Adversarial attacks and defenses in machine learning and deep neural network (DNN) have
been gaining significant attention due to the rapidly growing applications of deep learning in …

This working review shows recent agent-based models for financial market (artificial market
simulations) to discuss financial regulations and/or rules. This review aimed to introduce …

Pair trading is one of the most effective statistical arbitrage strategies which seeks a neutral
profit by hedging a pair of selected assets. Existing methods generally decompose the task …

Exchange-traded funds (ETFs) are mutual funds that invest in a diversified portfolio of many
financial assets. They are listed on stock exchanges and traded as financial instruments. As …

We investigated how arbitrage between an ETF market and the underlying markets affects
the price impact on each market though an agent-based simulation. The results showed that …

From 2010's, investors that invest leveraged exchanged-traded funds (L-ETFs) are
increasing. L-ETFs is listed funds try to track amplified returns of a stock index prices, eg …

Financial benchmarks estimate market values or reference rates used in a wide variety of
contexts, but are often calculated from data generated by parties who have incentives to …

Rapidly advancing algorithmic trading techniques and lagging financial market regulations
have led to opportunities for traders to use these advancements to their own advantage. This …