Finanzdienstleistungen (Praxis) Algorithmic Trading
Definition A computer program (Software) A process for placing trade orders like Buy, Sell It follows a defined sequence of instructions At a speed and frequency that is impossible for a human trader The defined sets of rules are based on timing, price, quantity, volatility, liquidity, news, or any mathematical model Can be used for: investment strategy or trading strategy market making pure speculation
Financial Instrumentes Bond: A debt investment in which an investor loans money to an entity (typically corporate or governmental) which borrows the funds for a defined period of time at a variable or fixed interest rate Stock: A portion of ownership in a corporation or Index of corporations. The holder of a stock is entitled to the company's earnings and is responsible for its risk for the portion of the company that each stock represents Foreign exchange: (FX, forex, Currency trading): The exchange of one currency for another, or the conversion of one currency into another currency
Exchange-traded derivatives Options: A financial derivative that represents a contract sold by one party (option writer) to another party (option holder). The contract offers the buyer the right, but not the obligation, to buy (call) or sell (put) a security or other financial asset at an agreedupon price (the strike price) during a certain period of time or on a specific date (exercise date). Futures: A financial contract obligating the buyer (long) to purchase an asset or the seller (short) to sell an asset, such as a physical commodity or a financial instrument, at a predetermined future date and price.
Backtesting: Interpreting the Past Involves simulating the performance of a trading strategy based on historical data. This provides an opportunity to estimate how effective a strategy would have been if it had been used in the past. Is used to optimize custom trading strategies using on historical data and analyze its performance to validate trading ideas The underlying theory is that any strategy that worked well in the past is likely to work well in the future, and conversely, any strategy that performed poorly in the past is likely to perform poorly in the future
Technical Indicators A result of mathematical calculations based on indications of price and/or volume The values obtained are used to for measuring and interpreting market behavior and forecast probable price changes Technical indicators look to predict the future price levels, or simply the general price direction, of a security by looking at past patterns. There are many technical indicators like Moving Average, Bollinger Bands, Momentum, Stochastic Oscillator
Moving Average Mean of time series data (observations equally spaced in time) from several consecutive periods. Called 'moving' because it is continually recomputed as new data becomes available, it progresses by dropping the earliest value and adding the latest value There are four different types of moving averages Simple Moving Average Exponential Moving Average Smoothed Moving Average Linear Weighted Moving Average
Simple Moving Average Is calculated by summing up the prices of an underlying over a certain number of single periods. This value is then divided by the number of periods with sma t = t: current time i=t n+1 t n Price i Price i : Price of Instrument at time i n: number of calculation periods
Simple Moving Average
Exponential Moving Average It is similar to a simple moving average, except that latest prices are of more value. The exponential moving average is also known as "exponentially weighted moving average". ema t = p Price t + 1 p ema t 1 with t: current time Price i : Price of Instrument at time t p: the percentage of latest price
Exponential Moving Average
Smoothed Moving Average Is calculated over a certain number of single periods as follows smma t = (n 1)smma t 1 +Price t smma 0 = i= n 1 0 Price i n with t: current time Price i : Price of Instrument at time n: number of calculation periods
Smoothed Moving Average
Linear Weighted Moving Average In Linear Weighted Moving Average the latest data is of more value than does the common simple moving average Is calculated over a certain number of single periods as follows with t: current time lwma t = i=t n+1 t t i=t n+1 Price i : Price of Instrument at time i n: number of calculation periods Price i (i t + n) (i t + n)
Linear Weighted Moving Average
Bollinger Bands A band (top line, bottom line) plotted two standard deviations away from a simple moving average (middle line) ml t = i=t n 1 t Price i n tl t = ml t + d Std t bl t = ml t d Std t with t: current time Price i : Price of Instrument at time i n: number of calculation periods Std t : Standard Deviation at time t
Bollinger Bands
References wikipedia.org investopedia.com mql4.com interactivebrokers.com