Subjects -> BUSINESS AND ECONOMICS (Total: 3570 journals)
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    - ECONOMIC SCIENCES: GENERAL (212 journals)
    - ECONOMIC SYSTEMS, THEORIES AND HISTORY (235 journals)
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    - HUMAN RESOURCES (103 journals)
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    - INTERNATIONAL COMMERCE (145 journals)
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    - TRADE AND INDUSTRIAL DIRECTORIES (2 journals)

INTERNATIONAL COMMERCE (145 journals)                     

Showing 1 - 136 of 136 Journals sorted alphabetically
Acta Economica Et Turistica     Open Access   (Followers: 1)
Advances in Accounting     Hybrid Journal   (Followers: 10)
African Journal of Economic and Sustainable Development     Hybrid Journal   (Followers: 17)
Amnis     Open Access   (Followers: 1)
Antitrust Bulletin     Hybrid Journal   (Followers: 8)
Asia and the Global Economy     Open Access  
Asian Journal of Shipping and Logistics     Open Access   (Followers: 2)
Botswana Journal of Economics     Open Access   (Followers: 1)
Career Development International     Hybrid Journal   (Followers: 18)
China Business Review     Full-text available via subscription   (Followers: 2)
China Economic Quarterly International     Open Access  
Competition and Regulation in Network Industries     Full-text available via subscription   (Followers: 7)
Critical Perspectives on International Business     Hybrid Journal   (Followers: 1)
Crossroads     Hybrid Journal  
Digital Finance : Smart Data Analytics, Investment Innovation, and Financial Technology     Hybrid Journal   (Followers: 3)
East Asian Community Review     Hybrid Journal  
EC Tax Review     Full-text available via subscription   (Followers: 5)
Economic Journal of Emerging Markets     Open Access   (Followers: 1)
Economics Research International     Open Access   (Followers: 1)
Ekonomia Międzynarodowa     Open Access  
EMAJ : Emerging Markets Journal     Open Access  
Emerging Markets Finance and Trade     Hybrid Journal   (Followers: 7)
Estudos Internacionais : revista de relações internacionais da PUC Minas     Open Access   (Followers: 1)
European Business Law Review     Full-text available via subscription   (Followers: 17)
European Company Law     Full-text available via subscription   (Followers: 11)
European Journal of International Management     Hybrid Journal   (Followers: 3)
Expert Journal of Business and Management     Open Access  
Foreign Trade Review     Hybrid Journal   (Followers: 3)
Global & Strategis     Open Access   (Followers: 1)
Global Summitry     Hybrid Journal   (Followers: 1)
Global Trade and Customs Journal     Full-text available via subscription   (Followers: 6)
Human Resource Development International     Hybrid Journal   (Followers: 19)
Human Resource Management International Digest     Hybrid Journal   (Followers: 18)
IMF Economic Review     Hybrid Journal   (Followers: 44)
IN VIVO     Full-text available via subscription   (Followers: 4)
Information Resources Management Journal     Full-text available via subscription   (Followers: 8)
Information Technologies & International Development     Open Access   (Followers: 81)
International Advances in Economic Research     Hybrid Journal   (Followers: 6)
International Business Review     Hybrid Journal   (Followers: 9)
International Commerce Review     Hybrid Journal   (Followers: 1)
International Economic Journal     Hybrid Journal   (Followers: 8)
International Economic Review     Hybrid Journal   (Followers: 61)
International Economics     Hybrid Journal   (Followers: 3)
International Economics and Economic Policy     Hybrid Journal   (Followers: 7)
International Entrepreneurship and Management Journal     Hybrid Journal   (Followers: 8)
International Environmental Agreements: Politics, Law and Economics     Hybrid Journal   (Followers: 14)
International Finance     Hybrid Journal   (Followers: 26)
International Insolvency Review     Hybrid Journal   (Followers: 4)
International Journal of Applied Behavioral Economics     Full-text available via subscription   (Followers: 18)
International Journal of Asian Business and Information Management     Full-text available via subscription   (Followers: 1)
International Journal of Commerce and Management     Hybrid Journal  
International Journal of Export Marketing     Hybrid Journal   (Followers: 1)
International Journal of Governance and Financial Intermediation     Hybrid Journal  
International Labor and Working-Class History     Full-text available via subscription   (Followers: 15)
International Labour Review     Partially Free   (Followers: 60)
International Marketing Review     Hybrid Journal   (Followers: 14)
International Public Management Journal     Hybrid Journal   (Followers: 8)
International Review of Applied Economics     Hybrid Journal   (Followers: 6)
International Review of Economics     Hybrid Journal   (Followers: 4)
International Review of Economics & Finance     Hybrid Journal   (Followers: 28)
International Review of Finance     Hybrid Journal   (Followers: 9)
International Review of Financial Analysis     Hybrid Journal   (Followers: 8)
International Review of Law and Economics     Hybrid Journal   (Followers: 27)
International Review of Retail, Distribution and Consumer Research     Hybrid Journal   (Followers: 3)
International Review of Social History     Full-text available via subscription   (Followers: 32)
International Review on Public and Nonprofit Marketing     Hybrid Journal   (Followers: 3)
