The box spread arbitrage conditions: theory, tests, and investment strategies

This paper develops and tests arbitrage bounds for a combinationof two option spread positions known as a box spread. This strategyinvolves the simultaneous use of four options and creates aposition that is equivalent to riskless lending. The no-arbitrageconditions are compared to existing arbitrage bounds and aretested using Chicago Board Options Exchange data.     

A note on sufficient conditions for no arbitrage

It is shown that the absence of call spread, butterfly spread and calendar spread arbitrages is sufficient to exclude all static arbitrages from a set of option price quotes across strikes and maturities on a single underlier.     

Dynamic mode decomposition for financial trading strategies

We demonstrate the application of an algorithmic trading strategy based upon the recently developed dynamic mode decomposition on portfolios of financial data. The method is capable of characterizing complex dynamical systems, in this case financial market dynamics, in an equation-free manner by decomposing the state of the system into low-rank terms whose temporal coefficients in time are known. By extracting key temporal coherent structures (portfolios) in its sampling window, it provides a regression to a best fit linear dynamical system, allowing for a predictive assessment of the market dynamics and informing an investment strategy. The data-driven analytics capitalizes on stock market patterns, either real or perceived, to inform buy/sell/hold investment decisions. Critical to the method is an associated learning algorithm that optimizes the sampling and prediction windows of the algorithm by discovering trading hot-spots. The underlying mathematical structure of the algorithms is rooted in methods from nonlinear dynamical systems and shows that the decomposition is an effective mathematical tool for data-driven discovery of market patterns.     

Return enhancement trading strategies for size based portfolios

Recent theoretical work suggests that definitions of market efficiency that allow for the possibility of time-varying risk-premia will generally lead to return sign predictability. Consistent with this theory, we show that a logit model based on the lagged value of the market risk premium is useful for successfully predicting the return sign for CRSP small decile portfolio returns, but not large ones. We additionally employ this model in market timing simulations of micro-cap mutual funds in which investment can actually be made. The results indicate that a market-timing strategy based on our return-sign forecasting model outperforms a buy-and-hold strategy for 13 of 14 micro-cap funds studied. On average, the buy-and-hold strategy produces an average compound return of 11.98% per annum versus an average of 16.60% for the market-timing strategy. Nevertheless, trading restrictions make the return-sign forecasting model more practical to employ by the micro-cap fund portfolio manager rather than the individual fund investor.

An anatomy of trading strategies

In this article we use a single unifying framework to analyzethe sources of profits to a wide spectrum of return-based tradingstrategies implemented in the literature. We show that lessthan 50% of the 120 strategies implemented in the article yieldstatistically significant profits and, unconditionally, momentumand contrarian strategies are equally likely to be successful.However, when we condition on the return horizon (short, medium,or long) of the strategy, or the time period during which itis implemented, two patterns emerge. A momentum strategy isusually profitable at the medium (3- to 12-months) horizon,while a contrarian strategy nets statistically significant profitsat long horizons, but only during the 1926-1947 subperiod. Moreimportantly, our results show that the cross-sectional variationin the mean returns of individual securities included in thesestrategies play an important role in their profitability. Thecross-sectional variation can potentially account for the profitabilityof momentum strategies and it is also responsible for attenuatingthe profits from price reversals to long-horizon contrarianstrategies.     

Mispricing of dual-class shares: Profit opportunities,arbitrage, and trading

This is the first paper to examine the microstructure of how mispricing is created and resolved. We study dual-class shares with equal cash flow rights and show that a simple trading strategy exploiting gaps between their prices appears to create abnormal profits after transactions costs. Trade and quote data show that investors shift their trading patterns to take advantage of gaps. Contrary to common perception, long–short arbitrage plays a minor part in eliminating gaps, and one-sided trades correct most of them. We also show that the more liquid share class is usually responsible for the price discrepancies.     

