Pairs Trading Strategy for A and H Shares Based on Kalman-HMM Approach

Pairs trading is a statistical arbitrage strategy that takes advantage of unbalanced financial markets. A common difficulty for quantitative trading participants is the detection of market institutional changes in financial markets. In order to solve this issue, the hidden Markov model (HMM) is applied for status detection. The research objective is to use Kalman filter to predict and the hidden Markov model (HMM) to identify state transitions on the basis of screening transaction pairs with obvious co-integration relationship. This research would prove the profitability of the strategy and the ability to resist risk through the combination of these two methods with real data. The empirical results showed that compared with the traditional cointegration strategy, the holding yield increased from 1.6% to 16.2% and the maximum pullback reduced to 0.02%. Further research is required to improve trading rules.

Hedge Fund Strategies in the Post-Crisis Era

This chapter examines the performances of various hedge fund strategies based on various reward-to-risk ratios after the 2008 global crisis. We document that a majority of hedge fund strategies deliver lower average returns compared to equities and bonds; yet the volatilities of their returns have also been low. The equity hedge strategy has the highest reward-to-risk ratios among the major strategy categories, whereas the relative value arbitrage strategy has the lowest. Technology/healthcare, merger arbitrage, discretionary thematic, and asset-backed arbitrage strategies tend to have the highest reward-to-risk ratios in their respective categories. Time-series regressions of hedge fund strategy returns on various fund pricing factors provide evidence that hedge funds, on average, do not generate abnormal returns once the pricing factors are controlled for. We also document that hedge fund strategy returns generally load negatively on the bond market and aggregate credit risk factors and positively on the market portfolio.

Investment Strategies of Hedge Funds

This chapter reviews a number of different hedge fund strategies, including equity hedge, long/short, market neutral, relative value arbitrage, convertible arbitrage strategy, capital structure arbitrage strategy, fixed income arbitrage strategy, yield curve arbitrage strategy, other relative value arbitrage strategies, emerging markets strategies, global macro strategies, event driven strategies, distressed securities, and merger arbitrage strategies. In addition, the author discusses the growth and performance of different strategies, as well as fraud, fund failures, activism, and regulation.

Machine Learning in Futures Markets

In this paper, we demonstrate how a well-established machine learning-based statistical arbitrage strategy can be successfully transferred from equity to futures markets. First, we preprocess futures time series comprised of front months to render them suitable for our returns-based trading framework and compile a data set comprised of 60 futures covering nearly 10 trading years. Next, we train several machine learning models to predict whether the h-day-ahead return of each future out- or underperforms the corresponding cross-sectional median return. Finally, we enter long/short positions for the top/flop-k futures for a duration of h days and assess the financial performance of the resulting portfolio in an out-of-sample testing period. Thereby, we find the machine learning models to yield statistically significant out-of-sample break-even transaction costs of 6.3 bp—a clear challenge to the semi-strong form of market efficiency. Finally, we discuss sources of profitability and the robustness of our findings.

ARBITRAGE OPPORTUNITIES USING HYBRID FINANCIAL INSTRUMENTS

The article discusses the features of the “convertible arbitrage” strategy using a hybrid financial instrumentconvertible bonds. The characteristics of convertible bonds as a financial market instrument are given. The article analyzes the conduct of convertible arbitrage in terms of the motives and factors that affect the implementation of the strategy; the basic possible scenarios are given.

The application of the improved option parity arbitrage model in SSE 50ETF option

The SSE 50ETF option is China's first stock index option product launched in 2015. For a number of reasons, the options market can sometimes create arbitrage opportunities. Based on the theory of option parity arbitrage and taking into account the transaction costs, this paper explores effective options arbitrage strategies and practices them. Based on the theory of option parity arbitrage and taking into account the transaction costs, this paper establishes an effective option arbitrage strategy model and puts it into practice. The results show that there are indeed arbitrage opportunities in the market that exceed the risk-free rate of return, but there are not many such opportunities, and there is not much arbitrage space under many opportunities. This is not only the embodiment of high market efficiency, but also the result of taking various transaction costs into full consideration in this paper to ensure the effectiveness of arbitrage.