International Small Business Journal     Hybrid Journal   (Followers: 11)
International Studies of Management and Organization     Full-text available via subscription   (Followers: 8)
International Trade Journal : Western Hemispheric Studies     Hybrid Journal   (Followers: 2)
International Transactions In Operational Research     Hybrid Journal   (Followers: 2)
Intertax     Full-text available via subscription   (Followers: 4)
Japanese Political Economy     Full-text available via subscription   (Followers: 1)
Journal for International Business and Entrepreneurship Development     Hybrid Journal   (Followers: 8)
Journal of Accounting and Finance in Emerging Economies     Open Access  
Journal of Advanced Research in Economics and International Business     Full-text available via subscription  
Journal of Antitrust Enforcement     Hybrid Journal   (Followers: 1)
Journal of Chinese Economic and Foreign Trade Studies     Hybrid Journal   (Followers: 2)
Journal of Chinese Human Resource Management     Hybrid Journal   (Followers: 4)
Journal of Comparative International Management     Full-text available via subscription  
Journal of Contemporary European Research     Open Access   (Followers: 16)
Journal of Economics and International Finance     Open Access   (Followers: 1)
Journal of International Accounting, Auditing and Taxation     Hybrid Journal   (Followers: 5)
Journal of International Business Policy     Hybrid Journal  
Journal of International Business Studies     Hybrid Journal   (Followers: 48)
Journal of International Commerce, Economics and Policy     Hybrid Journal  
Journal of International Consumer Marketing     Hybrid Journal   (Followers: 9)
Journal of International Development     Hybrid Journal   (Followers: 32)
Journal of International Economics     Hybrid Journal   (Followers: 38)
Journal of International Entrepreneurship     Hybrid Journal   (Followers: 10)
Journal of International Financial Management & Accounting     Hybrid Journal   (Followers: 4)
Journal of International Financial Markets, Institutions and Money     Hybrid Journal   (Followers: 19)
Journal of International Food & Agribusiness Marketing     Hybrid Journal   (Followers: 2)
Journal of International Management     Hybrid Journal   (Followers: 5)
Journal of International Marketing     Full-text available via subscription   (Followers: 24)
Journal of International Money and Finance     Hybrid Journal   (Followers: 37)
Journal of International Trade & Economic Development: An International and Comparative Review     Hybrid Journal   (Followers: 11)
Journal of International Trade Law and Policy     Hybrid Journal   (Followers: 19)
Journal of Korea Trade     Full-text available via subscription   (Followers: 1)
Journal of Monetary Economics     Hybrid Journal   (Followers: 95)
Journal of Revenue and Pricing Management     Hybrid Journal   (Followers: 4)
Journal of Reviews on Global Economics     Open Access  
Journal of the Association for Consumer Research     Full-text available via subscription   (Followers: 7)
Journal of the Japanese and International Economies     Hybrid Journal   (Followers: 4)
Journal of Theoretical and Applied Electronic Commerce Research     Open Access  
Journal of World Trade     Full-text available via subscription   (Followers: 19)
Jurnal Hubungan Internasional     Open Access  
Jurnal Ilmu Ekonomi Terapan     Open Access  
L'Année du Maghreb     Open Access   (Followers: 1)
Management international / International Management / Gestiòn Internacional     Full-text available via subscription   (Followers: 3)
Management International Review     Hybrid Journal   (Followers: 7)
MEED Middle East Economic Digest     Full-text available via subscription   (Followers: 1)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
PharmacoEconomics     Full-text available via subscription   (Followers: 26)
Proceedings of the International Conference on Business Excellence     Open Access  
Qualitative Research in Financial Markets     Hybrid Journal   (Followers: 2)
Quarterly Journal of Political Science     Full-text available via subscription   (Followers: 18)
Regional Formation and Development Studies     Open Access  
Relações Internacionais (R:I)     Open Access  
Research World     Hybrid Journal  
Review of International Economics     Hybrid Journal   (Followers: 14)
Review of International Political Economy     Hybrid Journal   (Followers: 40)
Revista Brasileira de Gestão de Negócios     Open Access  
Revista Multiface Online     Open Access  
Revue internationale de l'économie sociale     Full-text available via subscription  
Revue Internationale du Travail     Full-text available via subscription   (Followers: 3)
Revue internationale P.M.E. : économie et gestion de la petite et moyenne entreprise     Full-text available via subscription   (Followers: 1)
South African Journal of International Affairs     Hybrid Journal   (Followers: 6)
South American Development Society Journal     Open Access  
Studies in Comparative International Development     Hybrid Journal   (Followers: 16)
Syracuse Journal of International Law and Commerce     Open Access   (Followers: 3)
TDM Transnational Dispute Management Journal     Full-text available via subscription   (Followers: 5)
Transnational Corporations Review     Hybrid Journal  
World Competition     Full-text available via subscription   (Followers: 9)
World Food Policy     Hybrid Journal   (Followers: 3)
World Oil Trade     Hybrid Journal  
World Trade and Arbitration Materials     Full-text available via subscription   (Followers: 8)

