basis for further research that tests a richer and more detailed set of hypotheses.

Why Does Oil Matter?: Commuting and Aggregate Fluctuations
Ready, Robert C.,Roussanov, Nikolai L.,Zurowska, Ewelina
SSRN
Oil price shocks are known to have a sizable macroeconomic impact, despite a relatively small fraction of total expenditures that is devoted to energy. Using micro data we document a significant effect of oil prices on labor supply and commuting distance, especially among low-skilled workers who face large commuting costs, relative to their wages. In addition, equity returns of firms in less skill-intensive industries are more sensitive to oil price fluctuations. Motivated by this empirical evidence, we employ a two-sector endogenous growth model with an oil-dependent commuting friction to examine the effect of oil shocks on employment, real wages, and growth, as well as equity prices. Negative oil supply shocks followed by oil price increases depress labor supply, especially in the less capital-intensive low-skill sector, where employment is most sensitive to the cost of commuting. As a result, output growth slows down in the medium run as innovation and capital are reallocated towards the less affected high-skill sector, resulting in subsequent rise in the skill premium.

iCurrency?
arXiv

We discuss the idea of a purely algorithmic universal world iCurrency set forth in [Kakushadze and Liew, 2014] (https://ssrn.com/abstract=2542541) and expanded in [Kakushadze and Liew, 2017] (https://ssrn.com/abstract=3059330) in light of recent developments, including Libra. Is Libra a contender to become iCurrency? Among other things, we analyze the Libra proposal, including the stability and volatility aspects, and discuss various issues that must be addressed. For instance, one cannot expect a cryptocurrency such as Libra to trade in a narrow band without a robust monetary policy. The presentation in the main text of the paper is intentionally nontechnical. It is followed by an extensive appendix with a mathematical description of the dynamics of (crypto)currency exchange rates in target zones, mechanisms for keeping the exchange rate from breaching the band, the role of volatility, etc.

Ð¤Ð¸Ð½Ð°Ð½ÑÐ¾Ð²Ð°Ñ ÑÐ¸ÑÑ‚ÐµÐ¼Ð° Ñ†Ð¸Ñ„Ñ€Ð¾Ð²Ð¾Ð¹ ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸ÐºÐ¸: Ð¿Ñ€Ð¾Ð±Ð»ÐµÐ¼Ñ‹ Ñ„Ð¾Ñ€Ð¼Ð¸Ñ€Ð¾Ð²Ð°Ð½Ð¸Ñ (The Financial System of the Digital Economy: Problems of Formation)
Kondratjev, Alexey
SSRN
Russian Abstract: Ð' ÑÑ‚Ð°Ñ‚ÑŒÐµ Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸Ñ€ÑƒÑŽÑ‚ÑÑ Ð¿Ñ€Ð¾Ð±Ð»ÐµÐ¼Ñ‹ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð¸Ð½Ñ„Ñ€Ð°ÑÑ‚Ñ€ÑƒÐºÑ‚ÑƒÑ€Ñ‹ Ñ„Ð¸Ð½Ð°Ð½ÑÐ¾Ð²Ð¾Ð¹ ÑÐ¸ÑÑ‚ÐµÐ¼Ñ‹ Ñ†Ð¸Ñ„Ñ€Ð¾Ð²Ð¾Ð¹ ÑÐºÐ¾Ð½Ð¾Ð¼Ð¸ÐºÐ¸ Ð² Ð Ð¾ÑÑÐ¸Ð¸. ÐŸÑ€ÐµÐ´Ð»Ð°Ð³Ð°ÐµÑ‚ÑÑ Ñ€ÑÐ´ Ð¼ÐµÑ€Ð¾Ð¿Ñ€Ð¸ÑÑ‚Ð¸Ð¹ Ð¿Ð¾ Ñ„Ð¾Ñ€Ð¼Ð¸Ñ€Ð¾Ð²Ð°Ð½Ð¸ÑŽ ÑÑ„Ñ„ÐµÐºÑ‚Ð¸Ð²Ð½Ð¾Ð¹ ÑÐ¸ÑÑ‚ÐµÐ¼Ñ‹ Ð²Ñ‹Ð¿ÑƒÑÐºÐ° Ð¸ Ð¾Ð±Ñ€Ð°Ñ‰ÐµÐ½Ð¸Ñ Ñ†Ð¸Ñ„Ñ€Ð¾Ð²Ñ‹Ñ… Ñ„Ð¸Ð½Ð°Ð½ÑÐ¾Ð²Ñ‹Ñ… Ð°ÐºÑ‚Ð¸Ð²Ð¾Ð², ÑƒÑ‚Ð¸Ð»Ð¸Ñ‚Ð°Ñ€Ð½Ñ‹Ñ… Ñ†Ð¸Ñ„Ñ€Ð¾Ð²Ñ‹Ñ… Ð¿Ñ€Ð°Ð², Ñ†Ð¸Ñ„Ñ€Ð¾Ð²Ð¾Ð¹ Ð²Ð°Ð»ÑŽÑ‚Ñ‹ Ñ†ÐµÐ½Ñ‚Ñ€Ð°Ð»ÑŒÐ½Ð¾Ð³Ð¾ Ð±Ð°Ð½ÐºÐ°.English Abstract: The article analyzes the problems of creating the infrastructure of the financial system of the digital economy in Russia. A number of measures are proposed to form an effective system of issuance and circulation of digital financial assets, utilitarian digital rights, central bank digital currency.

