Although the understanding of and motivation behind individual trading behavior is an important puzzle in finance, little is known about the connection between an investor's portfolio structure and her trading behavior in practice. In this paper, we investigate the relation between what stocks investors hold, and what …
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Study shows adding similar investors can either increase or decrease profits, depending on their strategy.
Optimizes a portfolio for an investor preferring accepted securities over a reference security.
This article considers a model for alternative processes for securities prices and compares this model with actual return data of several securities. The distributions of returns that appear in the model can be Gaussian as well as non-Gaussian; in particular they may have two peaks. We consider a discrete Markov chain …
The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPO) have barely been explored. We fill this gap in the literature by analysing investor clusters in the first two years after the IPO filing in the Helsinki S…
Study on stock portfolio concentration among Finnish households and investors.
We develop a finite horizon continuous time market model, where risk averse investors maximize utility from terminal wealth by dynamically investing in a risk-free money market account, a stock written on a default-free dividend process, and a defaultable bond, whose prices are determined via equilibrium. We analyze fi…
We investigate the trading behavior of Finnish individual investors trading the stocks selected to compute the OMXH25 index in 2003 by tracking the individual daily investment decisions. We verify that the set of investors is a highly heterogeneous system under many aspects. We introduce a correlation based method that…
Study compares price patterns of cryptocurrencies and stocks using machine learning.
Matrix factorization was used to generate investment recommendations for investors. An iterative conjugate gradient method was used to optimize the regularized squared-error loss function. The number of latent factors, number of iterations, and regularization values were explored. Overfitting can be addressed by either…
A continuous-time consumption-investment model with constraint is considered for a small investor whose decisions are the consumption rate and the allocation of wealth to a risk-free and a risky asset with logarithmic Brownian motion fluctuations. The consumption rate is subject to an upper bound constraint which linea…
Trend following in cryptocurrencies yields high returns, similar to commodities.
Generalizes Black-Scholes model for option pricing under uncertainty.
Study shows institutional investments significantly impact cryptocurrency market evolution.
Empirical investor networks (EIN) proposed by \cite{Ozsoylev-Walden-Yavuz-Bildik-2014-RFS} are assumed to capture the information spreading path among investors. Here, we perform a comparative analysis between the EIN and the cellphone communication networks (CN) to test whether EIN is an information exchanging network…
We consider an investor who seeks to maximize her expected utility derived from her terminal wealth relative to the maximum performance achieved over a fixed time horizon, and under a portfolio drawdown constraint, in a market with local stochastic volatility (LSV). In the absence of closed-form formulas for the value …
By incorporating market impact and asymmetric sensitivity into the evolutionary minority game, we study the coevolutionary dynamics of stock prices and investment strategies in financial markets. Both the stock price movement and the investors' global behavior are found to be closely related to the phase region they fa…
We propose an indicator to measure the degree to which a particular news article is novel, as well as an indicator to measure the degree to which a particular news item attracts attention from investors. The novelty measure is obtained by comparing the extent to which a particular news article is similar to earlier new…
A time-varying network reveals community structure in cryptocurrencies.
Investor optimizes wealth in a market with non-traded endowment, deriving expansions up to second order.
Cryptocurrencies return cross-predictability and technological similarity yield information on risk propagation and market segmentation. To investigate these effects, we build a time-varying network for cryptocurrencies, based on the evolution of return cross-predictability and technological similarities. We develop a …
We study the dynamics of order flows around large intraday price changes using ultra-high-frequency data from the Shenzhen Stock Exchange. We find a significant reversal of price for both intraday price decreases and increases with a permanent price impact. The volatility, the volume of different types of orders, the b…
The paper presents new machine learning methods: signal composition, which classifies time-series regardless of length, type, and quantity; and self-labeling, a supervised-learning enhancement. The paper describes further the implementation of the methods on a financial search engine system to identify behavioral simil…
Investor skill levels affect optimal portfolio size, study shows.
Young investors, especially students, dominate Indonesian stock exchanges.
Modeling investor behavior from financial advisor notes using NLP.
Study finds investor sentiment has a significant positive relationship with stock returns in Moroccan and Tunisian markets.
Derives a new formula for measuring risk aversion in markets.
Growth-optimal portfolios are guaranteed to accumulate higher wealth than any other investment strategy in the long run. However, they tend to be risky in the short term. For serially uncorrelated markets, similar portfolios with more robust guarantees have been recently proposed. This paper extends these robust portfo…
Social media reduces individual investors' disposition effect through negative information.
Robo-advisor learns investor's risk preference through portfolio choices.
This paper analyzes how multiple investors can exploit relative arbitrage opportunities.
Deep learning models improve stock market portfolio returns.
Investment disputes increase stock volatility, especially for companies with negative outcomes.
Research identifies four motivational groups for crypto-metaverse landowners.
Study shows cryptocurrency investor base affects volatility.
Investors suffer welfare loss despite having better information.
A deterministic trading strategy by a representative investor on a single market asset, which generates complex and realistic returns with its first four moments similar to the empirical values of European stock indices, is used to simulate the effects of financial regulation that either pricks bubbles, props up crashe…
Study reveals investor behavior in NFT bubbles.
Multilayer networks are attracting growing attention in many fields, including finance. In this paper, we develop a new tractable procedure for multilayer aggregation based on statistical validation, which we apply to investor networks. Moreover, we propose two other improvements to their analysis: transaction bootstra…
Covid lockdown increased interest in Italian stock market, leading to new investors.
Investor flows in Korean equity market transmit shared information, not private signals.
Game theory models storage investment to balance market competition and profits.
The paper examines stability of shares in Proof of Stake protocol, identifying different investor behaviors and phase transitions.
Geometric approach combines asset returns and investor views for better portfolio optimization.
Simulation reveals relationships in stock market pyramid schemes.
Study investor attention using search volume data before and after mobile device popularity.
Study investor sentiment and disagreement on StockTwits during COVID-19.