           

Similar Journals
Journal Cover
Digital Finance : Smart Data Analytics, Investment Innovation, and Financial Technology
Number of Followers: 3  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Online) 2524-6186
Published by Springer-Verlag Homepage  [2469 journals]
  • DeepVaR: a framework for portfolio risk assessment leveraging
           probabilistic deep neural networks

    • Free pre-print version: Loading...

      Abstract: Abstract Determining and minimizing risk exposure pose one of the biggest challenges in the financial industry as an environment with multiple factors that affect (non-)identified risks and the corresponding decisions. Various estimation metrics are utilized towards robust and efficient risk management frameworks, with the most prevalent among them being the Value at Risk (VaR). VaR is a valuable risk-assessment approach, which offers traders, investors, and financial institutions information regarding risk estimations and potential investment insights. VaR has been adopted by the financial industry for decades, but the generated predictions lack efficiency in times of economic turmoil such as the 2008 global financial crisis and the COVID-19 pandemic, which in turn affects the respective decisions. To address this challenge, a variety of well-established variations of VaR models are exploited by the financial community, including data-driven and data analytics models. In this context, this paper introduces a probabilistic deep learning approach, leveraging time-series forecasting techniques with high potential of monitoring the risk of a given portfolio in a quite efficient way. The proposed approach has been evaluated and compared to the most prominent methods of VaR calculation, yielding promising results for VaR 99% for forex-based portfolios.
      PubDate: 2022-04-13
       
  • Convolutional signature for sequential data

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      Abstract: Abstract Signature is an infinite graded sequence of statistics known to characterize geometric rough paths. While the use of the signature in machine learning is successful in low-dimensional cases, it suffers from the curse of dimensionality in high-dimensional cases, as the number of features in the truncated signature transform grows exponentially fast. With the idea of Convolutional Neural Network, we propose a novel neural network to address this problem. Our model reduces the number of features efficiently in a data-dependent way. Some empirical experiments including high-dimensional financial time series classification and natural language processing are provided to support our convolutional signature model.
      PubDate: 2022-04-04
       
  • Indices on cryptocurrencies: an evaluation

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      Abstract: Abstract Several cryptocurrency (CC) indices track the dynamics of the rising CC sector, and soon ETFs will be issued on them. We conduct a qualitative and quantitative evaluation of the currently existing CC indices. As the CC sector is not yet consolidated, index issuers face the challenge of tracking the dynamics of a fast-growing sector that is under continuous transformation. We propose several criteria and various measures to compare the indices under review. Major differences between the indices lie in their weighting schemes, their coverage of CCs and the number of constituents, the level of transparency, and thus, their accuracy in mapping the dynamics of the CC sector. Our analysis reveals that simple market cap-weighted indices outperform their competitors. Interestingly, increasing the number of constituents does not automatically lead to a better fit of the CC sector. All codes are available on .
      PubDate: 2022-02-21
      DOI: 10.1007/s42521-022-00048-8
       
