Advanced Trading and Investment - Assignment Example

Advanced Trading and Investing Assignment Name Institution Instructor Course Date Table of Contents 0 Running Head: Advanced Trading and Investing Assignment 0 Advanced Trading and Investing Assignment 11 1 Introduction 2 The actual rules you tested for step (2), 2 A diagnosis of the backtest 2 Risk analysis 4 6 First chart shows returns of closing and 40‐day closing average followed by returns of 2‐day and 5‐day closing average. The third graph shows returns of order of 50‐day extreme High and Low close. The returns for fourth rule that while the fifth is the fifth rule. 6 Conclusions 7 The actual rules you used for step (3) 7 A diagnosis of the backtest, including realistic transaction costs 7 Risk analysis 8 The following shows returns of strategy selected. From the chart it be noted that returns are going down in 2016 towards the end. The codes are in R studio file. 8 Conclusions 8 Final conclusions 9 Introduction The main aim is to test a trading system on ASX 200 futures using Quantstrat of R studio software. Futures consists of a portfolio designed to reflect the composition of some broad-based market index it does so by holding securities in the same proportion as the index itself. In fact an ideal index fund would be one holding all available common stocks in exact proportion to their outstanding market value. However, such an ideal fund would be impossible to contract and mange. Therefore this paper will use ASX 200 futures and hope will be a good surrogate for this ideal analysis. In the analysis two items will considered transaction cost and price of the future. First the expenses involved in handling a truly transact the future because the construction of the future is entirely based upon maintaining proportions of the index being followed. Transaction fee is charge for managing funds it helps in to defraying the cost of operating the portfolios-including such expenses as brokerage fees, transfer costs and analysts’ salaries. As such considerably lower transaction costs are involved because fewer purchases and sales of futures would take place. The baseline strategy is to be to add them up selection strategy and goes long if the sum is positive, and short if the sum is negative, taking all trades The actual rules you tested for step (2), A diagnosis of the backtest My investment approach involves selection of the future as I would describe my trading approach as threshold approach where if the combined sum is 3 (‐3) I will long. This implies that if rules 1, 2 and 3 all say long (short) the n an investment is made. Using these approaches one generates a list of possible strategies. The first step is to carry out strategies using a threshold approach when combined sum is 3 or more go long and combined sum is -3 or more. The selection of his rules for investment is 1. Close versus 40‐day closing average a. Close > 40‐day average, buy next day (+1) b. Close < 40‐day average, short next day (‐1) 2. 2‐day versus 5‐day closing average a. Average 2‐day close < average 5‐day close, buy next day (+1) b. Average 2‐day close > average 5‐day close, short next day (‐1) 3. Order of 50‐day extreme High/Low closes a. Highest close of the last 50 days is before the lowest close of the last 50 days, buy next day (+1) b. Lowest close of the last 50 days is before the highest close of the last 50 days, short next day (‐1) 4. 10‐day range indicator a. Daily range less than the 10 day average range, buy next day if todays close was higher (+1) or short if it was lower (‐1) b. Daily range greater than the 10 day average range, buy next day if todays close was lower (+1) or short if it was higher (‐1) 5. 15‐day average High/Low indicator = (average high of last 15 days + average low of last 15 days) / 2 baseline strategy. He also often uses: a. Close > 15‐day average High/Low indicator, buy next day (+1) b. Close < 15‐day average High/Low indicator, short next day (‐1) The following Risk analysis From the chart blow shows time series of Financial market price volatility has a notable characteristic that is changing with time. The early research done by Mandelbrot (1963) and Fama (1965) shows that bigger fluctuation tends to centralize in certain periods of time, which is similar to smaller ones in other periods of time and is termed “volatility cluster”. This phenomena that is quite strong in holding that a financial variable varies when the market undulates, is quite common in financial time-series. Most traditional analysis such as multiple linear regression and ARMA model assume the residual error has expectation zero as well as independent covariance, which can not be objective and clearly describe the behavior and characteristics of how market price and return vary with