èµ„äº§ç®¡ç†çš„æ³•ç†åŸºç¡€ä¸Žè¿è¡Œæ¨¡å¼ï¼šç¾Žå›½ç»éªŒåŠå¯¹ä¸­å›½çš„å¯ç¤º (The Legal Basis and Operational Models of Asset Management: The US Experiences and Implications for China)
Huang, (Robin) Hui
SSRN
Chinese Abstract: ä¸­æ–‡æ'˜è¦ï¼šã€Šèµ„ç®¡æ„è§ã€‹çš„ä¸Šä½æ³•ä¾æ®äº‰è®®å¾ˆå¤§ï¼Œæœ¬è´¨ä¸Šæ˜¯å¯¹èµ„äº§ç®¡ç†çš„æ³•ç†åŸºç¡€å'Œè¿è¡Œæ¨¡å¼å­˜åœ¨åˆ†æ­§ï¼Œåœ¨å€Ÿé‰´ç¾Žå›½ç­‰å¢ƒå¤–ç»éªŒæ—¶è¦æ³¨æ„å®žè´¨é‡äºŽå½¢å¼ã€‚ç¾Žå›½çš„æŠ•èµ„å…¬å¸æ˜¯èµ„äº§ç®¡ç†çš„ä¸»è¦è½½ä½"ï¼ŒåŒ…æ‹¬å¤šç§ä¸åŒçš„ç»„ç»‡å½¢å¼ï¼Œè€ŒæŠ•èµ„é¡¾é—®åœ¨æä¾›å'¨è¯¢å»ºè®®ä¹‹å¤–ï¼Œä¹Ÿä¸ºå®¢æˆ·ç®¡ç†èµ„äº§ï¼Œç»å¸¸æ˜¯èµ„äº§ç®¡ç†çš„å®žé™…ä¸»ä½"ã€‚æŠ•èµ„é¡¾é—®æŽ¨åŠ¨æŠ•èµ„å…¬å¸ï¼ˆå…±åŒåŸºé‡'ï¼‰çš„è®¾ç«‹ï¼Œå¹¶è´Ÿè´£èµ„äº§ç®¡ç†ï¼ŒæŽ¥å—æŠ•èµ„å…¬å¸è'£äº‹ä¼šå'Œè‚¡ä¸œå¤§ä¼šçš„ç›'ç£ã€‚ç›¸æ¯"è€Œè¨€ï¼Œæˆ'å›½çš„èµ„äº§ç®¡ç†ä»¥ä¿¡æ‰˜å¥'çº¦åž‹ä¸ºä¸»ï¼Œè¾ƒå°'é‡‡ç"¨å…¬å¸ç­‰å…¶ä»–ç»„ç»‡å½¢å¼ï¼›ç¾Žå›½é‡‡ç"¨â€œæŠ•èµ„è€…â€"æŠ•èµ„å…¬å¸â€"æŠ•èµ„é¡¾é—®â€æž¶æž„ï¼Œè€Œæˆ'å›½æ˜¯â€œæŠ•èµ„è€…â€"ç®¡ç†äººâ€æž¶æž„ï¼›ç¾Žå›½çš„æŠ•èµ„é¡¾é—®ä¸Žæˆ'å›½çš„æŠ•èµ„é¡¾é—®åœ¨åŠŸèƒ½ä¸Šè¿¥å¼‚ï¼Œå› è€Œæˆ'å›½ä¸å®œç…§æ¬ç¾Žå›½ã€ŠæŠ•èµ„é¡¾é—®æ³•ã€‹ï¼›æˆ'å›½èµ„äº§ç®¡ç†åœ¨ç»„ç»‡å½¢å¼ä¸Šåº"å½"å…è®¸å¤šå…ƒï¼Œä½†åœ¨è¡Œä¸ºç›'ç®¡ä¸Šåº"å½"ç»Ÿä¸€ã€‚English Abstract: The Opinion on Asset Management has seen a heated debate on its legal basis, reflecting the differences of views on the underlying legal relationships of asset management and its models of operation. When examining overseas experiences, notably the US, one needs to focus more on substance than form. The main vehicle for carrying on asset management in the US is the investment company, which can take many different organizational forms. Investment advisors do not only provide investment advice, but more importantly, manage assets for their clients. Investment advisors promote the establishment of mutual funds and then provide asset management services under the supervision of the board of directors and shareholders meeting of the investment company. In contract, Chinaâ€™s asset management mainly takes the form of trust, and seldom uses other forms such as companies. While the mutual fund in the US adopts â€˜investor-investment company-investment advisorâ€™ structure, it is structured as â€˜investor-managerâ€™ in China. From a functional perspective, the US-style investment advisor is very different from the investment advisor in China. It is suggested that China should allow asset management to take a diversity of business forms but adopt a consistent standard for regulating functionally similar business activities.