MIT 15 875 - Forecasting Market Price Movements with System Dynamics

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Forecasting Market Price Movements with System DynamicsChris LimXiao LinDavid SteinmillerClient DescriptionClient DescriptionClient: Jantz Morgan• An investment management firm • Maintains an investment portfolio that they rebalance at the beginning of each month based on the predictions for that month of a System Dynamics model• Would like a model that explains market movements that defy rational valuation methodsOur concept of how the market worksOur concept of how the market worksFrom Traditional Finance and Behavioral Finance Theory we defined three types of investing styles:• Value: trade on intrinsic value of stock/firm• Technical: trade on price and volume movements• Psychological: trade on buzzBalancing and Reinforcing effects of these styles: • Value trading tends to bring prices to a stable value• Technical and Psychological trading tends to reinforce price changes (Momentum trading)Interacting with ClientsInteracting with ClientsOur belief:Client has a model that predicts how a rational market worksThus, they have successfully modeled the value loopOur job is:• to find forcing and delay factors that make the value loop appear irrational• to add loops to that model to include irrationalityClient:Unwilling to show us their proprietary modelDescribed a potential reference mode that shows market irrationality: monthly rank reversalModelingModelingMethodology:Focus on single examples of each investing style:• Value Investment loop: driven by P/E ratio• Technical Investment loop driven by price changes and volume• Psychological Investment loop driven by number of articles written about a given stockResults:• Using these loops we were able to generate a monthly reversal in price• Not confident in the resultsChallengesChallengesDefining a phenomena that can be modeled • Important phenomena occur on a wide range of time scales• Client demonstrated “rank order reversal” (apparently statistically significant)• Monthly reversals in price are the exception, not the rulePrice is the easiest thing to observe; partially for this reason we made it central to our model• Price is not the main driver of momentum tradingMarket workings are not transparent• Data for table functionsUnable to correctly weight the styles of investingWhat we’ve learned about modeling the marketWhat we’ve learned about modeling the marketMore difficult to get data than we had imagined• Much of the data is not public• Public data exists in multiple sets of accessibilityVolume and liquidity are central to market functioningKeep the model as simple as possible and never model aloneWhat we’ve learned about the ClientWhat we’ve learned about the ClientClient:• Does not have a model of how the market works, instead they have a model predicts that intrinsic value• Client model is very simple (few loops) but data rich• Client believes very strongly in the model and the model has performed well using historical dataClient Problem: • At small scale, trading costs reduce returns• To continue to show returns, fund must grow to past a threshold size• To grow, investors require a track record• To build a track record, fund must have investorsClient needs to pursue sales and marketing moreShould be willing to give up more of their upside to build the fundFuture Work on this topicFuture Work on this topicAccess to data•Table functions incomplete• Work with a brokerage company so as to get access to all public dataExpanding the Model• Impact and growing importance of trading due to hedgingSetting the time frame• Better understanding of how much time it takes for components to interact consistentlyConsider speculative trading as exogenousModelModelExcess DemandBuy/Sell Ratio+Volume+Volume TableFunctionChange in Price+Volume/ShareAvailable Shares+-+Moving AverageConvergence/Divergence(MACD)Expectation ofPrice Change++RPrice+Price to EarningsratioForecastedEarnings+--On balance volume(OBV)++BBTarget P/E ratio+Buzz FactorBuzz Factor TableFunction++++R+Lemmings LoopStrike while theiron is hotWhat goes up, mustcome downThe well is


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MIT 15 875 - Forecasting Market Price Movements with System Dynamics

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