Is smarter better? A comparison of adaptive, and simple moving average trading strategies

This study examines the comparative performance of an Adaptive Moving Average (AMA) on the Australian All Ordinaries, Dow Jones Industrial Average, and Standard and Poor's 500 stock market indices. The theoretical advantage of the Adaptive Moving Average over fixed length Simple Moving Average (SMA) trading systems is its ability to automatically respond to changing market conditions dependant upon the level of volatility in the market. While the strategy is confirmed to have some market timing ability, the overall results show returns to the Adaptive Moving Average cannot compensate for the cost of trade therefore lending support for the use of a long run passive strategy.     

Estimating the profits from trading strategies

Price improvement is the difference between the execution priceof an order and the quoted bid or ask when the order was submitted.We show that expected price improvement falls off dramaticallyas the size of the order approaches the quoted depth, and becomesnegative for larger orders. This is particularly important forsmall firms because the quoted depths are low. Using quotedspreads and depths and our estimate of expected price improvement,we show that trading strategies that attempt to exploit theweekly predictability of small-firm returns would be swampedby transaction costs.     

Asymmetric return dynamics and technical trading strategies

We investigate the profitability of technical trading strategies based on an asymmetric reverting property of stock returns. We identify an asymmetry in return dynamics for daily returns on the S&P 500 index. Return dynamics evolve along a positive (negative) unconditional mean after a prior positive (negative) return. The trading strategies based on this asymmetry generate a positive return for buy signals, a negative return for sell signals, and a positive return for the spread between buy and sell signals. Our results imply that the observed asymmetry in return dynamics is the main source of profitability for the implied strategies, thereby corroborating arguments for the usefulness of technical trading strategies.     

S&P 500 trading strategies and stock betas

This paper shows that S&P 500 stock betas are overstatedand the non-S&P 500 stock betas are understated becauseof liquidity price effects caused by the S&P 500 tradingstrategies. The daily and weekly betas of stocks added to theS&P 500 index during 1985-1989 increase, on average, by0.211 and 0.130. The difference between monthly betas of otherwisesimilar S&P 500 and non-S&P 500 stocks also equals 0.125during this period. Some of these increases can be explainedby the reduced nonsynchroneity of S&P 500 stock prices,but the remaining increases are explained by the price pressureor excess volatility caused by the S&P 500 trading strategies.I estimate that the price pressures account for 8.5 percentof the total variance of daily returns of a value-weighted portfolioof NYSE/AMEX stocks. The negative own autocorrelations in S&P500 index returns and the negative cross autocorrelations betweenS&P 500 stock returns provide further evidence consistentwith the price pressure hypothesis.     

Constant-collateral pyramiding trading strategies in futures markets

This paper introduces constant-collateral pyramiding trading strategies, which can be implemented in the futures markets. For these strategies, expressions are derived for effective constraints on the number of futures contracts in the trader’s portfolio and on the trader’s wealth. Implications of the results are drawn regarding the degree of pyramiding adopted by a subgroup of noise traders who underestimate the probability of receiving a margin call when they engage in positive feedback strategies. Suggestions are made regarding how market regulators can use margin requirements to encourage these traders to adopt less aggressive pyramiding strategies.     

Optimal VWAP trading under noisy conditions

This article proposes an empirically tractable way to incorporate intra-day noise into a VWAP trading rule. In volatile markets, news arrives unexpectedly and rapidly. This should influence a trader’s trading decisions. However, the literature has not incorporated such information into an algorithmic trading framework. Subsequently, this paper presents a Dynamic VWAP (DVWAP) framework that allows informed traders to utilize random news; and thus, improve trade-execution.     

Trend-following trading strategies in commodity futures: A re-examination

This paper examines the performance of trend-following trading strategies in commodity futures markets using a monthly dataset spanning 48 years and 28 markets. We find that all parameterizations of the dual moving average crossover and channel strategies that we implement yield positive mean excess returns net of transactions costs in at least 22 of the 28 markets. When we pool our results across markets, we show that all of the trading rules earn hugely significant positive returns that prevail over most subperiods of the data as well. These results are robust with respect to the set of commodities the trading rules are implemented with, distributional assumptions, data-mining adjustments and transactions costs, and help resolve divergent evidence in the extant literature regarding the performance of momentum and pure trend-following strategies that is otherwise difficult to explain.     

