nep-fmk New Economics Papers
on Financial Markets
Issue of 2021‒05‒24
five papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses By Sean Cao; Wei Jiang; Junbo L. Wang; Baozhong Yang
  2. Optimal Portfolio with Power Utility of Absolute and Relative Wealth By Andrey Sarantsev
  3. Dynamic Portfolio Allocation in High Dimensions using Sparse Risk Factors By Bruno P. C. Levy; Hedibert F. Lopes
  4. Hedging Goals By Thomas Krabichler; Marcus Wunsch
  5. Investment funds, monetary policy, and the global financial cycle By Kaufmann, Christoph

  1. By: Sean Cao; Wei Jiang; Junbo L. Wang; Baozhong Yang
    Abstract: An AI analyst we build to digest corporate financial information, qualitative disclosure and macroeconomic indicators is able to beat the majority of human analysts in stock price forecasts and generate excess returns compared to following human analyst. In the contest of “man vs machine,” the relative advantage of the AI Analyst is stronger when the firm is complex, and when information is high-dimensional, transparent and voluminous. Human analysts remain competitive when critical information requires institutional knowledge (such as the nature of intangible assets). The edge of the AI over human analysts declines over time when analysts gain access to alternative data and to in-house AI resources. Combining AI’s computational power and the human art of understanding soft information produces the highest potential in generating accurate forecasts. Our paper portraits a future of “machine plus human” (instead of human displacement) in high-skill professions.
    JEL: G11 G12 G14 G31 M41
    Date: 2021–05
  2. By: Andrey Sarantsev
    Abstract: Portfolio managers often evaluate performance relative to benchmark, usually taken to be the Standard & Poor 500 stock index fund. This relative portfolio wealth is defined as the absolute portfolio wealth divided by wealth from investing in the benchmark (including reinvested dividends). The classic Merton problem for portfolio optimization considers absolute portfolio wealth. We combine absolute and relative wealth in our new utility function. We also consider the case of multiple benchmarks. To both absolute and relative wealth, we apply power utility functions, possibly with different exponents. We obtain an explicit solution and compare it to the classic Merton solution. We apply our results to the Capital Asset Pricing Model setting.
    Date: 2021–05
  3. By: Bruno P. C. Levy; Hedibert F. Lopes
    Abstract: We propose a fast and flexible method to scale multivariate return volatility predictions up to high-dimensions using a dynamic risk factor model. Our approach increases parsimony via time-varying sparsity on factor loadings and is able to sequentially learn the use of constant or time-varying parameters and volatilities. We show in a dynamic portfolio allocation problem with 455 stocks from the S&P 500 index that our dynamic risk factor model is able to produce more stable and sparse predictions, achieving not just considerable portfolio performance improvements but also higher utility gains for the mean-variance investor compared to the traditional Wishart benchmark and the passive investment on the market index.
    Date: 2021–05
  4. By: Thomas Krabichler; Marcus Wunsch
    Abstract: Goal-based investing is concerned with reaching a monetary investment goal by a given deadline, which differs from mean-variance optimization in modern portfolio theory. In this article, we expand the close connection between goal-based investing and option hedging that was originally discovered in [Bro99b] by allowing for varying degrees of investor risk aversion using lower partial moments of different orders. Moreover, we show that maximizing the probability of reaching the goal (quantile hedging, cf. [FL99]) and minimizing the expected shortfall (efficient hedging, cf. [FL00]) yield, in fact, the same optimal investment policy. Finally, we develop an innovative approach to goal-based investing using methods of reinforcement learning, demonstrating its flexibility vis-\`a-vis general market dynamics incorporating transaction costs.
    Date: 2021–05
  5. By: Kaufmann, Christoph
    Abstract: This paper studies the role of international investment funds in the transmission of global financial conditions to the euro area using structural Bayesian vector auto regressions. While cross-border banking sector capital flows receded significantly in the aftermath of the global financial crisis, portfolio flows of investors actively searching for yield on financial markets world-wide gained importance during the post-crisis “second phase of global liquidity” (Shin, 2013). The analysis presented in this paper shows that a loosening of US monetary policy leads to higher investment fund inflows to equities and debt globally. Focussing on the euro area, these inflows do not only imply elevated asset prices, but also coincide with increased debt and equity issuance. The findings demonstrate the growing importance of non-bank financial intermediation over the last decade and have important policy implications for monetary and financial stability. JEL Classification: F32, F42, G15, G23
    Keywords: capital flows, international spillovers, Monetary policy, non-bank financial intermediation
    Date: 2021–05

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