  • Adaptive order flow forecasting with multiplicative error models

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      Abstract: Abstract A flexible statistical approach for the analysis of time-varying dynamics of transaction data on financial markets is here applied to intra-day trading strategies. A local adaptive technique is used to successfully predict financial time series, i.e. the buyer- and the seller-initiated trading volumes and the order flow dynamics. Analysing order flow series and its information content of mini Nikkei 225 index futures traded at the Osaka Securities Exchange in 2012 and 2013, a data-driven optimal length of local windows up to approximately 1–2 h is reasonable to capture parameter variations and is suitable for short-term prediction. Our proposed trading strategies achieve statistical arbitrage opportunities and are, therefore, beneficial for quantitative finance practice.
      PubDate: 2022-01-05
      DOI: 10.1007/s42521-021-00047-1
       
  • Machine learning for financial forecasting, planning and analysis: recent
           developments and pitfalls

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      Abstract: Abstract This article is an introduction to machine learning for financial forecasting, planning and analysis (FP&A). Machine learning appears well suited to support FP&A with the highly automated extraction of information from large amounts of data. However, because most traditional machine learning techniques focus on forecasting (prediction), we discuss the particular care that must be taken to avoid the pitfalls of using them for planning and resource allocation (causal inference). While the naive application of machine learning usually fails in this context, the recently developed double machine learning framework can address causal questions of interest. We review the current literature on machine learning in FP&A and illustrate in a simulation study how machine learning can be used for both forecasting and planning. We also investigate how forecasting and planning improve as the number of data points increases.
      PubDate: 2021-12-16
      DOI: 10.1007/s42521-021-00046-2
       
  • Special issue on Financial Forensics and Fraud Investigation in the Era of
           Industry 4.0

    • Free pre-print version: Loading...

      PubDate: 2021-12-01
      DOI: 10.1007/s42521-021-00044-4
       
  • Correction to: Modeling asset allocations and a new portfolio performance
           score

    • Free pre-print version: Loading...

      PubDate: 2021-12-01
      DOI: 10.1007/s42521-021-00042-6
       
  • Special Issue on Artificial Intelligence, Machine Learning and Platform
           Innovation in Quantitative Finance (MathFinance Conference 2020/2021)

    • Free pre-print version: Loading...

      PubDate: 2021-12-01
      DOI: 10.1007/s42521-021-00043-5
       
  • COVID risk narratives: a computational linguistic approach to the
           econometric identification of narrative risk during a pandemic

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      Abstract: Abstract In this paper, we study the role of narratives in stock markets with a particular focus on the relationship with the ongoing COVID-19 pandemic. The pandemic represents a natural setting for the development of viral financial market narratives. We thus treat the pandemic as a natural experiment on the relation between prevailing narratives and financial markets. We adopt natural language processing (NLP) on financial news to characterize the evolution of important narratives. Doing so, we reduce the high-dimensional narrative information to few interpretable and important features while avoiding over-fitting. In addition to the common features, we consider virality as a novel feature of narratives, inspired by Shiller (Am Econ Rev 107:967–1004, 2017). Our aim is to establish whether the prevailing narratives drive or are driven by stock market conditions. Focusing on the coronavirus narratives, we document some stylized facts about its evolution around a severe event-driven stock market decline. We find the pandemic-relevant narratives are influenced by stock market conditions and act as a cellar for brewing a perennial economic narrative. We successfully identified a perennial risk narrative, whose shock is followed by a severe market drop and a long-term increase of market volatility. In the out-of-sample test, this narrative went viral since the start of the global COVID-19 pandemic, when the pandemic-relevant narratives dominate news media, show negative sentiment and were more linked to “crisis” context. Our findings encourage the use of narratives to evaluate long-term market conditions and to early warn event-driven severe market declines.
      PubDate: 2021-11-29
      DOI: 10.1007/s42521-021-00045-3
       
  • Delta force: option pricing with differential machine learning

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      Abstract: Abstract We show how and why to use a financially meaningful differential regularization method when pricing options by Monte Carlo simulation, be that in polynomial regression or neural network context.
      PubDate: 2021-10-04
      DOI: 10.1007/s42521-021-00041-7
       
