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The purpose of this paper is to communicate the science and art of stop losses.

This paper uses theoretical reasoning, Monte Carlo simulation, and empirical data to support and validate the claims made.

The paper expands on the reasoning introduced by risk management and shows that a stop loss is highly significant and can be the difference between zero and positive expectation in a stochastic market.

Risk and uncertainty both play a major part in people's lives. Every day, the paper is forced to make decisions based upon asymmetric information and unknowns. The paper might be tempted to conclude that decision making in an uncertain and risky world is something well understood. This is not true.

This paper aims to reduce information asymmetry and ultimately help people make better financial decisions. The buy‐and‐hold investment strategy also known as buy‐and‐hope has little scientific support. The author claims no originality when it comes to the practical implementation of the concepts discussed in this paper.

This paper aims to present a methodology for constructing cointegrated portfolios consisting of different cryptocurrencies and examines the performance of a number of trading strategies for the cryptocurrency portfolios.

The authors apply a series of statistical methods, including the Johansen test and Engle–Granger test, to derive a linear combination of cryptocurrencies that form a mean-reverting portfolio. Trading systems are designed and different trading strategies with stop-loss constraints are tested and compared according to a set of performance metrics.

The paper finds cointegrated portfolios involving four cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Bitcoin Cash (BCH) and Litecoin (LTC), and the corresponding trading strategies are shown to be profitable under different configurations.

The main contributions of the study are the use of multiple altcoins in addition to bitcoin to construct a cointegrated portfolio, and the detailed comparison of the performance of different trading strategies with and without stop-loss constraints.

The purpose of this paper is to provide the current state of knowledge about the Flash Crash. It has been one of the remarkable events of the decade and its causes are still a matter of debate.

This paper reviews the literature since the early days to most recent findings, and critically compares the most important hypotheses about the possible causes of the crisis.

Among the causes of the Flash Crash, the literature has propsed the following: a large selling program triggering the sales wave, small but not negligible delays suffered by the exchange computers, the micro-structure of the financial markets, the price fall leading to margin cover and forced sales, some types of feedback loops leading to downward price spiral, stop-loss orders coupled with scarce liquidity that triggered price reduction. On its turn leading to further stop-loss activation, the use of Intermarket Sweep Orders, that is, orders that sacrificed search for the best price to speed of execution, and dumb algorithms.

The results of the previous section are condensed in a set of policy implications and recommendations.

The purpose of this paper is to prove the effectiveness of minimum semi‐absolute deviations (MSAD) method in dynamic portfolio investment.

In financial investment, the classical static portfolio theory of Markowitz type lacks the dynamic adaptability to the changing market situations. This paper proposes a dynamic portfolio theory which uses MSAD criterion on a moving window to replace the Markowitz mean‐variance analysis.

Two specific models are developed to test the validity of the MSAD method: the first model constructs a portfolio consisting of Shanghai‐Shenzhen 300 Index and a national debt as two contrarian assets; the second model constructs a portfolio consisting of a complete set of 18 Chinese stock sector indices and a national debt. The empirical results of the test using six‐year monthly data (2005 to 2010) provide significant evidence that the MSAD method is valid, producing superior returns of investment over the stock index during the test period.

The findings in this study clearly highlight the validity of the MSAD method in determining the weights of assets in Chinese stock markets.

In order to resolve the problem of portfolio investment in Chinese stock markets, the MSAD method with stop loss control strategy can be used for investors to obtain the weights of assets and control the risk.

This study analyzes and verifies the effectiveness of the MSAD method in dynamic portfolio investment. The stop loss control strategy designed and used in the MSAD method is a pioneering and exploratory experiment.