Lessons from the evolution of foreign exchange trading strategies

The adaptive markets hypothesis posits that trading strategies evolve as traders adapt their behavior to changing circumstances. This paper studies the evolution of trading strategies for a hypothetical trader who chooses portfolios from foreign exchange (forex) technical rules in major and emerging markets, the carry trade, and US equities. The results show that a backtesting procedure to choose optimal portfolios improves upon the performance of nonadaptive rules. We also find that forex trading alone dramatically outperforms the S&P 500, with much larger Sharpe ratios over the whole sample, but there is little gain to coordinating forex and equity strategies, which explains why practitioners consider these tools separately. Forex trading returns dip significantly in the 1990s but recover by the end of the decade and have been markedly superior to an equity position since 1998. Overall, trading rule returns still exist in forex markets—with substantial stability in the types of rules—though they have migrated to emerging markets to a considerable degree.     

Heterogeneous real-time trading strategies in the foreign exchange market

The foreign exchange (FX) market is worldwide, but the dealers differ in their geographical locations (time zones), working hours, time horizons, home currencies, access to information,transaction costs, and other institutional constraints. The variety of time horizones is large: from intra-day dealers, who close their positions every evening, to long-term investors and central banks. Depending on the constraints, the different market participats need different strategies to reach their goal, which is usually maximizing the profit, or rather a utility function including risk. Different intra-day trading strategies can be studied only if high-density data are available. Oslen & Associates (O & A) has collected and analysed large amounts of FX quotes by market makers around the clock (up to 5000 non-equally spaced prices per day for the German mark against US$). Based on these data, a set of real-time intra-day trading models has been developed. These models give explicit trading recommendations under realistic constraints. They are allowed to trade only during the opening hours of a market, depending on the time zone and local holidays. The models have been running real-time for more than three years, thus leading to an ex ante test. The test results, obtained with a risk-sensitive performance measure, are presented. All these trading models are profitable, but they differ in their risk behaviour and dealing frequency. If a certain profitable intra-day algorithm is tested with different working hours, its success can considerably change. A systematic study shows that the best choice of working hours is usually when the most important markets for the particular FX rate are active. All the results demonstrate that the assumption of a homogeneous 24-hour FX market with identical dealers, following an identical ‘rational expectation’, is far from reality. To explain the market dynamics, a heterogeneous model of the market with different types of dealers is more appropriate.     

Efficient trading strategies in the presence of market frictions

We provide a price characterization of efficient contingentclaims - that is, chosen by at least a rational agent - in multiperiodeconomies with market frictions. Frictions include market incompleteness,transaction costs, short-selling, and borrowing costs. We characterizethe inefficiency cost of a trading strategy - its required investmentminus the largest amount necessary to obtain the same utilitylevel - and we propose a measure of portfolio performance. Weshow that arbitrage bounds cannot be tightened based on efficiencywithout restricting preferences or endowments. We observe commoninvestment strategies becoming inefficient with market frictionsand others rationalized by them.     

The predictability of security returns with simple technical trading rules

Technical traders base their analysis on the premise that the patterns in market prices are assumed to recur in the future, and thus, these patterns can be used for predictive purposes. This paper uses the daily Dow Jones Industrial Average Index from 1897 to 1988 to examine the linear and nonlinear predictability of stock market returns with simple technical trading rules. The nonlinear specification of returns are modelled by single layer feedforward networks. The results indicate strong evidence of nonlinear predictability in the stock market returns by using the past buy and sell signals of the moving average rules.     

International tax arbitrage,financial parity conditions and preferential capital gains taxation

Using a finite-horizon general equilibrium model with uncertainty and money, we characterize situations where tax arbitrage opportunities may arise for international portfolio investors in an economy with heterogeneous capital income taxation when interest income and capital gains/losses are taxed differentially for some agents. We derive tax-modified uncovered interest parity conditions, Fisher conditions and forward prices similar to the no-tax ones, but augmented by tax-induced ‘risk-premium’ terms; covered interest parity and Fisher conditions remain unaffected by the introduction of capital income taxes as we bound tax-based arbitrage without restricting arbitrage per se.