time. Despite this difficulty, it is important to estimate and forecast the market volatility for investors and arbitrageurs; individual stock forecasting is also very important to personal investors. Since Engle (1982) pioneered a autoregressive conditional heteroscedasticity model; the so-called ARCH model that can accurately reflect how the observed coefficient varies with time, which can be interpreted by estimating UK inflation, numerous research has emerged in developing the model to study financial markets. First chart shows returns of closing and 40‐day closing average followed by returns of 2‐day and 5‐day closing average. The third graph shows returns of order of 50‐day extreme High and Low close. The returns for fourth rule that while the fifth is the fifth rule. Conclusions Three rules gave a positive of take all under threshold approach that is 2‐day versus 5‐day closing average, Order of 50‐day extreme High/Low closes and 10‐day range indicator as first three rules that determined investment strategy. The pragmatic results offered in the preceding section have some significant connotations for Art Collins 5‐rule strategies of investment and performance. What’s more, the main rationale behind trading systems is to develop rules that will help in improving portfolio performance and to make a distinction among strategies based to make improved promotion decisions. The actual rules you used for step (3) A diagnosis of the backtest, including realistic transaction costs  A threshold approach – for example, only go long(short) if the combined sum is (for example) 3 (‐3) or more.  A combination approach – for example go long(short) if rules 1, 2 and 3 all say long(short), etc. Using this approach he generates a list of possible strategies, with names like 145, 234, etc Risk analysis The following shows returns of strategy selected. From the chart it be noted that returns are going down in 2016 towards the end. The codes are in R studio file. Conclusions The combined approach indicates we take all after considering Close versus 40‐day closing average, Order of 50‐day extreme High/Low closes and 15‐day average High/Low indicator = (average high of last 15 days + average low of last 15 days) / 2 as the rules that gave positive results. Performance measures, conversely, are provide information regarding the hold-sell aspects and are for that reason of significance decision taken given that they present incentives that are not provided by objective performance measures. The combined approach performance measures provide information regarding all take aspects of the futures. In addition, diversity in performance measure can perk up incentive contracting by means of assuaging the predicament of goal congruence demonstrate that supplementary performance measures can have an effect on the manager’s effort allocation to make it more congruent with the principal’s objectives, which makes these measures valuable for decision purposes. Besides, by using combined approach performance measures in the successful strategies reward systems it would allow the principal to make a choice of strategic weights that take full advantage of the congruence between the rules and the resulting outcome of the firm. Final conclusions Final conclusions regarding Art Collins 5‐rule strategies The strategy gives complex solution if not properly implement, the result can be conflicting. Three rules are able to determine buy-sell decision for the futures. Under combined approach results was different from that of a threshold approach. The Close versus 40‐day closing average, Order of 50‐day extreme High/Low closes and 15‐day average High/Low indicator = (average high of last 15 days + average low of last 15 days) / 2 were able to determine the take all decision in combined approach. While threshold approach had 2‐day versus 5‐day closing average, Order of 50‐day extreme High/Low closes and 10‐day range indicator as first three rules that determined investment strategy. The pragmatic results offered in the preceding section have some significant connotations for Art Collins 5‐rule strategies of investment and performance. References Standard Life Investments Limited (2015). Unconstrained Investing : The Freedom To Perform Bruce(2015). Lecture 6 - Buying 52 week highs and selling 52 week lows using quantstrat Bond University Mayer, Z. (2016). Backtesting a Simple Stock Trading Strategy. available on https://www.r-bloggers.com/backtesting-a-simple-stock-trading-strategy/ (accessed on 1st December 2016) Diebold F X and R S Mariano, (2006) Comparing predictive accuracy, Journal of Business & Economic Statistics, 13, 253-263. Poon S and Granger C, (2003) Forecasting financial market volatility: a review, Journal of Economic Literature, 41, pp.478–539. Read More