This case involved foreign exchange transactions conducted by the First Defendants, a firm of commodities traders then trading as LHW Futures Ltd (LHW), on behalf of the Plaintiff who was an individual investing his own money in a private capacity. The Second Defendant, Mr Morris, was at all material times a senior account executive with LHW and dealt with the Plaintiff in relation to the transactions at issue. The events giving rise to this action occurred in the years 1984–85. The trading contract between LHW and a client would involve the client paying over a sum which would represent commission and margin on the particular currency trade. The commission, at 2 per cent of the total contract value, was high in comparison to other traders because it was a feature of these contracts that there would be no further margin calls to the client since an automatic stop loss mechanism was built in to the contract which had the effect that a client's total loss was limited to the amount of the original margin. In theory a client's profit on a currency contract was unlimited but in practice merely to break even and cover commission required a substantial rise in the price of the currency bought whereas a relatively small drop in its price would wipe out the client's position once and for all regardless of any subsequent rises. One defence expert testified that the likely effect of this form of currency trading contract was that approximately 90 per cent of investors would be wiped out while only 10 per cent profited. The Plaintiff in this action was an engineer and property developer with most of his assets tied up in a land bank and housing development. He was inexperienced in stock trading and commodities markets. In July 1985 the Plaintiff entered into two trades in Swiss Francs with LHW. He invested £2,600 in the first trade and £23,400 in the second. The Plaintiff was then passed on within LHW to Mr Morris, the Second Defendant, who dealt with ‘bigger clients’. On 30th July, 1985, Morris urged the Plaintiff to invest in one hundred lots of sterling at a total cost to him of £150,000. The Plaintiff bought ten lots of sterling at a cost of £15,000 paying £10,000 in cash and raising the balance by stripping it out of the earlier Swiss Franc deal. The price of sterling went against the Plaintiff and, as the stop loss position was about to be reached Mr Morris rang the Plaintiff to recommend he buy another ten lots of sterling at £15,000 to average out his position. Mr Morris was aware that the Plaintiff did not have the cash available and that he would have to borrow the necessary cash, as indeed he did. On 1st August the Plaintiff entered into the fourth trade at issue in this case. The stop loss position was reached on that trade too and the Plaintiffs position was wiped out. On 5th August the Plaintiff's trading position was closed and of his total stake of around £54,000 he recovered only £2,231.62.

Conventional study on the trading pattern of investors is either done in the viewpoint of the identity of investors or analyzed on the base of investor's type, which is categorized according to the number of transactions using only restricted security company data. Dataset in this paper is extended to all ELW series and investor's type such as the LP (Liquidity Provider). High-frequency traders are categorized on the base of average number of transactions per day and average trading volume per day. We analyze their trading pattern and relationship between P/L (profit and loss) and their trading pattern. Also We develop a new measurement tool, called the holding period, to comprehend the characteristic of high frequency trading and analyze the effect of holding period on P/L of investors.

Our empirical investigation shows that, for general investors, 1) their counterparties are LP during the execution of buy low and sell high trading strategy, 2) they lose in the cumulative P/L for the intermediate transaction although their average sell price is more expensive than average buy price, 3) due to the lack of risk management technique such as stop loss, they lose in the cumulative intermediate transaction P/L although their winning ratio is higher than losing ratio. On the other hand, 1) scalpers are mainly engaged in trading index ELW market, 2) due to the appropriate execution of stop loss, they win in the cumulative P/L for the intermediate transaction although their draw ratio and trading unit price are high. Meanwhile, due to the LP's passive characteristic for the buying execution after selling, their draw ratio is very low and their buy unit price is higher than sell unit price in comparison to other investor type, and their trading pattern is negatively related to that of the other investor type. Finally we confirm that the holding period is a significant impact on P/L of general investors and scalper.

As a policy proposal, it is necessary to introduce a market maker system in the individual stock options market for activating the stock options market, which has a more competitive market structure than ELW market. In the viewpoint of financial consumer protection, education on the time value reduction of contingent claim derivatives with finite maturity is necessary.

In this paper we conduct tests for two different trading rules, namely, the Dual Moving Average (DMA) model and the Channel Breakout (CHB) rule. These rules are tested across five futures contracts – the S&P 500, British Pound, US T‐Bonds, COMEX Gold and Corn using daily data over the period 1990 to 1998. Overwhelmingly, we find that the trading rules are unable to produce (gross or net) profits at any statistical level. While positive gross and net profits were available in four of the five markets, the profits were neither economically or statistically significant.

We propose a new model for the dynamics of the aggregate credit portfolio loss. The model is Markovian in two dimensions with the state variables being the total accumulated loss Lt and the stochastic default intensity λt. The dynamics of the default intensity are governed by the equation dλt=κ(ρ(Lt,t)−λt)dt+σλtdWt. The function ρ depends both on time t and accumulated loss Lt, providing sufficient freedom to calibrate the model to a generic distribution of loss. We develop a computationally efficient method for model calibration to the market of synthetic single tranche collateralized debt obligations (CDOs). The method is based on the Markovian projection technique which reduces the full model to a one-step Markov chain having the same marginal distributions of loss. We show that once the intensity function of the effective Markov chain consistent with the loss distribution implied by the tranches is found, the function ρ can be recovered with a very moderate computational effort. Because our model is Markovian and has low dimensionality, it offers a convenient framework for the pricing of dynamic credit instruments, such as options on indices and tranches, by backward induction. We calibrate the model to a set of recent market quotes on CDX index tranches and apply it to the pricing of tranche options.