  • Modeling asset allocations and a new portfolio performance score

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      Abstract: Abstract We discuss and extend a powerful, geometric framework to represent the set of portfolios, which identifies the space of asset allocations with the points lying in a convex polytope. Based on this viewpoint, we survey certain state-of-the-art tools from geometric and statistical computing to handle important and difficult problems in digital finance. Although our tools are quite general, in this paper, we focus on two specific questions. The first concerns crisis detection, which is of prime interest for the public in general and for policy makers in particular because of the significant impact that crises have on the economy. Certain features in stock markets lead to this type of anomaly detection: Given the assets’ returns, we describe the relationship between portfolios’ return and volatility by means of a copula, without making any assumption on investors’ strategies. We examine a recent method relying on copulae to construct an appropriate indicator that allows us to automate crisis detection. On real data the indicator detects all past crashes in the cryptocurrency market and from the DJ600-Europe index, from 1990 to 2008, the indicator identifies correctly 4 crises and issues one false positive for which we offer an explanation. Our second contribution is to introduce an original computational framework to model asset allocation strategies, which is of independent interest for digital finance and its applications. Our approach addresses the crucial question of evaluating portfolio management, and is relevant the individual managers as well as financial institutions. To evaluate portfolio performance, we provide a new portfolio score, based on the aforementioned framework and concepts. In particular, it relies on statistical properties of portfolios, and we show how they can be computed efficiently.
      PubDate: 2021-09-02
      DOI: 10.1007/s42521-021-00040-8
       
  • Cryptocurrency volatility markets

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      Abstract: Abstract By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.
      PubDate: 2021-08-02
      DOI: 10.1007/s42521-021-00037-3
       
  • Default analysis in mortgage risk with conventional and deep machine
           learning focusing on 2008–2009

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      Abstract: Abstract The rapidly growing mortgage market corresponds with the growth of mortgage backed securities. Since the economic crisis in 2008–2009, financial institutions that deal with mortgages have been working to develop more accurate numerical models for Residential Mortgage Backed Securities (RMBS) to minimize credit risk. Within this context, there is an increasing use of big data and artificial intelligence techniques accordingly. This research focuses on the U.S. RMBS analysis using machine learning to predict the Probability of Default (PD). Primary analysis involves the loan origination and performance characteristics and economic characteristics like home performance index (HPI) to investigate default probability in terms of credit risk. In this research, various machine learning models such as Logistic Regression, Random Forest, Linear Discriminant Analysis, K-Nearest Neighbors (KNN), Multi-layer Neural Network (MNN), Convolution Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) are used. Ultimately, this research provides comprehensive understanding and comparison in applying various machine learning algorithms to the financial discipline of RMBS to develop predictive models for calculating mortgage credit risk using the Fannie Mae loan data that include around 1.5 million of mortgage loans originating from 2005 to 2009 in the United States.
      PubDate: 2021-07-22
      DOI: 10.1007/s42521-021-00036-4
       
  • A blockchain-based forensic model for financial crime investigation: the
           embezzlement scenario

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      Abstract: Abstract The financial crime landscape is evolving along with the digitisation of financial services. Laws, regulations and forensic methodologies cannot efficiently cope with the growth pace of novel technologies, which translates into late adoption of measures and legal voids, providing a fruitful landscape for malicious actors. In this regard, the features offered by blockchain technology, such as immutability, verifiability, and authentication, enhance the robustness of financial forensics. This paper provides a taxonomy of the prevalent financial investigation techniques and a thorough state-of-the-art of blockchain-based digital forensic approaches. Moreover, we design and implement a forensic investigation framework based on standardised procedures and document the corresponding methodology for embezzlement scheme investigations. The feasibility and adaptability of our approach can be extended and embrace all types of fraud investigations and regular internal audits. We provide a functional Ethereum-based implementation, and we integrate standardised forensic flows and chain of custody preservation mechanisms. Finally, we discuss the challenges of the symbiotic relationship between blockchain and financial investigations, along with the managerial implication and future research directions.
      PubDate: 2021-07-15
      DOI: 10.1007/s42521-021-00035-5
       
  • Correction to: Default analysis in mortgage risk with conventional and
           deep machine learning focusing on 2008–2009

    • Free pre-print version: Loading...

