nep-fmk New Economics Papers
on Financial Markets
Issue of 2020‒02‒17
six papers chosen by

  1. Artificial Intelligence Platforms – A New Research Agenda for Digital Platform Economy By Mucha, Tomasz; Seppälä, Timo
  2. Stress Testing at the IMF By Tobias Adrian; James Morsink; Liliana B Schumacher
  3. Bond Losses and Systemic Risk By Klenio Barbosa; Dakshina De Silva; Liyu Yang; Hisayuki Yoshimoto
  4. Personal Traits and Trading in an Experimental Asset Market By Tomas Miklanek; Miroslav Zajicek
  5. Have the Risk Profiles of Large U.S. Bank Holding Companies Changed? By Kevin Lai; Ricardo Correa; Linda S. Goldberg
  6. Forecasting NIFTY 50 benchmark Index using Seasonal ARIMA time series models By Amit Tewari

  1. By: Mucha, Tomasz; Seppälä, Timo
    Abstract: Abstract Three out of nine of S&P500 digital platform companies stand out as building own artificial intelligence (AI) platforms. There is overwhelming empirical evidence of AI technologies are being central to running a digital platform business. However, the current research agenda is not directing researchers to study AI technologies in the context of digital platforms. We have divided the proposed AI platforms research agenda as follows: The first set of questions we propose relates to an overall conceptualization of AI platforms. Thereafter, we recognize specific aspects of AI platforms, which need to be investigated in detail to gain understanding that is more complete. The second set of questions we propose relates to understanding the dynamics between AI platforms and the broader socio-economic context. This topic might be particularly relevant to economies of countries without indigenous AI platforms. Our paper builds on the proposition that AI is a general-purpose technology, which by itself carries properties of a digital platform.
    Keywords: Platforms, Digital Platform Economy, Artificial Intelligence, AI platforms, Research agenda
    JEL: M1 M21 O3 O33
    Date: 2020–02–06
  2. By: Tobias Adrian; James Morsink; Liliana B Schumacher
    Abstract: Stress Testing at the IMF
    Keywords: Financial crises;Financial institutions;Macroprudential policies and financial stability;Financial systems;Macro-financial analysis;DPPP,solvency,stress test,IMF,individual bank,Gar
    Date: 2020–02–05
  3. By: Klenio Barbosa; Dakshina De Silva; Liyu Yang; Hisayuki Yoshimoto
    Abstract: This paper documents the existence of primary dealers' losses in Treasury bond markets and investigates how these losses affect dealers' market value. Using a novel data set that tracks more than 2,350 primary-to-secondary transactions, we find that bond losses for primary dealers are prevalent and were severe during the financial crisis. Our results indicate that liquidity constraints are a major source of bond losses observed in primary-to-secondary trades. We also find that financial sector value is correlated with these losses. Using an alternating market experiment, we show that bond losses are higher under discriminatory auctions as compared to uniform auctions.
    Keywords: Bond Losses, Treasury Bonds, Liquidity Constraint, Auction Mechanisms
    JEL: C57 C58 D44
    Date: 2020
  4. By: Tomas Miklanek; Miroslav Zajicek
    Abstract: We study the relationship between personal traits and trading outcomes in continuous double auction asset markets. There are mixed theoretical predictions about this relationship followed by similarly mixed empirical evidence. We examine the correlation of cognitive skills, willingness to speculate, risk attitude, willingness to compete, and overconfidence with trading activity in a very simple experimental market with one asset and no uncertainty about the fundamental value. We build on a market setting very close to the canonical one of Smith, Suchanek and Williams (1988) with a constant fundamental value. We conclude that willingness to speculate is the main driver of trading activity. Willingness to speculate and cognitive skills are the only significant predictors for achieved profits from trading. Our experimental results could provide a benchmark for trading activity outcomes in more complicated, real world asset market environments.
    Keywords: experimental economics; asset market; trading activity; personal traits;
    JEL: C91 D91 D53
    Date: 2020–01
  5. By: Kevin Lai (Federal Reserve Bank of New York, Research and Statistics Group); Ricardo Correa; Linda S. Goldberg
    Abstract: After the global financial crisis, regulatory changes were implemented to support financial stability, with some changes directly addressing capital and liquidity in bank holding companies (BHCs) and others targeting BHC size and complexity. Although the overall size of the largest U.S. BHCs has not decreased since the crisis, the organizational complexity of these same organizations has declined, with less notable changes being observed in their range of businesses and geographic scope (Goldberg and Meehl, forthcoming). In this post, we explore how different types of BHC risks—risks that can influence the probability that a BHC is stressed, as well as the chance of systemic implications—have changed over time. The results are mixed: Levels of most BHC risks tend to be higher than in the years immediately preceding the crisis, but are markedly lower than the levels seen during and immediately following the crisis.
    Keywords: Crisis; Bank; Risk; Bank Holding Company
    JEL: G2
    Date: 2020–02–03
  6. By: Amit Tewari
    Abstract: This paper analyses how Time Series Analysis techniques can be applied to capture movement of an exchange traded index in a stock market. Specifically, Seasonal Auto Regressive Integrated Moving Average (SARIMA) class of models is applied to capture the movement of Nifty 50 index which is one of the most actively exchange traded contracts globally [1]. A total of 729 model parameter combinations were evaluated and the most appropriate selected for making the final forecast based on AIC criteria [8]. NIFTY 50 can be used for a variety of purposes such as benchmarking fund portfolios, launching of index funds, exchange traded funds (ETFs) and structured products. The index tracks the behaviour of a portfolio of blue chip companies, the largest and most liquid Indian securities and can be regarded as a true reflection of the Indian stock market [2].
    Date: 2020–01

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