# Tag Info

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I am not sure Dark Pools (DP) have been created to avoid "market manipulation". They have been created by firms because they found an advantage to create them (see Market Microstructure in Practice, L and Laruelle Eds.). The main reasons have been: spare market fees, for DP created by brokers (like UBS MTF); spare market impact, for block pools (like ...

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A public order book gives traders information not only on the current price of a security, but also the volume and structure of the entire supply and demand schedule. Such information can be used for arbitrage and market manipulation strategies in various ways: Spoofing: Inserting a large limit order as an apparent buy or sell signal which is canceled any ...

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It doesn't matter since multiplication is commutative (in $\mathbb{R}$); you will always end up losing the same.

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This effect is coming from the supply and demand in the options markets. Many portfolio managers want (or need) to buy out of the money put options, and many are willing to sell out of the money call options (thereby funding the purchase of put options). Now, when the market goes down, dealers find themselves short vol and they need to buy options to cover ...

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Given one satisfies margin requirements anyone can short exchange traded options as long as local regulators permit (American retail investors at present are not permitted, for example, to trade futures options . As long as there is a market and one finds a willing counterpart nothing speaks against shorting options contracts. Some brokers might require a ...

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Here is a collection of papers. The general idea is that the market has investor classes that share different expectations. When in bubble territory, many investors generally agree that assets are overpriced, but they still invest in expectation of more investors entering the market (the greater fools). There are also sophisticated investors who know assets ...

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The opening and closing prices are set during an auction. If there are overnight news, then the opening auction will reflect information which wasn't there during the closing auction. And even without the auctions, the last traded price yesterday results from different orders than the first traded price today.

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The problem of when to exercise an option with Bermudan features is an optimal stopping problem. I have a done a lot of work on how to do these things when the state space is high dimensional. There are various more complicated problems where the contract is more difficult eg swing options.

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Of course, optimal control is at the core of math finance. Take few applications: Option Pricing: you have an exposure to a time dependent combination of market factors; you have some knowledge of their dynamics. They are partly deterministic, partly stochastic (i.e. random). At each "time step" you can adjust your portfolio at a given cost. Your goal is ...

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It's not bad but you have to backtest the method out-of-sample. Say you have discovered an indicator that works 100% in history, you still cannot be sure if it works next time. Another advise is you might want to investigate the distribution of loss when your system fails to work. If your system delivers 1% every time you trade, and loses 10% each time it ...

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In the long term you will underperform buy & hold because you need an accuracy of at least 65%. See these papers for more: Bauer, R.; Dahlquist, J.: „Market Timing and Roulette Wheels Revisited“, CFA Institute, 2012. http://www.cfapubs.org/doi/pdf/10.2469/irpn.v2012.n1.10 Sharpe, W.: “Likely Gains from Market Timing”, Financial Analysts Journal, ...

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QuantConnect provides an open source, community driven project called Lean. The project has thousands of engineers using it to create event driven strategies, on any resolution data, any market or asset class. Our system models margin leverage and margin calls, cash limitations, transaction costs. We maintain a full cashbook of your currencies. Its about as ...

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I answered @Anilca's question in SO (and the answer was accepted) I summarize my answer with the working solution: public class Aroon : IndicatorCalculatorBase { public override List<OhlcSample> OhlcList { get; set; } private readonly int _period; public int Period { get { return _period; } } public Aroon(int ...

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1) Spurious autocorrelation of non-synchronous trading data was analyzed in this article: http://www.amazon.com/An-econometric-analysis-nonsynchronous-trading/dp/1245789457 During some time intervals a lot of trades occur and during some nothing happens(so prices are stale). So serial correlation of traded prices may be present but this may be due to stale ...

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It's not unusual to find a financial time series with positive trend samples biased between 55-60%, depending on the period sampled. Stocks tend to have an upward drift over the long run. When you account for the drift, I would say, that number is really not much better than chance. A better way to verify your question would be to make certain to build ...

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Directional forecast is insufficient. You could have a signal that has 100% accuracy and you would not necessarily be able to profit from it because of transaction cost, implementation etc.

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Of course you can sell options and you can certainly sell options on most major indices. Thinkorswim (TDAmeritrade) offers and excellent platform. Moreover, one can short options without "full" account privileges provided a defined risk trade is entered (such as an iron condor or call spread)

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It depends on the derivatives exchange but e.g. Eurex exchange can also be used by retail investors as long as they are qualified (concerning their max. risk level) and their bank offers access to it (some at least do that).

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There is trading happening overnight. A nice paper is Dong Lou et. al: http://personal.lse.ac.uk/loud/OvernightMom.pdf They explain the overnight trading and actually document that most known anomalies occur on that period.

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Yes, that can be really sophisticated even using such nice tools as pandas. But the basic idea is to find position enters & exits to derive cashflow. Here is my code to derive all that stuff from generated signals (in my backtester signals are fractions of 2 stocks in portfolio for each moment). I hope I've found all bugs here, but no warranties. ...

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In testing such a strategy, I have noticed that some days it performs extremely well (sometimes yielding a 75% win rate with 12/14 trades winning) whereas others it bombs (20% win rate with only 2/10 trades winning). This is the key. From the information you provided it would appear that you have failed to consider the effects of draw-down. The ...

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Just take a look at the bid ask spreads plus transaction costs. It's nonsense what you are saying because on one side you implicitly assume enough liquidity so you market maker executes the Delta of your position. On the other hand you assume the market is liquid so you can move the market when you sell your position.

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The way to do gradual position entry and exit is to use multiple trend following rules, each of which is responsible for managing a part of the available capital. Only if all the trading rules agree will 100% of the capital be deployed. As a simple example, suppose you have three rules. The first rule is based on 10 day momentum; this rule produces a score ...

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Before making regression you have to perform test on fractional integration on each component. The power and size of traditional unit root tests are poor. The tests’ weak power implies that the statistical tests cannot distinguish between a unit root process and a fractionally integrated series with long memory (Baillie, 1996). As a consequence, a ...

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When an exchange (or ECN) receives an order, there is no identifier of the buyer or seller. Therefore the only place that this is available is at the broker themselves. No broker would be willing to provide this information even on an anonymized basis and it would be a violation of other laws and regulations (such as Regulation S-P). ...

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Theoretically "information" about stock prices is still arriving (including information about developments outside the United States) and the futures market is doing its best in estimating what the price of the index would be if it was trading. In practice, during the night, traders are following the foreign markets (Europe, Asia) and adjusting the price of ...

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Actually, a lot of finance and economics are centered around optimal control problems. Traditionally, most economies are modeled as dynamic systems. In finance, portfolio optimizations, advanced option pricing etc are all optimal control problems. You could look at the book Non Linear Option Pricing, it has a lot of optimal control problems.

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Every match that hits the tape from the perspective of displayed ECNs is a market order matched with a limit order. You can think of this in terms of makers and takers. If I want to buy MSFT at 51.00 and post a limit for that price 3 microseconds before you post your limit to sell at 51.00 then I am the maker and you are the taker. And your sell order will ...

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If you are after treasuries, you can check http://www.newyorkfed.org/research/staff_reports/sr381.pdf which discusses trade impact on BrokerTec. If you are after equities, the literature is enormous, you can pretty much google for "trade impact limit order book" or smth similar. In practice, it's an empirical approach: you put all the factors, that seem ...

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As a beginner in AlgoTrading QuantConnect and Quantopian are great for practice and improving your skills but for a serious Algo Trader , they are basically useless. An Algo Trader requires flexibility to investigate trading ideas and add or remove libraries or parts of the system that do not work. You need to automatically and constantly reevaluate your ...

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