      PubDate: 2021-06-01
      DOI: 10.1007/s42521-021-00039-1
       
  • Profitability of cryptocurrency Pump and Dump schemes

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      Abstract: Abstract One of the price manipulation schemes achieved by artificially increasing the trading volume of the target asset, Pump and Dump (P&D) schemes, has a long history in the stock market and is usually considered unlawful. In cryptocurrency markets, however, this scheme has not been well-regulated and uniquely orchestrated through a new type of social media platform such as Telegram. This paper aims to identify the features of P&D organized through Telegram and examine the market resilience to these activities. The regression model will be placed, in a Bayesian hierarchical framework, to clarify variables that contribute to the profitability (i.e., price change) of P&D attempts. It is revealed that the effect of trading volume on profitability significantly differs across each exchange market. Particularly, Yobit and Cryptopia are more sensitive (easily manipulated) to the increase in the trading volume than Binance and Bittrex, while controlling other significant factors, including the timing of the pump (hourly, yearly), the currency, and the Telegram channel. Furthermore, this paper builds a machine learning model to identify the price hike (successful schemes) given information before the pump starts and achieved more than 75% accuracy using tree-based ensemble models. The contribution of this paper is to provide a detailed analysis of P&D schemes using a novel statistical approach, while particularly focusing on the effect of each exchange, therefore provides a better understanding of how the market is manipulated by the crowd of people in social media platforms.
      PubDate: 2021-06-01
      DOI: 10.1007/s42521-021-00034-6
       
  • Robo-advising: a dynamic mean-variance approach

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      Abstract: Abstract In contrast to traditional financial advising, robo-advising needs to elicit investors’ risk profile via several simple online questions and provide advice consistent with conventional investment wisdom, e.g., rich and young people should invest more in risky assets. To meet the two challenges, we propose to do the asset allocation part of robo-advising using a dynamic mean-variance criterion over the portfolio’s log returns. We obtain analytical and time-consistent optimal portfolio policies under jump-diffusion models and regime-switching models.
      PubDate: 2021-06-01
      DOI: 10.1007/s42521-021-00028-4
       
  • How to gauge investor behavior' A comparison of online investor
           sentiment measures

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      Abstract: Abstract Given the increasing interest in and the growing number of publicly available methods to estimate investor sentiment from social media platforms, researchers and practitioners alike are facing one crucial question – which is best to gauge investor sentiment' We compare the performance of daily investor sentiment measures estimated from Twitter and StockTwits short messages by publicly available dictionary and machine learning based methods for a large sample of stocks. To determine their relevance for financial applications, these investor sentiment measures are compared by their effects on the cross-section of stocks (i) within a Fama and MacBeth (J Polit Econ 81:607–636, 1973) regression framework applied to a measure of retail investors’ order imbalances and (ii) by their ability to forecast abnormal returns in a model-free portfolio sorting exercise. Interestingly, we find that investor sentiment measures based on finance-specific dictionaries do not only have a greater impact on retail investors’ order imbalances than measures based on machine learning approaches, but also perform very well compared to the latter in our asset pricing application.
      PubDate: 2021-06-01
      DOI: 10.1007/s42521-021-00038-2
       
  • CATE meets ML

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      Abstract: Abstract For treatment effects—one of the core issues in modern econometric analysis—prediction and estimation are two sides of the same coin. As it turns out, machine learning methods are the tool for generalized prediction models. Combined with econometric theory, they allow us to estimate not only the average but a personalized treatment effect—the conditional average treatment effect (CATE). In this tutorial, we give an overview of novel methods, explain them in detail, and apply them via Quantlets in real data applications. We study the effect that microcredit availability has on the amount of money borrowed and if 401(k) pension plan eligibility has an impact on net financial assets, as two empirical examples. The presented toolbox of methods contains meta-learners, like the doubly-robust, R-, T- and X-learner, and methods that are specially designed to estimate the CATE like the causal BART and the generalized random forest. In both, the microcredit and 401(k) example, we find a positive treatment effect for all observations but conflicting evidence of treatment effect heterogeneity. An additional simulation study, where the true treatment effect is known, allows us to compare the different methods and to observe patterns and similarities.
      PubDate: 2021-06-01
      DOI: 10.1007/s42521-021-00033-7
       
  • Accuracy of deep learning in calibrating HJM forward curves

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      Abstract: Abstract We price European-style options written on forward contracts in a commodity market, which we model with an infinite-dimensional Heath–Jarrow–Morton (HJM) approach. For this purpose, we introduce a new class of state-dependent volatility operators that map the square integrable noise into the Filipović space of forward curves. For calibration, we specify a fully parametrized version of our model and train a neural network to approximate the true option price as a function of the model parameters. This neural network can then be used to calibrate the HJM parameters based on observed option prices. We conduct a numerical case study based on artificially generated option prices in a deterministic volatility setting. In this setting, we derive closed pricing formulas, allowing us to benchmark the neural network based calibration approach. We also study calibration in illiquid markets with a large bid-ask spread. The experiments reveal a high degree of accuracy in recovering the prices after calibration, even if the original meaning of the model parameters is partly lost in the approximation step.
      PubDate: 2021-04-10
      DOI: 10.1007/s42521-021-00030-w
       
 
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