Suitable for many types of traders day traders forex binary options algotrading etc and for a short

Kevvy Kim 13 3. How do I officially track the performance of my quant strategy? I have a quant strategy that I want to implement in order to establish an official track record, but I'm not sure what I have to do. Evidence that supports the assumption that prices are random processes I have heard that the price of stock or future changing over time is a random process, namely, a martingale, and no one can have an edge.

Is there any evidence supporting this assumption? How to properly set strategy parameters and select portfolio I have the following strategy pipeline which is a function of several hyperparameters and execution parameters: FTSE, where I have 8 years of past data daily. I also have a list of its constituents. For each stock, I have the following features: Efficient integration of tick data feed with signal generation The goal is to design the integration of processes generating trading signal doing analytics on a stream of asynchronous tick data retrieved using the native Python TWS API of Interactive Brokers.

What are the consequences of violating Hansen-Jagannathan bounds? Note I have added much more detail to this question I have decided to add the detail without altering the original text since a number of those of you offering assistance asked for clarification. Nick Firoozye 6. Is the emphasis on highly sophisticated analysis of widely available Then we proceed to do Dionysios Gerogiadis 18 3.

Now if this is what you think, then I have bad news for you. From my own reading and investment experience, I assure that the odds of success are stacked heavily against you. This contrasts with long-term investment over a period of years and even decades.

But I argue that it is hard to start from no experience and become an effective trader, which means earning money consistently in the long run. The amount is comparable to a full-time minimum-wage job, and the time period is intended to reduce the effects of luck. Firstly, day trading implies interacting in the field of finance.

This is a technical field that has its own set of terminology and concepts, and also requires modest mathematical skills. For example if you are buying a bond, you should understand that at the basic level it represents a piece of debt with a fixed payment schedule.

Digging deeper, you should understand bond concepts like coupon, yield, face value, credit rating, default, and so on. Learning these financial concepts [0] is non-trivial because there are many of them, and some can have long explanations and subtle catches.

If you think you can start trading without understanding these, you are already setting yourself up for failure. Public news is worthless for making effective trade decisions. The efficient-market hypothesis is a widely held belief that states that the price of a security stock, bond, etc. For example, if an oil company just discovered new resources which is considered a good thing , then its price will rise — but in reality, its price will have already risen by the time the news article reaches you, which means you would be too late to profit from the news.

Since public news is out of the question, this implies one of two things: As you can see, all 3 sources of information — public news, insider information, and guessing — have serious drawbacks; as a result, you are unlikely to make effective trades solely based on information.

As a corollary to the EMH , it means stock prices are always correct and fair, every day, every minute. If you buy something because you expect its price to go up in the future, it would be a mistake to attribute your expectation to intuition or common sense — your expectation is based on mere belief , because anything that is a fact is already reflected in the security price.

These forecasts are a mixture of public news and mere guessing, which is not information that you can profit from. Irrational behaviors and cognitive biases cost you real money. These flaws in human reasoning are studied academically in fields like economics, game theory, and psychology, but when you make financial decisions according to a false interpretation of reality, you will end up with money-losing consequences with high probability.

People acquire essentially all of these biases by nature; it takes conscious effort to recognize them and mentally train against them. These irrational behaviors take a bit of reading and serious thinking to understand, but truly recognizing them in real life is much harder than it sounds. When learning about these behaviors, the examples are purposely contrived and quite clear-cut.

Institutional investors are big, powerful players in the financial markets. For example, these are organizations that control a mutual fund, pension fund, hedge fund, university endowment fund, etc.

When institutional investors make investment decisions, they do it with expertise and influence. They employ professionals who are trained in finance and have experience working in the field; they employ people whose job is to monitor prices, analyze trends, and find non-obvious facts about the world.

Because of their large size, they can negotiate discounts and special deals with sellers; moreover, they can buy smaller companies outright and revamp their management for better profitability. You, as an individual investor, have none of these advantages.

In addition to humans, computer programs also participate in trading. Modern computers are spectacularly cheap and powerful, and a single computer can easily do a billion calculations per second [2]. A program running on a computer can analyze millions of data points in thousands of stocks a second, and have sophisticated algorithms to find patterns, all backed by knowledge from decades of academic and corporate research.

Moreover, these programs can react to fluctuating prices, incoming orders, and financial news on a millisecond-by-millisecond basis.